Ms.Sathya B

Ms.Sathya B

Research Scholar
Area: Bioinformatics
Affiliation: Department of Genetic Engineering, Kattankulathur Campus, SRM Institute of Science and Technology (formerly known as SRM University)

Education

Other Details:

Research Interests:

• Pharmacophore Modeling
• Screening of large virtual compound libraries
• Molecular dynamics simulation
• Quantitative Structure Activity Relationship Study

Selected Publications:

• Sathya B, Rupa M, Santhosh Kumar N, Sohn H, and Thirumurthy M (2016). Molecular Modeling Study on Diazine Indole Acetic Acid Derivatives for CRTH2 Inhibitory Activity. Combinatorial Chemistry & High Throughput Screening, vol. 19(6), pp.444-460.
• Sathya B, Santhosh Kumar N, Hang Lee S, and Thirumurthy M (2016). Structural characterization of human CRTh2: a combined homology modeling, molecular docking and 3D-QSAR-based in silico approach. Medicinal Chemistry Research, vol.  25(4), pp.653-671.
• Sathya B, Kulkarni S.A, Sohn H and Thirumurthy M (2015). Identification of leads through insilico approaches utilizing benzylthio-1H-benzo[d]imidazol-1yl acetic acid derivatives: A potent CRTh2 antagonist. Journal of Molecular Structure, vol. 1102, pp. 25-41.
• Sathya B, Sohn H, and Thirumurthy M (2015). Computational analysis of CRTH2 receptor antagonist: A Ligand- based CoMFA and CoMSIA approach. Computational Biology and Chemistry, vol. 56, pp. 109-121.
• Sathya B, Akila Parvathy D, Ramesh Kumar G (2015). NGS Meta data analysis for identification of SNP and INDEL patterns in human airway transcriptome: A preliminary indicator for lung cancer, Applied and Translational Genomics, vol. 4, PP. 4-9.
• Santhosh Kumar N, Sathya B, and Thirumurthy M (2017). Theoretical analysis of somatostatin receptor 5 with antagonists and agonists for the treatment of neuroendocrine tumors. Molecular Diversity, vol. 21(2), pp.367-384.
• Santhosh Kumar N, Sathya B, Sohn H, Panneer D, and Thirumurthy M (2017). 3D-QSAR studies on indole and 7-azoindole derivatives as ROCK-2 inhibitors: An integrative computational approach. Computational Biology and Chemistry, vol. 71, pp.104-116.

Work in Progress:

• Identifying the potent lead compounds for Janus Kinase enzymes (JAK).
• Optimizing the available JAK inhibitors using Quantitative Structure Activity Relationship Study.

Achievements and Awards:

• Awarded with CSIR-SRF fellowship