Literature DB >> 24981490

Scoring functions for protein-ligand interactions: a critical perspective.

Tanja Schulz-Gasch1, Martin Stahl2.   

Abstract

Scoring functions play an essential role in structure-based virtual screening. They are required to guide the docking of candidate compounds to structures of receptor binding sites, to select probable binding modes, and to discriminate binders from non-binders. Although many scoring functions have successfully been used to identify novel ligands for a wide variety of targets, much work remains to be done to avoid incorrect prediction of binding modes and high numbers of false positives. This review gives an overview of the current state of the field and outlines key issues for the further development of scoring functions.:
© 2004 Elsevier Ltd . All rights reserved.

Year:  2004        PMID: 24981490     DOI: 10.1016/j.ddtec.2004.08.004

Source DB:  PubMed          Journal:  Drug Discov Today Technol        ISSN: 1740-6749


  15 in total

Review 1.  Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go.

Authors:  N Moitessier; P Englebienne; D Lee; J Lawandi; C R Corbeil
Journal:  Br J Pharmacol       Date:  2007-11-26       Impact factor: 8.739

2.  Scoring confidence index: statistical evaluation of ligand binding mode predictions.

Authors:  Maria I Zavodszky; Andrew W Stumpff-Kane; David J Lee; Michael Feig
Journal:  J Comput Aided Mol Des       Date:  2009-01-20       Impact factor: 3.686

3.  Assessing protein-ligand interaction scoring functions with the CASF-2013 benchmark.

Authors:  Yan Li; Minyi Su; Zhihai Liu; Jie Li; Jie Liu; Li Han; Renxiao Wang
Journal:  Nat Protoc       Date:  2018-03-08       Impact factor: 13.491

4.  Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking.

Authors:  Spandana Makeneni; David F Thieker; Robert J Woods
Journal:  J Chem Inf Model       Date:  2018-03-09       Impact factor: 4.956

5.  Modeling of peroxide activation in artemisinin derivatives by serial docking.

Authors:  Roy J Little; Alexis A Pestano; Zaida Parra
Journal:  J Mol Model       Date:  2009-01-14       Impact factor: 1.810

6.  Target flexibility: an emerging consideration in drug discovery and design.

Authors:  Pietro Cozzini; Glen E Kellogg; Francesca Spyrakis; Donald J Abraham; Gabriele Costantino; Andrew Emerson; Francesca Fanelli; Holger Gohlke; Leslie A Kuhn; Garrett M Morris; Modesto Orozco; Thelma A Pertinhez; Menico Rizzi; Christoph A Sotriffer
Journal:  J Med Chem       Date:  2008-09-12       Impact factor: 7.446

7.  Vina-Carb: Improving Glycosidic Angles during Carbohydrate Docking.

Authors:  Anita K Nivedha; David F Thieker; Spandana Makeneni; Huimin Hu; Robert J Woods
Journal:  J Chem Theory Comput       Date:  2016-01-19       Impact factor: 6.006

8.  Molecular Docking: From Lock and Key to Combination Lock.

Authors:  Ashutosh Tripathi; Vytas A Bankaitis
Journal:  J Mol Med Clin Appl       Date:  2017-02-10

Review 9.  Advances and challenges in protein-ligand docking.

Authors:  Sheng-You Huang; Xiaoqin Zou
Journal:  Int J Mol Sci       Date:  2010-08-18       Impact factor: 5.923

10.  NNScore: a neural-network-based scoring function for the characterization of protein-ligand complexes.

Authors:  Jacob D Durrant; J Andrew McCammon
Journal:  J Chem Inf Model       Date:  2010-10-25       Impact factor: 4.956

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