Abstract
ABSTRACTBackgroundThe structural information on proteins in their ligand-bound conformational state is invaluable for protein function studies and rational drug design. Compared to the number of available sequences, not only is the repertoire of the experimentally determined structures of holo-proteins limited, these structures do not always include pharmacologically relevant compounds at their binding sites. In addition, binding affinity databases provide vast quantities of information on interactions between drug-like molecules and their targets, however, often lacking structural data. On that account, there is a need for computational methods to complement existing repositories by constructing the atomic-level models of drug-protein assemblies that will not be determined experimentally in the near future.ResultsWe created eModel-BDB, a database of 200,005 comparative models of drug-bound proteins based on 1,391,403 interaction data obtained from the Binding Database and the PDB library of 31 January 2017. Complex models in eModel-BDB were generated with a collection of the state-of-the-art techniques, including protein meta-threading, template-based structure modeling, refinement and binding site detection, and ligand similarity-based docking. In addition to a rigorous quality control maintained during dataset generation, a subset of weakly homologous models was selected for the retrospective validation against experimental structural data recently deposited to the Protein Data Bank. Validation results indicate that eModel-BDB contains models that are accurate not only at the global protein structure level but also with respect to the atomic details of bound ligands.ConclusionsFreely available eModel-BDB can be used to support structure-based drug discovery and repositioning, drug target identification, and protein structure determination.
Highlights
The structural information on proteins in their ligand-bound conformational state is invaluable for protein function studies and rational drug design
In addition to a rigorous quality control maintained during dataset generation, a subset of weakly homologous models was selected for the retrospective validation against experimental structural data recently deposited to the Protein Data Bank
The first phase is to construct structure models for single protein chains 50–999 amino acids in length obtained from BindingDB with eThread [6], which supports both close and remote homology modeling. eThread employs Modeller, a commonly used comparative modeling program (RRID:SCR 008395) [7], to build apo-protein structures based on alignments produced by 3-fold recognition algorithms, HH-suite [8], SparksX [9], and RaptorX [10]
Summary
Structural bioinformatics is becoming an increasingly important component of modern drug discovery. As of June 2018, BindingDB contained 1,450,120 binding data; only 2,291 ligand-protein crystal structures with BindingDB affinity measurements are available in the PDB To bridge this gap, we created eModel-BDB, a new database of 200,005 high-quality drug-protein complex models involving 108,363 unique drug-like compounds and 2,791 proteins from the BindingDB. We created eModel-BDB, a new database of 200,005 high-quality drug-protein complex models involving 108,363 unique drug-like compounds and 2,791 proteins from the BindingDB This repository was constructed with a state-of-the-art protocol to generate protein models in their ligand-bound conformational state, employing meta-threading, pocket detection, and protein structure and ligand chemical alignment techniques. In contrast to other databases comprising protein models in the unbound conformational state generated through traditional structure modeling [4, 5], eModel-BDB includes annotated structure models of drug-protein complexes with known binding affinities
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