Computational SNP Analysis and Molecular Simulation Revealed the Most Deleterious Missense Variants in the NBD1 Domain of Human ABCA1 Transporter

Dash, Raju; Ali, Md. Chayan; Rana, Md. Liton; Munni, Yeasmin Akter; Barua, Largess; Jahan, Israt; Haque, Mst Fatema; Hannan, Md. Abdul; Moon, Il Soo

doi:10.3390/ijms21207606

Cited by 27 publications

(22 citation statements)

References 120 publications

(141 reference statements)

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“…Prior studies on mutant protein–ligand complexes have produced similar results with the analysis of RMSD, H-bonds, and SASA [ 69 , 70 , 71 , 72 ]. It was also observed that the fluctuation was high for the 0–125 ns simulation compared to the 150–250 ns simulation for these three analyses, specifically for RMSD ( Figure 8 A2,B2,C2).…”

Section: Discussionmentioning

confidence: 69%

Comprehensive Characterization of the Coding and Non-Coding Single Nucleotide Polymorphisms in the Tumor Protein p63 (TP63) Gene Using In Silico Tools

et al. 2021

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Single nucleotide polymorphisms (SNPs) help to understand the phenotypic variations in humans. Genome-wide association studies (GWAS) have identified SNPs located in the tumor protein 63 (TP63) locus to be associated with the genetic susceptibility of cancers. However, there is a lack of in-depth characterization of the structural and functional impacts of the SNPs located at the TP63 gene. The current study was designed for the comprehensive characterization of the coding and non-coding SNPs in the human TP63 gene for their functional and structural significance. The functional and structural effects of the SNPs were investigated using a wide variety of computational tools and approaches, including molecular dynamics (MD) simulation. The deleterious impact of eight nonsynonymous SNPs (nsSNPs) affecting protein stability, structure, and functions was measured by using 13 bioinformatics tools. These eight nsSNPs are in highly conserved positions in protein and were predicted to decrease protein stability and have a deleterious impact on the TP63 protein function. Molecular docking analysis showed five nsSNPs to reduce the binding affinity of TP63 protein to DNA with significant results for three SNPs (R319H, G349E, and C347F). Further, MD simulations revealed the possible disruption of TP63 and DNA binding, hampering the essential protein function. PolymiRTS study found five non-coding SNPs in miRNA binding sites, and the GTEx portal recognized five eQTLs SNPs in single tissue of the lung, heart (LV), and cerebral hemisphere (brain). Characterized nsSNPs and non-coding SNPs will help researchers to focus on TP63 gene loci and ascertain their association with certain diseases.

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Section: Discussionmentioning

confidence: 69%

Comprehensive Characterization of the Coding and Non-Coding Single Nucleotide Polymorphisms in the Tumor Protein p63 (TP63) Gene Using In Silico Tools

et al. 2021

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“…Again, to expose the changes in protein dynamics, we conducted principal component analysis (PCA), representing most of the dominant motions during the simulations [ 17 , 29 ]. Remarkably, all variants were found to have more variances than that of the wild-type, such as G11R, G32R, G120E, and A156D with variances of 60.9%, 53.9%, 53.9%, and 58.8%, respectively, in the first three PCs, whereas wild-type has a variance of 43.2%.…”

Section: Resultsmentioning

confidence: 99%

“…MD simulation was performed by YASARA Dynamics software by using Assisted Model Building with Energy Refinement (AMBER 14) force field [ 70 , 71 ], as previously described [ 17 , 72 , 73 , 74 ]. In the beginning, structure, variants, and native were cleaned and the hydrogen bond network was optimized.…”

Section: Methodsmentioning

confidence: 99%

“…The nsSNPs, which occurred in the coding region and caused amino acid substitutions, are the most responsible for phenotypic change and are associated with many genetic diseases due to their effect on protein structure, charge, solubility, stability, and function [ 15 , 16 ]. In light of this fact, it is expected that the presence of nsSNPs in NAGK might have a considerable impact on both canonical and non-canonical functions; however, analyzing the impact of a large number of nsSNPs using an experimental approach is more time consuming and expensive [ 17 , 18 ]. Therefore, we investigate the possible damaging effects of nsSNPs in NAGK structural dynamics using bioinformatics and molecular simulation approaches.…”

Section: Introductionmentioning

confidence: 99%

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Computational Insights into the Deleterious Impacts of Missense Variants on N-Acetyl-d-glucosamine Kinase Structure and Function

Dash

Mitra

Munni

et al. 2021

IJMS

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An enzyme of the mammalian amino-sugar metabolism pathway, N-acetylglucosamine kinase (NAGK), that synthesizes N-acetylglucosamine (GlcNAc)-6-phosphate, is reported to promote dynein functions during mitosis, axonal and dendritic growth, cell migration, and selective autophagy, which all are unrelated to its enzyme activity. As non-enzymatic structural functions can be altered by genetic variation, we made an effort in this study aimed at deciphering the pathological effect of nonsynonymous single-nucleotide polymorphisms (nsSNPs) in NAGK gene. An integrated computational approach, including molecular dynamics (MD) simulation and protein–protein docking simulation, was used to identify the damaging nsSNPs and their detailed structural and functional consequences. The analysis revealed the four most damaging variants (G11R, G32R, G120E, and A156D), which are highly conserved and functional, positioned in both small (G11R and G32R) and large (G120E and A156D) domains of NAGK. G11R is located in the ATP binding region, while variants present in the large domain (G120E and A156D) were found to induce substantial alterations in the structural organizations of both domains, including the ATP and substrate binding sites. Furthermore, all variants were found to reduce binding energy between NAGK and dynein subunit DYNLRB1, as revealed by protein–protein docking and MM-GBSA binding energy calculation supporting their deleteriousness on non-canonical function. We hope these findings will direct future studies to gain more insight into the role of these variants in the loss of NAGK function and their role in neurodevelopmental disorders.

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“…In silico bioinformatics tools, including SIFT, polyphen, condel, CADD, DANN, FATHMM, M-CAP, MetalR, MutPred, MutationAssessor, PROVEAN, VEST3, fathmm-MKL, I mutant3.0, iSTABLE, MuPro, PhD-SNP, PANTHER, SNPs and GO, and SNAP2 have been associated for this study. SIFT [ 57 ] is a PSI-Blast logarithm-based in-silico tool that uses sequence homology and predicts the potential role of amino acid substitution on protein function [ 58 ]. The prediction value of SIFT ranges from 0 to 1.…”

Section: Methodsmentioning

confidence: 99%

Structural Consequence of Non-Synonymous Single-Nucleotide Variants in the N-Terminal Domain of LIS1

Choi

Mitra

Munni

et al. 2022

IJMS

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Disruptive neuronal migration during early brain development causes severe brain malformation. Characterized by mislocalization of cortical neurons, this condition is a result of the loss of function of migration regulating genes. One known neuronal migration disorder is lissencephaly (LIS), which is caused by deletions or mutations of the LIS1 (PAFAH1B1) gene that has been implicated in regulating the microtubule motor protein cytoplasmic dynein. Although this class of diseases has recently received considerable attention, the roles of non-synonymous polymorphisms (nsSNPs) in LIS1 on lissencephaly progression remain elusive. Therefore, the present study employed combined bioinformatics and molecular modeling approach to identify potential damaging nsSNPs in the LIS1 gene and provide atomic insight into their roles in LIS1 loss of function. Using this approach, we identified three high-risk nsSNPs, including rs121434486 (F31S), rs587784254 (W55R), and rs757993270 (W55L) in the LIS1 gene, which are located on the N-terminal domain of LIS1. Molecular dynamics simulation highlighted that all variants decreased helical conformation, increased the intermonomeric distance, and thus disrupted intermonomeric contacts in the LIS1 dimer. Furthermore, the presence of variants also caused a loss of positive electrostatic potential and reduced dimer binding potential. Since self-dimerization is an essential aspect of LIS1 to recruit interacting partners, thus these variants are associated with the loss of LIS1 functions. As a corollary, these findings may further provide critical insights on the roles of LIS1 variants in brain malformation.

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Computational SNP Analysis and Molecular Simulation Revealed the Most Deleterious Missense Variants in the NBD1 Domain of Human ABCA1 Transporter

Cited by 27 publications

References 120 publications

Comprehensive Characterization of the Coding and Non-Coding Single Nucleotide Polymorphisms in the Tumor Protein p63 (TP63) Gene Using In Silico Tools

Comprehensive Characterization of the Coding and Non-Coding Single Nucleotide Polymorphisms in the Tumor Protein p63 (TP63) Gene Using In Silico Tools

Computational Insights into the Deleterious Impacts of Missense Variants on N-Acetyl-d-glucosamine Kinase Structure and Function

Structural Consequence of Non-Synonymous Single-Nucleotide Variants in the N-Terminal Domain of LIS1

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