Avinash Mishra
Also known as: Avinash
Growdea Tech., Griffith University, Indian Institute of Technology Delhi
0000-0003-4125-6670
About
Dr. Avinash is a Researach Associate at the Indian Institute of Technology-Delhi (India). Earlier, he was a Managing Director & Co-Founder at Novo Informatics Pvt. Ltd. In NI, his role includes heading Research & Development (R&D) activities and Techno-Commercialization of the products to be developed in the domain of Target Modeling & Lead Molecule Discovery. He was also an Indo-Australian Gold fellow at Griffith University, Australia.At Griffith University, he worked on computational drug design, protein structure prediction and implementation of machine learning approach to solve biological and chemical problems. Earlier, he worked in AstraZeneca R&D in the Computational Biology Division and was engaged in developing protocols for identification of new target molecules. His first post-doctoral research was on design of small peptides to stop insulin aggregation. He completed this work at Chemical Engineering department- Indian Institute of Technology (IIT) Delhi. He earned his doctoral degree (PhD) from IIT-Delhi at supercomputing facility for bioinformatics and computational biology (SCFBio). During his doctoral research he was involved with protein folding team where he worked to design scoring function to identify good protein models. His initial research in post-graduation was focused on Ribosomal RNA’s Conformational Analysis and its features at Institute of Bioinformatics and Applied Biotechnology (IBAB-India). He was awarded at many national and international platform for his start-up business idea and his scientific contributions.
Employment
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Growdea Tech. CEO2019 - Present
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Griffith University Post Doctoral Fellow2017 - 2018
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Indian Institute of Technology Delhi Post Doctoral Fellow2016 - 2017
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (22)
- ADMET-vault: an interactive framework for real-time ADMET prediction and molecular optimization Save
- Integrated virtual screening and compound generation targeting H275Y mutation in the neuraminidase gene of oseltamivir-resistant influenza strains Save
- Mechanistic Explanation of Activation and Inhibition of Crucial Enzymes Involved in Melanin Production Save
- Higher concentration of trehalose dihydrate stabilizes recombinant IgG1 under forced stress conditions Save
- Differentiating stable and unstable protein using convolution neural network and molecular dynamics simulations Save
- Identifying potential compounds from Bacopa monnieri (brahmi) against coxsackievirus A16 RdRp targeting HFM disease (tomato flu) Save
- Pharmacophore screening to identify natural origin compounds to target RNA-dependent RNA polymerase (RdRp) of SARS-CoV2 Save
- Virtual diffraction simulations using the quasi-coarse-grained dynamics method to understand and interpret plasticity contributions during in situ shock experiments Save
- Synergistic Effects of Natural Compounds Toward Inhibition of SARS-CoV-2 3CL Protease Save
- Quantitative Toxicity Prediction via Meta Ensembling of Multitask Deep Learning Models Save