In silico Gene Characterization and biological annotation of Aspergillus niger CBS 513.88

Genome annotation is the process of estimation of biological features from genomic data. The target of a genome annotation is to identify the key features of the genome sequence particularly, the genes and gene products. The characteristics of a gene, its products, and gene prediction programs of Aspergillus niger are discussed. Although the number of genomes in genomic databases are increasing day by day, genome-wide analyses are affected by the quality of the genome annotations. This study illustrates the importance of integrative approaches for automatic annotations of genomes of Aspergillus niger by computational methods. However, the annotation process is more complicated in Eukaryotes; we used a comparative study for gene prediction using the FgenesH algorithm by various software providers. The final annotation of Aspergillus niger CBS 513.88. has been created as a GB file in Artemis, A sequence viewer and annotation tool was developed in the anger Institute

Genome analysis of biosurfactant producing bacterium, Bacillus tequilensis.

Bioremediation is crucial for recuperating polluted water and soil. By expanding the surface area of substrates, biosurfactants play a vital role in bioremediation. Biosurfactant-producing microbes release certain biosurfactant compounds, which are promoted for oil spill remediation. In the present investigation, a biosurfactant-producing bacterium Bacillus tequilensis was isolated from Chilika Lake, Odisha, India (latitude and longitude: 19.8450 N 85.4788 E). Whole-Genome Sequencing (WGS) of Bacillus tequilensis was carried out using Illumina NextSeq 500. The size of the whole genome of Bacillus tequilensis was 4.47 MB consisting of 4,478,749 base pairs forming a circular chromosome with 528 scaffolds, 4492 protein-encoding genes (ORFs), 81 tRNA genes, and 114 ribosomal RNA transcription units. The total raw reads were 4209415, and the processed reads were 4058238 with 4492 genes. The whole genome obtained from the present investigation was used for genome annotation, variant calling, variant annotation, and comparative genome analysis with other existing Bacillus species. In this study, a pathway was constructed which describes the biosurfactant metabolism of Bacillus tequilensis. The study identified that genes such as SrfAD, SrfAC, SrfAA and SrfAB are involved in biosurfactant synthesis. The sequence of the genes SrfAD, SrfAC, SrfAA, SrfAB was deposited in GenBank database with accession MUG02427.1, MUG02428.1, MUG02429.1, MUG03515.1 respectively. The whole genome sequence was submitted to GenBank with an accession RMVO00000000 and the raw fastq reads were submitted to SRA, NCBI repository with an accession: SRX5023292

Hypothesis Insights from the predicted epitope similarity between Mycobacterium tuberculosis virulent factors and its human homologs

Abstract: Mycobacterium tuberculosis is known to be associated with several autoimmune diseases such as systemic lupus erythematous, rheumatoid arthritis and multiple sclerosis. This is attributed to sequence similarity between virulent factors and human proteins. Therefore, it is of interest to identify such regions in the virulent factors to assess potential autoimmune related information. M. tb specific virulent factors were downloaded from the VFDB database and its human homologs were identified using the sequence comparison search tool BLASTP. Both virulent proteins and their corresponding human homologs were further scanned for epitopes (B cell and HLA class I and II allele specific) using prediction programs (BCPRED and NETMHC). Data shows the presence of matching 22 B-cell, 79 HLA class II and 16 HLA class I specific predicted epitopes in these virulent factors having human homologs. A known peptide (HAFYLQYKNVKVDFA) associated with autoimmune atopic dermatitis is shown in the superoxide dismutase homolog structures of the bacterium (PDB ID: 1IDS) and human (PDB ID: 2QKC). This data provides insight into the understanding of infection-associated auto-immunit

3D Structure Development of Chikungunya Virus and its Structural Characterization – an In silico approach

The 3 Dimensional structure of a protein is an expedient for structure based drug design and identifying the conformational epitopes that are foremost for designing the vaccines. Chikungunya (CHIKV) is a heat sensitive RNA virus which causes a viral disease which is transmitted in humans by human-mosquito-human transmission. Disease mostly found in the tropic and subtropical countries mainly in South India and in few other Asian countries. The primary transmission agents of Chikungunya Virus are yellow fever mosquito (_Aedes aegypti_) and forest day mosquito (_Aedes albopictus_). The forest day mosquito bites during day time and hence day time mosquito bite is the main reason for transmission. The main distinctive of the disease is a fever along with an arthritic type of pain in the joints. 3D Structure of Chikungunya virus is not encountered in the PDB Databank. A Comparative modeling method was used for the prediction of the 3D structure of Chikungunya virus. Modeled structure prvided substantial parameters under Ramachandran plot and stereochemical aspects of main chain and side chains through PROCHECK analysis. Finally the energy minimization protocols yielded a score of -12063.947 KJ/Mol and RMSD Value of 0.29oA. Structure Validation procedures proffer the use of present modeled structures for structure based drug design and other confirmative applications

Molecular dynamic simulations reveal suboptimal binding of salbutamol in T164I variant of β2 adrenergic receptor.

The natural variant C491T (rs1800088) in ADRB2 gene substitutes Threonine to Isoleucine at 164th position in β2AR and results in receptor sequestration and altered binding of agonists. Present investigation pursues to identify the effect of T164I variation on function and structure of β2AR through systematic computational approaches. The study, in addition, addresses altered binding of salbutamol in T164I variant through molecular dynamic simulations. Methods involving changes in free energy, solvent accessibility surface area, root mean square deviations and analysis of binding cavity revealed structural perturbations in receptor to incur upon T164I substitution. For comprehensive understanding of receptor upon substitution, OPLS force field aided molecular dynamic simulations were performed for 10 ns. Simulations revealed massive structural departure for T164I β2AR variant from the native state along with considerably higher root mean square fluctuations of residues near the cavity. Affinity prediction by molecular docking showed two folds reduced affinity of salbutamol in T164I variant. To validate the credibility docking results, simulations for ligand-receptor complex were performed which demonstrated unstable salbutamol-T164I β2AR complex formation. Further, analysis of interactions in course of simulations revealed reduced ligand-receptor interactions of salbutamol in T164I variant. Taken together, studies herein provide structural rationales for suboptimal binding of salbutamol in T164I variant through integrated molecular modeling approaches