Biology subjects

Muthamilselvan, S.

Publications and source records attributed to Muthamilselvan, S..

2 recordsLinked to original sources

bioRxiv2021

End-to-end computational approach to the design of RNA biosensors for miRNA biomarkers of cervical cancer

Cervical cancer is a global public health subject as it affects women in the reproductive ages, and accounts for the second largest burden among cancer patients worldwide with an unforgiving 50% mortality rate. Poor awareness and access to effective diagnosis have led to this enormous disease burden, calling for point-of-care, minimally invasive diagnosis methods. Here, an end-to-end quantitative approach for a new kind of diagnosis has been developed, comprising identification of optimal biomarkers, design of the sensor, and simulation of the diagnostic circuit. Using miRNA expression data in the public domain, we identified circulating miRNA biomarkers specific to cervical cancer using multi-tier screening. Synthetic riboregulators called toehold switches specific for the biomarker panel were then designed. To predict the dynamic range of toehold switches for use in genetic circuits as biosensors, we developed a generic grammar of these switches, and built a multivariate linear regression model using thermodynamic features derived from RNA secondary structure and interaction. The model yielded predictions of toehold efficacy with an adjusted R2 = 0.59. Reaction kinetics modelling was performed to predict the sensitivity of the second-generation toehold switches to the miRNA biomarkers. Simulations showed a linear response between 10nM and 100nM before saturation. Our study demonstrates an end-to-end workflow for the efficient design of genetic circuits geared towards the effective detection of unique genomic signatures that would be increasingly important in todays world. The approach has the potential to direct experimental efforts and minimise costs. All resources including the machine learning toolkit, reaction kinetics simulation, designed toehold sequences, genetic circuits, data and sbml files for replicating and utilizing our study are provided open-source with the iGEM Foundation (https://github.com/igem2019) under GNU GPLv3 licence.

synthetic biology↗

bioRxiv2020

Computational studies of drug repurposing targeting P-glycoprotein mediated multidrug-resistance phenotypes in agents of neglected tropical diseases

Mammalian ABCB1 P-glycoprotein is an ATP- dependent efflux pump with broad substrate specificity associated with cellular drug resistance. Homologous to this role in mammalian biology, the P-glycoprotein of agents of neglected tropical diseases (NTDs) mediates the emergence of multidrug-resistance phenotypes. The clinical and socioeconomic implications of NTDs are exacerbated by the lack of research interest among Big Pharma for treating such conditions. This work aims to characterise P-gp homologues in certain agents of key NTDs, namely O_LIProtozoa: Leishmania major, Trypanosoma cruzi; C_LIO_LIHelminths: Onchocerca volvulus, Schistosoma mansoni. C_LI PSI-BLAST searches against the genome of each of these organisms confirmed the presence of P-gp homologues. Each homologue was aligned against five P-gp sequences of known structure, to identify the most suitable template based on sequence homology, phylogenetic nearest neighbor, and query coverage. Antibiotics used in the current line of therapy against each of these pathogens were identified using PubChem and their SMILES structures were converted to PDB using BABEL software. Potential antibiotics to test against the set of FDA-approved antibiotics were identified based on similarity to the chemical class of the known drugs and repurposing of the existing drugs. Docking studies of the respective modelled Pgp structures and the set of antibiotic ligands were carried out using AutoDock and the most tenable target-ligand conformations were assessed. The interacting residues within 4.5 [A] of the ligand were identified, and the binding pockets were studied. The relative efficacy of the new drugs and the interacting pump residues were identified. Our studies could lay the foundation for the development of effective synergistic or new therapies against key neglected tropical diseases.

bioinformatics↗