Membrane proteins such as G-protein coupled receptors (GPCRs) and ion channels, are integral components of cellular biology and major players in health and disease. Their roles in signal transduction, cellular communication, and ion transport make them prime targets for therapeutic interventions. The advent of advanced computational techniques, particularly those augmented by artificial intelligence, has revolutionized the study of these proteins. Despite significant progress, challenges remain due to the complex environment and dynamic behavior of membrane proteins, thereby prompting further exploration and refinement of computational methods.

Recent advances leverage AI to considerably improve the accuracy of structural predictions and offer dynamic simulations that mimic real-life conditions. These technological breakthroughs are crucial in capturing the vast conformational landscape of membrane proteins. Multiscale simulations, which integrate molecular dynamics with network analysis, offer comprehensive insights from the molecular level to the systemic level, linking protein interactions to broader physiological responses. Although promising, there is a continual need to enhance computational models to better represent physiological environments and to validate predictions with experimental data.

This Research Topic aims to further explore and extend computational and AI-driven methodologies in the study of membrane proteins. The objective is to bridge the gap between detailed mechanistic insights and practical therapeutic applications, ultimately leading to more efficient drug discovery processes for challenging targets like GPCRs and ion channels.

To gather further insights in mathematical modeling and AI applications in membrane protein research, we welcome articles addressing, but not limited to, the following themes:

• Developments in AI-enhanced structural prediction of membrane proteins
• Advanced simulation techniques capturing membrane protein dynamics
• Integrating multiscale models to understand membrane protein functions
• Application of computational models in drug discovery and development
• Bridging computational predictions with experimental validations

Submissions of original research articles, review papers, and case studies are encouraged to provide a comprehensive understanding of the current advancements and future directions in this evolving field.

Topic Editor Myungjin Lee is employed by OncoC4 Inc., Rockville, United States. All other Topic Editors declare no competing interests with regards to the Research Topic subject.

Are you interested in contributing a manuscript to this Research Topic?

Computational advancements in structural prediction and multiscale simulations of membrane proteins for drug discovery