Biology subjects

Mustafa, M. I.

Publications and source records attributed to Mustafa, M. I..

At least 19 recordsLinked to original sources

bioRxiv2020

Epitope-Based Peptide Vaccine against Bombali Ebolavirus Viral Protein 40: An Immunoinformatics Combined with Molecular Docking Studies

BackgroundBombali Ebolavirus is RNA viruses belong to the Filoviridae family. They are causing lethal hemorrhagic fever with high mortality rate. Despite having available molecular knowledge of this virus, no approved vaccine or antiviral drugs have been developed yet for the eradication of Bombali Ebolavirus infections in humans. Objectivethe present study described a multi epitope-based peptide vaccine against Bombali Ebolavirus matrix protein VP40, using several immunoinformatics tools. Materials and MethodsThe six strains of Ebolavirus were retrieved from NCBI and Uniprot databases and submitted to VaxiJen to identify the most antigenic protein among all. Then PSIPRED, SOPMA, QMEAN, and PROCHECK tools were used to check the protein quality. T-cell prediction, population coverage, and molecular docking analysis were achieved to select peptides containing multiple Bombali VP40 epitopes showing interaction with multiple HLA molecules for expected immune response across the world. ResultBombali Ebola (YP_009513276.1) was found to be the most antigenic protein among all. Which it has been used in all required analysis. For T cell three epitopes showed high affinity to MHC class I (YSFDSTTAA, VQLPQYFTF, and MVNVISGPK) and high population coverage against Africa and the world. Furthermore in MHC class II, six promising epitopes that associated with most common MHC class II alleles. ConclusionThe above result conclude that, these peptides capable of provoking T-cell response and being interacted with a wide range of HLA molecules have a strong potential to be a vaccine against Bombali Ebolavirus.

bioinformatics↗

bioRxiv2020

Identification of High risk nsSNPs in Human TP53 Gene Associated with Li Fraumeni Syndrome: An In Silico Analysis Approach

BackgroundLi-Fraumeni syndrome (LFS) is a cancer-prone conditions caused by a germline mutation of the TP53 gene on chromosome 17p13.1. It has an autosomal dominant pattern of inheritance with high penetrance. PurposeThe aim of this study is to identify the high-risk pathogenic nsSNPs in PT53 gene that could be involved in the pathogenesis of Li-Fraumeni syndrome. MethodsThe nsSNPs in the human PT53 gene retrieved from NCBI, were analyzed for their functional and structural consequences using various in silico tools to predict the pathogenicity of each SNP. SIFT, Polyphen, PROVEAN, SNAP2, SNPs&Go, PHD-SNP, and P-Mut were chosen to study the functional inference while I-Mutant 3.0, and MUPro tools were used to test the impact of amino acid substitutions on protein stability by calculating {Delta}{Delta}G value. The effects of the mutations on 3D structure of the PT53 protein were predicted using RaptorX and visualized by UCSF Chimera. ResultsA total of 845 PT53 nsSNPs were analyzed. Out of 7 nsSNPs of PT53 three of them (T118L, C242S, and I251N) were found high-risk pathogenic. ConclusionIn this study, out of 7 predicted high-risk pathogenic nsSNPs, three high-risk pathogenic nsSNPs of PT53 gene were identified, which could be used as diagnostic marker for this gene. The combination of sequence-based and structure-based approaches is highly effective for pointing pathogenic regions.

bioinformatics↗

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

Phytochemical Screening and Antimicrobial Activity of Ziziphus spina-christi Stem Barks

This study was carried out in Khartoum State, during December 2017 The plant of Ziziphus spina-christi belong to family Rhamnaceae and locally known as Cedar, it was chosen for this study because of its using traditionally in treatment of many diseases. Microwave-assisted extraction (MAE) approach had been used to the dried sample at 170{degrees}C to reduce both time and extraction solvent volume, and to decrease the damage of bioactive compounds without extending the period of extraction. 20 g of sample was soaked with Petroleum ether, Ethyl-acetate, ethanol, methanol and distilled water for 72 hour. The extracts were concentrated using rotary evaporator at 40{degrees}C and were stored at 4{degrees}C. The phytochemical screening were carried out on different extracts of Ziziphus spina-christi stem bark and they showed to contain high amount of Tannins (4+ in all extracts), moderate amount of flavonoids and Triterpenes, trace amount of coumarins and Alkaloids and high amount of Saponins, Anthraquinones and Cardiac glycosides. The antimicrobial activity of extracts were evaluated against four standard bacteria species (gram positive; Bacillus subtilis, Staphylococcus aureus) and (gram negative; Escherichia coli, Pseudomonas aeruginosa; in addition of one standard fungi (Candida albicans). The results of antimicrobial tests indicated that the methanolic extract inhibited the growth of all microorganisms and most extracts showed several points of antimicrobial activity. These findings act as platform to assist in cure of bacterial and fungal infections.

biochemistry↗

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

Phytochemical screening and antimicrobial activities studies of Acacia nilotica fruit cover

This study was carried out in Khartoum state, during November, 2019. Acacia nilotica was chosen for this study because of its using traditionally in treatment of many diseases. The Phytochemical constitutions of A. nilotica were investigated with aim to identify the antimicrobial effects of this plant. The dried fruit cover of Acacia nilotica was extracted successively with petroleum-ether, chloroform, methanol and distilled water. The phytochemical screening carried out on different extracts of Acacia nilotica fruit cover showed high amount of Glycosides, Flavonoids and Terpenoids (in all extracts) and moderate amount of Tannin in methanol and distilled water extracts, Alkaloids (acid and base) in methanol extract and Saponin in methanol and petroleum-ether extracts. The antimicrobial activity of extracts were evaluated against four standard bacteria species (gram positive bacteria; Staphylococcus aureus, Bacillus subtilis) and (gram negative bacteria; Pseudomonas aeruginosa, Escherichia coli). The plates were inoculated for sensitivity testing, minimum inhibitory concentration (MIC) was measured. The results of antimicrobial investigation show that the distilled water and methanolic extracts inhibited the growth of all microorganisms (Specified by the zone of inhibition). The results provide promising baseline information for potential use of these crude extracts in drug development programs in the pharmaceutical industries.

biochemistry↗

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

Comprehensive Analysis of HEXB Protein Reveal Forty Two Novel nsSNPs That May Lead to Sandhoff disease (SD) Using Bioinformatics

BackgroundSingle Nucleotide Polymorphisms (SNPs) in the HEXB gene are associated with a neurodegenerative disorder called Sandhoff disease (SD) (GM2 gangliosidosis-O variant). This study aimed to predict the possible pathogenic SNPs of this gene and their impact on the protein using different bioinformatics tools. MethodsSNPs retrieved from the NCBI database were analyzed using several bioinformatics tools. The different algorithms collectively predicted the effect of single nucleotide substitution on both structure and function of beta subunit beta subunit of both hexosaminidase A and hexosaminidase B proteins. ResultsForty nine mutations were found to be extremely damaging to the structure and function of the HEXB gene protein. ConclusionAccording to this study, forty two novel nsSNP in HEXB are predicted to have possible role in Sandhoff disease using different bioinformatics tools, beside two SNPs found to have effect on miRNAs binding site affecting expression of HEXB gene. Our findings may assist in genetic study and diagnosis of Sandhoff disease.

bioinformatics↗

bioRxiv2019

Insilico Analysis Reveal Three novel nsSNPs May effect on GM2A protein Leading to AB variant of GM2 gangliosidosis

BackgroundAB variant of GM2 gangliosidosis caused as a result of mutations in GM2 activator gene (GM2A) which is regarded as neurodegenerative disorder. This study aimed to predict the possible damaging SNPs of this gene and their impact on the protein using different bioinformatics tools. MethodsSNPs retrieved from the NCBI database were analyzed using several bioinformatics tools. The different tools collectively predicted the effect of single nucleotide substitution on both structure and function of GM2 activator. ResultsThree novel mutations were found to be highly damaging to the structure and function of the GM2A gene. ConclusionFour SNPs were found to be highly damaging SNPs that affect function, structure and stability of GM2A protein, which they are: C99Y, C112F, C138S and C138R, three of them are novel SNPs (C99Y, C112F and C138S). Also 46 SNPs were predicted to affect miRNAs binding sites on 3UTR leading to abnormal expression of the resulting protein. These SNPs should be considered as important candidates in causing AB variant of GM2 gangliosidosis and may help in diagnosis and genetic screening of the disease.

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

The Association between SLC25A15 Gene Polymorphisms and Hyperornithinemia-hyperammonemia-homocitrullinuria Syndrome: Using In Silico Analysis

BackgroundHyperornithinemia-hyperammonemia-homocitrullinuria (HHH) syndrome is an autosomal recessive inborn error of the urea cycle. It is caused by mutations in the SLC25A15 gene that codes the mitochondrial ornithine transporter. The aim of this study is to detect and identify the pathogenic SNPs in SLC25A15 gene through a combination set of bioinformatics tools and their effect on the structure and function of the protein.\n\nMethodsThe deleterious SNPs in SLC25A15 are detected by various bioinformatics tools, with addition to identifying their effects on the structure and function of this gene.\n\nResults20 deleterious SNPs out 287of were found to have their own damaging effects on the structure and function of the SLC25A15 gene.\n\nConclusionThis study is the first in silico analysis of SLC25A15 using a selection of bioinformatics tools to detect functional and structural effects of deleterious SNPs. Finding the pathogenic SNPs is a promising start to innovate new, useful SNP diagnostic markers for medical testing and for safer novel therapies specifically targeting mutant SLC25A15.

bioinformatics↗

bioRxiv2019

Thirty five novel nsSNPs may effect on ADAMTS13 protein leading to Thrombotic thrombocytopenic purpura (TTP) using bioinformatics approach

BackgroundGenetic polymorphisms in the ADAMTS13 gene are associated with thrombotic thrombocytopenic purpura or TTP, a life-threatening microangiopathic disorder. This study aims to predict the possible pathogenic SNPs of this gene and their impact on the protein structure and function using insilico methods.\n\nMethodsSNPs retrieved from the NCBI database were analyzed using several bioinformatics tools. The different algorithms applied collectively to predictthe effect of single nucleotide substitution on both structure and function of the ADAMTS13 protein.\n\nResultsFifty one mutations were found to be highly damaging to the structure and function of the protein. Of those, thirty five were novel nsSNPs not previously reported in the literature.\n\nConclusionAccording to our analysis we found thirty five nsSNPs effects on ADAMTS13 protein leading to thrombotic thrombocytopenic purpura using computational approach. Bioinformatics tools are vital in prediction analysis, making use of increasingly voluminous biomedical data thereby providing markers for screening or for genetic mapping studies.

bioinformatics↗

bioRxiv2019

Epitope-based peptide vaccine against glycoprotein G of Nipah henipavirus using immunoinformatics approaches

BackgroundNipah virus (NiV) is a member of the genus Henipavirus of the family Paramyxoviridae, characterized by high pathogenicity and endemic in South Asia, first emerged in Malaysia in 1998. The case-fatality varies from 40% to 70% depending on the severity of the disease and on the availability of adequate healthcare facilities. At present no antiviral drugs are available for NiV disease and the treatment is just supportive. Clinical presentation ranges from asymptomatic infection to fatal encephalitis. Bats are the main reservoir for this virus, which can cause disease in humans and animals. The last investigated NiV outbreak has occurred in May 2018 in Kerala.\n\nObjectiveThis study aims to predict effective epitope-based vaccine against glycoprotein G of Nipah henipavirus using immunoinformatics approaches.\n\nMethods and MaterialsGlycoprotein G of Nipah henipavirus sequence was retrieved from NCBI. Different prediction tools were used to analyze the nominees epitopes in BepiPred-2.0: Sequential B-Cell Epitope Predictor for B-cell, T-cell MHC class II & I. Then the proposed peptides were docked using Autodock 4.0 software program.\n\nResults and ConclusionsPeptide TVYHCSAVY shows a very strong binding affinity to MHC I alleles while FLIDRINWI shows a very strong binding affinity to MHC II and MHC I alleles. This indicates a strong potential to formulate a new vaccine, especially with the peptide FLIDRINWI that is likely to be the first proposed epitope-based vaccine against glycoprotein G of Nipah henipavirus. This study recommends an in-vivo assessment for the most promising peptides especially FLIDRINWI.

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↗