Matched Molecular Pair-based Data Sets for Computer-aided Medicinal Chemistry

Overview

Journal F1000Res

Specialties Biomedical Engineering
Science

Date 2014 Mar 18

PMID 24627802

Citations 4

Authors

Ye Hu

Antonio de la Vega de Leon

Bijun Zhang

Jurgen Bajorath

Affiliations

Soon will be listed here.

Abstract

Matched molecular pairs (MMPs) are widely used in medicinal chemistry to study changes in compound properties including biological activity, which are associated with well-defined structural modifications. Herein we describe up-to-date versions of three MMP-based data sets that have originated from in-house research projects. These data sets include activity cliffs, structure-activity relationship (SAR) transfer series, and second generation MMPs based upon retrosynthetic rules. The data sets have in common that they have been derived from compounds included in the ChEMBL database (release 17) for which high-confidence activity data are available. Thus, the activity data associated with MMP-based activity cliffs, SAR transfer series, and retrosynthetic MMPs cover the entire spectrum of current pharmaceutical targets. Our data sets are made freely available to the scientific community.

Citing Articles

Automatic Identification of Analogue Series from Large Compound Data Sets: Methods and Applications.

Naveja J, Vogt M Molecules. 2021; 26(17).

PMID: 34500724 PMC: 8433811. DOI: 10.3390/molecules26175291.

A probabilistic molecular fingerprint for big data settings.

Probst D, Reymond J J Cheminform. 2018; 10(1):66.

PMID: 30564943 PMC: 6755601. DOI: 10.1186/s13321-018-0321-8.

Using ChEMBL web services for building applications and data processing workflows relevant to drug discovery.

Nowotka M, Gaulton A, Mendez D, Bento A, Hersey A, Leach A Expert Opin Drug Discov. 2017; 12(8):757-767.

PMID: 28602100 PMC: 6321761. DOI: 10.1080/17460441.2017.1339032.

Follow up: Compound data sets and software tools for chemoinformatics and medicinal chemistry applications: update and data transfer.

Hu Y, Bajorath J F1000Res. 2014; 3:69.

PMID: 25520777 PMC: 4264635. DOI: 10.12688/f1000research.3713.1.

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