In silico Analysis of Anti-cervical Cancer Drug Off-Target Effects on Diverse Protein Isoforms for Enhanced Therapeutic Strategies

Abstract

Background. Cervical cancer is a serious medical condition that affects hundreds of thousands of individuals worldwide annually. The selection and analysis of suitable gene targets in the early stages of drug design are crucial for combating this disease. However, overlooking the presence of various protein isoforms may result in unwanted therapeutic or harmful side effects. Objective. This study aimed to provide a computational analysis of the interactions between cervical cancer drugs and their targets, influenced by alternative splicing. Methods. Using open-access databases, we targeted 45 FDA-approved cervical cancer drugs that target various genes having more than two distinct protein-coding isoforms. To check the conservation of binding pocket in isoforms of the genes, multiple sequence analysis was performed. To better understand the associations between proteins and FDA-approved drugs at the isoform level, we conducted molecular docking analysis. Results. The study reveals that many drugs lack potential targets at the isoform level. Further examination of various isoforms of the same gene revealed distinct ligand-binding pocket configurations, including differences in size, shape, electrostatic characteristics, and structure. Conclusions. This study highlights the potential risks of focusing solely on the canonical isoform, and ignoring the impact of cervical cancer drugs on- and off-target effects at the isoform level. These findings emphasize the importance of considering interactions between drugs and their targets at the isoform level to promote effective treatment outcomes.

Keywords

• cervical cancer
• isoforms
• molecular docking
• interaction analysis
• bioinformatics approaches