Biology subjects

Jeyakanthan, J.

Publications and source records attributed to Jeyakanthan, J..

3 recordsLinked to original sources

bioRxiv2023

An integrated bioinformatics approach to identify candidate biomarkers and the evaluation of drugs for pheochromocytoma

ObjectivesIdentification of the most potential druggable targets and drugs for treating pheochromocytoma by understanding the molecular mechanisms in the progression of pheochromocytoma and discovering additional biomarkers for early diagnosis. MethodsThe differential gene expression in microarray data was analyzed using CRAN packages such as Geoquery, Affy, Limma, Tidyverse, GOchord, etc., and functional and pathway enrichment was performed through the David database, Further PPI network is constructed by retrieving the Protein partners were retrieved from the STRING database. The top 3 ranked gene products from cytohubba were docked with the ligand molecules, which are all in phase III trials. The complex with the highest binding affinity was simulated using molecular dynamics simulations for 100ns, PCA and FEL analysis were performed to determine the stability of the complex at each time interval additionally miRNA and TRFs were predicted for the prominent genes. ResultsAs a result of functional enrichment, most of the 97 differentially expressed genes (DEGs) are involved in cancer-causing pathways. Pheochromocytomas were associated with CDC42, VEGFA, PIK3R1, ITGAV, and LAMB-1, among prominent genes among the ten hub genes. Simulated results verified the effectiveness of targeting VEGFA with Lenvatinib. ConclusionsWe found that differentially expressed genes in the interactome and hub genes with high correlations could serve as biomarkers, along with their miRNAs and TRFs. By targeting VEGFA as a drug target, Lenvatinib displays a high affinity for VEGFA, as it interacts with other genes through homodimerization, activation, phosphorylation, and dephosphorylation. It also appears to interact with the VEGFA protein via hydrogen bonds. In conclusion, this study suggests that Lenvatinib might be a promising anticancer agent that could treat pheochromocytoma, and VEGF-A, CDC42, PIK3R1, as well as several predicted miRNAs, such as miR-224 and miR-221, might be biomarkers for the early diagnosis.

bioinformatics↗

bioRxiv2021

Characterization of the NiRAN domain from RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV-2

Apart from the canonical fingers, palm and thumb domains, the RNA dependent RNA polymerases (RdRp) from the viral order Nidovirales possess two additional domains. Of these, the function of the Nidovirus RdRp associated nucleotidyl transferase domain (NiRAN) remains unanswered. The elucidation of the 3D structure of RdRp from the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), provided the first ever insights into the domain organisation and possible functional characteristics of the NiRAN domain. Using in silico tools, we predict that the NiRAN domain assumes a kinase or phosphotransferase like fold and binds nucleoside triphosphates at its proposed active site. Additionally, using molecular docking we have predicted the binding of three widely used kinase inhibitors and five well characterized anti-microbial compounds at the NiRAN domain active site along with their drug-likeliness as well as DFT properties. For the first time ever, using basic biochemical tools, this study shows the presence of a kinase like activity exhibited by the SARS-CoV-2 RdRp. Interestingly, the proposed kinase inhibitors and a few of the predicted nucleotidyl transferase inhibitors significantly inhibited the aforementioned enzymatic activity. In line with the current global COVID-19 pandemic urgency and the emergence of newer strains with significantly higher infectivity, this study provides a new anti-SARS-CoV-2 drug target and potential lead compounds for drug repurposing against SARS-CoV-2.

bioinformatics↗

bioRxiv2019

Structural and functional characterization of oligomeric states of proteins in RecFOR pathway

RecFOR pathway is the principal repair pathway for double strand break and single strand gap repair in Thermus thermophilus. RecF and RecR exist as monomer and dimer in solution, interestingly; they undergo condition-dependent dimerization and tetramerization, respectively during the DNA break repair. However, their importance in protein-protein and protein-DNA interactions remains elusive. In this study, the three-dimensional crystal structures of the wild type RecF and RecR proteins are determined. Thereafter, the structural information is used to mutate the interface residues to cysteine to stabilize the dimeric and tetrameric states of the RecF and RecR proteins, respectively. A comparative study for their interactions with other cognate proteins and ssDNA in native and SSB (single strand binding protein) bound states was performed. RecF or RecFR complex displays a negligible affinity towards ssDNA. Conversely, the RecF mutants and its complexes with wild type RecR showed affinity towards ssDNA, suggesting, distinct modes of interaction of RecF and RecFR complex for ssDNA binding. In the presence of RecO, the stabilized tetrameric RecR showed a lower binding affinity for ssDNA as compared to the SSB bound ssDNA, indicating the importance of tetrameric RecR in stabilizing the RecOR complex on the SSB coated ssDNA. This provides an insight into the reduction of the binding affinity of SSB proteins with the ssDNA, which in turn enhances the recruitment of RecA for strand exchange.

biophysics↗