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MULEY, V. Y.

Publications and source records attributed to MULEY, V. Y..

2 recordsLinked to original sources
bioRxiv2021

Human transcriptional gene regulatory network compiled from 14 data resources

Transcriptional regulatory network (TRN) orchestrates spatio-temporal expression of genes to generate cellular responses for survival. The transcription factors (TF) regulating expression of their target genes (TG) are the fundamental units of TRN. Several databases have been developed to catalogue human TRN based on low- and high-throughput experimental and computational studies considering their importance in understanding cellular physiology. However, literature lacks comparative assessment on the strength and weakness of each database. In this study, we compared over 2.2 million regulatory pairs between 1,379 TF and 22,518 TG assembled from 14 data resources. Our study reveals that the TF and TG were common across data resources but not their regulatory pairs. We observed that the TF and TG of the regulatory pairs showed weak expression correlation, significant gene ontology overlap, co-citations in PubMed and low numbers of TF-TG pairs representing transcriptional repression relationships. Furthermore, each TF-TG regulatory pair assigned a combined confidence score reflecting its reliability based on its presence in multiple databases and co-expression. The TRN containing 2,246,598 TF-TG pairs, of which, 44,284 with the information on TFs activating or repressing effects on their TG is available upon request. This study brings the information about transcriptional regulation scattered over the literature and databases at one place in the form of one of the most comprehensive and complete human TRNs assembled to date, which will be a valuable resource for benchmarking TRN prediction tools, and to the scientific community working in functional genomics, gene expression and gene regulation analysis.

bioinformatics↗
bioRxiv2021

SARS-CoV-2 Entry Protein TMPRSS2 and Its Homologue, TMPRSS4 Adopts Structural Fold Similar to Blood Coagulation and Complement Pathway Related Proteins

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) utilizes TMPRSS2 receptor to enter target human cells and subsequently causes coronavirus disease 19 (COVID-19). TMPRSS2 belongs to the type II serine proteases of subfamily TMPRSS, which is characterized by the presence of the serine-protease domain. TMPRSS4 is another TMPRSS member, which has a domain architecture similar to TMPRSS2. TMPRSS2 and TMPRSS4 have been shown to be involved in SARS-CoV-2 infection. However, their normal physiological roles have not been explored in detail. In this study, we analyzed the amino acid sequences and predicted 3D structures of TMPRSS2 and TMPRSS4 to understand their functional aspects at the protein domain level. Our results suggest that these proteins are likely to have common functions based on their conserved domain organization. Furthermore, we show that the predicted 3D structure of their serine protease domain has significant similarity to that of plasminogen which dissolves blood clot, and of other blood coagulation related proteins. Additionally, molecular docking analyses of inhibitors of four blood coagulation and anticoagulation factors show the same high specificity to TMPRSS2 and TMPRSS4 3D structures. Hence, our observations are consistent with the blood coagulopathy observed in COVID-19 patients and their predicted functions based on the sequence and structural analyses offer avenues to understand better and explore therapeutic approaches for this disease.

bioinformatics↗