Biology subjects

Murshed, N. S.

Publications and source records attributed to Murshed, N. S..

11 recordsLinked to original sources

bioRxiv2020

Extensive In Silico Analysis of the Functional and Structural Consequences of SNPs in Human ARX Gene

Early infantile epileptic encephalopathy 1 (EIEE1) is a rare but devastating neurologic disorder that displays concomitant cognitive and motor impairment, and is often presented in the first months of life with severe intellectual disability. The objective of this study is to classify the most deleterious nsSNPs in ARX gene that may cause EIEE1 disease. Despite the reported association of ARX gene mutations with vulnerability to several neurologic condition, there is lack of in silico analysis on the functional and structural impacts of single nucleotide polymorphisms (SNPs) of the ARX at protein level. Therefore, the pathogenic nsSNPs in the human ARX obtained from NCBI were analyzed for their functional and structural impact using bioinformatics tools like SIFT, Polyphen, PROVEAN, I-Mutant, and MUPro. The effects of the mutations on tertiary structure of the human ARX protein were predicted using RaptorX and visualized by UCSF Chimera while STRING was used to investigate its protein-protein interaction. Our extensive in silico analysis revealed 11 mutations that will significantly alter the structure of human ARX protein; that may disturb the domain which will affect the function of the protein. Extensive in silico analysis of the functional and structural consequences of SNPs in human ARX gene revealed 11 mutations (L535Q, R528S, R380L, V374D, L343Q, T333N, T333S, R332H, R330H, G34R and L33P) that may cause EIEE1.Therefore, can be used as diagnostic markers for EIEE1.

bioinformatics↗

bioRxiv2020

In Silico Analysis of B3GALTL Gene Reveling 13 Novel Mutations Associated with Peters'-plus syndrome

BackgroundPeters-plus syndrome is a rare autosomal recessive disorder, which is characterized by a specific malformation of the eye that includes corneal opaqueness and iridocorneal adhesions (Peters anomaly) along with other systemic manifestations. Furthermore, various researches report the association between B3GALTL gene and Peters-plus syndrome. In the current work we aim to analyze the deleterious SNPs in B3GALTL gene that predispose to Peters-plus syndrome. Methodthe associated SNPs of the coding region of the B3GALTL gene was acquired from National Center for Biotechnology Information and then analyzed by eight softwares (SIFT, Polyphen2, Proven, SNAP2, SNP@GO, PMut, Imutant and Mupro). The physiochemical properties of the resulted SNPs were then analyzed by Hope project website and visualized by chimera software. ResultThirteen novel mutations (Y172C, A222V, C260R, C260Y, D349G, I354K, R377C, G379C, G393R, G393E, G395E, G425E, R445W) are discovered in B3GALTL gene to cause deleterious effects leading to the development of Peters-plus syndrome. ConclusionThirteen novel mutations in B3GALTL gene are predicted to cause Peters-plus syndrome.

bioinformatics↗

bioRxiv2020

Immunoinformatic design of multi epitopes peptide-based universal cancer vaccine using matrix metalloproteinase-9 protein as a target

BackgroundCancer remains a major public health hazard despite the extensive research over the years on cancer diagnostic and treatment, this is mainly due to the complex pathophysiology and genetic makeup of cancer. A new approach toward cancer treatment is the use of cancer vaccine, yet the different molecular bases of cancers reduce the effectiveness of this approach. In this work we aim to use matrix metalloproteinase-9 protein (MMP9) which is essential molecule in the survival and metastasis of all type of cancer as a target for universal cancer vaccine design. Methodreference sequence of matrix metalloproteinase-9 protein was obtained from NCBI databases along with the related sequence, which is then checked for conservation using BioEdit, furthermore the B cell and T cell related peptide were analyzed using IEDB website. The best candidate peptide were then visualized using chimera software. ResultThree Peptides found to be good candidate for interactions with B cells (SLPE, RLYT, and PALPR), while ten peptides found as a good target for interactions with MHC1 (YRYGYTRVA, YGYTRVAEM, YLYRYGYTR, WRFDVKAQM, ALWSAVTPL, LLLQKQLSL, LIADKWPAL, KLFGFCPTR, MYPMYRFTE, FLIADKWPA) with world combined coverage of 94.77%. In addition, ten peptides were also found as a good candidates for interactions with MHC2 (KMLLFSGRRLWRFDV, GRGKMLLFSGRRLWR, RGKMLLFSGRRLWRF, GKMLLFSGRRLWRFD, TFTRVYSRDADIVIQ, AVIDDAFARAFALWS, FARAFALWSAVTPLT, MLLFSGRRLWRFDVK, GNQLYLFKDGKYWRF, NQLYLFKDGKYWRFS), with world combined coverage of 90.67%. CONCLUSION23 peptide-based vaccine was designed for use as a universal cancer vaccine which has a high world population coverage for MHC1(94.77%) and MHC2 (90.67%) related alleles.

immunology↗

bioRxiv2020

Design of multi epitope-based peptide vaccine against E protein of human 2019-nCoV: An immunoinformatics approach

BackgroundNew endemic disease has been spread across Wuhan City, China on December 2019. Within few weeks, the World Health Organization (WHO) announced a novel coronavirus designated as coronavirus disease 2019 (COVID-19). In late January 2020, WHO declared the outbreak of a "public-health emergency of international concern" due to the rapid and increasing spread of the disease worldwide. Currently, there is no vaccine or approved treatment for this emerging infection; thus the objective of this study is to design a multi epitope peptide vaccine against COVID-19 using immunoinformatics approach. MethodSeveral techniques facilitating the combination of immunoinformatics approach and comparative genomic approach were used in order to determine the potential peptides for designing the T cell epitopes-based peptide vaccine using the envelope protein of 2019-nCoV as a target. ResultsExtensive mutations, insertion and deletion were discovered with comparative sequencing in COVID-19 strain. Additionally, ten peptides binding to MHC class I and MHC class II were found to be promising candidates for vaccine design with adequate world population coverage of 88.5% and 99.99%, respectively. ConclusionT cell epitopes-based peptide vaccine was designed for COVID-19 using envelope protein as an immunogenic target. Nevertheless, the proposed vaccine is rapidly needed to be validated clinically in order to ensure its safety, immunogenic profile and to help on stopping this epidemic before it leads to devastating global outbreaks.

bioinformatics↗

bioRxiv2019

Identification of Six novel missense single nucleotide polymorphisms in MAOA gene predisposing to aggressive behavior. Bioinformatics study.

BackgroundAn astonishing observation is that aggressive behavior is actually a highly heritable. Recent experimental work and behavior research has linked individual variation in a functional polymorphism of the monoamine oxidase-A gene (MAOA) to the occurrence of anger-driven aggression. Aggressive antisocial and violent behavior has become a regularly debated topic in the scientific community; the impending question is what is the source of aggressive behavior, is it genetic or environmental or is it just an individual choice. This study aims to analyses the SNPs found in MAOA gene and it is possible association to aggressive behavior. MethodVarious bioinformatics software (SIFT, PolyPhen-2, PROVEAN, SNAP22, SNP&GO and PMut)is used to analyses the SNPs within the MAOA gene to study the structural and functional implication on the associated protein, which is further clarified using chimera software. Then gene-gene interaction is studied with geneMANIA software. Furthermore, conservation and annotation studies were done through the ConSurf server and Variant Effect Predictor (VEP) respectively. ResultSix missense SNPs were found to affect the structural and functional prospect of MAOA protein. ConclusionGenetic mutation within MAOA is likely to be associated with aggressive behavior; this will enrich future management and screening possibilities for this behavior.

bioinformatics↗

bioRxiv2019

Extensive In Silico Analysis of ATL1 Gene: Discovered Five Mutations that may Cause Hereditary Spastic Paraplegia Type 3A

BACKGROUNDHereditary spastic paraplegia type 3A (SPG3A) is a neurodegenerative disease inherited type of Hereditary spastic paraplegia (HSP). It is the second most frequent type of HSP; which Characterized by muscle stiffness with paraplegia and early-onset of symptoms. This is the first translational bioinformatics analysis in a coding region of ATL1 gene which aims to categorize nsSNPs to be used as genomic biomarkers; also it may play a key role in pharmacogenomics by evaluating drug response for this disabling disease.\n\nMETHODSThe raw data of ATL1 gene were retrieved from dbSNP database, and then run into numerous computational analysis tools. Additionally; we submitted the common six deleterious outcomes from the previous functional analysis tools to I-mutant 3.0, and MUPro respectively, to investigate their effect on structural level. The 3D structure of ATL1 was predicted by RaptorX and modeled using UCSF Chimera to compare the differences between the native and the mutant amino acids.\n\nRESULTSFive nsSNPs out of 249 were classified as the most deleterious (rs746927118, rs979765709, rs119476049, rs864622269, rs1242753115).\n\nCONCLUSIONSIn this study the impact of nsSNPs in the ATL1 gene was investigated by various bioinformatics tools, that revealed five nsSNPs (V67F, T120I, R217Q, R495W and G504E) are deleterious SNPs, which have a functional impact on ATL1 protein; and therefore, can be used as genomic biomarkers specifically before 4 years old; also it may play a key role in pharmacogenomics by evaluating drug response for this disabling disease.

bioinformatics↗

bioRxiv2019

Identification of novel key biomarkers in Simpson-Golabi-Behmel Syndrome: Evidence from bioinformatics analysis

BackgroundThe Simpson-Golabi-Behmel Syndrome (SGBS) or overgrowth Syndrome is a rare inherited X-linked condition characterized by pre- and postnatal overgrowth. The aim of the present study is to identify functional non-synonymous SNPs of GPC3 gene using various in silico approaches. These SNPs are supposed to have a direct effect on protein stability through conformation changes.\n\nMaterial and methodsThe SNPs were retrieved from the Single Nucleotide Polymorphism database (dbSNP) and further used to investigate a damaging effect using SIFT, PolyPhen, PROVEAN, SNAP2, SNPs&GO, PHD-SNP and P-mut, While we used I-mutant and MUPro to study the effect of SNPs on GPC3 protein structure. The 3D structure of human GPC3 protein is not available in the Protein Data Bank, so we used RaptorX to generate a 3D structural model for wild-type GPC3 to visualize the amino acids changes by UCSF Chimera. For biophysical validation we used project HOPE. Lastly we run conservational analysis by BioEdit and Consurf web server respectively.\n\nResultsour results revealed three novel missense mutations (rs1460413167, rs1295603457 and rs757475450) that are found to be the most deleterious which effect on the GPC3 structure and function.\n\nConclusionThis present study could provide a novel insight into the molecular basis of overgrowth Syndrome.

bioinformatics↗

bioRxiv2019

In Silico Genetics Revealing Novel Mutations in CEBPA Gene Associated with Acute Myeloid Leukemia

BackgroundMyelodysplastic syndrome/Acute myeloid leukemia (MDS/AML) is a highly heterogeneous malignant disease; affects children and adults of all ages. AML is one of the main causes of death in children with cancer. However, It is the most common acute leukemia in adults, with a frequency of over 20 000 cases per year in the United States of America alone.\n\nMethodsThe SNPs were retrieved from the dbSNP database. this SNPs were submitted into various functional analysis tools that done by SIFT, PolyPhen-2, PROVEAN, SNAP2, SNPs&GO, PhD-SNP and PANTHER, while structural analysis were done by I-mutant3 and MUPro. The most damaging SNPs were selected for further analysis by Mutation3D, Project hope, ConSurf and BioEdit softwares.\n\nResultsA total of five novel nsSNPs out of 248 missense mutations were predicted to be responsible for the structural and functional variations of CEBPA protein.\n\nConclusionIn this study the impact of functional SNPs in the CEBPA gene was investigated through different computational methods, which determined that (R339W, R288P, N292S N292T and D63N) are novel SNPs have a potential functional effect and can thus be used as diagnostic markers and may facilitate in genetic studies with a special consideration of the large heterogeneity of AML among the different populations.

bioinformatics↗

bioRxiv2019

Comprehensive bioinformatics analysis of L1CAM gene revealed Novel Pathological mutations associated with L1 syndrome

BackgroundMutations in the human L1CAM gene cause a group of neurodevelopmental disorders known as L1 syndrome (CRASH syndrome). The L1CAM gene provides instructions for producing the L1 protein, which is found all over the nervous system on the surface of neurons. L1 syndrome involves a variety of characteristics but the most common characteristic is muscle stiffness. Patients with L1 syndrome can also suffer from difficulty speaking, seizures, and underdeveloped or absent tissue connecting the left and right halves of the brain. MethodThe human L1CAM gene was studied from dbSNP/NCBI, 1499 SNPs were Homo sapiens; of which 450 were missense mutations. This selected for Comprehensive bioinformatics analysis by several in silico tools to investigate the effect of SNPs on L1CAM proteins structure and function. Results34 missense mutations (26 novel mutations) out of 450 nsSNPs that are found to be the most deleterious that effect on the L1CAM structural and functional level. ConclusionBetter understanding of L1 syndrome caused by mutations in L1CAM gene was achieved using Comprehensive bioinformatics analysis. These findings describe 35 novel L1 mutations which improve our understanding on genotype-phenotype correlation. And can be used as diagnostic markers for L1 syndrome and besides in cancer diagnosis specifically in breast cancer.

bioinformatics↗

bioRxiv2019

In silico analysis of IDH3A gene revealed Novel mutations associated with Retinitis Pigmentosa

BackgroundRetinitis Pigmentosa (RP) refers to a group of inherited disorders characterized by the death of photoreceptor cells leading to blindness. The aim of this study is to identify the pathogenic SNPs in the IDH3A gene and their effect on the structure and function of the protein. Methodwe used different bioinformatics tools to predict the effect of each SNP on the structure and function of the protein. Result20 deleterious SNPs out of 178 were found to have a damaging effect on the protein structure and function. Conclusionthis is the first in silico analysis of IDH3A gene and 20 novel mutations were found using different bioinformatics tools, and they could be used as diagnostic markers for Retinitis Pigmentosa.

bioinformatics↗

bioRxiv2019

In Silico Analysis and Modeling of Novel Pathogenic Single Nucleotide Polymorphisms (SNPs) in Human CD40LG Gene

AbstractO_ST_ABSBackgroundC_ST_ABSThe X-linked hyper-immunoglobulin M syndrome (XHIGM) is a rare, inherited immune deficiency disorder. It is more common in males. Characterized by elevated serum IgM levels and low to undetectable levels of serum IgG, IgA and IgE. Hyper-IgM syndrome is caused by mutations in the CD40LG gene. Located in human Xq26. CD40LG acts as an immune modulator in activated T cells. MethodWe used different bioinformatics tools to predict the effect of each SNP on the structure and function of the protein. Result8 novel SNPs out of 233 were found to have most deleterious effect on the protein structure and function. While modeling of nsSNPs was studied by Project HOPE software. ConclusionBetter understanding of Hyper-IgM syndrome caused by mutations in CD40LG gene was achieved using in silico analysis. This is the first in silico functional analysis of CD40LG gene and 8 novel mutations were found using different bioinformatics tools, and they could be used as diagnostic markers for hyper-IgM syndrome. These 8 novel SNPs may be important candidates for the cause of different types of human diseases by CD40LG gene.

bioinformatics↗