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Identifying drug targets and evaluating KLK3-targeted inhibitors for prostate cancer using in-silico and in-vitro
Imran Zafar1, Shaista Shafiq1, Adil Jamal1
1Department of Biotechnology, Faculty of Science, The University of Faisalabad (TUF), Faisalabad, Punjab, Pakistan.
Abstract:
Prostate cancer remains a significant oncological challenge, driven by molecular factors such as KLK3 (kallikrein-related peptidase 3). Text mining of 237,357 PubMed articles identified KLK3 as the most frequently cited protein (10,477 mentions in titles; 162,619 in abstracts), with strong co-mentions of AR, TMPRSS2, and ERG (χ2, *p* < 0.001). Structural modeling of KLK3 (PDB: 2ANY) using I-TASSER yielded a high-confidence 3D structure (C-score: 0.73), validated by Ramachandran analysis, with 99.5% of residues falling in favored regions. Phytochemical profiling of Curcuma longa revealed potent bioactive constituents, with leaf extracts showing the highest total phenolic (510.7 ± 0.07 µg/mL) and flavonoid (498.9 ± 0.05 µg/mL) content. LC-MS identified 23 bioactive compounds, which exhibited exceptional binding affinity. Virtual screening of FDA-approved drugs (- 11.8 to - 9.4 kcal/mol), food-derived compounds (- 10.0 to - 9.1 kcal/mol), and natural products (- 11.4 to - 8.8 kcal/mol) revealed significant differences in binding affinities. MK3207 showed the highest binding affinity (- 11.7 kcal/mol), followed by MolPort-039-338-696 (- 11.4 kcal/mol), with key interactions at PHE-110 and THR-167. In-silico docking shows that MK3207 exhibits the strongest binding affinity to KLK3 (- 11.7 kcal/mol), with accuracy validated by an RMSD of 0.195 Å. Pharmacokinetic and drug-likeness evaluation of MK3207 indicated moderate solubility (Log S: - 4.58 to - 5.02), high lipophilicity (consensus log Po/w: 3.39), favorable drug-likeness (no PAINS/Lipinski violations, bioavailability score: 0.55, synthetic accessibility: 5.21). MD simulations (100 ns) confirmed stable KLK3-ligand binding (final RMSD: 4.3 Å protein, 3.1 Å ligand; average RMSD: 3.99 Å C-α, 3.97 Å backbone, 5.41 Å sidechain). The complex exhibited moderate flexibility (RMSF peaks: 1-4 Å), 28.32% secondary structure, and persistent interactions (hydrophobic: VAL-49, PHE-110; hydrogen bonds: THR-167, SER-213). MM-GBSA analysis revealed strong binding energy (- 75.57 to - 66.36 kcal/mol) and consistent ligand efficiency. This study bridges computational drug discovery and phytochemical analysis, nominating Curcuma longa derivatives and MK3207 as promising KLK3 inhibitors for PC therapy.
Insights
This study identifies KLK3 as a key protein in prostate cancer (PC) and nominates Curcuma longa derivatives and MK3207 as potential KLK3 inhibitors. Computational drug discovery and phytochemical analysis highlight their promise for PC therapy.
Area of Science:
- Computational drug discovery and phytochemical analysis applied to oncology.
- Molecular biology and structural bioinformatics.
- Natural product chemistry and pharmacology.
Background:
- Prostate cancer (PC) presents a significant oncological challenge, with KLK3 (kallikrein-related peptidase 3) identified as a key molecular driver.
- Text mining of extensive literature revealed KLK3 as a highly cited protein, frequently co-mentioned with AR, TMPRSS2, and ERG, underscoring its central role in PC.
- The need for novel therapeutic strategies targeting KLK3 in PC necessitates the exploration of potent inhibitors.
Purpose of the Study:
- To computationally model the 3D structure of KLK3 and identify potential inhibitors through virtual screening.
- To investigate the phytochemical profile of Curcuma longa for bioactive compounds with KLK3 inhibitory potential.
- To evaluate the binding affinity, drug-likeness, and pharmacokinetic properties of identified lead compounds.
Main Methods:
- Text mining of PubMed articles to identify key proteins and co-mentions related to prostate cancer.
- Protein structure modeling using I-TASSER and validation via Ramachandran analysis.
- Phytochemical profiling of Curcuma longa extracts using LC-MS, followed by virtual screening and molecular docking of identified compounds and known drugs against KLK3.
- Pharmacokinetic and drug-likeness assessments, molecular dynamics (MD) simulations, and MM-GBSA binding energy calculations.
Main Results:
- A high-confidence 3D structure of KLK3 was generated. Curcuma longa leaf extracts showed high phenolic and flavonoid content, with 23 identified bioactive compounds.
- Virtual screening identified MK3207 as the top-ranked compound with the highest binding affinity (-11.7 kcal/mol) to KLK3, demonstrating favorable interactions.
- MK3207 exhibited favorable drug-likeness and pharmacokinetic properties, with stable binding confirmed by 100 ns MD simulations and strong binding energy via MM-GBSA analysis.
Conclusions:
- This study successfully integrates computational drug discovery with phytochemical analysis to identify promising KLK3 inhibitors for prostate cancer therapy.
- Curcuma longa derivatives and the compound MK3207 are nominated as potential therapeutic agents targeting KLK3 in prostate cancer.
- The findings provide a strong foundation for further preclinical development of these candidates for PC treatment.
