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Dr. Mushtaq Ahmad Wani

Project Scientist-I · Discovery Informatics Group, NPMC Division, CSIR-IIIM, Jammu Indian Institute of Integrative Medicine,Jammu

https://researchid.co/wanihayat10
@niper.irins.org
16Scopus Publications
242Google Scholar Citations
9Google Scholar h-index
7Google Scholar i10-index

Research Interests

Computer-aided architectural design (CAAD), Chemoinformatics, Machine learning, ML Classification models, Artificial Intelligence (AI), Bioinformatics, Pharmacoinformatics, Tuberculosis, Molecular modeling, Pattern Recognition, and Pharmacophore development

Biography

His research work focused on computational modelling for the design and optimization of novel small molecules as potential next-generation inhibitors of mycobacterium cytochrome bc1-aa3 super complex. His research interests include the development of machine learning models, artificial intelligence, molecular modelling, and Pharmacophore mapping.

Education

(2017-2023) Doctor of Philosophy (Pharmacoinformatics) at National Institute of Pharmaceutical Education & Research, Kolkata, West Bengal, India (2015-2017) Masters of pharmacy (Pharmacoinformatics) from National Institute of Pharmaceutical Education and Research, S.A.S Nagar, Punjab, India (2010-2015) Bachelor of Pharmacy from University of Kashmir: Srinagar, Jammu, and Kashmir, India

Recent Scopus Publications

  1. An integrated machine learning and computational framework with experimental validation for the identification of novel CXCR4 inhibitors
    European Journal of Medicinal Chemistry, 2026
  2. Integrating in silico and in vitro approaches for identifying potential TNF-α inhibitors
    International Journal of Biological Macromolecules, 2025
  3. Targeting tryparedoxin-dependent peroxidase (TXNPx) enzyme to identify repurposing drug candidates from FDA-approved drugs and natural products using virtual screening, ADME/Tox and MD simulations
    Biochemistry and Biophysics Reports, 2025
  4. Machine learning framework coupled with CADD for predicting sphingosine kinase 1 inhibitors
    Computers in Biology and Medicine, 2025
  5. Computer-aided drug design approaches for the identification of potent inhibitors targeting elongation factor G of Mycobacterium tuberculosis
    Journal of Molecular Graphics and Modelling, 2025

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