Life Sciences & Biotechnology
Title : | Understanding the efficacy of existing drug molecules on COVID-19 through an interactive pathway: A deep learning-based predictive model |
Area of research : | COVID-19 Research, Life Sciences & Biotechnology, Mathematical Sciences |
Focus area : | Mathematical modelling for COVID-19 |
Principal Investigator : | Prof Rajat Kumar De, Professor, Indian Statistical Institute (ISI), Kolkata |
Timeline Start Year : | 2020 |
Contact info : | rajat@isical.ac.in |
Details
Executive Summary : | This study aims to adopt/ develop a machine learning (ML) based methodology to predict several new potential drugs for the treatment of SARS-CoV-2. |
Outcome/Output: | It was observed that AI-based image processing techniques had a colossal application in the detection of COVID-19 pneumonia in patients, based on chest x-ray, chest computed tomography (CT) and chest high resolution computed tomography (HRTC) images. Further, AI-based predictive models had shown potential in the identification of effective drugs molecules, repurposing of which might help in the treatment of COVID-19 disease. Based on literature reviews and an auto-encoder based deep learning methodology, Mozenavir, Oseltamivir and Di-hydro-artemisinin has been identified as probable drug molecules that might be effective in the treatment of SARS-CoV-2 virus.
The available structure of SARS-CoV-2 virus has been analysed and through knowledge-based docking, and identified probable binding sites for vitamin D3 and Ivermectin. It thus opens up new avenues for repurposing of these drug molecules as potential drugs against SARS-CoV-2 viral infection. |
Organizations involved