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Molecular modeling studies on benzimidazole carboxamide derivatives as PARP-1 inhibitors using 3D-QSAR and docking
Huahui Zeng1, Huabei Zhang, Fubin Jang
1Key Laboratory of radiopharmaceuticals of Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China.
Abstract:
Poly(ADP-ribose) polymerases (PARPs) play significant roles in various cellular functions including DNA repair and control of RNA transcription. PARP-1 inhibitors have been demonstrated to potentiate the effect of cytotoxic agents or radiation in a number of animal tumor models. To understand the structure-activity correlation of cyclic amine-containing benzimidazole carboxamide-based PARP-1 inhibitors, we have carried out a combined molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling study. Two types of satisfactory substructure-based 3D-QSAR models were built, including the comparative molecular field analysis (CoMFA) model (r(2) , 0.913; q(2) , 0.743) and comparative molecular similarity indices analysis (CoMSIA) model (r(2) , 0.869; q(2) , 0.734), to predict the biologic activity of new compounds. Docking studies were performed to explore the binding mode between all of the inhibitors and the PARP-1 and produce the bioactive conformation of each compound in the whole data set. The docked conformer-based alignment strategy gave the best 3D-QSAR models, CoMFA model (r(2) , 0.899; q(2) , 0.712) and CoMSIA model (r(2) , 0.889; q(2) , 0.744), respectively. The structural insights obtained from both the 3D-QSAR contour maps and molecular docking help to better interpret the structure-activity relationship. The information obtained from molecular modeling studies helped us to predict the activity of new inhibitors and further design some novel and potent PARP-1 enzyme inhibitors.
Insights
This study developed computational models to understand how cyclic amine-containing benzimidazole carboxamide structures inhibit Poly(ADP-ribose) polymerase-1 (PARP-1). These models aid in designing more effective PARP-1 inhibitors for potential cancer therapies.
Area of Science:
- Medicinal Chemistry
- Computational Biology
- Molecular Pharmacology
Background:
- Poly(ADP-ribose) polymerases (PARPs) are crucial in DNA repair and RNA transcription.
- PARP-1 inhibitors show promise in enhancing cancer treatments when combined with chemotherapy or radiation.
Purpose of the Study:
- To investigate the structure-activity relationship of benzimidazole carboxamide-based PARP-1 inhibitors.
- To develop predictive computational models for designing novel PARP-1 inhibitors.
Main Methods:
- Combined molecular docking and 3D-QSAR modeling (CoMFA and CoMSIA).
- Utilized a docked conformer-based alignment strategy for model building.
- Analyzed 3D-QSAR contour maps and docking results for structural insights.
Main Results:
- Developed robust 3D-QSAR models (CoMFA: r²=0.913, q²=0.743; CoMSIA: r²=0.869, q²=0.734).
- The docked conformer-based alignment yielded improved models (CoMFA: r²=0.899, q²=0.712; CoMSIA: r²=0.889, q²=0.744).
- Identified key structural features influencing PARP-1 inhibition.
Conclusions:
- Molecular modeling provides valuable insights into PARP-1 inhibitor structure-activity relationships.
- The developed models can predict the activity of new compounds.
- Facilitates the rational design of novel and potent PARP-1 enzyme inhibitors.
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