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      Prediction and assessment of deleterious and disease causing nonsynonymous single nucleotide polymorphisms (nsSNPs) in human FOXP4 gene: An in - silico study

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          Abstract

          In humans, FOXP gene family is involved in embryonic development and cancer progression. The FOXP4 (Forkhead box protein P4) gene belongs to this FOXP gene family. FOXP4 gene plays a crucial role in oncogenesis. Single nucleotide polymorphisms are biological markers and common determinants of human diseases. Mutations can largely affect the function of the corresponding protein. Therefore, the molecular mechanism of nsSNPs in the FOXP4 gene needs to be elucidated. Initially, the SNPs of the FOXP4 gene were extracted from the dbSNP database and a total of 23124 SNPs was found, where 555 nonsynonymous, 20525 intronic, 1114 noncoding transcript, 334 synonymous were obtained and the rest were unspecified. Then, a series of bioinformatics tools (SIFT, PolyPhen2, SNAP2, PhD SNP, PANTHER, I-Mutant2.0, MUpro, GOR IV, ConSurf, NetSurfP 2.0, HOPE, DynaMut2, GeneMANIA, STRING and Schrodinger) were used to explore the effect of nsSNPs on FOXP4 protein function and structural stability. First, 555 nsSNPs were analyzed using SIFT, of which 57 were found as deleterious. Following, PolyPhen2, SNAP2, PhD SNP and PANTHER analyses, 10 nsSNPs (rs372762294, rs141899153, rs142575732, rs376938850, rs367607523, rs112517943, rs140387832, rs373949416, rs373949416 and rs376160648) were common and observed as deleterious, damaging and diseases associated. Following that, using I-Mutant2.0 and MUpro servers, 7 nsSNPs were found to be the most unstable. GOR IV predicted that these seven nsSNPs affect protein structure by altering the protein contents of alpha helixes, extended strands, and random coils. Following DynaMut2, 5 nsSNPs showed a decrease in the ΔΔG value compared with the wild-type and were found to be responsible for destabilizing the corresponding protein. GeneMANIA and STRING network revealed interaction of FOXP4 with other genes. Finally, molecular dynamics simulation analysis revealed consistent fluctuation in RMSD and RMSF values, Rg and hydrogen bonds in the mutant proteins compared with WT, which might alter the functional and structural stability of the corresponding protein. As a result, the aforementioned integrated comprehensive bioinformatic analyses provide insight into how various nsSNPs of the FOXP4 gene change the structural and functional properties of the corresponding protein, potentially proceeding with the pathophysiology of human diseases.

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          The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest

          Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known, but novel interactions continue to be discovered, and the information remains scattered across different database resources, experimental modalities and levels of mechanistic detail. The STRING database ( https://string-db.org/ ) systematically collects and integrates protein–protein interactions—both physical interactions as well as functional associations. The data originate from a number of sources: automated text mining of the scientific literature, computational interaction predictions from co-expression, conserved genomic context, databases of interaction experiments and known complexes/pathways from curated sources. All of these interactions are critically assessed, scored, and subsequently automatically transferred to less well-studied organisms using hierarchical orthology information. The data can be accessed via the website, but also programmatically and via bulk downloads. The most recent developments in STRING (version 12.0) are: (i) it is now possible to create, browse and analyze a full interaction network for any novel genome of interest, by submitting its complement of encoded proteins, (ii) the co-expression channel now uses variational auto-encoders to predict interactions, and it covers two new sources, single-cell RNA-seq and experimental proteomics data and (iii) the confidence in each experimentally derived interaction is now estimated based on the detection method used, and communicated to the user in the web-interface. Furthermore, STRING continues to enhance its facilities for functional enrichment analysis, which are now fully available also for user-submitted genomes.
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            Structure and Dynamics of the TIP3P, SPC, and SPC/E Water Models at 298 K

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              SIFT web server: predicting effects of amino acid substitutions on proteins

              The Sorting Intolerant from Tolerant (SIFT) algorithm predicts the effect of coding variants on protein function. It was first introduced in 2001, with a corresponding website that provides users with predictions on their variants. Since its release, SIFT has become one of the standard tools for characterizing missense variation. We have updated SIFT’s genome-wide prediction tool since our last publication in 2009, and added new features to the insertion/deletion (indel) tool. We also show accuracy metrics on independent data sets. The original developers have hosted the SIFT web server at FHCRC, JCVI and the web server is currently located at BII. The URL is http://sift-dna.org (24 May 2012, date last accessed).
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                Author and article information

                Contributors
                Journal
                Heliyon
                Heliyon
                Heliyon
                Elsevier
                2405-8440
                15 June 2024
                30 June 2024
                15 June 2024
                : 10
                : 12
                : e32791
                Affiliations
                [a ]Department of Nutrition and Food Technology, Jashore University of Science and Technology, Jashore, 7408, Bangladesh
                [b ]Department of Genetic Engineering & Biotechnology, Bangabandhu Sheikh Mujibur Rahman Maritime University, Dhaka, 1216, Bangladesh
                [c ]Department of Genetic Engineering & Biotechnology, Jashore University of Science and Technology, Jashore, 7408, Bangladesh
                [d ]Laboratory of Computational Biology, Biological Solution Centre, Jashore, 7408, Bangladesh
                [e ]BIRTAN-Bangladesh Institute of Research and Training on Applied Nutrition, Jhenaidah, 7300, Bangladesh
                [f ]Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, 11451, Saudi Arabia
                Author notes
                [* ]Corresponding author. Department of Nutrition and Food Technology, Jashore University of Science and Technology, Jashore, 7408, Bangladesh. rmkmostafa@ 123456gmail.com
                [** ]Corresponding author. hasanm_agb@ 123456yahoo.com
                Article
                S2405-8440(24)08822-4 e32791
                10.1016/j.heliyon.2024.e32791
                11237951
                38994097
                1d34f140-14ab-4e30-b803-28084dd32779
                © 2024 The Author(s)

                This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

                History
                : 1 May 2024
                : 10 June 2024
                Categories
                Research Article

                foxp4 gene,functional prediction,stability prediction,secondary and tertiary structure and interaction analysis

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