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Updated: Jun 20, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
Published on: February 23, 2024
Systematic computational strategies for identifying protein targets and lead discovery
Arti Kataria1, Ankit Srivastava2, Desh Deepak Singh3
1Laboratory of Bacteriology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH) Hamilton MT 59840 USA.
None:
Computational algorithms and tools have retrenched the drug discovery and development timeline. The applicability of computational approaches has gained immense relevance owing to the dramatic surge in the structural information of biomacromolecules and their heteromolecular complexes. Computational methods are now extensively used in identifying new protein targets, druggability assessment, pharmacophore mapping, molecular docking, the virtual screening of lead molecules, bioactivity prediction, molecular dynamics of protein-ligand complexes, affinity prediction, and for designing better ligands. Herein, we provide an overview of salient components of recently reported computational drug-discovery workflows that includes algorithms, tools, and databases for protein target identification and optimized ligand selection.
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