From Genome Mining to Protein Engineering: A Structural Bioinformatics Route
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Overview
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Abstract
This chapter outlines applications in genome mining, along with computational methods to predict protein structure and protein-ligand docking. It offers a simple computational route to rapidly identify proteins of interest from genomic and proteomic data, to accurately predict their three-dimensional structures, and to dock small molecules to their binding pockets and strategies to improve their biophysical properties depending on the needs of the experimental researcher.
References
1.
Scherlach K, Hertweck C
. Mining and unearthing hidden biosynthetic potential. Nat Commun. 2021; 12(1):3864.
PMC: 8222398.
DOI: 10.1038/s41467-021-24133-5.
View
2.
Han X, Wang Y, Chen Y, Lin L, Wu Q
. Transcriptome sequencing and expression analysis of terpenoid biosynthesis genes in Litsea cubeba. PLoS One. 2013; 8(10):e76890.
PMC: 3793921.
DOI: 10.1371/journal.pone.0076890.
View
3.
Robey M, Caesar L, Drott M, Keller N, Kelleher N
. An interpreted atlas of biosynthetic gene clusters from 1,000 fungal genomes. Proc Natl Acad Sci U S A. 2021; 118(19).
PMC: 8126772.
DOI: 10.1073/pnas.2020230118.
View
4.
Polturak G, Osbourn A
. The emerging role of biosynthetic gene clusters in plant defense and plant interactions. PLoS Pathog. 2021; 17(7):e1009698.
PMC: 8253395.
DOI: 10.1371/journal.ppat.1009698.
View
5.
Blin K, Shaw S, Kloosterman A, Charlop-Powers Z, van Wezel G, Medema M
. antiSMASH 6.0: improving cluster detection and comparison capabilities. Nucleic Acids Res. 2021; 49(W1):W29-W35.
PMC: 8262755.
DOI: 10.1093/nar/gkab335.
View