European Journal of Pharmacology 997 (2025) 177608

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European Journal of Pharmacology

journal homepage: www.elsevier.com/locate/ejphar

Exploring 4th generation EGFR inhibitors: A review of clinical outcomes

and structural binding insights
Amina Tariq a , Muhammad Shoaib a, Lingbo Qu a,b , Sana Shoukat c , Xiaofei Nan d,**,
Jinshuai Song a,*
a
College of Chemistry, Pingyuan Laboratory, and State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Zhengzhou University, Zhengzhou, Henan,
450001, China
b
Institute of Chemistry, Henan Academy of Science, Zhengzhou, Henan, 450046, China
c
Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials (Ministry of Education), Shandong University, Jinan, 250061, China
d
School of Computer Science and Artificial Intelligence, Zhengzhou University, Zhengzhou, Henan, 450001, China

A R T I C L E I N F O A B S T R A C T

Keywords: Epidermal growth factor receptor (EGFR) is a potential target for anticancer therapies and plays a crucial role in
Tyrosine kinase inhibitors cell growth, survival, and metastasis. EGFR gene mutations trigger aberrant signaling, leading to non-small cell
EGFR lung cancer (NSCLC). Tyrosine kinase inhibitors (TKIs) effectively target these mutations to treat NSCLC. While
Mutations
the first three generations of EGFR TKIs have been proven effective, the emergence of the EGFR-C797S resistance
NSCLC
Deep generative models
mutation poses a new challenge. To address this, various synthetic EGFR TKIs have been developed. In this
review, we have summarized the EGFR TKIs reported in the past five years, focusing on their clinical outcomes
and structure-activity relationship analysis. We have also explored binding modes and interactions between the
binding pocket and ligands to provide insights into the mechanisms of these inhibitors, which contribute to
advancements in targeted cancer therapy. Additionally, artificial Intelligence-driven methods, including recur­
sive neural networks and reinforcement learning, have revolutionized EGFR inhibitor design by facilitating rapid
screening, predicting EGFR mutations, and novel compound generation.

1. Introduction often referred to as wild type EGFR. Its structure comprises an extra­
cellular portion, a transmembrane (TM) segment, and an intracellular
Epidermal growth factor receptor (EGFR) is identified as the most TK domain (Fig. 1). The activation of EGFR involves the binding of li­
popular bio-molecular target for non-small cell lung cancer (NSCLC) gands to the extracellular portion, which induces conformational
(Bethune et al., 2010). Targeted therapy has received significant atten­ changes in the receptor. These conformational changes lead to the
tion from the scientific community in recent years (Mountzios, 2018). dimerization of EGFR. The specific tyrosine residues in the intracellular
Specialized targeted treatments, known as EGFR tyrosine kinase in­ tyrosine kinase undergo auto-phosphorylation, activating downstream
hibitors (TKIs), are designed to block the activity of the tyrosine kinase signaling pathways. This ultimately regulates cellular functions like cell
(Sandor et al., 2023). EGFR is a cell surface receptor protein that is found growth and proliferation (Arkhipov et al., 2013). The well-defined
on the outer membrane of various types of cells in the human body. The structure of EGFR, especially within the intracellular TK domain, is a
dysregulation of EGFR can be associated with several malignancies in key target for therapeutic interventions. Thus, understanding the
humans, making it a significant target for targeted cancer therapy. This structural details of EGFR tyrosine kinase is crucial for developing such
receptor family includes four members EGFR (also known as ErbB1 or therapies (Ohashi et al., 2013).
HER1), ErbB2 (HER2 or Neu), ErbB3 (HER3), and ErbB4 (HER4) In this review, we have collected recent progresses on 4th generation
(Yarden and Sliwkowski, 2001). All members of the EGFR family play EGFR TKIs that have been designed, developed, and clinically evaluated
essential roles in cell signaling and regulating various cellular processes in the last five years. We summarized the interaction mechanism from
(Wang et al., 2016b). EGFR typically contains around 1186 amino acids their structure-activity relationship (SAR) and molecular binding mode

* Corresponding author.
** Corresponding author.
E-mail addresses: iexfnan@zzu.edu.cn (X. Nan), jssong@zzu.edu.cn (J. Song).

https://doi.org/10.1016/j.ejphar.2025.177608
Received 2 February 2025; Received in revised form 24 March 2025; Accepted 7 April 2025
Available online 9 April 2025
0014-2999/© 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

analysis. We have also explored the potential use of artificial intelligence EGFR mutations are specific genetic alterations in the EGFR gene
(AI) in developing novel and selective inhibitors for EGFR mutants. (Lynch et al., 2004). The EGFR gene comprises 28 exons; mutations in
specific exons play a critical role in tumorigenesis. These mutations are
2. Structural features and mutations in tyrosine kinase pivotal in developing targeted therapies in cancer treatment (Ladanyi
and Pao, 2008). Fig. 3 summarizes some common mutations occurring
The intracellular TK domain is divided into three regions: the N-lobe, in the EGFR kinase. One of the most common mutations in NSCLC are
C-lobe, and ATP-binding site (Fig. 2) (Jura et al., 2011; Stamos et al., EGFR Exon 19 deletions, which are considered activating mutations that
2002). The N-lobe of a tyrosine kinase domain is typically smaller and are highly sensitive to EGFR TKIs. These deletions result in the removal
contains five β-strands and the αC-helix. This αC-helix is critical for of specific amino acids (i.e. 746-750 (Leu-Arg-Glu-Ala motif)) in the
stabilizing the active conformation of the tyrosine kinase. The N-lobe tyrosine domain of EGFR. Point mutations involving a replacement of
plays a role in binding ATP and coordinating its phosphate groups one residue with another residue are also commonly found in NSCLC.
during phosphorylation reactions. The C-lobe is mainly helical and The L858R mutation in exon 21 is also an activating mutation
embraces the highly flexible activation loop (A loop). The C-lobe con­ (Shigematsu et al., 2005). It involves a replacement of a leucine (L)
tains key structural elements involved in catalysis, including the cata­ residue with arginine (R) at the 858th position in the EGFR protein. This
lytic loop and the hinge region. The deep cleft in between the N-lobe and mutation is also highly responsive to EGFR TKIs. The rarely found point
C-lobe serves as the binding pocket for the adenine ring of ATP (Jura mutations are G719S, G719A, G719C, and L861Q (He et al., 2012;
et al., 2011; Zhao et al., 2016). Shigematsu et al., 2005).
The conformational state of the catalytic domain (CD) of a kinase Some resistance mutations develop during EGFR TKI treatment, like
protein, whether it is in an active or inactive state, is determined by the secondary mutations (T790M) and tertiary mutations (exon 20 in­
structural arrangement of the DFG motif (Asp-Phe-Gly motif), αC-Helix sertions and C797S) (Ohashi et al., 2013; Pao et al., 2005; Thress et al.,
and Activation Loop (A Loop) (Liu et al., 2013) (Fig. 2 C). The DFG motif 2015). Resistance can develop over time, limiting the effectiveness of
lies within the A-loop of the kinase. In the active state, the DFG motif is these tyrosine kinase inhibitor-based therapies. EGFR mutations are
typically in a “DFG-in” conformation, with the aspartate coordinating a often identified through genetic testing of tumor tissue or liquid bi­
magnesium ion to assist in ATP binding and catalysis. The αC-helix is opsies. The presence of specific EGFR mutations can guide treatment
typically in an “in” position with the A loop extended to adopt an “A loop decisions, with targeted therapies being the preferred option for patients
open” conformation, helping to stabilize the active conformation of the with EGFR-activating mutations (Irmer et al., 2007).
kinase (Hubbard, 1997). In the inactive state, the DFG motif adopts a
“DFG-out” conformation, where the phenylalanine swings away from 3. EGFR tyrosine kinase inhibitors
the active site. The αC-helix shifts to an “out” position with A loop in a
“closed” conformation covering and blocking the ATP binding site in an EGFR TKIs are categorized into different generations based on their
inactive state (Hari et al., 2013; Hubbard et al., 1994). development and characteristics (Sandor et al., 2023) (Fig. 4). Patients

Fig. 1. Illustration depicting the EGFR molecular domains and the exons responsible for encoding them. EGFR is situated on chromosome 7 and comprises 28 exons.
It encompasses an extracellular domain, a transmembrane domain (TM domain), a juxta-membrane domain (JM domain), an intracellular protein tyrosine kinase
domain responsible for ligand binding, and a C-terminal segment. (B) EGFR plays a key role in various signaling pathways and governs multiple cellular functions.

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Fig. 2. (A) Crystal Structure of EGFR tyrosine kinase domain and its structural features (PDB ID = 2GS2). (B) The location of active site cleft for ATP binding and
allosteric site right behind ATP binding site (PDB ID = 5ZWJ). (C) The "αC-in" and "αC-out" conformations of the αC helix, the open and extended state of the
activation loop (A-loop) representing active (yellow) and inactive (purple) conformations of the EGFR kinase domain (PDB ID = 2GS2, 2GS7). (For interpretation of
the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3. This diagram presents various EGFR mutations. The classical EGFR mutations (indicated in green) are responsive to EGFR-TKI therapy, while the acquired
resistance mutations (depicted in red), T790M and C797S, are the most frequently encountered mutations after treatment with 1st, 2nd, and 3rd generation. (For
interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

who have EGFR-activating mutations like exon-19 deletions and L859R, resistance often develops through the emergence of secondary muta­
the therapeutic effect can be achieved by using 1st generation EGFR tions like T790M in exon 20 (Huang and Fu, 2015). T790M mutation is
TKIs. Gefitinib and Erlotinib are both quinolinamine-based 1st genera­ known to restrict the access of certain EGFR TKIs to the ATP-binding site
tion TK inhibitors, exhibiting a positive clinical response (50–80 %) of the EGFR kinase, acting like a gatekeeper (Wang et al., 2016a).
(Hosomi et al., 2020; Yang et al., 2015). They reversibly and competi­ To overcome the resistance caused by the T790M mutation, several
tively bind to kinase via the ATP binding site, inhibiting its activity and second-generation EGFR TKIs. These 2nd generation inhibitors faced
providing longer progression-free survival in NSCLC patients (Miyazaki challenges related to their dose-limiting toxicity and maximum tolerated
et al., 2018). After nearly one year of treatment with 1st generation TKIs, dose (MTD), which resulted in certain side effects like diarrhea and skin

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Fig. 4. Development of EGFR tyrosine kinase inhibitors for different mutated EGFR.

rashes (Westover et al., 2018). Afatinib is an irreversible 2nd generation particularly the EGFRC797S mutation, has been a focus of ongoing
TK inhibitor of EGFR, ErbB2, and ErbB4. It showed promising results research and drug development in the past few years. The mutations,
against wild-type (EGFRWT) and double mutant (EGFRL858R/T790M) of such as EGFRDel19/T790M/C797S or EGFRL858R/T790M/C797S, present signif­
EGFR with IC50 values of 0.5 nM and 10 nM, respectively, and is the only icant challenges in addressing the EGFR-mutated NSCLC (Helena et al.,
FDA-approved drug from the 2nd generation inhibitor (Helena and Pao, 2015; Remon et al., 2024). Researchers and pharmaceutical companies
2013; Li et al., 2008). Similarly, Dacomitinib (PF-00299804) is also an have been working to discover new small-molecule inhibitors that can
irreversible inhibitor of EGFR, ErbB2, and ErbB4 with IC50 values of 6, effectively target these triple mutations. Some of these inhibitors have
45.7, and 73.7 nM in enzyme essay but unexpectedly exhibited poor shown hopeful results in preclinical studies (Lim et al., 2023; Shum
activity among patients in clinical trials (Engelman et al., 2007; Gon­ et al., 2022; Spira et al., 2022). The structures and activities of the re­
zales et al., 2008). ported compounds are listed in Table 1.
3rd generation TKIs were also developed to combat with T790M
mutation. Most of these inhibitors have an aminopyrimidine scaffold
and an acryl amide warhead, which covalently binds with CYS797. 4.1. ATP-competitive inhibitors for C797S mutation
Osimertinib is a prominent example of a 3rd-generation irreversibly
inhibits the activity of tyrosine kinase. It significantly inhibits the pro­ ATP-competitive inhibitors compete directly with ATP for the ATP-
liferation of PC9 NSCLC cells and shows IC50 values of 17 and 15 nM in binding site within the kinase domain. These inhibitors interfere with
EGFRDel19(46-50) and H1975 cells (EGFRT790M/L858R), sparing the wild- the kinase’s ability to phosphorylate its target proteins, disrupting
type EGFR with the IC50 value of 480 nM in LoVo cells. It exhibits intracellular signaling pathways and ultimately inhibiting cell growth
promising clinical activity with mild side effects. (Carlisle and Ram­ and division (Wang et al., 2016b).
alingam, 2019; Li et al., 2021; Ward et al., 2013). Olmutinib is also a
covalent 3rd generation inhibitor showed potent inhibitory activity in 4.1.1. Aminoquinazoline derivatives
HCC827 (EGFRDel19(46-50)) and H1975 (EGFRL858R/T790M) cell line with The discovery of 2-aryl-4-aminoquinazoline as a promising molecu­
GI50 values of 7 and 32 nM (Park et al., 2016). Lazertinib, another 3rd lar core revolutionized the design of EGFR inhibitors due to its
generation inhibitor significantly inhibits the proliferative activity of remarkable ability to inhibit EGFR kinase activity (Das and Hong, 2019).
Ba/F3 cells (EGFRT790M/L858R) and exhibited the EC50 value of 7.4 nM. Among notable discoveries, compound 1 emerged as a standout lead. It
Lazertinib recently gained FDA approval in combination with ami­ exhibited potent activity against EGFRDEL19/T790M/C797S with an
vantamab to treat patients with EGFRT790M mutation-positive NSCLC impressive IC50 value of 0.149 μM and demonstrated 163-fold selectivity
(Besse et al., 2025; Heppner et al., 2022). over wild-type EGFR. Detailed interaction analysis sheds light on its
The clinical treatment of patients harboring the EGFRT790M mutation strong inhibitory activity. The phenolic group in compound 1 forms
by 3rd generation TKIs is hampered by the emergence of an additional bidentate hydrogen bonds with the key hinge residues Met-793 and
tertiary C797S resistance mutation. In addition, some other less common Gln-791, which are further reinforced by hydrophobic interactions be­
resistance mutations may also appear, such as exon 20 insertion, L718Q, tween its phenyl ring and the side chain of Met-790. Additional
L792H, and L796S (Niederst et al., 2015; Wu, 2016). hydrogen bonds between the pyridin-3-yl-methylamine group and
Ser-797 contribute to its selectivity and potency toward EGFR triple
4. 4th generation EGFR inhibitors mutant (Fig. 5 A). This compound set the stage for deeper exploration of
the 2-aryl-4-aminoquinazoline scaffold (Park et al., 2017). Inspired by
Overcoming the resistance caused by EGFR tertiary mutations, the potential of this scaffold, Zhang et al. synthesized a series of de­
rivatives, among them compound 2 stood out. It demonstrated potent

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Table 1
Compounds with their structures, reported site of action, mode of inhibition, and anti-tumor activity in different EGFR enzymatic assays and cell lines.
Sr. Compounds Reported site of Action Mode of Anti-tumor activity Ref.
No. Inhibition

1 ATP binding site Non- Covalent EGFRDEL19/T790M/C797S IC50 = 0.149 μM Zhou et al. (2021)
EGFRWT IC50 = 24.3 μM

2 ATP binding site Non- Covalent H1975 (EGFRL858R/T790M) IC50 = 3.3 μM Zhang et al. (2020)
H1975 (EGFRL858R/T790M/C797S) IC50 =
1.2 μM
Enz EGFRL858R/T790M/C797S IC50 = 0.63
μM

3 ATP binding site Non- Covalent H1975 (EGFRL858R/T790M) IC50 = 13.41 Zhou et al. (2021)
μM
A549 (EGFRWT) IC50 = 14.33 μM
H460 (EGFRWT) IC50 = 17.81 μM
Ba/F3 (EGFRDel19/T790M/C797S) IC50 =
91 μM
Enz (EGFRL858R/T790M) IC50 = 0.74 μM
Enz (EGFRWT) IC50 = >10 μM
4 ATP binding site Non- Covalent H1975 (EGFRL858R/T790M) IC50 = 4.9 μM Xu et al. (2024)
Ba/F3 (EGFRDel19/T790M/C797S) IC50 =
0.22 μM
Enz (EGFRL858R/T790M) IC50 = 0.33 μM
Enz (EGFRDel19/T790M/C797S) IC50 =
0.133 μM
Enz (EGFRWT) IC50 = >10 μM

5 ATP binding site Non- Covalent A549 EGFRWT IC50 = 0.77 μM Zhang et al. (2024)
H1975 EGFRL858R/T790M IC50 = 6.9 μM
Ba/F3 EGFRDel19/T790M/C797S IC50 =
98.9 μM

6 ATP binding site Covalent H1975 (EGFRL858R/T790M) IC50 = 15 nM Li et al. (2021)

A549 (EGFRWT) IC50 = 480 nM
HCC827 (EGFRdel19) = 17 nM

7 ATP binding site Non- Covalent Enz EGFRWT IC50 = 29 nM Ding et al. (2022)
Enz EGFRL858R/T790M IC50 = 10 nM
Enz EGFRL858R/T790M/C797S IC50 = 242
nM
H1975 (EGFRL858R/T790M) IC50 = 1.56
μM
A549 (EGFRWT) IC50 = 2.53 μM

8 ATP binding site Non- Covalent Enz EGFRWT IC50 = 743 nM Ding et al. (2022)
Enz EGFRL858R/T790M IC50 = 42 nM
EGFRL858R/T790M/C797S IC50 = 137 nM
H1975 (EGFRL858R/T790M) IC50 = 1.82
μM
A549 (EGFRWT) IC50 = 2.14 μM

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Table 1 (continued )
Sr. Compounds Reported site of Action Mode of Anti-tumor activity Ref.
No. Inhibition

9 ATP binding site Non- Covalent Enz EGFRWT IC50 = >1000 nM Su et al. (2020)
Enz EGFRL858R/T790M IC50 = 156.6 nM
Enz EGFRL858R/T790M/C797S IC50 = 218.3
nM
Enz EGFRDel19/T790M/C797S IC50 = 15.3
nM
A549 (EGFRWT) IC50 = 20.48 μM
H1975 (EGFRL858R/T790M) IC50 = 16.18
μM
BaF3 (EGFRDel19/T790M/C797S) IC50 =
8.51 μM
10 ATP binding site Non- Covalent Enz EGFRWT IC50 = 307 nM Chen et al. (2022)
Enz EGFRL858R/T790M/C797S IC50 = 23.6
nM
A431 (EGFRWT) IC50 = 2.003 μM
Ba/F3 EGFRL858R/T790M/C797S IC50 =
0.036 μM
Ba/F3 EGFRDel19/T790M/C797S IC50 =
0.052 μM
11 ATP binding site Non- Covalent Enz EGFRL858R/T790M/C797S IC50 = 14 nM Dong et al. (2023)
Enz EGFRWT IC50 = 5000 nM
H1975 EGFRL858R/T790M IC50 = 0.096
μM
H1975 EGFRL858R/T790M/C797S IC50 =
0.014 μM
BaF3 (EGFRL858R/T790M/C797S) IC50 =
0.026 μM
A549 (EGFRWT) IC50 = 22.6 μM
12 ATP binding site Non- Covalent BaF3 (EGFRdel19/T790M) IC50 = 150.3 nM Uchibori et al. (2017)
BaF3 (EGFRdel19//C797S) IC50 = 39.9 nM
Ba/F3 EGFRDel19/T790M/C797S IC50 =
67.2 nM

13 ATP binding site Non- Covalent Enz EGFRL858R/T790M IC50 = 0.2 nM Fang et al. (2022)
Enz EGFRL858R/T790M/C797S IC50 = 0.3
nM
Enz EGFRdel19/T790M/C797S IC50 = 0.2 nM
PC-9 (EGFRdel19/T790M/C797S) IC50 =
66.7 nM
BaF3 (EGFRdel19/T790M/C797S) IC50 =
1.526 nM
14 ATP binding site Non- Covalent Enz EGFRL858R/T790M/C797S IC50 = 9.9 Zhang et al. (2023)
nM
Enz EGFRL858R IC50 = 56.88 nM
Enz EGFRT790M/L858R IC50 = 32.7 nM
Enz EGFRWT IC50 = 152.2 nM
H1975 (EGFRT790M/L858R) IC50 = 468.2
nM
H1975 (EGFRL858R/T790M/C797S) IC50 =
330 nM
15 ATP binding site Non- Covalent Enz EGFRDel19/T790M/C797S IC50 = 0.31 Guo et al. (2022)
nM
Enz EGFRL858R/T790M/C797S IC50 = 0.09
nM
Ba/F3 EGFRDel19/T790M/C797S IC50 = 14
nM

16 ATP binding site Covalent Enz EGFRL858R/T790M/C797S IC50 = 110 Ferlenghi et al. (2021)
nM
Enz EGFRWT IC50 = 30 nM

17 ATP binding site Non- Covalent Enz EGFRWT IC50 = 151 nM Liu et al. (2022)
Enz EGFRDel19/L858R/T790M IC50 = 2.4
nM
Enz EGFRL858R/T790M/C797S IC50 = 3.1
nM
H1975 EGFRDel19/T790M IC50 = 0.09 nM
Ba/F3 EGFRL858R/T790M/C797S IC50 =
0.12 nM
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Table 1 (continued )
Sr. Compounds Reported site of Action Mode of Anti-tumor activity Ref.
No. Inhibition

Ba/F3 EGFRDel19/T790M/C797S IC50 =

0.09 nM
18 ATP binding site Non- Covalent Enz EGFRWT IC50 = 21.18 nM Lim et al. (2023)
Enz EGFRDel19/L858R/T790M IC50 = 1.79
nM
Enz EGFRL858R/C797S IC50 = 5.35 nM
Ba/F3 EGFRWT + EGF (10 ng/ml) IC50
= 314 nM
Ba/F3 EGFRL858R/T790M/C797S IC50 = 49
nM
Ba/F3 EGFRDel19/T790M/C797S IC50 = 202
nM
19 ATP binding site Non- Covalent Enz EGFRL858R/T790M/C797S IC50 = 0.25 Kashima et al. (2020b)
nM
A431 (EGFRWT) IC50 = 1200 nM
NIH3T3 (EGFRDel19/T790M/C797S) IC50 =
20 nM
NIH3T3 (EGFRL858R/T790M/C797S) IC50 =
45 nM

20 ATP binding site Non- Covalent A549 (EGFRWT) IC50 = 1.03 μM Wang et al. (2022a)
A431 (EGFRWT) IC50 = 2.97 μM
PC-9 EGFRL858R/T790M/C797S IC50 =
0.013 μM
Enz EGFRL858R/T790M/C797S IC50 = 0.010
μM

21 ATP binding site Non- Covalent Enz EGFRWT IC50 = 683 nM Eno et al. (2022)
Enz EGFRL858R/T790M IC50 = 0.4 nM
Enz EGFRL858R/T790M/C797S IC50 = 0.5
nM
A431 (EGFRWT) IC50 = 544 nM
H1975 EGFRL858R/T790M IC50 = 1.1 nM
Ba/F3 EGFRL858R/T790M/C797S IC50 = 3.2
nM
Ba/F3 EGFRDel19/T790M/C797S IC50 = 4.0
nM
22 ATP binding site Non- Covalent Enz EGFRWT IC50 = >150 μM Minnelli et al. (2022)
Enz EGFRL858R/T790M IC50 = 12 μM
Enz EGFRL858R/T790M/C797S IC50 = 16 μM

23 ATP binding site Non- Covalent A549 EGFRWT IC50 = 6.67 μM Palabindela et al. (2022)

24 ATP binding site Non- Covalent A549 EGFRWT IC50 = 8.18 μM Palabindela et al. (2022)

25 ATP binding site Non- Covalent EGFR IC50 = 0.597 μM Zou et al. (2021)
HER2 IC50 = 0.908 μM
A431 (EGFR) IC50 = 1.893 μM
SK-BR-3 (HER2) IC50 = 1.93 μM

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Table 1 (continued )
Sr. Compounds Reported site of Action Mode of Anti-tumor activity Ref.
No. Inhibition

26 ATP binding site Non- Covalent EGFR IC50 = 71 nM Al-Wahaibi et al. (2024)
HER2 IC50 = 31 nM
A431 (EGFR) IC50 = 25 nM

27 ATP binding site Non- Covalent Enz EGFRL858R/T790M IC50 = 12.5 nM Juchum et al. (2017)
Enz EGFRL858R/T790M/C797S IC50 = 7.64
nM

28 ATP binding site Non- Covalent Enz EGFRL858R/T790M IC50 = 8.39 nM Juchum et al. (2017)
Enz EGFRL858R/T790M/C797S IC50 = 8.83
nM

29 ATP binding site Non- Covalent A431 (EGFRWT) IC50 = 4 μM Gunther et al. (2017)
H1975 EGFRL858R/T790M IC50 = 0.4 μM
Enz EGFRL858R/T790M IC50 = <1 nM
Enz EGFRL858R/T790M/C797S IC50 = 8 nM

30 ATP binding site Non- Covalent A431 (EGFRWT) IC50 = 17 μM Gunther et al. (2017)
H1975 EGFRL858R/T790M IC50 = 7.2 μM
Enz EGFRL858R/T790M IC50 = <1 nM
Enz EGFRL858R/T790M/C797S IC50 = 7 nM

31 Allosteric site Non- Covalent Enz EGFRL858R/T790M IC50 = 0.2 nM Jia et al. (2016)
Ba/F3 EGFRL858R/T790M IC50 = >10 μM

32 Allosteric site Non- Covalent Enz EGFRL858R/T790M IC50 = 0.26 nM To et al. (2022)
Ba/F3 EGFRL858R/T790M IC50 = 0.61 μM

33 Allosteric site Non- Covalent Enz EGFRL858R/T790M IC50 = 0.063 nM To et al. (2022)
Enz EGFRL858R/T790M/C797S IC50 = 0.083
nM
Ba/F3 EGFRL858R/T790M/C797S IC50 =
0.05 μM

34 Allosteric site Non- Covalent Enz EGFRL858R/T790M IC50 = 0.3 nM Gero et al. (2022)
Ba/F3 EGFRL858R/T790M IC50 = 0.49 μM

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Table 1 (continued )
Sr. Compounds Reported site of Action Mode of Anti-tumor activity Ref.
No. Inhibition

35 Allosteric site Non- Covalent Enz EGFRWT IC50 = >1000 nM De Clercq et al. (2019)
Enz EGFRL858R/T790M IC50 = 11 nM
Enz EGFRL858R/T790M/C797S IC50 = 13 nM
Ba/F3 EGFRWT IC50 = 3.2 μM
Ba/F3 EGFRL858R/T790M IC50 = 0.36 μM
Ba/F3 EGFRL858R/T790M/C797S IC50 =
0.20 μM

36 Allosteric site Non- Covalent Enz EGFRL858R/T790M IC50 = 0.1 nM Gero et al. (2022)
Ba/F3 EGFRL858R/T790M IC50 = 0.32 μM
Ba/F3 EGFRL858R/T790M/C797S IC50 =
0.02 μM
Cetux co-dosing Cell IC50 = 0.003 μM

37 ATP binding site Non- Covalent Enz EGFRL858R/T790M/C797S IC50 = 369.2 Li et al. (2019)
nM

38 ATP and Allosteric site Non- Covalent Enz EGFRL858R/T790M/C797S IC50 = 2.2 Li et al. (2019)
nM
A549 (EGFRWT) IC50 = 1.24 μM
H1975 EGFRL858R/T790M IC50 = 3.03 μM
Ba/F3 EGFRL858R/T790M/C797S IC50 =
0.64 μM

39 Orthosteric and Non- Covalent Enz EGFRL858R/T790M/C797S IC50 = 32 nM Wittlinger et al. (2021)
Allosteric Sites Enz EGFRL858R/T790M IC50 = 51 nM
Ba/F3 EGFRWT IC50 = >10 μM
Ba/F3 EGFRL858R/T790M IC50 = >10 μM
Ba/F3 EGFRL858R/T790M/C797S IC50 =
>10 μM

40 Orthosteric and Non- Covalent Enz EGFRL858R/T790M/C797S IC50 = 4.9 Wittlinger et al. (2021)
Allosteric Sites nM
Enz EGFRL858R/T790M IC50 = 1.5 nM
Ba/F3 EGFRWT IC50 = >10 μM
Ba/F3 EGFRL858R/T790M IC50 = 4.4 μM
Ba/F3 EGFRL858R/T790M/C797S IC50 =
>10 μM

41 ATP and Allosteric site Non- Covalent Enz EGFRL858R/T790M/C797S IC50 = 0.128 Dou et al. (2022)
μM
Ba/F3 EGFRL858R/T790M/C797S IC50 =
0.75 μM
Ba/F3 EGFRDel19/T790M/C797S IC50 =
0.09 μM

42 ATP and Allosteric site Non- Covalent A549 (EGFRWT) IC50 = 1.45 μM Fan et al. (2023)
H1975 EGFRL858R/T790M IC50 = 11 μM
Ba/F3 EGFRL858R/T790M/C797S IC50 =
3.67 μM
BaF3 EGFRDel19/T790M/C797S IC50 = 3.46
μM

(continued on next page)

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Table 1 (continued )
Sr. Compounds Reported site of Action Mode of Anti-tumor activity Ref.
No. Inhibition

43 ATP and Allosteric site Covalent Enz EGFRL858R/T790M/C797S IC50 = 1.8 Wittlinger et al. (2024b)
nM
H1975 EGFRL858R/T790M EC50 = 580 nM
HCC827 EGFRDel19 EC50 = 140 nM
Ba/F3 EGFRL858R/T790M/C797S EC50 =
>10,000 nM
Ba/F3 EGFRL858R/T790M EC50 = 770 nM
Ba/F3 EGFRWT EC50 = 950 nM

44 ATP and Allosteric site Non- Covalent A549 (EGFRWT) IC50 = 5.14 μM Hu et al. (2024)
H1975 EGFRL858R/T790M IC50 = 2.95 μM
Ba/F3 EGFRL858R/T790M/C797S IC50 =
0.42 μM
Ba/F3 EGFRDel19/T790M/C797S IC50 =
0.41 μM

45 ATP and Allosteric site Covalent Enz EGFRL858R/T790M/C797S IC50 = 1.2 Wittlinger et al. (2024a)
nM
H1975 EGFRL858R/T790M EC50 = 330 nM
HCC827 EGFRDel19 EC50 = 160 nM
Ba/F3 EGFRL858R/T790M/C797S EC50 =
3900 nM
Ba/F3 EGFRL858R/T790M EC50 = 430 nM
Ba/F3 EGFRWT EC50 = 750 nM
46 ATP binding site Covalent Ba/F3 EGFRWT IC50 = 34.5 nM Zhang and Zhu (2021)
Ba/F3 EGFRexon20 ins. IC50 = 2.7–22.5
nM

47 ATP binding site Covalent EGFR exon 20 NPH insertion IC50 = 20.4 nM Wang et al. (2022d)
EGFR exon 20 ASV insertion IC50 = 20.4 nM
EGFRL858R/T790M IC50 = 1.1 nM
Her2 exon 20 YVMA IC50 = 7.5 nM
A431 EGFRWT IC50 = 80.4 nM

48 ATP binding site Covalent A431 EGFRWT IC50 = 1660 nM Murray et al. (2022)
EGFRexon20 insNPG = 7 nM
EGFRdel19/T790M IC50 = 13 nM

49 ATP binding site Non-Covalent Enz EGFRWT IC50 = >1000 nM Nishiya et al. (2021)
Enz EGFRL858R/T790M IC50 = >1000 nM

50 ATP binding site Non-Covalent EGFRdel19/T790M/C797S IC50 = 739 nM (Fukuda et al., 2021a; Nishiya
EGFRdel19/T790M IC50 = 493 nM et al., 2021)
EGFRL858R/T790M/C797S IC50 = 595 nM

(continued on next page)

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Table 1 (continued )
Sr. Compounds Reported site of Action Mode of Anti-tumor activity Ref.
No. Inhibition

51 ATP binding site Non-Covalent Enz EGFRWT IC50 = 307.7 nM Fukuda et al. (2021a)
Enz EGFRL858R/T790M IC50 = 134.8 nM

52 ATP binding site Non-Covalent Enz EGFRWT IC50 = 4.6 nM Fukuda et al. (2021a)
Enz EGFRL858R/T790M IC50 = 1.7 nM

53 ATP binding site Non-Covalent A549 EGFRWT IC50 = 178.1 μM Huang et al. (2021b)
H1975 EGFRL858R/T790M IC50 = 82.2 μM
H1975-MS35 EGFRL858R/T790M/C797S
IC50 = 47.2 μM

inhibition of EGFRL858R/T790M/C797S and EGFRL858R/T790M in H1975 cells cavity in the hydrophobic pocket, which can accommodate a molecular
with the IC50 of 1.2 μM and 3.3 μM, respectively. Furthermore, it moiety in the para-position of phenol, as shown in the figure. These
exhibited favorable microsomal stability in the liver species of humans, findings provide new structural design strategies for new potential leads
rats, and mice. Despite its promising activity, compound 2 suffered from (Fig. 5 (A) (C) (D)).
low bioavailability (F = 18.6 % in male Sprague Dawley rats). SAR and
binding mode analysis highlights that the pyrimidine moiety at the R2 4.1.2. Aminopyrimidine derivatives
position occupied the back hydrophobic pocket and interacted with the The aminopyrimidine core has proven to be a keystone in the
Met-790. The benzonitrile moiety at the R1 position contributed via development of potent EGFR inhibitors. Among the notable examples is
pi-alkyl interactions with the residue Val726. The quinazoline-core Osimertinib 6, an FDA-approved 3rd generation drug for treating NSCLC
interacted with other residues Ala-743, Lys-745, Leu-788, Asp855, and patients harboring the T790M mutation (Godin-Heymann et al., 2008;
Met-766 in the ATP binding site (Fig. 5 B) (Zhang et al., 2020). These Greig, 2016). This drug exerts its effects by covalently binding to the
insights underscored its distinct binding mode compared to other com­ ATP binding site via a bond between the acrylamide group and C797
pounds in the class. active thiol. However, the emergence of C797S mutation disrupts this
Zhou et al. also made an effort and designed six series of derivatives covalent interaction and has posed significant challenges (Thress et al.,
and evaluated their biological activities. Among these, compound 3 2015). Ding and colleagues embarked on a journey to enhance osi­
showed remarkable cell growth inhibitory effects against multiple cell mertinib’s efficacy by modifying its terminal acrylamide and N-indole.
lines, including A549, NCI-H46O, and H1975 with IC50 values of 14.33 Two compounds 7 and 8 showed better inhibitory activities than other
μM, 17.81 μM, and 13.4 μM respectively. It also demonstrated a 91 % analogues. Compound 7 showed the IC50 values of 29, 10, and 242 nM in
inhibition rate in Ba/F3-EGFRDell9/T790M/C797S cells and triggered EGFRWT, EGFRL858R/T790M, and EGFRL858R/T790M/C797S mutants, respec­
apoptosis in a dose-dependent manner. Interestingly, the binding mode tively (Ding et al., 2022). However, compound 8 displayed IC50 of 42 nM
of compound 3 was similar to compound 1. It showed interaction with against EGFRL858R/T790M/C797S mutant, prompting further evaluation.
Ser797 in EGFRT790M/C797S but did not interact with Cys797 in Further testing on cell cycle distribution assays, dual acridine orange/­
EGFRL858R/T790M (Zhou et al., 2019). In their progressive work, they ethidium bromide staining assays, along wound healing assays in H1975
identified compound 4, which showed potential activities against and A549 cell lines, revealed that compound 8 induced apoptosis and
EGFRDEL19/T790M/C797S and EGFRL858R/T790M enzymatic assays with IC50 arrest the cell cycle at the G1 or G0 phase. Another compound 9 was
values of 0.33 and 0.133 μM, respectively. It demonstrated significant reported with a terminal hydroxyl alkyl chain at indole and has
tumor growth inhibition (25 %) in in-vivo H1975-xenograft models (Xu demonstrated significant inhibiting action against triple mutant
et al., 2024). The SAR emphasized the critical role of phenolic hydroxyl (EGFR19D/T790M/C797S) showing IC50 of 15.3 nM. It shows higher selec­
group in binding to hinge residues i.e Gln-791 and Met-793. The het­ tivity over EGFR wild type (IC50 > 1000 nM) (Su et al., 2020). Moreover,
erocyclic ring attached to the amine via a small carbon chain (i.e. -CH2) 9 was able to suppress the proliferative activity of BaF3 cells (EGFR19­
del/T790M/C797S
also affected the activity of compounds (Fig. 5). ) with an IC50 value of 8.5 μM. It is seen that it also
Adding to this narrative, an aminothienopyrimidine derivative, significantly induces apoptosis and halts the cell cycle at G1 by sup­
compound 5, emerged as a notable inhibitor of the C797S triple mutant. pressing the phosphorylation of EGFR and its downstream signaling
It displayed potent inhibitory activity in H1975 and A549 cells with IC50 pathways in a dose-dependent manner (Su et al., 2020). The SAR and
of 6.90 μM and 0.77 μM, respectively. Additionally, it significantly binding mode analysis illuminated the critical role of the 4-aminopyri­
suppressed the proliferation of EGFRex19del/T790M/C797S mutant cells with midine core which anchors the compounds to the hinge region of the
an IC50 of 98.90 μM. It was also found to induce apoptosis, reduce the EGFR kinase as shown in Fig. 6 A. The long and flexible side chains on
mitochondrial membrane potential, and arrest the cell cycle at the S- the indole particularly those with terminal hydroxyl groups enhanced
phase. Importantly, it demonstrated a good safety profile with minimal the activity by interacting with the ASP-855 from the DFG motif. The
toxicity, offering strong potential for future optimization (Zhang et al., EWGs on the acryl amide also improved activity, such as pyrimidine and
2024). The docking results indicated that it has a similar binding mode 2-chloro-pyridine, stabilizing the interactions in the solvent-exposed
to compound 1. However, it can be seen that there is still a large vacant regions. The terminal side chain dimethylethylamino is also important

11
A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

Fig. 5. SAR studies and the binding mode of (A) Compound 1in 5XGN, (B) Compound 2 in 5ZWJ, (C) Compound 3 in 5XGN, and (D) Compound 4 in 5ZWJ.

for potency, as it stabilizes binding by avoiding steric clashes. pharmacokinetic (PK) profile, indicating excellent draggability (LD50 >
Chen et al. used a structure-guided macrocyclization approach and 5000 mg/kg, F = 28.07 %) (Dong et al., 2023). The SAR analysis
designed derivatives of 4-indolyl-2 phenylaminopyrimidine. This highlights the importance of indazole and indole scaffolds whose hy­
approach led to Compound 10 which potently inhibited EGFRL858R/ drophobic interactions underpin potency. The methyl and ethyl sul­
T790M/C797S
and EGFR19del/T790M/C797S mutants with IC50 of 23.6 and phonyl group at the indole moiety improved both activity and selectivity
15.8 nM respectively. Despite strong kinase inhibition and promising via hydrogen bonding with Lys-745.
cellular activities, it suffers from poor pharmacokinetics and low selec­
tivity across a broad kinase panel, indicating the need for further opti­ 4.1.3. Diaminopyrimidine derivative
mization (Chen et al., 2022). Notably, macrocyclization is suggested to Diaminopyrimidine-based inhibitor Brigatinib 12, is an FDA-
improve the potency by locking the molecule in an un-flipped confor­ approved potent and selective ALK inhibitor, that also proved effective
mation in the kinase’s ATP binding pocket (Fig. 6 B). for brain metastases (Ali et al., 2019). Appealingly, the early in-vitro
Expanding on these structural innovations Dong et al. designed a studies revealed that 12 exhibited good inhibitory activity against the
core scaffold by strategic cyclization of osimertinib, and yielded Com­ EGFRDel19/T790M/C797S cell line but did not show a satisfactory thera­
pound 11. It showed remarkable potency against EGFRL858R/T790M/C797S peutic effect (Huang et al., 2016; Uchibori et al., 2017). These findings
with an IC50 value of 14 nM. The addition of ethyl sulfonyl enhanced the prompted researchers to modify 12 to enhance its potency. Fang et al.
activity of the compound significantly, likely due to the formation of designed and synthesized a series of compounds based on the structure
hydrogen bonds with conserved LYS-745 residue (Fig. 6 C). Beyond its of brigatinib and assessed their biological activities against EGFR triple
enzymatic efficacy, compound 11 demonstrated a positive safety and mutants. Among them, compound 13 emerged as a standout,

12
 A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

Fig. 6. (A) SAR studies and the binding mode of Osimertinib derivatives and cocrystal structure of (B) Compound 10 in EGFR T790M/C797S and (C) Compound 11 in
EGFR L858R/T790M/C797S.

showcasing remarkable cellular potency against Ba/F3-EG­ phosphoryl is extended towards the solvent region. Guo et al. pushed the
FRex19del/T790M/C797S and PC9-EGFRL858R/T790M/C797S cell lines with IC50 boundaries further by introducing compound 15, a potent inhibitor with
values of 66.7 nM and 1.5 nM respectively. Beyond its potency, it low nanomolar efficacy against EGFRL858R/T790M/C797S and EGFR
del19/T790M/C797S
demonstrated good bioavailability and a favorable pharmacokinetic kinase assays with IC50 values of 0.09 and 0.31 nM,
profile in preclinical models, establishing itself as a promising candidate respectively (Guo et al., 2022). Its strategic design incorporated a benzo
for further investigation (Fang et al., 2022). The SAR and binding mode heterocyclic phosphoxy group to enhance hydrophobic interactions in
analysis shows its optimal potency against triple mutant EGFR. The the back pocket while a heterocyclic 4-membered ring with thioether at
bulkier phenyl ring1 enhanced the hydrophobic interactions in the back the piperazine tail enhances the stability as it is exposed to the solvent
pocket. However, the introduction of hydrophilic or sulfone groups region. The substitution of bromide at the pyrimidine ring is found to be
contributed to stability by engaging the solvent-exposed regions (Fig. 7). more favorable than the chloride as it enhances the potency via hy­
Zhang et al. contributed further by designing and synthesizing 2- drophobic interactions. Compound 15 not only showed strong inhibi­
amine-4-oxyphosaniline pyrimidine derivatives. Compound 14 stood tory effects but also demonstrated a positive pharmacokinetic profile
out for its antiproliferative activities against H1975 (EGFRL858R/T790M) and low toxicity (Guo et al., 2022).
and H1975 (EGFRL858R/T790M/C797S) cell lines with IC50 values of 4.7 and In the search for a more robust candidate Ferlenghi et al. developed a
0.33 μM respectively (Zhang et al., 2023). Notably, compound 14 was a sulfonyl fluoride derivative compound 16, that irreversibly inhibited
reversible, non-covalent inhibitor with favorable metabolic stability in EGFRL858R/T790M/C797S mutant through a covalent bond between sul­
rat and human liver microsomes (Zhang et al., 2023). The SAR analysis fonamide bond and Lys745. It exhibited the IC50 value of 300 nM against
underscored the critical role of alkyl substitutions at C5’ in ring-2 is EGFRL858R/T790M/C797S (Ferlenghi et al., 2021). However, its inhibitory
important for activity (Fig. 7 A). The binding mode investigation showed effect against Ba/F3 cells was short-lived, likely due to competition with
that compound 14 was arranged differently in the pocket with tail ATP. Therefore further optimization of the 2-anilinopyrimidine scaffold
morpholine directed toward Lys-745 in the back pocket. The methoxy and reactive warhead is needed to improve targeting Lys745 (Ferlenghi
group in the ring-2 and amine attached to this ring binds with the hinge et al., 2021).
residues Met-793 and Pro-794 via hydrogen bonds. The ring-1 with The evolution of these efforts culminated in compound 17, which

13
­
A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

Fig. 7. (A) The SAR studies and (B) x-ray co-crystal structure of compound 12 in EGFRL858R/T790M/C797S (PDB ID: 7ZYM).

displayed potent inhibition of kinase activities in triple mutants bonds with the Met-793 of the hinge. The tail piperidine group forms salt
EGFRL858R/T790M/C797S and EGFR19del/T790M/C797S, showcasing the IC50 bridges with the residues Glu-804 and Asp-800. Through these iterative
of 3.1 nmolL-1 and 2.4 nmolL-1 respectively (Liu et al., 2022). Cellular advancements, diaminopyrimidine-based compounds evolved into a
experiments revealed that it effectively hindered the phosphorylation promising class of inhibitors against EGFR-C797S mutants. This class of
process in BaF3 cells expressing high levels of EGFRL858R/T790M/C797S or compounds is predicted to yield a clinical candidate for cancers driven
EGFR19del/T790M/C797S. With the IC50 in the low nanomolar range, it by EGFR triple mutants.
effectively suppressed tumor growth in xenograft models, achieving
83.5 % and 136.6 % tumor growth inhibition rate (TGI) at dosage levels 4.1.4. Substituted pyrimidines
of 30 and 60 mg/kg, respectively (Liu et al., 2022). The binding mode Kashima et al. identified compound (19) through high-throughput
orientation of 17 showed that there is a hydrogen bond formation be­ screening. It is a non-covalent ATP competitive inhibitor exhibiting
tween the Lys-745 and phosphine oxide, in addition to a bidentate sub-nanomolar potency in EGFRDel19/T790M/C797S and EGFR L858R/T790M/
C797S
hydrogen bonding between the aminopyrimidine core and hinge biochemical assay with IC50 value of 0.28 and 45 nmol/L respec­
Met-793 (Liu et al., 2022). tively. It effectively blocks EGFR phosphorylation in NIH3T3 cells with
BBT-176 (compound 18) is another promising 4th generation tyro­ an IC50 0f 20 nM with higher selectivity over EGFR wild type (Kashima
sine kinase inhibitor which is currently in the clinical trial. This com­ et al., 2020a). The binding mode analysis revealed that compound 19
pound showed strong inhibitory effects in Ba/F3-EGFR19del/T790M/C797S anchors firmly to the hinge region via hydrogen bonds with Gln-791 and
cells with an IC50 value of 49 nmol/L. It showed minimal off-target ef­ Met793. The sulfonyl from the cyclopropylsulfonyl-pyrazole interacts
fects, with significant tumor regression in preclinical models (Lim et al., with Lys-745, while pyrazole and pyrimidine ring are directed towards
2023). The SAR analysis underscores the importance of sulfone modi­ the Met-790. Interestingly due to its ability to bind with EGFR-αC-he­
fications in ring1 and the piperidine group in the tail for enhancing the lix-in conformation, enhanced its activity against EGFRDel19/T790M/C797S
potency and selectivity of the compound. The interaction analysis (Fig. 8 A).
showed that the aminopyrimidine of compound 18 forms hydrogen The journey continued with the work of Wang et al. they identified a

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A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

Phenylpyrrolo-pyrimidineamine scaffold through another high EGFRex19del, H1975-EGFRL858R/T790M, A431-EGFRWT, Ba/F3-

throughput screening approach. By exploring the SAR, they discovered EGFRL858R/T790M/C797S and Ba/F3- EGFRex19del/T790M/C797S cell lines
compound 20 which showed potency against EGFRL858R/T790M/C797S respectively (Eno et al., 2022). The SAR and binding mode analysis of
with IC50 of 0.010 μM. It also effectively inhibited the proliferation in compound 21 revealed that naphthyridine core forms essential
PC-9 cells (EGFRL858R/T790M/C797S) with the IC50 of 0.013 μM (Wang hydrogen bonds with Met-793 and Gln-791. The piperidinol ring forms
et al., 2022a). The SAR and binding mode analysis revealed that the hydrogen bond with the Lys-745 in the back pocket. The azetidine ring
substitution of cyclo-pentyl at the R3 position of pyrrolo[2,3-d] pyrim­ with sulfone substitution improved potency via interacting with Lys-716
idine scaffold showed optimal activity with hydrophobic interactions and Lys-728. The addition of azetidine with sulphone substitution also
near the hydrophobic pocket. The larger groups at the R4 position improved the potency and selectivity of the compound (Fig. 8C). Com­
induced steric hindrance and results in loss of key hydrophobic in­ pound 21 has demonstrated promising in-vivo efficacy in tumor xeno­
teractions (Wang et al., 2022a). The substitution of piperidine at 4-posi­ graft models, and exhibited a favorable safety profile, paving the way for
tion of phenyl maintained the activity of the compound via stabilizing it clinical trials. Currently, it is undergoing phase I/II clinical trials (Shum
in solvent-exposed region while other groups like N-morpholino or et al., 2022). It is being tested as a single agent and in combination with
1-(2-methoxyethyl)piperazine reduced the activity of compounds (Fig. 8 Osimertinib. The final results will reveal its role in combating the C797S
B). mutation.
Among these discoveries, another breakthrough emerged with the
2,7-naphthyridine-based derivative Compound 21. This inhibitor 4.1.5. Nitroffavone and tryptanthrin derivatives
exhibited broad spectrum efficacy against EGFR mutants. It exhibited By the virtual screening, Minnelli Cristina and others identified a
IC50 values of 130 nM, 1.1 nM, 544 nM, 3.2 nM and 4.2 nM in PC9- mutant selective core, a flavone that was rationally modified to develop

Fig. 8. (A) The x-ray co-crystal structure of compound 19 in EGFRL858R/T790M/C797S (6LUB) (B) The SAR and binding mode of compound 20 and (C) compound 21.

15
A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

compound 22. It reversibly inhibits EGFRL858R/T790M/C797S and gained from the in-vitro studies provided valuable directions for struc­
EGFRL858R/T790M mutants with a higher affinity. It shows IC50 values of tural refinement. For instance, the side-chain modification was shown to
16 μM and 12 μM in EGFRL858R/T790M/C797S and EGFRL858R/T790M, significantly influence compound’s physiochemical properties.
respectively, showing high selectivity over EGFR wild type (IC50= >150 Substituting the heterocyclic moiety on the acrylamide facilitated pi-pi
μM). The SAR and binding mode analysis revealed that the C6- stacking involved in various hydrophobic interactions with Leu-718,
nitrophenoxy moiety on flavone provides strong and stable in­ Val-726, Ala-743, Met-766, Leu-799, and Met793. Meanwhile, incor­
teractions with hinge residues, while the C3′-phenoxy moiety further porating bulky and hydrophobic substituents at the C4-position of the
enhanced the activity (Fig. 9 A). The efficacy of 22 in the in-vivo has not quinoline further strengthened the binding affinity via hydrophobic
been mentioned yet and still needs further study (Minnelli et al., 2022). interactions (Fig. 10 A) (Zou et al., 2021).
In another effort, a series of aminothiazole-induced tryptanthrin de­ Compound 26 is also discovered as a dual-targeting inhibitor of
rivatives were tested against cancer cell lines as prospective anticancer EGFR/HER2. It exhibited remarkable potency in the EGFR and HER2
agents and EGFR inhibitors. Two compounds, 23 and 24, showed better kinase assay, with IC50 values of 71 nM and 31 nM. In addition, com­
activity against the growth of A549 with IC50 values of 6.67 and 8.18 pound 26 demonstrated a strong anti-proliferative effect against the
μM, respectively. The SAR analysis highlights tryptanthrin amino­ A549 cell line, with an IC50 value of 25 nM. It triggered apoptosis
thiazole with methoxy and cyano group substitution on phenyl, which is through multiple mechanisms, such as activating caspase-3, caspase-8,
directly connected to the thiazole ring, showed better activity in EGFR and Bax, while suppressing Bcl-2 levels, which is a key anti-apoptotic
kinase. However, the -Br and -Cl substitutions showed moderate activity. protein (Al-Wahaibi et al., 2024). The SAR and interaction mode anal­
It is also revealed that substitution at thiazole ring N-atom causes steric ysis of compound 26 shed light on its structure-function relationship.
conflicts with key residues in the binding pocket. The molecular docking Substitutions at the 1- and 6- positions of the core introduced steric
analysis shows that 23 and 24 interact with EGFR by hydrogen bonds hindrance, disrupting critical interactions with residues such as Pro-794,
through some key amino acids Thr-830, Asp-831, and Lys-721 (2.736), Phe-795, and Met-793. Conversely, incorporating a sulfonamide group
respectively (Fig. 9 B) (Palabindela et al., 2022). Together, these find­ with an electron-withdrawing group, such as pyrimidine, enhanced in­
ings underscore the potential of these compounds while leaving room for teractions with critical residues Lys-745 and Thr-854. Furthermore,
further optimization and validation. modifications at the 1- position of the quinoline scaffold were found to
diminish activity as shown in Fig. 10 B.
4.1.6. Quinoline derivatives
Quinoline-based heterocyclic compounds have emerged as a crucial 4.1.6.1. Trisubstituted imidazole derivatives. Trisubstituted imidazoles
scaffold in drug discovery due to their ability to inhibit tyrosine kinase are valuable scaffolds in drug design, offering a balance of structural
activities (Wissner et al., 2007). Focusing on the scaffold’s importance, rigidity and functional diversity that enhances biological activities and
various derivatives were designed and screened against EGFR/HER2 target specificity (Günther et al., 2016). Compounds based on trisub­
receptors. Zou et al. identified compound 25, which emerge as a dual stituted imidazoles originally optimized for targeting EGFRL858R/T790M
inhibitor with IC50 of values of 0.597 μM for EGFR and 0.908 μM for demonstrated unexpected potency against EGFRL858R/T790M/C797S.
HER2. The compound demonstrated potent apoptotic-inducing capa­ Compounds 27 and 28 featuring aliphatic alcohol moieties were eval­
bilities, as revealed in Cell cycle analysis and apoptosis experiments. uated as reversible inhibitors targeting the EGFRL858R/T790M/C797S. These
Despite it’s potential, compound 25 is an early-stage candidate requiring compounds demonstrated promising inhibitory activity suggesting their
further optimization and investigation (Zou et al., 2021). The insights potential as effective alternatives to irreversible TKIs. Furthermore, their

Fig. 9. The SAR and binding mode of (A) Compound 22 and (B) Compound 23 in EGFR kinase.

16
A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

Fig. 10. SAR studies and the binding mode of (A) Compound 25 in EGFR, (B) Compound 26 in EGFR.

kinase selectivity was further characterized through p38α MAP kinase kinase and affecting the potency. The isoindolinones contribute to the
inhibition screening (Juchum et al., 2017). In another study compounds specificity of the compounds by snugly fitting into the allosteric pocket.
29 and 30 found to be effectively inhibit triple mutant The thiazoleamide helps anchor compounds in the allosteric site via key
EGFRL858R/T790M/C797S with single digit IC50 values of 8 nM and 7 nM hydrogen bond interaction with Asp-855 from the DFG motif. The
respectively (Gunther et al., 2017). Different substitutions on the imid­ phenolic hydrogen forms a hydrogen bond with Phe-856, stabilizing the
azole core form multiple interactions with different residues in the ATP inactive conformation. The phenyl group engages in the pi-pi stacking
binding site. The binding mode analysis of 27 and 28 revealed that they interaction with Phe-723 in p-loop and piperazine or piperidine shows
strongly interact with the hinge region via bidentate hydrogen bonds critical interaction with Glu-749 and Glu-758 (Fig. 11 A). De Clercq et al.
between the central pyridinylimidazole and Met-793. The also identified another compound 35, a dibenzodiazepinone derivative
para-fluorophenyl ring is oriented toward the Met-790 while the with a phenylpiperazine group, as a potent and selective allosteric in­
aliphatic alcohol side-chain is targeted towards the Asn-842 to form a hibitor. It exhibited strong inhibitory activity against EGFRL858R/T790M
hydrogen bond (Juchum et al., 2017). Compounds 29 and 30 bind to the EGFRL858R/T790M/C797S mutants in biochemical assays, with IC50 values
hinge via aminopyridine with acrylamide or propionamide directed of 11 and 13 nM respectively. Additionally, in combination with
toward the Cys-797 or Ser-797. Additionally, these compounds establish cetuximab, It demonstrated significant anti-proliferative effects in BaF3-
interaction with the Asp side chain in the DFG-motif, contributing to EGFRL858R/T790M cells (IC50 = 0.36 μM) and BaF3-EGFRL858R/T790M/C797S
their inhibitory potency (Gunther et al., 2017). cells (IC50 = 0.20 μM) (De Clercq et al., 2019).
All these allosteric inhibitors depend on the combination with
4.2. Allosteric inhibitors cetuximab to show effective antiproliferative activity against BaF3-
EGFRL858R/T790M/C797S. To overcome this limitation, Thomas and co-
The allosteric kinase inhibitors are potential non-irreversible in­ workers reported a series of allosteric inhibitors based on the scaffold
hibitors with effective responses against C797S mutation as they are the hopping approach. The optimized compound 36 containing quinazoli­
alternative approach as compared to the ATP competitive inhibitors. none scaffold delivered significant potency without the phenol group.
(EAI045 (31), JBJ-04-125-02 (32), JBJ-09-063 (33), and 34 are some Compound 36 achieved tumor regression upon 25 mg/kg and 50 mg/kg
isoindolinones-based identified allosteric inhibitors with a phenolic dosage per day administration in H1975 (EGFRL858R/T790M) tumor effi­
group. EAI045 (31), individually, has very small cellular and in vivo cacy model; both doses were well tolerated (Gero et al., 2022). (36)
activity (Jia et al., 2016). JBJ-04-125-02 (32) was able to demonstrate exhibited good in-vivo efficiency with an oral bioavailability of 24 %.
good antiproliferative activity in a Ba/F3 EGFRL858R/T790M cell assay as a The co-crystal structure of (36) in EGFRT790M/V948R showed how it in­
single-agent but poor bioavailability along with disappointing oral PK teracts with different residues. The amide NH forms a hydrogen bond
profile (Niggenaber et al., 2020; To et al., 2019). To improve the with the Asp-855 while the quinazolinone core positions the phenyl
bioavailability and permeability by reducing the number of hydrogen piperidine in the grove next to the alpha-C helix, which allows the
bond donors, the N-methyl piperazine (34) and N-methyl piperidine interaction between piperidine nitrogen and Glu-758. As the hydroxyl
JBJ-09-063 (33) were prepared, but they did not significantly impact group is absent on the phenyl ring the hydrogen bond with Glu-758 was
oral exposure. The enhanced in vivo potency was observed for (33) with missing (Fig. 11 C) (Gero et al., 2022). The isoindolinones and quina­
tumor regression against triple mutant (EGFRL858R/T790M/C797S) model zolinone cores both attain same binding mode in the allosteric pocket
upon a 50 mg/kg dose per day on a cost of effect on EGFRWT (To et al., however the slight increase in the potency has been seen in compound
2022). (36) with 5-fluorine quinazolinone core.
The SAR and interaction analysis of isoindolinones-based com­
pounds explained how different structural components interacted with

17
A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

Fig. 11. (A) The SAR analysis of isoindolinones, (B) The x-ray co-crystal structure of Compound 33 and, (C)compound 36 in EGFRT790M/V948R.

4.3. Bivalent inhibitors a high clearance rate, limiting its pharmacokinetic profile (Li et al.,
2019).
The bivalent inhibitors simultaneously bind to the orthosteric site Wittlinger et al. identified compounds 39 and 40 featuring a pyr­
(ATP binding site) and the allosteric site of the EGFR kinase. By engaging idinyl imidazole-fused benzylisoindolinedione scaffold. They target
two sites, these types of inhibitors achieve stronger inhibitory effects. both ATP and allosteric sites. In kinase assay, 40 with acryl amide war
The two pharmacophores of a bivalent inhibitor are often connected by a head demonstrated IC50 values of 4.9 and 47 nM against EGFRL858R/
T790M/C797S
flexible or rigid linker, which ensures the simultaneous occupation of and EGFRWT, respectively. Compound 39 with amide
both sites. Li, Q. et al. developed a series of reversible inhibitors by showed IC50 values of 32 and 5.8 nM against EGFRL858R/T790M/C797S and
modifying the structure of vandetinib (37) among which compound 38 EGFRWT, respectively. Compound 40 was found to be more selective
demonstrated the most promising activity against EGFRL858R/T790M/ than compound 39 (Wittlinger et al., 2021). 40 demonstrated modest
C797S
(IC50 = 2.2 nM) by effectively binding both the ATP and allosteric cetuximab-independent and mutant-selective cellular efficacies at the
sites. It also exhibited significant anti-proliferative activities against cellular level in single EGFRL858R (2.0 μM) and double mutants
BaF3-EGFRL858R/T790M/C797S cells with IC50 value of 0.64 μM (Li et al., EGFRL858R/T790M (4.4 μM). Furthermore, for EGFRL858R/T790M/C797S the
2019). The binding mode analysis revealed that its quinazoline core exhibited IC50 value was greater than 1.1 μM. The binding mode analysis
forms a crucial hydrogen bond with Met-793 in the ATP binding site, of compound 39 in T790M mutant EGFR showed how they span in the
stabilizing the binding conformation. Additionally, the ATP and allosteric sites and interact with various residues (Fig. 12 A).
oxoisoindolin-2-phenylacetamide moiety extend into the hydrophobic The aminopyridine moiety anchors the inhibitor in the ATP site via a
allosteric site where the phenyl group engages in pi-pi stacking with hydrogen bond with the Met-793. The imidazole moiety forms a
Phe-856, a key interaction for potency. The SAR investigation further hydrogen bond with Lys-745. The phenylamide linkage interacted with
confirmed that replacing the phenyl group with cyclohexane drastically the Thr-854 and Asp-866. For compound 40, it was expected that the
reduced activity, while the fluorine substitution enhances the binding methoxyphenyl acrylamide would position itself toward Cys-797 to
affinity through hydrophobic and electrostatic interactions. However, form a covalent bond (Wittlinger et al., 2021).
preliminary rat studies on compound 38 indicated its poor solubility and Dou et al reported a 4-anilinoquinazoline derivative compound 41

18
A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

that simultaneously occupied the allosteric and ATP binding sites (Dou reduce potency (Fig. 12 B). These changes to the linker result in a loss of
et al., 2022). This inhibitor would span both the allosteric site and ATP critical interactions with the residues Lys-745, Met-766, and Met793
binding site. It exhibited strong anti-proliferative effects in due to steric clash. The substitution allosteric component on the phenyl
BaF3-EGFR19del/T790M/C797S cells (IC50 = 0.09 μM) and 4-position was more suitable than the 3-position. The binding mode
BaF3-EGFRL858R/T790M/C797S cells (IC50 = 0.75 μM). Furthermore, it analysis of (42) in EGFRT790M showed that the quinazoline moiety fits in
inhibited downstream signaling by inhibiting the EGFR autophosphor­ the ATP binding site by making a hydrogen bond with the hinge
ylation in BaF3 cells expressing EGFR19del/T790M/C797S mutation and Met-793. The methylene amide linker enhances flexibility and allows
demonstrated significant anti-cancer activity in the xenograft model better alignment of the phenylamide moiety in the allosteric pocket,
(Dou et al., 2022). The interaction analysis of the compound showed where it forms hydrogen bonds with the Lys-745 and Met766 and
that the phenyl group contributed to the hydrophobic interactions with pi-stacking interaction with the Phe-856.
the residues in the allosteric pocket. Wittlinger et al. developed and characterized C-linked and N-linked
Fan et al. designed a series of pyrrolopyrimidine and quinazoline- bivalent inhibitors to compare their effectiveness in inhibiting EGFR
based derivatives fused with EAI001, which serve as allosteric compo­ kinase activity. The C-linked bivalent inhibitors demonstrated superior
nents. Compound 42 exhibited moderate inhibitory activity against potency, with the IC50 values in the range of 0.063–0.064 nM against
H1975-EGFRL858R/T790M and Ba/F3-EGFRdel19/T790M/C797S with the IC50 EGFRL858R/T790M/C797S whereas N-linked inhibitors were significantly
value of 11 μM and 3.46 μM. It could potentially inhibit the proliferation weaker (Wittlinger et al., 2024b). The C-linked Compound 43 was
of Ba/F3-EGFRL858R/T790M/C797S (IC50 = 3.67 μM); however, it showed identified as the most potent inhibitor effectively suppressing EGFR
more potency against Ba/F3-EGFRWT (1.45 μM) (Fan et al., 2023). The phosphorylation and downstream signaling (pERK and pAKT). The
SAR investigation of this compound series revealed that lengthening the binding mode analysis showed that it C-linked amide linker facilitated
linkage between the quinazoline and phenyl ring enhances potency, additional hydrogen bonds with Thr-854 and Asp-855 which were ab­
while simple alkylation, over-extension, or bulkier groups (e.g., CONH2) sent in N-linked analogues. The C-linked benzo moiety adopted an

Fig. 12. (A) The binding mode of compound 39 in EGFRT790M/V948R, (B) Structure-activity of Compound 42 and, (C) Compound 44.

19
A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

inward conformation leading to better pocket fit and water displace­ 4.5. Natural inhibitors
ment (Wittlinger et al., 2024b).
Hu, L. et al. also develop a bivalent inhibitor by combining the 1- Natural products provide a vast reservoir for discovering new hits
oxoisoindolin-2-yl group and aminopyrimidine scaffold via a linker and leads in modern drug development. Many plant-driven compounds
phenyl group (Fig. 12 C). Compound 44 was found to be the most potent possess antitumor effects and can have therapeutical potential (Guo
among the series as it showed IC50 values of 0.42 μM and 0.41 μM in Ba/ et al., 2024; Hashim et al., 2024). To find a novel inhibitor Nishiya, and
F3-EGFRL858R/T790M/C797S and Ba/F3-EGFRdel19/T790M/C797S cells. It in­ his coworker found 49 (lamellarin N) which was found to be effective
duces apoptosis at the concentration of 0.8 μM in NCI-H1975- against the EGFRC797S mutant. Its derivative lamellarin 14 (50) reduced
EGFRL858R/T790M/C797S cells. However, it did show selectivity over the viability of cells expressing the EGFRdel19/T790M/C797S triple mutant,
EGFRWT. The binding mode of compound 44 analysis showed that the 2- as well as cells expressing EGFRdel19/T790M and EGFRL858R/T790M/C797S
aminopyrimidine is a critical pharmacophore as it forms a hydrogen with the IC50 values of 739 nM, 493 nM and 595 nM respectively in PC-9
bond with the Met-793 in the ATP site. At the same time, the 4-(piper­ cell line (Nishiya et al., 2021).
azin-1-yl) phenyl substitution improves the binding via favorable hy­ Compound 51, a man-made lactam derivative inspired by the marine
drophobic interactions in the allosteric pocket. The linker phenyl group natural compound lamellarin 14 and its derivatives, were prepared and
forms weak H-pi-interaction with the Lys745 (Hu et al., 2024). assessed as effective, non-covalent inhibitors for T790M/L858R double
Wittlinger, F. et al. developed and optimized a series of reversible mutant. These synthetic azalamellarin analogues demonstrated notable
and irreversible bivalent “Type V” inhibitors based on trisubstituted inhibitory activities in an in vitro kinase assay and were found to surpass
imidazole. Compound 45 emerged as the most potent and demonstrated the corresponding lamellarins (Fukuda et al., 2021a). Notably, the
the IC50 of 1.2 nM in EGFRL858R/T790M/C797S biochemical assays. It also azalamellarin derivative 52 demonstrated the highest inhibitory activity
exhibited significant antiproliferative activities against EGFRL858R/ against the double T790M/L858R mutation, with an IC50 value of 1.7
T790M/C797S
, and EGFRL858R/T790M in Ba/F3 cells with the EC50 values of nM, compared to 4.6 nM for the wild type EGFR. The observed inhibi­
0.15 μM and 0.43 μM respectively (Wittlinger et al., 2024a). The binding tory activity was attributed to the hydrogen bond between NH group of
mode of (45) showed that the 2-aminopyridine moiety forms a hydrogen the lactam and the carbonyl group of a methionine residue 793 (Fig. 13)
bond with Met-793, anchoring the inhibitor in the ATP site while the (Fukuda et al., 2021b).
imidazole core interacts with catalytic Lys-745, further strengthening Another compound, Quercetin (53), was tested for its cytotoxic ef­
the binding. The hydroxyphenyl isoindolinone moiety binds to the fect on the culture of NSCLC cells harboring C797S mutation. It showed
allosteric site forming hydrogen bonds with Thr-854 and Asp-855 while an IC50 value of 47.2 μM in H1975-MS35 (EGFRL858R/T790M/C797S) cell
engaging in the pi-stacking with Phe-856 (Wittlinger et al., 2024a). line (Huang et al., 2021a). Although these compounds exhibited anti­
The molecular weight and the number of Hydrogen bond acceptors tumor activity, they suffer from limited availability at the targeted site
and donors increased significantly, resulting in low cellular perme­ and kinase selectivity. However, these compounds can serve as struc­
ability. Other than this, the selectivity is also an issue. There is still much tural scaffolds for developing new EGFR inhibitors.
work that has to be done on this type of inhibitor to achieve effective
inhibition and a better PK profile. 5. Artificial intelligence and EGFR TKIs

4.4. EGFRexon20 insertion inhibitors AI, particularly deep learning (DL) and large language models (LLM),
has revolutionized drug discovery by enabling target identification,
Exon 20 insertions (ex20ins) in EGFR represent the third most repurposing, property and activity prediction, and lead compound
common mutations, accounting for a prevalence rate of 4–9 % among all generation and optimization. These technologies enable rapid identifi­
documented EGFR mutations (Oxnard et al., 2013; Yasuda et al., 2012). cation and validation of potential drug targets by analyzing large data­
They constitutively upregulate kinase activity and develop as resistance sets including gene expression profiles, biological pathways, and
to both first and second-generation TKIs. Mobocertinib (46) was protein-protein interaction networks (Yadav and Tripathi, 2018). ML
designed to address NSCLCs at the molecular level by selectively tar­ algorithms, such as recursive neural networks (RNN), graph convolu­
geting these EGFR ex20ins mutants. It exhibited favorable efficacy in tional networks (GCN), and knowledge graph embedding (KGE)
phase 1 & 2 clinical studies with significant inhibitory activity in
wild-type and EGFR ex20ins (IC50 = 34.5 nM and IC50 = 2.7–22.5 nM,
respectively). However, it showed some prevalent side-effects like skin
rash and diarrhea; other than these, some adverse events like pulmonary
toxicity, cardiotoxicity, fetal-embryo toxicity, and gastrointestinal
toxicity were also observed (grade 3 or higher Treatment-related
adverse events 35–50 %) (Kobayashi and Mitsudomi, 2016; Naidoo
et al., 2015; Wang et al., 2022b).
Another inhibitor, Sunvozertinib (47), sharing the same amino-
pyrimidine scaffold with mobocertinib, was developed as an oral, irre­
versible, and selective inhibitor. It demonstrates potent antitumor ac­
tivity in both cell lines and xenograft models (Wang et al., 2022d). In
ongoing phase I clinical studies, sunvozertinib has been well-tolerated
up to 400 mg once daily. Both preclinical and phase I clinical data
indicate a favorable safety, pharmacokinetic (PK), and efficacy profile
for sunvozertinib (Wang et al., 2022c). BLU-451 compound 48 is also a
new covalent inhibitor of EGFRexon20ins. It is a CNS penetrant that can
cross blood-brain barriers and would be effective in brain metastasis
(Pearson et al., 2022). It can selectively inhibit EGFRexon20ins, sparing
wild-type EGFR. The phase I/II clinical trial is ongoing (Spira et al.,
2022).
Fig. 13. The binding mode of compound 52 in EGFRL858R/T790M/V948R(Fukuda
et al., 2021a).

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A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

techniques (Wang et al., 2024b) are further advancing the process of models through trial-and-error approaches, rewarding desired out­
identifying drug targets and predicting drug properties by utilizing comes, and penalizing the undesired ones (Botvinick et al., 2019). Deep
biomolecular structures and clinical records. Models like AlphaFold2, reinforcement learning and diffusion models, further enhance the dis­
ESMFold and EMBER3D offer advanced capabilities in protein structure covery process that has been used in SBDD like de novo drug design
prediction (Bertoline et al., 2023; Lin et al., 2023). (Shoaib et al., 2025; Ståhl et al., 2019; Zhou et al., 2019).
The power of AI is also being harnessed in drug screening and drug Several AI-driven models have been specifically applied to generate
repurposing. ML algorithms can process diverse datasets, including novel inhibitors for EGFR, which is a critical target in cancer therapy
molecular structures, biological activity profiles and clinical data to showcasing the potential of these technologies in cancer therapy. Such
identify potential drug candidates with remarkable precision. Advanced as, SBMolGen (Structure-Based de Novo Molecular Generator) integrates
AI tools, like PockDrug, predict druggable pockets on proteins while Monte Carlo tree-based search and docking simulations to generate
deep learning (DL) models like AlphaFold enhance these predictions by novel molecules for various targets (Fig. 14 A) (Ma et al., 2021). The
providing detailed structural insights (You et al., 2022). These combi­ RNN model in SBMolGen was trained on 250,000 molecules from the
nations aid in discovering novel drugs and repurposing existing ones for ZINC database and was benchmarked with EGFR and three other target
challenging targets like EGFR (Khan et al., 2024; Kojima et al., 2022; proteins (Irwin et al., 2012; Mysinger et al., 2012). The ATNC model
Rombach et al., 2022). combines attention (AT) and differentiable neural computer (DNC)
DL-based generative models focus on algorithms that are capable of modules to generate valid and novel SMILES strings and identify stable
generating novel data samples resembling the underlying patterns and small-molecule structures for EGFR and other kinases (Putin et al.,
distribution of the training datasets (Tropsha et al., 2024). These models 2018). Another approach utilizes fine-tuned GPT-2 and long short-term
use molecular descriptors that are represented as vectors in high (LSTM) models to design inhibitors from extensive bioactive ligands’
dimensional spaces, processed through neural network architectures datasets by post-generation filtering ensuring drug-like properties.
such as recurrent neural networks (RNN) (Mandic and Chambers, 2001), Comparative studies revealed that LSTM showed superiority in pro­
variational autoencoders (VAE) (Kingma, 2013) and graph convolu­ ducing valid and potent inhibitors with stronger binding affinities
tional neural networks (GCN) (Ma et al., 2019), etc. Reinforcement (Dasser et al., 2024). Another more advanced DeepILC model was
learning (RL) adds another dimension to drug discovery by training DL introduced by Zhung et al. based on the 3D generative framework that

Fig. 14. EGFR tyrosine kinase inhibitor generation with higher binding affinities, (A) compound generated by SBMolGen model and, (B) Compound generated by
using GLDM model.

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A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

incorporates universal protein-ligand interaction patterns, such as 6.1. ATP site inhibitor
hydrogen bonds and hydrophobic interactions, to guide ligand design.
By focusing on local interactions within binding pockets, DeepICL can Several ATP site inhibitors have been designed and evaluated,
distinguish mutant EGFR from the wild type, enabling the design of demonstrating promising anti-tumor activities against EGFR C797S tri­
mutant selective inhibitors (Zhung et al., 2024). ple mutants. Compounds based on aminopyrimidine (Dong et al., 2023;
As other generative model approaches rely on training with activity Su et al., 2020), diaminopyrimidine (Guo et al., 2022; Zhang et al.,
data for a specific target protein. The 3D generative models can be 2023), and 2,7-naphthyridine (Shum et al., 2022) have shown encour­
helpful in data-limited scenarios by leveraging structural knowledge to aging activities in both in-vivo and in-vitro essays. However, some of the
guide molecule generation. Recently, latent diffusion Models (DMs) compounds face challenges with bioavailability and selectivity (Zhang
have emerged as a powerful approach for generative tasks by operating et al., 2020; Zhou et al., 2021). These inhibitors bind to the ATP site
in the compressed latent space. They demonstrated superior perfor­ through their core scaffolds, interacting with some key hinge residues
mance in generating valid, unique and novel molecules. Wang et al. Gln-791, Met-793, Cys-797, and mutated S797. Specific substitutions on
reported a graph latent generative model (GLDM) for generating po­ the scaffolds enhance hydrophobic interactions in the back pocket with
tential drug candidates with higher binding affinities (Fig. 14 B). The residues Ala-718, Val726, Ala-743, Leu-788, and Asp855. Additionally,
generated molecule was found to be more drug-like and easy to syn­ incorporating sulfone or phosphine groups facilitate additional
thesize (Wang et al., 2024a). hydrogen bond interaction with Lys-745. Despite the encouraging re­
MORLD (Molecule Optimization by Reinforcement Learning and sults, many compounds require further structural optimization, partic­
Docking) is a deep generative model that optimizes the compounds ularly to improve the efficacy, selectivity and pharmacokinetic profile
using reinforcement learning, guided by docking simulations that serve for better clinical outcomes.
as feedback. MORLD employs molecule deep q-networks (MolDQN) to
refine chemical structures based on binding affinities and chemistry 6.2. Allosteric inhibitor
domain knowledge (Jeon and Kim, 2020; Zhou et al., 2019). Collec­
tively, AI-driven methodologies have opened new avenues in EGFR in­ Allosteric inhibitors provided a breakthrough in targeting the
hibitor design. They offer tools to generate, optimize, and evaluate novel EGFRL858R/T790M/C797S (Zhao et al., 2018). However, these inhibitors
compounds. From generative modeling to reinforcement learning and exhibit limited inhibitory activity against EGFRdel19/T790M/C797S variant
advanced architectures like DeepICL and GLDM, these technologies (Jia et al., 2016). To enhance their effectiveness, a combination with
demonstrate the potential of AI in addressing critical biotargets, offering monoclonal antibody is often necessary (To et al., 2019; Tripathi and
innovative solutions. Biswal, 2021). Quinazolinone and Isoquinolinone-based allosteric in­
hibitors have demonstrated promising anti-tumor activities (Gero et al.,
6. Conclusions 2022). The Thiazoleamide in their structure helps these compounds
anchor in the Allosteric site by interacting with the Asp-855 and
EGFR plays a significant role in the progression of non-small cell lung Phe-856. Additional interactions with residues like Phe-723, Glu-749
cancer (NSCLC). Various drugs, including gefitinib, erlotinib, and Osi­ and Glu-758 further stabilize their binding. Nonetheless, the efficacy of
mertinib, have been employed as tyrosine kinase inhibitors in clinical allosteric inhibitors can be compromised by restricted access to the
treatments. However, their effectiveness is halted due to the emergence subunits of the EGFR dimer. Therefore, Further work is essential to
of resistance mutations (i.e. C797S). Several inhibitors based on enhance their potency.
different scaffolds and binding interactions have been developed and
reported as ATP site, Allosteric site, and bivalent inhibitors to overcome 6.3. Bivalent inhibitor
resistance. Different types of EGFR inhibitors based on their mechanism
of action and key interactions have been Summarized in Table 2. Bivalent inhibitors have shown moderate cellular potency against

Table 2
Summary of different types of EGFR inhibitors based on their mechanism of action and key interactions.
Type of EGFR Subtype Mechanism of action/Key interactions Key Features
Inhibitor

ATP-site Aminoquinazoline derivatives • Bind competitively to the ATP-binding pocket. Selective for mutant EGFR (e.g., L858R,
Inhibitors • Form hydrogen bond with Gln-791 and Met-793. exon19 del., C797S).
• Interact with mutated residues Met-790 and Ser-797.
Aminopyrimidine derivatives • Form hydrogen bond with Met-793. Effective against EGFR triple mutants.
• Sulfonyl group interacts with catalytic Lysine 745. (EGFRL858R/T790M/C797S and EGFR19del/T790M/
C797S
).
Diaminopyrimidine derivatives • Form hydrogen bonds with Met-793, Pro-794. Selective inhibition of triple mutant EGFR.
• Engage Lys-745 in the back hydrophobic pocket. Preclinical focus (Compound BBT-176).
• Additional Interactions with Glu-804 and Asp-800.
Substituted pyrimidines • Form hydrogen bonds with Gln-791, Met-793. High potency against C797S-EGFR mutants.
• Engage hydrophobic pocket residues. BLU-945 undergoing phase I/II clinical trials.
• Sulphone substitution enables interaction with Lys-745.
Nitroffavone and Tryptanthrin • Form hydrogen bonds with Lys-721, Thr-880, Asp-831. Potent against wild-type and some resistant
derivatives mutants.
Quinoline derivatives • Interact with various residues Pro-794, Phe-795, Met-793, Lys- Show dual potency against EGFR and HER2.
745, Thr-854. Leu-718, Val-726, Ala-743, Met-766, and Leu-
799.
Trisubstituted imidazole derivatives • Form hydrogen bonds with Met-793. Potency against EGFRL858R/T790M and
• Engage Met-790 and Cys/Ser-797 residue. EGFRL858R/T790M/C797S.
Allosteric Isoindolinones, dibenzodiazepinone, and • Form hydrogen bonds with Asp-855, Phe856. Often used in combination with cetuximab for
Inhibitors quinazolinone derivatives. • Additional interactions with Phe-723, Glu-749 and Glu-758 EGFRL858R/T790M/C797S.
Bivalent ​ • Simultaneously Interacts with ATP and allosteric site. Showed potency against EGFRL858R/T790M/
C797S.
inhibitors • Some important interacting residues are Lys-745, Met-793, But challenges with cellular
Met-766, Thr-854, Asp-855, Phe-856, Asp-866. permeability.

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A. Tariq et al. European Journal of Pharmacology 997 (2025) 177608

EGFRL858R/T790M/C797S and EGFRdel19/L858R/T790M variants. These com­ While these scaffolds have proven effective in designing effective in­
pounds are likely to form strong, deep binding interactions with EGFR, hibitors like gefitinib and osimertinib, their limited diversity poses a
which may facilitate the discovery of highly effective inhibitors (Dou challenge in addressing resistance mechanisms and targeting a broader
et al., 2022; Wittlinger et al., 2024a). However, they struggle to differ­ range of EGFR mutations. AI-based deep generative models can offer a
entiate between wild-type and mutant EGFR, and their large molecular promising solution to this challenge by enabling the discovery of novel
weight results in limited cellular efficacy and poor bioavailability. Key scaffolds (Dasser et al., 2024; Wang et al., 2024a). Machine learning
residues such as Met-793, Thr-855 and Asp-866 in the ATP site and algorithms can analyze large datasets of molecular structures and their
Lys-745 and Met-766 in the allosteric site play critical roles in their interactions in kinase binding sites and predict the scaffolds with
binding. Structural insights of these inhibitors can guide optimization optimal binding energies and selectivity for EGFR mutants (Zhung et al.,
efforts to enhance their target specificity and pharmacokinetic profile. 2024).
Several inhibitors have been developed to target C797S triple mu­
tations. Some of them are also selected for clinical trials (Dong et al., 7.3. Drug repurposing for new mutations
2021; Eno et al., 2022; Kashima et al., 2020b), but none has been
approved by FDA for clinical use yet. The journey to develop efficient To resist the next-generation EGFR mutations, existing EGFR in­
inhibitors for C797S triple mutants is still ongoing. hibitors and other marketed drugs could be screened by drug repur­
posing technologies (Pushpakom et al., 2019). AI and machine learning
7. Future perspectives play a pivotal role in this process by analyzing the structure-activity
relationship of these inhibitors and predicting the impact of specific
The emergence of resistance to EGFR TKIs, such as osimertinib, poses modifications on their efficiency, selectivity, and toxicity (Garg et al.,
a significant challenge to the ongoing effective treatment of NSCLC 2024). This approach significantly reduces the time, cost, and resources
patients harboring EGFR mutations. These mutations disrupt the sta­ involved in the experimental optimization of compounds (Corsello et al.,
bility, binding affinity, and structural conformations of EGFR protein. 2017).
For example, the T790M mutation increases the kinase affinity for ATP
due to the loss of interactions with T790. This mutation increases the
CRediT authorship contribution statement
flexibility of kinase, reducing its stability. Computational approaches
such as molecular dynamic simulation (i.e metadynamics, accelerated
Amina Tariq: Writing – review & editing, Writing – original draft,
molecular dynamics and umbrella sampling) can help us to understand
Formal analysis, Data curation, Conceptualization. Muhammad
these drug resistance mechanisms. The use of molecular docking and
Shoaib: Writing – review & editing, Software, Methodology, Investi­
molecular dynamic simulations proved indispensable in elucidating the
gation. Lingbo Qu: Validation, Methodology, Investigation, Data cura­
precise binding mechanisms of the target small molecules (Elkamhawy
tion. Sana Shoukat: Visualization, Validation, Software, Formal
et al., 2022; Son et al., 2023).
analysis. Xiaofei Nan: Writing – review & editing, Visualization, Vali­
dation, Software, Formal analysis. Jinshuai Song: Writing – review &
7.1. Overcoming resistance editing, Supervision, Software, Resources, Conceptualization.

The development and use of 1st, 2nd and 3rd generation EGFR TKIs
have not been able to fully overcome drug resistance because resistance Declaration of competing interest
is also driven by a complex network between the genes and signaling
pathways that regulate tumor growth (Pal et al., 2022). One approach to The authors declare that they have no known competing financial
address resistance is combining ATP site inhibitors with the allosteric interests or personal relationships that could have appeared to influence
inhibitors, which stabilizes the P-loop conformation and enhance the work reported in this paper.
cooperative binding. This synergy improves the inhibition of resistant
EGFR mutants (Beyett et al., 2022). However, when a drug targets a Acknowledgments
single pathway or gene, the tumor often compensates by activating
alternative pathways, allowing cancer to continue growing despite the We acknowledge financial support from the National Natural Science
treatment. As a result, these therapies fail to achieve the desired thera­ Foundation of China (No. 22173083). The Fundamental Research Funds
peutic outcomes as the tumor adapts and bypasses the inhibition. Ma­ of State Key Laboratory of Cotton Bio-breeding and Integrated Utiliza­
chine learning models can predict potential bypass pathways and help to tion, China (No. CBIU2023ZZ14).
design multi-targeted therapies improving treatment efficacy (Zhou
et al., 2023). Data availability
Approximately 10–20 % of NSCLC patients harbor rare EGFR mu­
tations, which further complicates the development of effective targeted Data will be made available on request.
treatments (Trinh and Abughanimeh, 2024). Limited knowledge of how
these mutations affect protein-drug interactions and downstream References
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