Bolaji Olawale

Nigeria

Leveraging Computational approaches in identifying Novel HER-2+ Breast Cancer Potential Therapeutics: Integrating Virtual Screening and MD Simulation

Olawale Quadri Bolajia 1,9, Temitope Isaac Adelusi2,9, Taiwo Ooreoluwa Ojo3,9, Ibrahim Damilare Boyenle4, Abdul-Quddus Kehinde Oyedele5, Taiwo Temitope Ogunjobi6, Adegboye Oyewole Oyaronbi6, Sukurat Oluwatoyin Ayoola7, Abdeen Tunde Ogunlana8,9
1. National Institute for Pharmaceutical Research and Development, Idu Industrial District, Abuja, Nigeria
2. Department of Surgery, School of Medicine, University of Connecticut Health, Farmington Ave, Connecticut 06030, USA
3. Chemiron Care Ltd, Agbara Industrial Estate, Ogun State, Nigeria
4. Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, USA
5. Department of Chemistry, University of New Haven, CT, USA
6. Department of Biochemistry, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria
7. Department of Public Health, College of Medicine, University of Ibadan, Oyo State, Nigeria
8. Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria
9. Computational Molecular Biology and Drug Discovery Laboratory, Department of Biochemistry, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria

Abstract

Background

Breast cancer, particularly the Human epidermal growth factor receptor 2 positive subtype, presents a significant global health challenge due to its high prevalence and mortality rates. This study delves into the molecular intricacies of HER-2 positive breast cancer, with an emphasis on the role of the HER-2 oncoprotein and its associated signaling pathways in cell growth, differentiation, and survival. In our pursuit of overcoming the limitations of one of the leading therapeutic options, Lapatinib, such as its inhibition of hERG, we embarked on a comprehensive research journey.

Methods

Computational methods and diverse screening protocols were employed. Our approach involved dual-stage molecular docking, initially with a library of PubChem-curated compounds, revealing compound 90196902 as the best of the set. This was followed by the docking of DataWarrior-generated structural analogs of Compound 90196902, using various docking protocols such as SP, XP, and IFD. Lead-like compounds from docking protocol were then subjected to ADME and toxicity analysis, molecular mechanics and molecular dynamics simulation.

Results

Three promising drug candidates (Compound_56, Compound_81, and Compound_339) were identified, showing excellent interaction with the target. Additionally, binding free energy calculations, ADME and Toxicity profiling, and Molecular dynamics simulations presented these compounds as lead-like.

Conclusions

Compound_56 showed the most promising pharmacodynamic and pharmacokinetic properties, coupled with substantial structural stability. While immensely promising, further optimization and pre-clinical investigation are imperative to validate this compound as a viable alternative to existing therapies for HER-2 positive breast cancer.