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A novel algorithm for the virtual screening of extensive small molecule libraries against ERCC1/XPF protein-protein
Salma Ghazy1,2, Lalehan Oktay1,2, Serdar Durdaği1,2,3
1Department of Biophysics, Computational Biology and Molecular Simulations Laboratory, School of Medicine, Bahçeşehir University, İstanbul, Turkiye.
Background And Aim:
Cancer cell's innate chemotherapeutic resistance continues to be an obstacle in molecular oncology. This theory is firmly tied to the cancer cells' integral DNA repair mechanisms continuously neutralizing the effects of chemotherapy. Amidst these mechanisms, the nuclear excision repair pathway is crucial in renovating DNA lesions prompted by agents like Cisplatin. The ERCC1/XPF complex stands center-stage as a structure-specific endonuclease in this repair pathway. Targeting the ERCC1/XPF dimerization brings forth a strategy to augment chemotherapy by eschewing the resistance mechanism integral to cancer cells. This study tracks and identifies small anticancer molecules, with ERCC1/XPF inhibiting potential, within extensive small-molecule compound libraries.
Materials And Methods:
A novel hybrid virtual screening algorithm, conjoining ligand- and target-based approaches, was developed. All-atom molecular dynamics (MD) simulations were then run on the obtained hit molecules to reveal their structural and dynamic contributions within the binding site. MD simulations were followed by MM/GBSA calculations to qualify the change in binding free energies of the protein/ligand complexes throughout MD simulations.
Results:
Conducted analyses highlight new potential inhibitors AN-487/40936989 from the SPECS SC library, K219-1359, and K786-1161 from the ChemDiv Representative Set library as showing better predicted activity than previously discovered ERCC1/XPF inhibitor, CHEMBL3617209.
Conclusion:
The algorithm implemented in this study expands our comprehension of chemotherapeutic resistance and how to overcome it through identifying ERCC1/XPF inhibitors with the aim of enhancing chemotherapeutic impact giving hope for ameliorated cancer treatment outcomes.
Insights
Researchers identified novel small molecules that inhibit the ERCC1/XPF complex, a key factor in cancer chemotherapy resistance. This discovery offers a new strategy to enhance cancer treatment effectiveness.
Area of Science:
- Molecular Oncology
- Drug Discovery
Background:
- Chemotherapeutic resistance in cancer is a major obstacle.
- DNA repair mechanisms, particularly nuclear excision repair involving the ERCC1/XPF complex, neutralize chemotherapy.
- Targeting ERCC1/XPF offers a strategy to overcome this resistance.
Purpose of the Study:
- To identify small molecules that inhibit the ERCC1/XPF complex.
- To develop a strategy to enhance chemotherapy efficacy by targeting cancer's resistance mechanisms.
Main Methods:
- Developed a hybrid virtual screening algorithm combining ligand- and target-based approaches.
- Utilized all-atom molecular dynamics (MD) simulations to analyze molecular interactions.
- Employed MM/GBSA calculations to assess binding free energies.
Main Results:
- Identified potential ERCC1/XPF inhibitors AN-487/40936989, K219-1359, and K786-1161.
- These novel inhibitors demonstrated superior predicted activity compared to a known inhibitor (CHEMBL3617209).
Conclusions:
- The developed algorithm aids in understanding and overcoming chemotherapeutic resistance.
- Identified ERCC1/XPF inhibitors hold promise for enhancing chemotherapeutic impact.
- This research offers potential for improved cancer treatment outcomes.
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