Literature DB >> 28510083

Software for molecular docking: a review.

Nataraj S Pagadala1, Khajamohiddin Syed2, Jack Tuszynski3,4.   

Abstract

Molecular docking methodology explores the behavior of small molecules in the binding site of a target protein. As more protein structures are determined experimentally using X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy, molecular docking is increasingly used as a tool in drug discovery. Docking against homology-modeled targets also becomes possible for proteins whose structures are not known. With the docking strategies, the druggability of the compounds and their specificity against a particular target can be calculated for further lead optimization processes. Molecular docking programs perform a search algorithm in which the conformation of the ligand is evaluated recursively until the convergence to the minimum energy is reached. Finally, an affinity scoring function, ΔG [U total in kcal/mol], is employed to rank the candidate poses as the sum of the electrostatic and van der Waals energies. The driving forces for these specific interactions in biological systems aim toward complementarities between the shape and electrostatics of the binding site surfaces and the ligand or substrate.

Keywords:  Docking accuracy; Flexible docking; Rigid body docking

Year:  2017        PMID: 28510083      PMCID: PMC5425816          DOI: 10.1007/s12551-016-0247-1

Source DB:  PubMed          Journal:  Biophys Rev        ISSN: 1867-2450


  129 in total

1.  Protein docking using a genetic algorithm.

Authors:  E J Gardiner; P Willett; P J Artymiuk
Journal:  Proteins       Date:  2001-07-01

2.  ConsDock: A new program for the consensus analysis of protein-ligand interactions.

Authors:  Nicodème Paul; Didier Rognan
Journal:  Proteins       Date:  2002-06-01

3.  ZDOCK: an initial-stage protein-docking algorithm.

Authors:  Rong Chen; Li Li; Zhiping Weng
Journal:  Proteins       Date:  2003-07-01

4.  Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy.

Authors:  Richard A Friesner; Jay L Banks; Robert B Murphy; Thomas A Halgren; Jasna J Klicic; Daniel T Mainz; Matthew P Repasky; Eric H Knoll; Mee Shelley; Jason K Perry; David E Shaw; Perry Francis; Peter S Shenkin
Journal:  J Med Chem       Date:  2004-03-25       Impact factor: 7.446

5.  Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques.

Authors:  E Katchalski-Katzir; I Shariv; M Eisenstein; A A Friesem; C Aflalo; I A Vakser
Journal:  Proc Natl Acad Sci U S A       Date:  1992-03-15       Impact factor: 11.205

6.  On the interaction of promiscuous antigenic peptides with different DR alleles. Identification of common structural motifs.

Authors:  D O'Sullivan; T Arrhenius; J Sidney; M F Del Guercio; M Albertson; M Wall; C Oseroff; S Southwood; S M Colón; F C Gaeta
Journal:  J Immunol       Date:  1991-10-15       Impact factor: 5.422

7.  Flexible protein docking refinement using pose-dependent normal mode analysis.

Authors:  Vishwesh Venkatraman; David W Ritchie
Journal:  Proteins       Date:  2012-06-18

8.  Present and future challenges and limitations in protein-protein docking.

Authors:  Carles Pons; Solène Grosdidier; Albert Solernou; Laura Pérez-Cano; Juan Fernández-Recio
Journal:  Proteins       Date:  2010-01

9.  Protein-protein docking using region-based 3D Zernike descriptors.

Authors:  Vishwesh Venkatraman; Yifeng D Yang; Lee Sael; Daisuke Kihara
Journal:  BMC Bioinformatics       Date:  2009-12-09       Impact factor: 3.169

10.  MS-DOCK: accurate multiple conformation generator and rigid docking protocol for multi-step virtual ligand screening.

Authors:  Nicolas Sauton; David Lagorce; Bruno O Villoutreix; Maria A Miteva
Journal:  BMC Bioinformatics       Date:  2008-04-10       Impact factor: 3.169

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  157 in total

1.  Interactive molecular dynamics in virtual reality for accurate flexible protein-ligand docking.

Authors:  Helen M Deeks; Rebecca K Walters; Stephanie R Hare; Michael B O'Connor; Adrian J Mulholland; David R Glowacki
Journal:  PLoS One       Date:  2020-03-11       Impact factor: 3.240

2.  Fragment Pose Prediction Using Non-equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations.

Authors:  Nathan M Lim; Meghan Osato; Gregory L Warren; David L Mobley
Journal:  J Chem Theory Comput       Date:  2020-03-27       Impact factor: 6.006

3.  Molecular modelling of quinoline derivatives as telomerase inhibitors through 3D-QSAR, molecular dynamics simulation, and molecular docking techniques.

Authors:  Keerti Vishwakarma; Hardik Bhatt
Journal:  J Mol Model       Date:  2021-01-07       Impact factor: 1.810

4.  Negative Image-Based Screening: Rigid Docking Using Cavity Information.

Authors:  Pekka A Postila; Sami T Kurkinen; Olli T Pentikäinen
Journal:  Methods Mol Biol       Date:  2021

Review 5.  Generative chemistry: drug discovery with deep learning generative models.

Authors:  Yuemin Bian; Xiang-Qun Xie
Journal:  J Mol Model       Date:  2021-02-04       Impact factor: 1.810

6.  Computing Ligands Bound to Proteins Using MELD-Accelerated MD.

Authors:  Cong Liu; Emiliano Brini; Alberto Perez; Ken A Dill
Journal:  J Chem Theory Comput       Date:  2020-09-23       Impact factor: 6.006

7.  Binding pose and affinity prediction in the 2016 D3R Grand Challenge 2 using the Wilma-SIE method.

Authors:  Hervé Hogues; Traian Sulea; Francis Gaudreault; Christopher R Corbeil; Enrico O Purisima
Journal:  J Comput Aided Mol Des       Date:  2017-10-05       Impact factor: 3.686

8.  A cross docking pipeline for improving pose prediction and virtual screening performance.

Authors:  Ashutosh Kumar; Kam Y J Zhang
Journal:  J Comput Aided Mol Des       Date:  2017-08-23       Impact factor: 3.686

9.  Metadynamics as a Postprocessing Method for Virtual Screening with Application to the Pseudokinase Domain of JAK2.

Authors:  Kara J Cutrona; Ana S Newton; Stefan G Krimmer; Julian Tirado-Rives; William L Jorgensen
Journal:  J Chem Inf Model       Date:  2020-05-27       Impact factor: 4.956

10.  Free-energy landscape of molecular interactions between endothelin 1 and human endothelin type B receptor: fly-casting mechanism.

Authors:  Junichi Higo; Kota Kasahara; Mitsuhito Wada; Bhaskar Dasgupta; Narutoshi Kamiya; Tomonori Hayami; Ikuo Fukuda; Yoshifumi Fukunishi; Haruki Nakamura
Journal:  Protein Eng Des Sel       Date:  2019-12-31       Impact factor: 1.650

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