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TMKit: a Python interface for computational analysis of transmembrane proteins

delete2023-08-17
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J
Jianfeng Sun
A
A. Kulandaisamy
J
Jinlong Ru
M
M. Michael Gromiha *
A
Adam P. Cribbs *
DOI:10.1093/bib/bbad288delete
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Abstract

Abstract

En 中文
Transmembrane proteins are receptors, enzymes, transporters and ion channels that are instrumental in regulating a variety of cellular activities, such as signal transduction and cell communication. Despite tremendous progress in computational capacities to support protein research, there is still a significant gap in the availability of specialized computational analysis toolkits for transmembrane protein research. Here, we introduce TMKit, an open-source Python programming interface that is modular, scalable and specifically designed for processing transmembrane protein data. TMKit is a one-stop computational analysis tool for transmembrane proteins, enabling users to perform database wrangling, engineer features at the mutational, domain and topological levels, and visualize protein-protein interaction interfaces. In addition, TMKit includes seqNetRR, a high-performance computing library that allows customized construction of a large number of residue connections. This library is particularly well suited for assigning correlation matrix-based features at a fast speed. TMKit should serve as a useful tool for researchers in assisting the study of transmembrane protein sequences and structures. TMKit is publicly available through and .
Keywords:
bioinformatics
transmembrane proteins
sequence analysis
structural biology
protein interaction interfaces
feature extraction
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Briefings in Bioinformatics cover
Briefings in Bioinformatics
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