Discovery of novel PARP1 inhibitors through computational drug design approaches.

Background: Triple-negative breast cancer (TNBC) is the most frequent malignancy in women. It is a prevalent condition, representing 15-20 % of all breast cancer cases, characterized by its aggressive subtype and unfavorable prognosis.

Objectives: The main aim of this study is to find and develop a potential novel therapeutic candidate for TNBC treatment utilizing luteolin derivatives compounds.

Methods: In this study, we used the stable TNBC protein structure from the Protein Data Bank (PDB) and selected luteolin, a bioactive compound known for its anti-cancer properties, to design potential anti-cancer drugs using computational methods. Structural activity relationship methodologies were used to evaluate active and inactive outcomes using pass prediction scores. Furthermore, we employed in-silico methods such as ADMET, drug-likeness evaluation, DFT quantum calculations, and Frontier Molecular Orbitals (HOMO and LUMO). Afterwards, we performed molecular docking for binding affinity and molecular dynamics simulations over 200 ns to validate interactions with TNBC protein RESULTS: Our results demonstrated that the ligands DM02, DM06, DM07, and DM09 did not violate Lipinski rules, and their reduced HOMO-LUMO energy gap indicates enhanced chemical reactivity and interaction with biological targets. The drug's maximum softness and minimum hardness values showed rapid metabolism and no hepatotoxicity, carcinogenicity, skin sensitization, or aquatic toxicity. Molecular docking studies revealed that DM02 and DM09, luteolin derivatives, have the highest binding affinity with the TNBC protein (PDB ID 5HA9) and our study confirms their stable interactions with the protein, suggesting potential therapeutic agents for TNBC.

Conclusions: Our computational data suggest that Luteolin derivatives have the potential to be utilized as therapeutic agents for TNBC. However, further experimental validation is needed to validate these findings.