Comprehensive In Silico Functional Prediction Analysis of CDKL5 by Single Amino Acid Substitution in the Catalytic Domain

Autor: Yuri Yoshimura, Atsushi Morii, Yuuki Fujino, Marina Nagase, Arisa Kitano, Shiho Ueno, Kyoka Takeuchi, Riko Yamashita, Tetsuya Inazu
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: International Journal of Molecular Sciences, Vol 23, Iss 20, p 12281 (2022)
Druh dokumentu: article
ISSN: 1422-0067
1661-6596
DOI: 10.3390/ijms232012281
Popis: Cyclin-dependent kinase-like 5 (CDKL5) is a serine/threonine protein kinase whose pathological mutations cause CDKL5 deficiency disorder. Most missense mutations are concentrated in the catalytic domain. Therefore, anticipating whether mutations in this region affect CDKL5 function is informative for clinical diagnosis. This study comprehensively predicted the pathogenicity of all 5700 missense substitutions in the catalytic domain of CDKL5 using in silico analysis and evaluating their accuracy. Each missense substitution was evaluated as “pathogenic” or “benign”. In silico tools PolyPhen-2 HumDiv mode/HumVar mode, PROVEAN, and SIFT were selected individually or in combination with one another to determine their performance using 36 previously reported mutations as a reference. Substitutions predicted as pathogenic were over 88.0% accurate using each of the three tools. The best performance score (accuracy, 97.2%; sensitivity, 100%; specificity, 66.7%; and Matthew’s correlation coefficient (MCC), 0.804) was achieved by combining PolyPhen-2 HumDiv, PolyPhen-2 HumVar, and PROVEAN. This provided comprehensive information that could accurately predict the pathogenicity of the disease, which might be used as an aid for clinical diagnosis.
Databáze: Directory of Open Access Journals
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