Insights into the interaction between statins and monocarboxylate transporter 1: a molecular docking approachl

• Main Author: Hassan, Nur Amirah Mumtaz Abd Jalil
• Format: Thesis
• Language: English
• Published: 2025
• Subjects: R Medicine; RA Public aspects of medicine; RC Internal medicine
• Online Access: http://eprints.usm.my/63389/

Statins are commonly prescribed in the management of cardiovascular diseases; however, they can lead to statin-associated muscle symptoms (SAMS), which are often related to mitochondrial dysfunction. Monocarboxylate transporter (MCT1) is a proton-linked monocarboxylate transporter that facilitates the cellular uptake of statins, influencing their pharmacokinetics and potential effects on cellular metabolism and mitochondrial function. Although direct interactions between statins and MCT1 are not well-documented, emerging evidence suggests that mitochondrial dysfunction associated with statins may involve MCT1-mediated mechanisms, potentially through alterations in lactate transport and metabolic regulation.. This study explores the molecular interactions between statins and MCT1, focusing on their binding affinities and the subsequent effects on mitochondrial function and gene regulation. The 3D structure of MCT1 from Rattus norvegicus was modeled using the Swiss-Model database, based on similar sequences from Mus musculus. Molecular docking analyses, employing both blind and specific docking methods, indicated that atorvastatin lactone had the highest binding affinity to MCT1 (-8.7 kcal/mol and -9.2 kcal/mol, respectively), followed by rosuvastatin lactone (-7.5 kcal/mol and -7.9 kcal/mol), simvastatin lactone (-7.7 kcal/mol for both), pravastatin lactone (-7.4 kcal/mol for both), and simvastatin acid (-5.7 kcal/mol and -6.0 kcal/mol). Of all statins analyzed, simvastatin acid does not have any hydrogen bonds with amino acid residues of MCT1 thus could explained its lowest binding affinity. It unlike other statins. Important binding residues, including LEU132, TYR70, and THR388, were identified as essential for ligand interactions. By identifying the key molecular interactions that contribute to SAMS, this study establishes a solid framework for early prediction of MCT1 involvement during the pathology process