Comprehensive evaluation of the MM-GBSA method on bromodomain-inhibitor sets

Author:

Çınaroğlu Süleyman Selim1,Timuçin Emel2

Affiliation:

1. Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, UK

2. Department of Biostatistics and Medical Informatics, School of Medicine, Acıbadem Mehmet Ali Aydınlar University, İstanbul, 34752, Turkey

Abstract

Abstract MM-PB/GBSA methods represent a higher-level scoring theory than docking. This study reports an extensive testing of different MM-GBSA scoring schemes on two bromodomain (BRD) datasets. The first set is composed of 24 BRPF1 complexes, and the second one is a nonredundant set constructed from the PDBbind and composed of 28 diverse BRD complexes. A variety of MM-GBSA schemes were analyzed to evaluate the performance of four protocols with different numbers of minimization and MD steps, 10 different force fields and three different water models. Results showed that neither additional MD steps nor unfixing the receptor atoms improved scoring or ranking power. On the contrary, our results underscore the advantage of fixing receptor atoms or limiting the number of MD steps not only for a reduction in the computational costs but also for boosting the prediction accuracy. Among Amber force fields tested, ff14SB and its derivatives rather than ff94 or polarized force fields provided the most accurate scoring and ranking results. The TIP3P water model yielded the highest scoring and ranking power compared to the others. Posing power was further evaluated for the BRPF1 set. A slightly better posing power for the protocol which uses both minimization and MD steps with a fixed receptor than the one which uses only minimization with a fully flexible receptor-ligand system was observed. Overall, this study provides insights into the usage of the MM-GBSA methods for screening of BRD inhibitors, substantiating the benefits of shorter protocols and latest force fields and maintaining the crystal waters for accuracy.

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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