Identification of deleterious nsSNPs in human HGF gene: in silico approach

Hoda, Anila; Çekani, Mirela Lika; Kolaneci, V.

doi:10.1080/07391102.2022.2164060

Cited by 7 publications

(4 citation statements)

References 58 publications

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“…All employed computational tools work on the principle of algorithms that are trained on a range of disease‐related missense mutations and controls [ 28 , 29 , 60 ]. Therefore, this findings needs to be further confirmed by the experimental laboratory settings [ 61 ]. Genome‐wide association studies (GWASs) can be employed to reliably identify missense SNPs in patients causing diseases [ 60 , 62 ].…”

Section: Discussionmentioning

confidence: 99%

Identifying Oncogenic Missense Single Nucleotide Polymorphisms in Human SAT1 Gene Using Computational Algorithms and Molecular Dynamics Tools

Mozibullah,

Khatun,

Sikder

et al. 2024

Cancer Reports

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BackgroundThe human SAT1 gene encodes spermidine/spermine N1‐acetyltransferase 1 (SSAT1), a regulatory biological catalyst of polyamine catabolism. Numerous essential biological processes, such as cellular proliferation, differentiation, and survival, depend on polyamines like spermidine and spermine. Thus, SSAT1 is involved in key cellular activities such as proliferation and survival of cells and mediates various diseases including cancer. A plethora of studies established the involvement of missense single nucleotide polymorphisms (SNPs) in numerous pathological conditions due to their ability to adversely affect the structure and subsequent function of the protein.AimsTo date, an in silico study to identify the pathogenic missense SNPs of the human SAT1 gene has not been accomplished yet. This study aimed to filter the missense SNPs that were functionally detrimental and pathogenic.Methods and ResultsThe rs757435207 (I21N) was ascertained to be the most deleterious and pathogenic by all algorithmic tools. Stability and evolutionary conservation analysis tools also stated that I21N variant decreased the stability and was located in the highly conserved residue. Molecular dynamics simulation revealed that I21N caused substantial alterations in the conformational stability and dynamics of the SSAT1 protein. Consequently, the I21N variant could disrupt the native functional roles of the SSAT1 enzyme.ConclusionTherefore, the I21N variant was identified and concluded to be an oncogenic missense variant of the human SAT1 gene. Overall, the findings of this study would be a great directory of future experimental research to develop personalized medicine.

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Section: Discussionmentioning

confidence: 99%

Identifying Oncogenic Missense Single Nucleotide Polymorphisms in Human SAT1 Gene Using Computational Algorithms and Molecular Dynamics Tools

Mozibullah,

Khatun,

Sikder

et al. 2024

Cancer Reports

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“…This assessment showed that the mutant complexes can show the least binding interactions than native complexes on the basis of their deleterious effect. On the other hand, similar in silico analysis of the HGF gene revealed that five nsSNPs (D358G, G648R, I550N, N175S, and R220Q) of the HGF are the most deleterious that hinder MET–HGF interaction [ 66 ].…”

Section: Discussionmentioning

confidence: 99%

An In silico Approach towards Finding the Cancer-Causing Mutations in Human MET Gene

Laskar,

Bappy,

Hossain

et al. 2023

International Journal of Genomics

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Mesenchymal–epithelial transition (MET) factor is a proto-oncogene encoding tyrosine kinase receptor with hepatocyte growth factor (HGF) or scatter factor (SF). It is found on the human chromosome number 7 and regulates the diverse cellular mechanisms of the human body. The impact of mutations occurring in the MET gene is demonstrated by their detrimental effects on normal cellular functions. These mutations can change the structure and function of MET leading to different diseases such as lung cancer, neck cancer, colorectal cancer, and many other complex syndromes. Hence, the current study focused on finding deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) and their subsequent impact on the protein’s structure and functions, which may contribute to the emergence of cancers. These nsSNPs were first identified utilizing computational tools like SIFT, PROVEAN, PANTHER-PSEP, PolyPhen-2, I-Mutant 2.0, and MUpro. A total of 45359 SNPs of MET gene were accumulated from the database of dbSNP, and among them, 1306 SNPs were identified as non-synonymous or missense variants. Out of all 1306 nsSNPs, 18 were found to be the most deleterious. Moreover, these nsSNPs exhibited substantial effects on structure, binding affinity with ligand, phylogenetic conservation, secondary structure, and post-translational modification sites of MET, which were evaluated using MutPred2, RaptorX, ConSurf, PSIPRED, and MusiteDeep, respectively. Also, these deleterious nsSNPs were accompanied by changes in properties of MET like residue charge, size, and hydrophobicity. These findings along with the docking results are indicating the potency of the identified SNPs to alter the structure and function of the protein, which may lead to the development of cancers. Nonetheless, Genome-wide association study (GWAS) studies and experimental research are required to confirm the analysis of these nsSNPs.

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“…In addition, it provides rapid prediction for many compounds, allows obtaining pioneering data in drug development activities, and missense SNPs with possible harmful effects in genes known to be associated with diseases can be detected, as in our study. Thanks to this detection, instead of analyzing hundreds or thousands of SNPs, those predicted in silico can be studied first in research [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of SNP in the CDH8 and CDH10 Genes Associated with Autism Using In-Silico Tools

Rezaeirad,

Karasakal,

Kaman

et al. 2024

Turkish Journal of Science and Technology

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Autism spectrum disorder (ASD) is defined as a pervasive and multifactorial neurodevelopmental disorder. It is characterized by repetitive behavioral patterns as well as symptoms of social interaction and communication disorder. The cadherin (CDH) superfamily is a large group of synaptic cell adhesion molecules and has been widely associated with neurodevelopmental disorders, including autism. The aim of this study is to evaluate the potentially harmful missense SNPs in CDH8 and CDH10 genes, which are associated with autism spectrum disorder and cause amino acid changes, using internet-based software tools. To predict the possible harmful effects of Missense SNPs; SIFT, PolyPhen-2, PROVEAN, SNPs&GO, Meta-SNP and SNAP2 software tools were used and possible common harmful ones were determined in all of them. Its effect on protein stabilization was investigated with I-Mutant 3.0 and MUpro tools. Three-dimensional models of these common damaging amino acid changes were evaluated with the HOPE software. As a result of in silico analysis of 577 missense SNPs in the CDH8 gene; The rs145143780 (Y572C) polymorphism common damaging ‎SNP has been detected by all software tools.‎ According to the results of the in silico analysis of 526 missense SNPs found in the CDH10 gene; The rs13174039 (V459G), rs147882578 (N485K), rs201423740 (Y306C), rs201956238 (F317L) and rs373340564 (R128C) common damaging SNPs have been identified in all polymorphisms by all software tools. As a result of this study, it is thought that the data obtained will make important contributions to future relevant experimental studies.

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Identification of deleterious nsSNPs in human HGF gene: in silico approach

Cited by 7 publications

References 58 publications

Identifying Oncogenic Missense Single Nucleotide Polymorphisms in Human SAT1 Gene Using Computational Algorithms and Molecular Dynamics Tools

Identifying Oncogenic Missense Single Nucleotide Polymorphisms in Human SAT1 Gene Using Computational Algorithms and Molecular Dynamics Tools

An In silico Approach towards Finding the Cancer-Causing Mutations in Human MET Gene

Evaluation of SNP in the CDH8 and CDH10 Genes Associated with Autism Using In-Silico Tools

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