COMPUTATIONAL TOOLS TO DETECT SINGLE NUCLEOTIDE POLYMORPHISM (SNP) IN NUCLEOTIDE SEQUENCES: A REVIEW

ABSTRACT Single nucleotide polymorphisms (SNPs) are basically single base pair alterations present in the genomic DNA. SNPs is usually treated as one of the most common genetic markers in case of plants, animals as well as the human genome to study the complex genetic traits and evolutionary status of the genome. SNPs are widely used as popular markers due to their continuous presence in the genome, highly reproducible, relatively easy to score. In addition to this, SNPs in coding sequences are used to directly examine the genetics of expressing genes and to study various polymorphic functional traits. Specifically the non-synonymous SNPs are more attractive because they alter the amino acid that ultimately affecting the protein functions. The direct application of SNP exists with pharmacogenomics study and crop improvement. Various strategies have been used for SNP discovery that comes from both observational and computational techniques. SNPs can be detected by laboratory based experimental methods, which are time consuming and expensive also the development costs are high. The implementations of Bioinformatics approach reduce the development cost of SNPs as it uses publicly available sequences from databases like expressed sequence tags (ESTS) that cause the development of SNP markers rapid and less expensive

COVID-19: An Updated Insight of the Pandemic

Novel coronavirus (SARS-CoV-2) out-broke in the city of Wuhan in China and widely spread across the globe in a pandemic manner, causing societal and economic disruptions. Though the origin of the novel virus is still a debating topic, it is certain that SARS-CoV-2 acquired human to human transmission capacity. Regardless of aggressive containment and quarantine approaches, the number of confirmed cases continues to rise and being reported due to its highly infectious nature. As of the time, there is a little scope for the antiviral drugs or vaccines for the treatment of coronavirus infection; due to the vigorous mutation rate in the viral genome. However, existing anti-parasite drugs like ivermectin and chloroquine could effectively inhibit the virus has been reported. Few of the vaccines have come up with certain degree of efficacy and many are under the clinical trial phase. The research on novel coronavirus is still in the preliminary stage. In this chapter, we systematically summarize the origin, transmission route, molecular characterization, pathogenic mechanism, contagious nature, clinical symptoms, diagnosis, treatment, mutation and infection as well as prevention strategy of coronavirus disease based on the recently available literature. In addition to this, this chapter presents updated insights of the current state of knowledge pertaining to novel coronavirus and can be referred for potential future studies

In silico Prediction of Anti–SARS-CoV-2 Effect of Dermaseptin Peptides from Amphibian Origin: Prediction of anti–SARS-CoV-2 effect of the dermaseptin peptides

The novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has now been declared as a global pandemic by the World Health Organization (WHO). Several drug molecules have been proposed that can be used against the virus. As an alternative to effective drug molecules, the antiviral peptides have the potential for effective application to control the infectious disease. In this work, the anti- SARS-CoV-2 effect of dermaseptin peptide molecules produced by the skin of the frog was evaluated by using the computational method. Three numbers of antiviral dermaseptin peptides were obtained by searching the antimicrobial peptide database (APD). First, the structure prediction of peptides was done by Pep Fold 2.0 server followed by structure validation by PROCHECK program. Then, the protein-peptide docking simulations were performed using the COVID-19 docking server. The peptides' binding affinity with the SARS-CoV-2 spike protein macromolecule was evaluated along with eight negative control peptides and human angiotensin converting enzymes 2 (ACE2). The protein-peptide docking and interaction analysis resulted in finding that dermaseptin-S9 peptide molecule was the most efficient molecule among the selected peptides with a binding energy of -331.54 KJ/mole. Hence, as a follow-up study, the dermaseptin-S9 peptide molecule can be further designed to enhance its specificity and binding affinity for its better use against the SARSCoV-2 disease. HIGHLIGHTS Three numbers of antiviral dermaseptin peptides from APD database were in silico evaluated against SARS-CoV-2 spike protein. The antiviral dermaseptin -S9 peptide showed the highest binding affinity towards the SARS-CoV-2 spike protein macromolecule. The hydrophobic property of the distributed amino acids of the derrmaseptin-9 molecule might be related to the binding affinity

In-silico gene co-expression network analysis in Paracoccidioides brasiliensis with reference to haloacid dehalogenase superfamily hydrolase gene

Context: Paracoccidioides brasiliensis, a dimorphic fungus is the causative agent of paracoccidioidomycosis, a disease globally affecting millions of people. The haloacid dehalogenase (HAD) superfamily hydrolases enzyme in the fungi, in particular, is known to be responsible in the pathogenesis by adhering to the tissue. Hence, identification of novel drug targets is essential. Aims: In-silico based identification of co-expressed genes along with HAD superfamily hydrolase in P. brasiliensis during the morphogenesis from mycelium to yeast to identify possible genes as drug targets. Materials and Methods: In total, four datasets were retrieved from the NCBI-gene expression omnibus (GEO) database, each containing 4340 genes, followed by gene filtration expression of the data set. Further co-expression (CE) study was performed individually and then a combination these genes were visualized in the Cytoscape 2. 8.3. Statistical Analysis Used: Mean and standard deviation value of the HAD superfamily hydrolase gene was obtained from the expression data and this value was subsequently used for the CE calculation purpose by selecting specific correlation power and filtering threshold. Results: The 23 genes that were thus obtained are common with respect to the HAD superfamily hydrolase gene. A significant network was selected from the Cytoscape network visualization that contains total 7 genes out of which 5 genes, which do not have significant protein hits, obtained from gene annotation of the expressed sequence tags by BLAST X. For all the protein PSI-BLAST was performed against human genome to find the homology. Conclusions: The gene co-expression network was obtained with respect to HAD superfamily dehalogenase gene in P. Brasiliensis

Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study

Context: Boswellic acid consists of a series of pentacyclic triterpene molecules that are produced by the plant Boswellia serrata. The potential applications of Bowsellic acid for treatment of cancer have been focused here. Aims: To predict the property of the bowsellic acid derivatives as anticancer compounds by various computational approaches. Materials and Methods: In this work, all total 65 derivatives of bowsellic acids from the PubChem database were considered for the study. After energy minimization of the ligands various types of molecular descriptors were computed and corresponding two-dimensional quantitative structure activity relationship (QSAR) models were obtained by taking Andrews coefficient as the dependent variable. Statistical Analysis Used: Different types of comparative analysis were used for QSAR study are multiple linear regression, partial least squares, support vector machines and artificial neural network. Results: From the study geometrical descriptors shows the highest correlation coefficient, which indicates the binding factor of the compound. To evaluate the anticancer property molecular docking study of six selected ligands based on Andrews affinity were performed with nuclear factor-kappa protein kinase (Protein Data Bank ID 4G3D), which is an established therapeutic target for cancers. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound. Conclusions: Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound

Antidiabetic, antioxidant and in silico studies of bacterial endosymbiont inhabiting Nephelium lappaceum L.

Endophytes, notably obtaining attention, have been abided by potential origins of bioactive metabolites. In the acquaint study, endophyte was isolated from the leaves of Nephelium lappaceum L. The chosen endosymbiont was identified by 16s rRNA partial genome sequencing and investigated for their antioxidant and antidiabetic activities. A preliminary phytochemical test was comported for the affirmation of phytoconstituents in endophytic crude extract (NLM). Antioxidant activities were conducted by using 2-diphenyl-1-picrylhydrazyl (DPPH) method and 2,2′-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid (ABTS) method to screen the radical scavenging potential. The evaluation of antidiabetic activities was done by using α-amylase and α-glucosidase inhibition assay. Qualitative phytochemical test on NLM affirmed the presence of phenols, carbohydrates, alkaloids, flavonoids, steroids, mucilage and glycosides. In silico parameters were also specified for antidiabetic activities. The antioxidant assay of NLM expressed proficient antioxidant activity of IC50±SEM 1.35±0.03 µg/mL and IC50±SEM 1.47±0.03 µg/mL, for ABTS and DPPH respectively. Antidiabetic assay results evidenced dose dependent percentage inhibition of the enzyme. The results testified estimable inhibition of α-amylase (IC50±SEM 2.549±0.08 µg/mL) and α-glucosidase inhibition (IC50±SEM 2.29±0.03µg/mL) compared to the standard drug (Acarbose). In silico study divulged that the ellagic acid component present in the plant was responsible for antidiabetic activity. Thus, the study shows that NLM has a wellspring of natural source of antioxidants and antidiabetic agents and furtherance of studies on its mechanism is recommended to know detailed facts