TY  - JOUR
A1  - Kalinowsky, Lena
A1  - Weber, Julia
A1  - Balasupramaniam, Shantheya
A1  - Baumann, Knut
A1  - Proschak, Ewgenij
T1  - A diverse benchmark based on 3D matched molecular pairs for validating scoring functions
T2  - ACS omega
N2  - 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.
KW  - Chemoinformatics
KW  - Free energy
KW  - Molecular association
KW  - Molecular docking
KW  - Physical and chemical properties
KW  - Proteins
Y1  - 2018
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/47211
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-472118
SN  - 2470-1343
N1  - 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.
VL  - 3
SP  - 5704
EP  - 5714
PB  - ACS Publications
CY  - Washington, DC
ER  -