Journal Article10.1038/NRD1549
Docking and scoring in virtual screening for drug discovery: methods and applications.
TL;DR: Key concepts and specific features of small-molecule–protein docking methods are reviewed, selected applications are highlighted and recent advances that aim to address the acknowledged limitations of established approaches are discussed.
read more
Abstract: Computational approaches that 'dock' small molecules into the structures of macromolecular targets and 'score' their potential complementarity to binding sites are widely used in hit identification and lead optimization Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes Here, we review key concepts and specific features of small-molecule-protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
A dual diffusion model enables 3D molecule generation and lead optimization based on target pockets
Lei Huang,Tingyang Xu,Yang Yu,Peilin Zhao,Xingjian Chen,Jing Han,Zhi Xie,Hailong Li,Wenge Zhong,Ka-Chun Wong,Hengtong Zhang +10 more
TL;DR: Researchers developed PMDM, a conditional deep generative model, for 3D molecule generation and lead optimization, outperforming baseline models across multiple metrics, and successfully optimized lead compounds for SARS-CoV-2 Mpro and CDK2 with improved in-vitro activities.
44
Efficient and Accurate Free Energy Calculations on Trypsin Inhibitors.
TL;DR: It is shown that the combination TPF/OSP gives the most accurate results and is 4.5 times more efficient than the rigorous thermodynamic integration (TI).
43
Computational protocol for predicting the binding affinities of zinc containing metalloprotein-ligand complexes.
Tarun Jain,Bhyravabhotla Jayaram +1 more
TL;DR: An all atom force field based computational protocol for estimating rapidly the binding affinities of zinc containing metalloprotein–ligand complexes, considering electrostatics, van der Waals, hydrophobicity, and loss in conformational entropy of protein side chains upon ligand binding is reported.
Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force field-based hit scoring functions improves the accuracy of structure-based virtual screening.
Jui-Hua Hsieh,Shuangye Yin,Xiang Simon Wang,Shubin Liu,Nikolay V. Dokholyan,Alexander Tropsha +5 more
TL;DR: It is demonstrated that the use of target-specific pose (scoring) filter in combination with a physical force field-based scoring function (MedusaScore) leads to significant improvement of hit rates in VS studies for 12 of the 13 benchmark sets from the clustered version of the Database of Useful Decoys (DUD).
Modelling the DFT structural and reactivity study of feverfew and evaluation of its potential antiviral activity against COVID-19 using molecular docking and MD simulations
TL;DR: In this paper , the antiviral behavior of feverfew plant in treating COVID-19 was studied and the binding energy of the complex seems to range in between -3.85 to -11.07 kcal/mol.
References
Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings
TL;DR: Experimental and computational approaches to estimate solubility and permeability in discovery and development settings are described in this article, where the rule of 5 is used to predict poor absorption or permeability when there are more than 5 H-bond donors, 10 Hbond acceptors, and the calculated Log P (CLogP) is greater than 5 (or MlogP > 415).
16.8K
Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function
Garrett M. Morris,David S. Goodsell,Robert Scott Halliday,Ruth Huey,William E. Hart,Richard K. Belew,Arthur J. Olson +6 more
TL;DR: It is shown that both the traditional and Lamarckian genetic algorithms can handle ligands with more degrees of freedom than the simulated annealing method used in earlier versions of AUTODOCK, and that the Lamarckia genetic algorithm is the most efficient, reliable, and successful of the three.
Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy.
Richard A. Friesner,Jay L. Banks,Robert B. Murphy,Thomas A. Halgren,Jasna Klicic,Daniel T. Mainz,Matthew P. Repasky,Eric H. Knoll,Mee Shelley,Jason K. Perry,David E. Shaw,Perry Francis,Peter S Shenkin +12 more
TL;DR: Glide approximates a complete systematic search of the conformational, orientational, and positional space of the docked ligand to find the best docked pose using a model energy function that combines empirical and force-field-based terms.
Development and validation of a genetic algorithm for flexible docking.
TL;DR: GOLD (Genetic Optimisation for Ligand Docking) is an automated ligand docking program that uses a genetic algorithm to explore the full range of ligand conformational flexibility with partial flexibility of the protein, and satisfies the fundamental requirement that the ligand must displace loosely bound water on binding.
6.5K
Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening.
Thomas A. Halgren,Robert B. Murphy,Richard A. Friesner,Hege S. Beard,Leah L. Frye,W. Thomas Pollard,Jay L. Banks +6 more
TL;DR: Comparisons to results for the thymidine kinase and estrogen receptors published by Rognan and co-workers show that Glide 2.5 performs better than GOLD 1.1, FlexX 1.8, or DOCK 4.01.