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BioinformaticsCommunications Chemistry
Peer-reviewed journal article

MdrDB: Mutation-induced drug resistance DataBase

Ziyi YangiD, Zhaofeng Ye, Jiezhong QiuiD, Rongjun FengiD, Danyu LiiD, Chang‐Yu HsiehiD, Jonathan AllcockiD, Shengyu ZhangiD

Abstract

AO_SCPLOWBSTRACTC_SCPLOWMutation-induced drug resistance - where the efficacy of drugs is diminished by structural changes in proteins - presents a significant challenge to drug development and the clinical treatment of disease. Understanding the effects of mutation on protein-ligand binding affinities is a key step in developing more effective drugs and therapies, but as a research community we are currently hindered by the lack of a comprehensive database of relevant information. To address this issue, we have developed MdrDB, a database of information related to changes in protein-ligand affinity caused by mutations in protein structure. MdrDB combines data from seven publicly available datasets with calculated biochemical features, as well as 3D structures computed with PyMOL and AlphaFold 2.0, to form the largest database of its kind. With 3D structural information provided for all samples, MdrDB was specifically created to have the size, breadth, and complexity to be useful for practical protein mutation studies and drug resistance modeling. The database brings together wild type and mutant protein-ligand complexes, binding affinity changes upon mutation ({Delta}{Delta}G), and biochemical features calculated from complexes to advance our understanding of mutation-induced drug resistance, the development of combination therapies, and the discovery of novel chemicals. In total, MdrDB contains 100,537 samples generated from 240 proteins (5,119 total PDB structures), 2,503 mutations, and 440 drugs. Of the total samples, 95,971 are based on available PDB structures, with the remaining 4,566 based on AlphaFold 2.0 predicted structures.

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02 /Specification & Classification

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