Title: In silico deleterious prediction of nonsynonymous single nucleotide polymorphisms in Neurexin1 gene for mental disorders
Authors: Ashraf Hendam; Ahmed Farouk Al-Sadek; Hesham Ahmed Hefny
Addresses: Bioinformatics Unit, Central Lab for Agricultural Experts Systems, Agricultural Research Center, Giza, 12611, Egypt ' Head of Bioinformatics Unit, Central Lab for Agricultural Experts Systems, Agricultural Research Center, Giza, 12611, Egypt ' Institute of Statistical Studies and Research (ISSR), Cairo University, Giza, 12613, Egypt
Abstract: Neurexin1 (NRXN1) gene is playing an important role in synaptic formation, plasticity and maturity. Studies have reported non-synonymous SNPs in NRXN1 in patient with mental disorders. The current work is applying computational tools on recoded NRXN1 SNPs in mental disorder patients. The aim of the work is to identify deleterious SNPs, determine damaged protein features (function, stability) and recognise potential protein regions for future research. The effect on protein function is predicted by PROVEAN, SIFT and PolyPhen-2 while protein stability is predicted by MUpro and I-Mutant2.0. Prediction results have identified 2 SNPs to be deleterious by all tools. Higher deleterious results in the stability tools with the percentages of 72%, 78% than the function tools with 25%, 41% and 47%. Agreement percentage of deleterious prediction between stability tools was 56% while 12.5% in the function tools. The identified regions of NRXN1 for future research are SP and LNS4.
Keywords: nonsynonymous SNP; in silico; Neurexin1; mental disorders; autism; PROVEAN; SIFT; PolyPhen-2; MUpro; I-Mutant2.0.
International Journal of Bioinformatics Research and Applications, 2020 Vol.16 No.1, pp.1 - 24
Received: 04 Feb 2017
Accepted: 27 Nov 2017
Published online: 02 Feb 2020 *