A diverse benchmark based on 3D matched molecular pairs for validating scoring functions

  • The prediction of protein–ligand interactions and their corresponding binding free energy is a challenging task in structure-based drug design and related applications. Docking and scoring is broadly used to propose the binding mode and underlying interactions as well as to provide a measure for ligand affinity or differentiate between active and inactive ligands. Various studies have revealed that most docking software packages reliably predict the binding mode, although scoring remains a challenge. Here, a diverse benchmark data set of 99 matched molecular pairs (3D-MMPs) with experimentally determined X-ray structures and corresponding binding affinities is introduced. This data set was used to study the predictive power of 13 commonly used scoring functions to demonstrate the applicability of the 3D-MMP data set as a valuable tool for benchmarking scoring functions.

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Author:Lena Kalinowsky, Julia Weber, Shantheya Balasupramaniam, Knut Baumann, Ewgenij ProschakORCiDGND
Parent Title (English):ACS omega
Publisher:ACS Publications
Place of publication:Washington, DC
Document Type:Article
Year of Completion:2018
Date of first Publication:2018/05/28
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2018/08/14
Tag:Chemoinformatics; Free energy; Molecular association; Molecular docking; Physical and chemical properties; Proteins
Page Number:11
First Page:5704
Last Page:5714
This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes.
Institutes:Biochemie, Chemie und Pharmazie / Pharmazie
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Open-Access-Publikationsfonds:Biochemie, Chemie und Pharmazie
Licence (English):License LogoCreative Commons - Namensnennung-Nicht kommerziell 4.0