Exploring breast cancer treatment paradigms: innovative design, molecular docking and dynamic simulation of LOXL2 inhibitors

ABSTRACT

The impact of the LOXL2 enzyme on cell invasion and metastasis is significantly notable in breast cancer (BC), making it a promising therapeutic target in cancer drug discovery. Considering the diverse functions of lysyl oxidase both extracellularly and intracellularly, inhibiting LOX activity emerges as a strategic approach to impede cancer progression and invasion. This study is uniquely designed to identify potential small molecules targeting LOXL2 in BC. Initially, we designed small molecuels and conducted docking studies using ChemDraw and AutoDock Vina, respectively. Assessment of ADME, drug-likeness and toxicological properties was carried out using online tools such as SwissADME, admetSAR, pkCSM and ProTox-II. The best docked candidates underwent further evaluation through 100 ns molecular dynamics simulations. Compound H.2.9 scored of −8.4 kcal/mol in docking, surpassing the control's (US10717733) −5.0 kcal/mol, indicating its potential as an LOXL2 inhibitor. ADME predictions indicated that all screened compounds adhere to Lipinski's rule of five. Additionally, toxicological predictions confirmed that these compounds are non-cytotoxic, non-hepatotoxic and non-carcinogenic. The RMSD, RMSF and MM-GBSA analyses affirmed the stability of the H.2.9 compound. The development of LOXL2 inhibitors instils optimism for effective therapies against both primary and metastatic cancers in the foreseeable future, contributing to advancements in cancer research.

Abbreviations: 2D, Two-dimensional; 3D, Three-dimensional; ADMET, Absorption, distribution, metabolism, excretion and toxicity; CADD, Computer-aided drug design; MD, Molecular dynamics; MMFF, Merck molecular force field; MOL, Molecular structure file; PDB, Protein data bank; PK, Pharmacokinetics; OPLS, Optimised potentials for liquid simulations; RMSD, Root mean square deviation; RMSF, Root mean square fluctuation; SASA, Solvent-accessible surface area; SDF, Structure data file; SMILES, Simplified molecular input line entry system; SPC, Simple-point charge

GRAPHICAL ABSTRACT

KEYWORDS:

• Breast cancer
• LOXL2 inhibitors
• molecular modelling
• in-silico
• molecular docking and dynamics

Acknowledgments

The authors also would like to thank the Department of Biochemistry for providing technical support. The authors are also grateful to Advanced Biological Invention Centre, Bioinventics (https://www.bioinventics.com/) and Centre for Artificial Intelligence in Precision Medicines, King Abdulaziz University for providing resources and manuscript formatting.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

O.A.B.: supervision, methodology, investigation; and M.R.I: conceptualisation, writing review and editing, software, bioinformatics analysis, data curation, validation, resources, visualisation, and original draft preparation. All authors have read and agreed to the published version of the manuscript.

Additional information

Funding

The authors would like to thank the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, for its financial support under grant number [G-1436-130-296].