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Most widely used ligand docking methods assume a rigid protein structure.
Development and validation of a genetic algorithm for flexible docking
Gareth Jones, Peter Willett, Robert C Glen, Andrew R Leach, and Robin Taylor · 1997
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Improved protein–ligand docking using gold
Marcel L Verdonk, Jason C Cole, Michael J Hartshorn, Christopher W Murray, and Richard D Taylor · 2003
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Glide: a new approach for rapid, accurate docking and scoring. 1. method and assessment of docking accuracy
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Evaluation of docking performance: comparative data on docking algorithms
Maria Kontoyianni, Laura M McClellan, and Glenn S Sokol · 2004
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Comparing protein–ligand docking programs is difficult
Jason C Cole, Christopher W Murray, J Willem M Nissink, Richard D Taylor, and Robin Taylor · 2005
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Synthesis, sar, and x-ray structure of human bace-1 inhibitors with cyclic urea derivatives
Heuisul Park, Kyeongsik Min, Hyo-Shin Kwak, Ki Dong Koo, Dongchul Lim, Sang-Won Seo, Jae-Ung Choi, Bettina Platt, and Deog-Young Choi · 2008
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Flexible ligand docking to multiple receptor conformations: a practical alternative
Maxim Totrov and Ruben Abagyan · 2008
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Ensemble docking from homology models
Eva Maria Novoa, Lluis Ribas de Pouplana, Xavier Barril, and Modesto Orozco · 2010
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Autodock vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading
Oleg Trott and Arthur J Olson · 2010
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Potential and limitations of ensemble docking
Oliver Korb, Tjelvar SG Olsson, Simon J Bowden, Richard J Hall, Marcel L Verdonk, John W Liebeschuetz, and Jason C Cole · 2012
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Rosetta ligand docking with flexible xml protocols
Gordon Lemmon and Jens Meiler · 2012
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Ligand pose and orientational sampling in molecular docking
Ryan G Coleman, Michael Carchia, Teague Sterling, John J Irwin, and Brian K Shoichet · 2013
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Docking challenge: protein sampling and molecular docking performance
Khaled M Elokely and Robert J Doerksen · 2013
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Receptor–ligand molecular docking
Isabella A Guedes, Camila S de Magalhães, and Laurent E Dardenne · 2014
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Dock 6: Impact of new features and current docking performance
William J Allen, Trent E Balius, Sudipto Mukherjee, Scott R Brozell, Demetri T Moustakas, P Therese Lang, David A Case, Irwin D Kuntz, and Robert C Rizzo · 2015
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Molecular docking and structure-based drug design strategies
Leonardo G Ferreira, Ricardo N Dos Santos, Glaucius Oliva, and Adriano D Andricopulo · 2015
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Machine learning in computational docking
Mohamed A Khamis, Walid Gomaa, and Walaa F Ahmed · 2015
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PDB-wide collection of binding data: current status of the PDBbind database
Zhihai Liu, Yan Li, Li Han, Jie Li, Jie Liu, Zhixiong Zhao, Wei Nie, Yuchen Liu, and Renxiao Wang · 2015
Ensemble docking in drug discovery: how many protein configurations from molecular dynamics simulations are needed to reproduce known ligand binding?
Wilfredo Evangelista Falcon, Sally R Ellingson, Jeremy C Smith, and Jerome Baudry · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Machine learning of coarse-grained molecular dynamics force fields
Jiang Wang, Simon Olsson, Christoph Wehmeyer, Adrià Pérez, Nicholas E Charron, Gianni De Fabritiis, Frank Noé, and Cecilia Clementi · 2019
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Protein model quality assessment using rotation-equivariant, hierarchical neural networks
Stephan Eismann, Patricia Suriana, Bowen Jing, Raphael J. L. Townshend, and Ron O. Dror · 2020
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Autodockfr: advances in protein-ligand docking with explicitly specified binding site flexibility
Pradeep Anand Ravindranath, Stefano Forli, David S Goodsell, Arthur J Olson, and Michel F Sanner · 2015
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Fast and accurate deep network learning by exponential linear units (elus)
Djork-Arné Clevert, Thomas Unterthiner, and Sepp Hochreiter · 2016
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Computational protein–ligand docking and virtual drug screening with the autodock suite
Stefano Forli, Ruth Huey, Michael E Pique, Michel F Sanner, David S Goodsell, and Arthur J Olson · 2016
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Fragment-linking approach using 19f nmr spectroscopy to obtain highly potent and selective inhibitors of β \beta -secretase
John B Jordan, Douglas A Whittington, Michael D Bartberger, E Allen Sickmier, Kui Chen, Yuan Cheng, and Ted Judd · 2016
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Protein–ligand scoring with convolutional neural networks
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A comprehensive map of molecular drug targets
Rita Santos, Oleg Ursu, Anna Gaulton, A Patrícia Bento, Ramesh S Donadi, Cristian G Bologa, Anneli Karlsson, Bissan Al-Lazikani, Anne Hersey, Tudor I Oprea, et al · 2017
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Coarse graining molecular dynamics with graph neural networks
Brooke E Husic, Nicholas E Charron, Dominik Lemm, Jiang Wang, Adrià Pérez, Maciej Majewski, Andreas Krämer, Yaoyi Chen, Simon Olsson, Gianni de Fabritiis, et al · 2020
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Combining docking pose rank and structure with deep learning improves protein–ligand binding mode prediction over a baseline docking approach
Joseph A Morrone, Jeffrey K Weber, Tien Huynh, Heng Luo, and Wendy D Cornell · 2020
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From machine learning to deep learning: Advances in scoring functions for protein–ligand docking
Chao Shen, Junjie Ding, Zhe Wang, Dongsheng Cao, Xiaoqin Ding, and Tingjun Hou · 2020
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A practical guide to large-scale docking
Brian J Bender, Stefan Gahbauer, Andreas Luttens, Jiankun Lyu, Chase M Webb, Reed M Stein, Elissa A Fink, Trent E Balius, Jens Carlsson, John J Irwin, et al · 2021
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Hierarchical, rotation-equivariant neural networks to select structural models of protein complexes
Stephan Eismann, Raphael J.L. Townshend, Nathaniel Thomas, Milind Jagota, Bowen Jing, and Ron O. Dror · 2021
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Gnina 1.0: molecular docking with deep learning
Andrew T McNutt, Paul Francoeur, Rishal Aggarwal, Tomohide Masuda, Rocco Meli, Matthew Ragoza, Jocelyn Sunseri, and David Ryan Koes · 2021
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Reliable and accurate solution to the induced fit docking problem for protein–ligand binding
Edward B Miller, Robert B Murphy, Daniel Sindhikara, Kenneth W Borrelli, Matthew J Grisewood, Fabio Ranalli, Steven L Dixon, Steven Jerome, Nicholas A Boyles, Tyler Day, et al · 2021
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Leveraging nonstructural data to predict structures and affinities of protein–ligand complexes
Joseph M Paggi, Julia A Belk, Scott A Hollingsworth, Nicolas Villanueva, Alexander S Powers, Mary J Clark, Augustine G Chemparathy, Jonathan E Tynan, Thomas K Lau, Roger K Sunahara, et al · 2021
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