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KinomeRun: An interactive utility for kinome target screening and interaction fingerprint analysis towards holistic visualization on kinome tree
Author(s) -
Ansar Samdani,
Vetrivel Umashankar
Publication year - 2020
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/cbdd.13705
Subject(s) - kinome , computer science , computational biology , visualization , drug discovery , data mining , bioinformatics , kinase , biology , microbiology and biotechnology
Kinases are key targets for many of the pathological conditions. Inverse screening of ligands serves as an essential mode to identify potential kinase targets in modern drug discovery research. Hence, we intend to develop KinomeRun, a robust pipeline for inverse screening and kinome tree visualization through the seamless integration of kinome structures, docking and kinome-drug interaction fingerprint analysis. In this pipeline, the hurdle of residue numbering in kinome is also resolved by creating a common index file with the conserved kinase pocket residues for comparative interaction analysis. KinomeRun can be used to screen the ligands of interest docked against multiple kinase structures in parallel around the kinase binding site and also to filter out the targets with unique interaction patterns. This automation is essential for prioritization of kinase targets that show specificity for a given drug and will also serve as a crucial tool kit for holistic approaches in kinase drug discovery. KinomeRun is developed using python and bash programming language and is distributed freely under the GNU GPL licence-3.0 and can be downloaded at https://github.com/inpacdb/KinomeRun. The tutorial videos for installation, target screening and customized filtration are available at https://www.youtube.com/playlist?list=PLuIaEFtMVgQ7v__WigQH9ilGVxrfI1LKs and also be downloaded for offline viewing from the github link.