International Journal of Computational Bioinformatics and In Silico Modeling
ABSTRACT: Disease 46,XY sex reversal 1, it is a condition characterized by male-to-female sex reversal in the presence of a normal 46,XY karyotype. Patients manifest rapid and early degeneration of their gonads, which are present in the adult as 'streak gonads', consisting mainly of fibrous tissue and variable amounts of ovarian stroma. As a result these patients do not develop secondary sexual characteristics at puberty. The external genitalia in these subjects are completely female, and Muellerian structures are normal. In this study we aimed to assess SRY gene nsSNPs to sort intolerance mutations from tolerance, the intolerance mutations if detected may be used as a good marker for disease 46, sex determination. Material and methods: SRY gene SNPs were retrieved from db SNP server, and processed for analysis using different types of bioinformatics tools and programs. Results: In the present study 11SNPs out of 26 rsSNPs collected from dbSNPs were included. SIFT, PROVEAN, PolyPhen and SNP&GO programs were used to assess functional effects of mutation on the protein. Results of Mutation3D server showed 5 mutations (V60L, I90M, K106I, I90M and I68T) these mutations were located in the protein domain) . Hydrogen bonding and clashes of the mutations I68T, G95E, Y127F, A113T and I90M showed different numbers of hydrogen bonding between mutant residue and wide type, the differences of H-bonding between the wild and mutant residues may indicated a significant effect on protein stability, these results were obtained by using Chimera program 1.8.
KeyWords: SRY gene, nsSNP, mutations.
How to cite: Alsadig Gassoum et al. Analysis of SRY gene nsSNPs using different bioinformatics tools and in silico programs. Int J Comput Bioinfo In Silico Model. 5(5) 2016: 849-857
ABSTRACT: Protein Kinase B (PKB) and Serum and Glucocorticoid-regulated Kinase 1 (SGK1) regulate important cellular functions and their overexpression can lead to cancer development. Since PKB and SGK1 are highly homologous and have similar activators and targets, SGK1 can provide alternate, PKB-independent, paths for cancer development. As a result, cancers with high SGK1 activity may acquire resistance to PKB-specific inhibitors, thus progressing despite treatment. Most kinases have very similar catalytic sites, making them challenging to target specifically. However, the allosteric sites of various kinases differ greatly, allowing for highly specific binding. In this work, we computationally designed novel druglike small molecules that could simultaneously inhibit PKB and SGK1 at their allosteric sites. Two known PKB-specific inhibitors, IQO and MK-2206, were used as initial templates to construct new molecules. We successfully designed three molecules that had similar or better druglike properties than the known PKB-specific inhibitors. The designed molecules showed no toxic or reproductive risks. In addition, their druglike properties indicated good bioavailability and promising overall drug potential. Two of the designed molecules bonded in the allosteric sites of both PKB and SGK1 with binding energies comparable to those of PKB complexes with IQO and MK-2206. The third designed molecule had a very high affinity for both PKB and SGK1. It bonded to the allosteric site of PKB, but only in the catalytic site of SGK1. The allosteric bindings of the designed molecules to either PKB or SGK1 modified the configuration of the kinase’s catalytic site in both cases. This prevented the binding of the ATP molecule in the catalytic site, a result that could potentially hinder cancer progression. Our results, coupled with previous experimental studies of the known PKB inhibitors, strongly suggest that the molecules designed here may be potent allosteric inhibitors of both PKB and SGK and may lead to the development of new, more effective cancer drugs.
KeyWords: Druglike Allosteric Inhibitors of PKB and SGK1 Kinases.
How to cite: A. Parmar et al. Computational Design of Druglike Allosteric Inhibitors of Protein Kinase B (PKB) and Serum and Glucocorticoid-regulated Kinase 1 (SGK1). Int J Comput Bioinfo In Silico Model. 5(5) 2016: 858-870
ABSTRACT: Cytomegalovirus belongs to Herpesviruses group. In humans it is commonly known as HCMV or Human Herpesvirus 5 (HHV-5). HCMV infection can also be life threatening for patients who are immunocompromised. The HCMV UL97-encoded protein kinase represents an important determinant of viral replication. This study have been taken up to model the UL97 Kinase and to predict the interaction between UL97 kinase and its potential inhibitors namely pyrrolopyrimidines, dihydroisoquinolines, 4-hydroxyquinoline carboxamides, and indolocarbazoles. By analyzing the energy minimization values, pyrrolopyrimidines were found to effectively inhibit UL97 kinase.
KeyWords: UL97 kinase, Human Cytomegalovirus.
How to cite: M. Amudha. In Silico Screening of Potent Inhibitor for HCMV UL97 Kinase. Int J Comput Bioinfo In Silico Model. 5(5) 2016: 871-875
ABSTRACT: RNA-Seq, a powerful transcriptome analysis approach, has become a popular alternative to traditional array-based methods for differential expression analysis in recent years. Numerous tools have been developed to incorporate the complexities in RNA-Seq analysis using various normalization schemes and statistical algorithms. This study aimed to compare 12 widely used RNA-Seq differential expression calling tools to assess their performance in controlling false positives at various sequencing depths and gene lengths using the Sequencing Quality Control (SEQC) Universal Human Reference dataset. Results showed that DESeq2, edgeR and limma-voom performed well in controlling false positives among the existing tools compared.
KeyWords: RNA-Seq, differential expression, false positive, tool comparison.
How to cite: Vedbar S. Khadka et al. Comparison of False Positive in Tools for Differential Gene Expression Calling in RNA-Seq Analysis. Int J Comput Bioinfo In Silico Model. 5(5) 2016: 876-885