Biology subjects

Makhawi, A. M.

Publications and source records attributed to Makhawi, A. M..

6 recordsLinked to original sources

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

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↗