Computational design of PARP-1 inhibitors: QSAR, molecular docking, virtual screening, ADMET, and molecular dynamics...

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Oncology

Background:

• Poly (ADP-ribose) polymerase-1 (PARP-1) inhibitors are effective against cancers with homologous recombination repair deficiencies, such as BRCA1/2-mutated breast and ovarian cancers.
• The phthalazinone scaffold is recognized for its ability to form potent and selective interactions within the PARP-1 active site.

Purpose of the Study:

• To discover and optimize novel PARP-1 inhibitors utilizing the phthalazinone scaffold.
• To evaluate the anticancer potential of newly designed compounds through computational methods.

Main Methods:

• Quantitative Structure-Activity Relationship (QSAR) modeling, including Multiple Linear Regression (MLR) and Support Vector Machines (SVM), was employed to predict inhibitory activity.
• Molecular docking simulations were performed to assess the binding interactions of compounds with the PARP-1 active site.
• Virtual screening and molecular dynamics (MD) simulations were utilized to identify and validate lead compounds.

Main Results:

• MLR and SVM models demonstrated high predictive accuracy for PARP-1 inhibition (MLR: R ²=0.944, Q ²=0.921; SVM: R ²=0.947, Q ²=0.887).
• Several novel compounds exhibited strong binding interactions with key residues (GLY227A, MET229A, PHE230A, TYR246A) in the PARP-1 active site, comparable to known inhibitors.
• A 200 ns MD simulation of the top-ranked compound (3a) confirmed stable binding and maintained intermolecular interactions under physiological conditions.

Conclusions:

• The phthalazinone scaffold is a promising basis for developing novel PARP-1 inhibitors.
• Computational approaches effectively identified potent anticancer compounds targeting PARP-1.
• The lead compound (3a) demonstrates favorable binding stability, warranting further investigation for cancer therapy.