Identification and Experimental Validation of Repurposable Drugs Targeting the Essential ClpP1 Protease of Mycobacterium tuberculosis
Tuberculosis (TB) remains a major global health challenge, necessitating the identification of novel therapeutic targets and accelerated drug discovery strategies. The caseinolytic protease (ClpP) complex of Mycobacterium tuberculosis (Mtb) is essential for proteostasis, stress adaptation, and bacterial survival, making it an attractive yet underexplored drug target. Comparative structural analysis also revealed significant differences between mycobacterial and human ClpP S1 pockets, suggesting opportunities for selective inhibition. In this study, a structure-based drug repurposing approach was employed to identify approved drugs targeting the S1 pocket of the ClpP1 subunit, a key regulatory site involved in proteolytic activation. Virtual screening of the approved drug library against the ClpP1 crystal structure (PDB ID: 4U0G) identified Saquinavir and Raltegravir as the most promising candidates, exhibiting binding affinities of –9.1 and –9.5 kcal/mol, respectively, and favorable interactions with critical S1 pocket residues. Molecular dynamics simulations over 200 ns confirmed stable ligand binding and persistent occupancy within the S1 pocket. In vitro evaluation against M. tuberculosis H37Ra demonstrated potent concentration-dependent antimycobacterial activity, with Saquinavir showing superior efficacy (IC50 = 0.01 ± 0.007 μM; MIC = 64 μM) compared with Raltegravir (IC50 = 0.1 ± 0.09 μM; MIC ≥ 128 μM). Growth kinetics, REMA, and statistical analyses further validated their inhibitory activity. These findings validate Saquinavir and Raltegravir as potential repurposable anti-tubercular agents for further mechanistic and preclinical evaluation.
Authors
- Kuldeep Kumar Roy (ORCID: https://orcid.org/0000-0001-9623-0617)
- Smriti Bhardwaj
Institutions
- University of Petroleum and Energy Studies (IN)
Publication Details
- Journal
- ChemRxiv
- Published
- 2026-11-01
- DOI
- https://doi.org/10.26434/chemrxiv.15011429/v1
- Primary Topic
- Computational Drug Discovery Methods
- Type
- preprint