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Discovery of novel PARP-1 inhibitors using tandem in silico studies: integrated docking, e-pharmacophore, deep
Aayushi Bhatnagar1, Virendra Nath1, Neeraj Kumar2
1Department of Pharmacy, School of Chemical Sciences and Pharmacy, Central University of Rajasthan, Ajmer, India.
Abstract:
Cancer accounts for the majority of deaths worldwide, and the increasing incidence of breast cancer is a matter of grave concern. Poly (ADP-ribose) polymerase-1 (PARP-1) has emerged as an attractive target for the treatment of breast cancer as it has an important role in DNA repair. The focus of the study was to identify novel PARP-1 inhibitors using a blend of tandem structure-based screening (Docking and e-pharmacophore-based screening) and artificial intelligence (deep learning)-based de novo approaches. The scrutiny of compounds having good binding characteristics for PARP-1 was carried out using a tandem mode of screening along with parameters such as binding energy and ADME analysis. The efforts afforded compound Vab1 (PubChem ID 129142036), which was chosen as a seed for obtaining novel compounds through a trained artificial intelligence (AI)-based model. Resultant compounds were assessed for PARP-1 inhibition; binding affinity prediction and interaction pattern analysis were carried out using the extra precision (XP) mode of docking. Two best hits, Vab1-b and Vab1-g, exhibiting good dock scores and suitable interactions, were subjected to 100 nanoseconds (ns) of molecular dynamics simulation in the active site of PARP-1 and compared with the reference Protein-Ligand Complex. The stable nature of PARP-1 upon binding to these compounds was revealed through MD simulation.Communicated by Ramaswamy H. Sarma.
Insights
Researchers identified novel Poly (ADP-ribose) polymerase-1 (PARP-1) inhibitors for breast cancer treatment. These compounds show potential for DNA repair-targeted therapies, validated through molecular dynamics simulations.
Area of Science:
- Medicinal Chemistry
- Computational Drug Discovery
- Oncology
Background:
- Breast cancer incidence is rising globally, necessitating novel therapeutic strategies.
- Poly (ADP-ribose) polymerase-1 (PARP-1) is crucial for DNA repair and a promising target for cancer treatment.
Purpose of the Study:
- To discover novel Poly (ADP-ribose) polymerase-1 (PARP-1) inhibitors for breast cancer therapy.
- To employ a hybrid approach combining structure-based screening and artificial intelligence for drug discovery.
Main Methods:
- Utilized tandem structure-based screening (docking, e-pharmacophore) and deep learning-based de novo design.
- Evaluated compounds based on binding energy, ADME properties, and PARP-1 inhibition.
- Conducted molecular dynamics simulations to assess binding stability of top candidates (Vab1-b, Vab1-g).
Main Results:
- Identified Vab1 as a lead compound, which was used to generate novel inhibitors via an AI model.
- Two potent inhibitors, Vab1-b and Vab1-g, demonstrated favorable binding affinity and interactions with PARP-1.
- Molecular dynamics simulations confirmed the stable binding of Vab1-b and Vab1-g to the PARP-1 active site.
Conclusions:
- The study successfully identified novel PARP-1 inhibitors with potential therapeutic applications in breast cancer.
- The integrated computational approach proved effective for discovering potent drug candidates targeting DNA repair pathways.
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