Research

Machine learning in Virtual screening is always challenging and still evolving. Our lab have developed A-HIOT tool which is making a reliable approach for bridging the long-standing gap between ligand-based and structure-based VS in finding the optimized hits for the desired receptor.

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We are now working on utlizing and improving A-HIOT tool and validating protocol and any idea on improvements/suggestions are welcome to join this project.

Code available for Automated Hit identification and Optimization Tool (A-HIOT) Gitlab

Neeraj Kumar, Vishal Acharya*, Machine intelligence-driven framework for optimized hit selection in virtual screening Journal of Cheminformatics 14, 48 (2022). https://doi.org/10.1186 Article (IF=8.48)

Neeraj Kumar, Vishal Acharya*, (2023) Machine intelligence-guided selection of optimized inhibitor for human immunodeficiency virus (HIV) from natural products. Computers in Biology and Medicine, 153:106525. Article (IF=7.7)

Neeraj Kumar, Vishal Acharya*, (2023) Advances in machine intelligence-driven virtual screening approaches for big-data. Medicinal Research Reviews, 44:939-974 | doi: 10.1002/med.21995 Article (IF=13.33)

Host-pathogen interactions are always challenging and rat race continuation still thrills. We have developed DLNet algorithm which is the first ever implementation of integrated deep learning and network biology approach to understand the adaptation of plant immune genes in response to multiple pathogens using genomics data.

Keeping with rat race, we are working on developing effector software prediction tool.

The code for DLNet algorithm is available GitLab

RicePathDLNet (Rice pathogen Deep Learning Network): Database for visualization software Browse

Ravi Kumar, Abhishek Khatri, Vishal Acharya*, Deep learning uncovers distinct behaviour of rice network to pathogens response. iScience, Cell Press (2022) Article (IF=6.107)

Ravi Kumar, Vishal Acharya*, (2023) Deep learning based protocol to construct an immune-related gene network of host-pathogen interactions in plants. STAR Protocols, Cell Press, 4:101934. https://doi.org/10.1016/j.xpro.2022.101934 Article

Ravi Kumar, Vishal Acharya*, (2023) Effector protein structures: a tale of evolutionary relationship. Trends in Plant Science, 28:746-748. https://doi.org/10.1016/j.tplants.2023.04.010. Article (IF=22.01)

1. Oxidative stress in human cancer

Meetal Sharma, Prince Anand, Yogendra Padwad, Vivek Dogra, Vishal Acharya*, DNA damage response proteins synergistically affect the cancer prognosis and resistance. Free radical Biology and medicine (2021) Article(IF=8.1)

2. Computational analysis of Neurodegenerative disorders

A. Leveraging Big Data & Empirical Analayis for Post-stroke Cognitive Impairment "Link Upcoming!!!!!"

B. Leveraging MRI & AI for cost-effective Alzheimer's severity assessment "Link Upcoming!!!!"

1. AI-powered Stomata Analaysis of Amaranthus diverse genotypes under stress conditions (Project)

2. AI-powered grading of Tea Leaves (Project)