PSICalc: A novel approach to identifying and ranking critical non-proximal interdependencies within the overall protein structure
Bioinformatics Advances, ISSN: 2635-0041, Vol: 2, Issue: 1, Page: vbac058
2022
- 3Citations
- 1Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations3
- Citation Indexes3
- Captures1
- Readers1
Article Description
Motivation: AlphaFold has been a major advance in predicting protein structure, but still leaves the problem of determining which sub-molecular components of a protein are essential for it to carry out its function within the cell. Direct coupling analysis predicts two-and three-Amino acid contacts, but there may be essential interdependencies that are not proximal within the 3D structure. The problem to be addressed is to design a computational method that locates and ranks essential non-proximal interdependencies within a protein involving five or more amino acids, using large, multiple sequence alignments (MSAs) for both globular and intrinsically unstructured proteins. Results: We developed PSICalc (Protein Subdomain Interdependency Calculator), a laptop-friendly, pattern-discovery, bioinformatics software tool that analyzes large MSAs for both structured and unstructured proteins, locates both proximal and non-proximal inter-dependent sites, and clusters them into pairwise (second order), third-order and higher-order clusters using a k-modes approach, and provides ranked results within minutes. To aid in visualizing these interdependencies, we developed a graphical user interface that displays these subdomain relationships as a polytree graph. To demonstrate, we provide examples of both proximal and non-proximal interdependencies documented for eukaryotic topoisomerase II including between the unstructured C-Terminal domain and the N-Terminal domain.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85148558023&origin=inward; http://dx.doi.org/10.1093/bioadv/vbac058; http://www.ncbi.nlm.nih.gov/pubmed/36699404; https://academic.oup.com/bioinformaticsadvances/article/doi/10.1093/bioadv/vbac058/6671262; https://dx.doi.org/10.1093/bioadv/vbac058; https://academic.oup.com/bioinformaticsadvances/article/2/1/vbac058/6671262
Oxford University Press (OUP)
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