Systematic computational strategies for identifying protein targets and lead discovery

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...

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Veröffentlicht in:MedChemComm 2024-07, Vol.15 (7), p.2254-2269
Hauptverfasser: Kataria, Arti, Srivastava, Ankit, Singh, Desh Deepak, Haque, Shafiul, Han, Ihn, Yadav, Dharmendra Kumar
Format: Artikel
Sprache:eng
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Zusammenfassung: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. Computational algorithms and tools have retrenched the drug discovery and development timeline.
ISSN:2632-8682
2040-2503
2632-8682
2040-2511
DOI:10.1039/d4md00223g