The review article by Kataria et al. provides a comprehensive overview of the computational drug discovery workflow for protein target identification, pharmacophore mapping, and virtual screening of lead molecules. However, I have following points that the authors should address:

1. The authors should add information on how a training dataset is utilized in gene-expression profile based protein target identification. Please emphasize on screening strategy in case multiple molecules bind to multiple protein targets.
2. Authors should incorporate information about newer and larger protein target databases such as drug2gene and DSigDB.
3. Please add information on QSAR methods for drug screening against protein targets and include their advantages and disadvantages with respect to modern day methods.
4. In the molecular modelling section, the authors should include information about AI-based structure prediction and modelling, example: Alpha-fold.
5. A small section on large supramolecular structures from cryo-electron microscopy and their utility as drug targets should be also included.
6. Also, including information on computational drug discovery and its correlation to clinical trials for new lead molecules, success and failures could immensely enhance the review article.

I recommend a minor revision before the manuscript could be accepted for publication in RSC Medicinal Chemistry.