Journal ArticleDOI
Latest developments in molecular docking: 2010-2011 in review.
TLDR
The main developments in docking in this period, covered in this review, are receptor flexibility, solvation, fragment docking, postprocessing, docking into homology models, and docking comparisons.Abstract:
The aim of docking is to accurately predict the structure of a ligand within the constraints of a receptor binding site and to correctly estimate the strength of binding. We discuss, in detail, methodological developments that occurred in the docking field in 2010 and 2011, with a particular focus on the more difficult, and sometimes controversial, aspects of this promising computational discipline. The main developments in docking in this period, covered in this review, are receptor flexibility, solvation, fragment docking, postprocessing, docking into homology models, and docking comparisons. Several new, or at least newly invigorated, advances occurred in areas such as nonlinear scoring functions, using machine-learning approaches. This review is strongly focused on docking advances in the context of drug design, specifically in virtual screening and fragment-based drug design. Where appropriate, we refer readers to exemplar case studies.read more
Citations
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Journal ArticleDOI
PLIP: fully automated protein–ligand interaction profiler
TL;DR: The protein-ligand interaction profiler (PLIP) is presented, a novel web service for fully automated detection and visualization of relevant non-covalent protein–ligand contacts in 3D structures, freely available at projects.tu-dresden.de/plip-web.
Journal ArticleDOI
Comprehensive evaluation of ten docking programs on a diverse set of protein-ligand complexes: the prediction accuracy of sampling power and scoring power.
TL;DR: Overall, the ligand binding poses could be identified in most cases by the evaluated docking programs but the ranks of the binding affinities for the entire dataset could not be well predicted by most docking programs.
Journal ArticleDOI
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,Robert C. Rizzo +8 more
TL;DR: This manuscript presents the latest algorithmic and methodological developments to the structure‐based design program DOCK 6.7 focused on an updated internal energy function, new anchor selection control, enhanced minimization options, a footprint similarity scoring function, a symmetry‐corrected root‐mean‐square deviation algorithm, a database filter, and docking forensic tools.
Journal ArticleDOI
Receptor–ligand molecular docking
TL;DR: The main topics and recent computational and methodological advances in protein–ligand docking are summarised, including protein flexibility, multiple ligand binding modes and the free-energy landscape profile for binding affinity prediction.
Journal ArticleDOI
Oncogenic protein interfaces: small molecules, big challenges
TL;DR: Some of the latest techniques to discover modulators of protein–protein interactions are described and how current drug discovery approaches have been adapted to successfully target these interfaces are described.
References
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Journal ArticleDOI
CSAR scoring challenge reveals the need for new concepts in estimating protein-ligand binding affinity.
Fedor N. Novikov,Alexey A. Zeifman,Oleg V. Stroganov,Viktor S. Stroylov,Val Kulkov,Ghermes G. Chilov +5 more
TL;DR: It is concluded that a significant increase of accuracy predictions necessitates breakthrough scoring approaches and the explicit accounting for water molecules, protein flexibility, and a more thermodynamically accurate method of dG calculation rather than single point energy calculation may lead to such breakthroughs.
Journal ArticleDOI
Combined Application of Cheminformatics- and Physical Force Field-Based Scoring Functions Improves Binding Affinity Prediction for CSAR Data Sets
Jui-Hua Hsieh,Shuangye Yin,Shubin Liu,Alexander Sedykh,Nikolay V. Dokholyan,Alexander Tropsha +5 more
TL;DR: It is found that the combination of QSBAR models and MedusaScore into consensus scoring function affords higher prediction accuracy than any of the contributing methods achieving R(2) values of 0.45/0.58 (Set1/Set2).
Journal ArticleDOI
Comparative binding energy analysis for binding affinity and target selectivity prediction
TL;DR: Strategies for applying COMBINE (COMparative BINding Energy) analysis, in conjunction with PIPSA (Protein Interaction Property Similarity Analysis) and ligand docking methods, to address the problem of drug design of compounds that bind selectively to their target receptors are investigated.
Journal ArticleDOI
Binding energy landscape analysis helps to discriminate true hits from high-scoring decoys in virtual screening.
TL;DR: This study suggests that incorporating information from binding energy landscape analysis can significantly increase the success rate of virtual screening.
Journal ArticleDOI
In silico fragment-based drug design
TL;DR: In silico fragment-based drug design (FBDD) holds great promise for historically challenging targets such as protein–protein interactions and future advances in force fields, scoring functions and automated methods for determining synthetic accessibility will all aid in delivering more successes with in silico FBDD.
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