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Journal of Computer-Aided Molecular Design, Volume 32
Volume 32, Number 1, January 2018
- Zied Gaieb, Shuai Liu, Symon Gathiaka, Michael Chiu
, Huanwang Yang, Chenghua Shao
D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies. 1-20 - Christina Athanasiou
Using physics-based pose predictions and free energy perturbation calculations to predict binding poses and relative binding affinities for FXR ligands in the D3R Grand Challenge 2. 21-44 - Matthew P. Baumgartner
Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2. 45-58 - Soumendranath Bhakat
Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling. 59-73 - Priscila da Silva Figueiredo Celestino Gomes
Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2. 75-87 - Xinqiang Ding, Ryan L. Hayes, Jonah Z. Vilseck, Murchtricia K. Charles, Charles L. Brooks III
CDOCKER and λ-dynamics for prospective prediction in D3R Grand Challenge 2. 89-102 - Rui Duan
Lessons learned from participating in D3R 2016 Grand Challenge 2: compounds targeting the farnesoid X receptor. 103-111 - Xavier Fradera
Performance of multiple docking and refinement methods in the pose prediction D3R prospective Grand Challenge 2016. 113-127 - Ying-Duo Gao, Yuan Hu
Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort. 129-142 - Hervé Hogues, Traian Sulea, Francis Gaudreault, Christopher R. Corbeil
Binding pose and affinity prediction in the 2016 D3R Grand Challenge 2 using the Wilma-SIE method. 143-150 - Maria Kadukova
Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2. 151-162 - Ashutosh Kumar, Kam Y. J. Zhang
A cross docking pipeline for improving pose prediction and virtual screening performance. 163-173 - Zeynep Kurkcuoglu, Panagiotis I. Koukos, Nevia Citro, Mikael E. Trellet, João P. G. L. M. Rodrigues, Irina S. Moreira
Performance of HADDOCK and a simple contact-based protein-ligand binding affinity predictor in the D3R Grand Challenge 2. 175-185 - Polo Chun-Hung Lam, Ruben Abagyan, Maxim Totrov
Ligand-biased ensemble receptor docking (LigBEnD): a hybrid ligand/receptor structure-based approach. 187-198 - Antonia S. J. S. Mey, Jordi Juárez Jiménez, Julien Michel:
Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations. 199-210 - Martin A. Olsson, Alfonso T. García-Sosa
Binding affinities of the farnesoid X receptor in the D3R Grand Challenge 2 estimated by free-energy perturbation and docking. 211-224 - Dzmitry Padhorny, David R. Hall, Hanieh Mirzaei, Artem B. Mamonov, Mohammad Moghadasi, Andrey Alekseenko
Protein-ligand docking using FFT based sampling: D3R case study. 225-230 - Manon Réau
Predicting the affinity of Farnesoid X Receptor ligands through a hierarchical ranking protocol: a D3R Grand Challenge 2 case study. 231-238 - Eko Aditya Rifai
Binding free energy predictions of farnesoid X receptor (FXR) agonists using a linear interaction energy (LIE) approach with reliability estimation: application to the D3R Grand Challenge 2. 239-249 - Veronica Salmaso
Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2. 251-264 - Christina E. M. Schindler, Friedrich Rippmann, Daniel Kuhn:
Relative binding affinity prediction of farnesoid X receptor in the D3R Grand Challenge 2 using FEP+. 265-272 - Edithe Selwa, Eddy Elisée
Blinded evaluation of farnesoid X receptor (FXR) ligands binding using molecular docking and free energy calculations. 273-286 - Bentley M. Wingert
Optimal affinity ranking for automated virtual screening validated in prospective D3R grand challenges. 287-297 - Oleksandr Yakovenko, Steven J. M. Jones
Modern drug design: the implication of using artificial neuronal networks and multiple molecular dynamic simulations. 299-311
Volume 32, Number 2, February 2018
- Johann Gasteiger, Yvonne C. Martin, Anthony Nicholls, Tudor I. Oprea
Leaving us with fond memories, smiles, SMILES and, alas, tears: a tribute to David Weininger, 1952-2016. 313-319 - Ryo Kunimoto
Design of a tripartite network for the prediction of drug targets. 321-330 - Zoltán Orgován, György G. Ferenczy
Validation of tautomeric and protomeric binding modes by free energy calculations. A case study for the structure based optimization of d-amino acid oxidase inhibitors. 331-345 - Miao Yu, Qiong Gu
Discovering new PI3Kα inhibitors with a strategy of combining ligand-based and structure-based virtual screening. 347-361 - Natalia Nikitina
Congestion game scheduling for virtual drug screening optimization. 363-374 - Mohammad Amin Valizade Hasanloei
A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities. 375-384 - Stefano Della-Longa
"In silico" study of the binding of two novel antagonists to the nociceptin receptor. 385-400
Volume 32, Number 3, March 2018
- Timur Gimadiev, Timur I. Madzhidov
Assessment of tautomer distribution using the condensed reaction graph approach. 401-414 - Sebastian Raschka, Anne M. Scott, Nan Liu, Santosh Gunturu, Mar Huertas, Weiming Li, Leslie A. Kuhn
Enabling the hypothesis-driven prioritization of ligand candidates in big databases: Screenlamp and its application to GPCR inhibitor discovery for invasive species control. 415-433 - Manuela Sabatino, Dante Rotili, Alexandros Patsilinakos
Disruptor of telomeric silencing 1-like (DOT1L): disclosing a new class of non-nucleoside inhibitors by means of ligand-based and structure-based approaches. 435-458 - Zainab K. Sanusi, Thavendran Govender
An insight to the molecular interactions of the FDA approved HIV PR drugs against L38L↑N↑L PR mutant. 459-471 - Stefania Villa
Structure-based drug design, synthesis and biological assays of P. falciparum Atg3-Atg8 protein-protein interaction inhibitors. 473-486 - Krishna P. Singh
Impact of graphene-based nanomaterials (GBNMs) on the structural and functional conformations of hepcidin peptide. 487-496
Volume 32, Number 4, April 2018
- David A. Winkler:
Sparse QSAR modelling methods for therapeutic and regenerative medicine. 497-509 - Sebastian Raschka, Alex J. Wolf, Joseph Bemister-Buffington, Leslie A. Kuhn
Protein-ligand interfaces are polarized: discovery of a strong trend for intermolecular hydrogen bonds to favor donors on the protein side with implications for predicting and designing ligand complexes. 511-528 - Francesco Manzoni, Ulf Ryde
Assessing the stability of free-energy perturbation calculations by performing variations in the method. 529-536 - Peter A. Hunt
WhichP450: a multi-class categorical model to predict the major metabolising CYP450 isoform for a compound. 537-546 - Jian Gao
Insight into the molecular mechanism of yeast acetyl-coenzyme A carboxylase mutants F510I, N485G, I69E, E477R, and K73R resistant to soraphen A. 547-557 - Shubhandra Tripathi
Insight into microtubule destabilization mechanism of 3, 4, 5-trimethoxyphenyl indanone derivatives using molecular dynamics simulation and conformational modes analysis. 559-572 - Xin Zhang
In-silico guided discovery of novel CCR9 antagonists. 573-582
Volume 32, Number 5, May 2018
- Sankalp Jain
Comparing the performance of meta-classifiers - a case study on selected imbalanced data sets relevant for prediction of liver toxicity. 583-590 - Luan Carvalho Martins
Investigation of the binding mode of a novel cruzain inhibitor by docking, molecular dynamics, ab initio and MM/PBSA calculations. 591-605 - Érica C. M. Nascimento
Binding free energy calculations to rationalize the interactions of huprines with acetylcholinesterase. 607-622 - Francesca Cardamone, Mattia Falconi
Molecular dynamics characterization of the SAMHD1 Aicardi-Goutières Arg145Gln mutant: structural determinants for the impaired tetramerization. 623-632 - Lu Lu, Hua Yu
DR2DI: a powerful computational tool for predicting novel drug-disease associations. 633-642 - Songling Ma
Discovery of a small-molecule inhibitor of Dvl-CXXC5 interaction by computational approaches. 643-655
Volume 32, Number 6, June 2018
- Mazen Y. Hamed:
Role of protein structure and the role of individual fingers in zinc finger protein-DNA recognition: a molecular dynamics simulation study and free energy calculations. 657-669 - Timothy Cholko
A molecular dynamics investigation of CDK8/CycC and ligand binding: conformational flexibility and implication in drug discovery. 671-685 - Thandokuhle Ntombela, Zeynab Fakhar
Molecular insight on the non-covalent interactions between carbapenems and l, d-transpeptidase 2 from Mycobacterium tuberculosis: ONIOM study. 687-701 - Erick Martins Ratamero, Dom Bellini, Christopher G. Dowson
Touching proteins with virtual bare hands - Visualizing protein-drug complexes and their dynamics in self-made virtual reality using gaming hardware. 703-709 - Sofja Tshepelevitsh
Prediction of partition and distribution coefficients in various solvent pairs with COSMO-RS. 711-722
Volume 32, Number 7, July 2018
- Dimitris K. Agrafiotis, M. Katharine Holloway, Scott A. Johnson
Chemistry, information and Frank: a tribute to Frank Brown. 723-729 - Ann E. Cleves
Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose. 731-757 - Tomoyuki Miyao, Jürgen Bajorath
Exploring ensembles of bioactive or virtual analogs of X-ray ligands for shape similarity searching. 759-767 - Saveliy Belkin
Inhibition of protein interactions: co-crystalized protein-protein interfaces are nearly as good as holo proteins in rigid-body ligand docking. 769-779 - Marcela Vettorazzi, Cintia Menéndez, Lucas Gutierrez, Sebastian A. Andujar, Gustavo Appignanesi, Ricardo D. Enriz
Theoretical models to predict the inhibitory effect of ligands of sphingosine kinase 1 using QTAIM calculations and hydrogen bond dynamic propensity analysis. 781-791 - Shibaji Ghosh, Kalyanashis Jana
Influence of gauche effect on uncharged oxime reactivators for the reactivation of tabun-inhibited AChE: quantum chemical and steered molecular dynamics studies. 793-807
Volume 32, Number 8, August 2018
- Yvonne C. Martin:
How medicinal chemists learned about log P. 809-819 - Hemavathy Nagarajan, Umashankar Vetrivel:
Demystifying the pH dependent conformational changes of human heparanase pertaining to structure-function relationships: an in silico approach. 821-840 - Matthew Habgood:
Conformational ensemble comparison for small molecules in drug discovery. 841-852 - Minh Khoa Nguyen, Léonard Jaillet, Stéphane Redon
Generating conformational transition paths with low potential-energy barriers for proteins. 853-867 - Mauricio Carrillo-Tripp
HTMoL: full-stack solution for remote access, visualization, and analysis of molecular dynamics trajectory data. 869-876
Volume 32, Number 9, September 2018
- Michael Zhenin, Malkeet Singh Bahia, Gilles Marcou
Rescoring of docking poses under Occam's Razor: are there simpler solutions? 877-888 - D. Sam Paul
Protein-small molecule docking with receptor flexibility in iMOLSDOCK. 889-900 - Yaping Li, Yinglan Pu, Hui Liu, Li Zhang, Xingyong Liu, Yan Li, Zhili Zuo
Discovery of novel wee1 inhibitors via structure-based virtual screening and biological evaluation. 901-915 - Jie Chen, Xiao Lin, Kyoung Jin Park, Kang Ro Lee, Hyun-Ju Park
Identification of protoberberine alkaloids as novel histone methyltransferase G9a inhibitors by structure-based virtual screening. 917-928 - Piya Patra
Quantum chemical studies on anion specificity of CαNN motif in functional proteins. 929-936
Volume 32, Number 10, October 2018
- Andrea Rizzi
Overview of the SAMPL6 host-guest binding affinity prediction challenge. 937-963 - Piero Procacci
SAMPL6 host-guest blind predictions using a non equilibrium alchemical approach. 965-982 - Phillip S. Hudson
Force matching as a stepping stone to QM/MM CB[8] host/guest binding free energies: a SAMPL6 cautionary tale. 983-999 - Tom Dixon, Samuel D. Lotz, Alex Dickson
Predicting ligand binding affinity using on- and off-rates for the SAMPL6 SAMPLing challenge. 1001-1012 - Lin Frank Song, Nupur Bansal
Detailed potential of mean force studies on host-guest systems from the SAMPL6 challenge. 1013-1026 - Octav Caldararu, Martin A. Olsson, Majda Misini Ignjatovic, Meiting Wang, Ulf Ryde
Binding free energies in the SAMPL6 octa-acid host-guest challenge calculated with MM and QM methods. 1027-1046 - Michail Papadourakis, Stefano Bosisio, Julien Michel
Blinded predictions of standard binding free energies: lessons learned from the SAMPL6 challenge. 1047-1058 - Kyungreem Han
Prediction of CB[8] host-guest binding free energies in SAMPL6 using the double-decoupling method. 1059-1073 - Naohiro Nishikawa
Comparison of the umbrella sampling and the double decoupling method in binding free energy predictions for SAMPL6 octa-acid host-guest challenges. 1075-1086 - Marie L. Laury
Absolute binding free energies for the SAMPL6 cucurbit[8]uril host-guest challenge via the AMOEBA polarizable force field. 1087-1095 - Yigitcan Eken
SAMPL6 host-guest challenge: binding free energies via a multistep approach. 1097-1115 - Mehtap Isik, Dorothy Levorse, Ariën S. Rustenburg, Ikenna E. Ndukwe, Heather Wang, Xiao Wang, Mikhail Y. Reibarkh
pK a measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments. 1117-1138 - Philipp Pracht
High accuracy quantum-chemistry-based calculation and blind prediction of macroscopic pKa values in the context of the SAMPL6 challenge. 1139-1149 - Nicolas Tielker, Lukas Eberlein, Stefan Güssregen, Stefan M. Kast
The SAMPL6 challenge on predicting aqueous pK a values from EC-RISM theory. 1151-1163 - Caitlin C. Bannan
SAMPL6 challenge results from a predictions based on a general Gaussian process model. 1165-117 - Qiao Zeng
Absolute and relative pK a predictions via a DFT approach applied to the SAMPL6 blind challenge. 1179-1189 - Samarjeet Prasad
An explicit-solvent hybrid QM and MM approach for predicting pKa of small molecules in SAMPL6 challenge. 1191-1201 - Edithe Selwa, Ian M. Kenney, Oliver Beckstein
SAMPL6: calculation of macroscopic pK a values from ab initio quantum mechanical free energies. 1203-1216
Volume 32, Number 11, November 2018
- Youlin Xue
Using steered molecular dynamics to study the interaction between ADP and the nucleotide-binding domain of yeast Hsp70 protein Ssa1. 1217-1227 - Noriyuki Yamaotsu
In silico fragment-mapping method: a new tool for fragment-based/structure-based drug discovery. 1229-1245 - Irena Majerz
Weak interactions in furan dimers. 1247-1258 - Paulo Siani
Parameterization of a coarse-grained model of cholesterol with point-dipole electrostatics. 1259-1271 - Gonzalo Cerruela García
Boosted feature selectors: a case study on prediction P-gp inhibitors and substrates. 1273-1294 - Laurence Leherte
Investigating cyclic peptides inhibiting CD2-CD58 interactions through molecular dynamics and molecular docking methods. 1295-1313
Volume 32, Number 12, December 2018
- Julio Caballero
Mycobacterium tuberculosis serine/threonine protein kinases: structural information for the design of their specific ATP-competitive inhibitors. 1315-1336 - Enrico Margiotta
Could the presence of sodium ion influence the accuracy and precision of the ligand-posing in the human A2A adenosine receptor orthosteric binding site using a molecular docking approach? Insights from Dockbench. 1337-1346 - E. Srinivasan
Quantum chemical and molecular mechanics studies on the assessment of interactions between resveratrol and mutant SOD1 (G93A) protein. 1347-1361 - Wen Hu, Liu Qin
Individually double minimum-distance definition of protein-RNA binding residues and application to structure-based prediction. 1363-1373 - Stefan A. P. Lenz, Stacey D. Wetmore
Structural explanation for the tunable substrate specificity of an E. coli nucleoside hydrolase: insights from molecular dynamics simulations. 1375-1388
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