Leveraging molecular dynamics simulations to study psychedelics and their receptors in future drug development.

Abstract

Introduction: Psychedelics show great promise for treating Central Nervous System (CNS) disorders but are limited by side effects like hallucinations. Molecular dynamics (MD) simulations offer atomic-level insights into receptor interactions, helping to overcome these challenges and guide the development of safer, more effective psychedelic-based therapies.

Areas covered: This perspective reviews how MD simulations provide atomic-level insights into key psychedelic-receptor mechanisms: biased signaling, receptor multimerization, and lipid modulation. We also discuss MD's role in validating cryo-EM binding sites, alongside challenges in force fields, structural data, and system complexity that must be overcome to advance rational CNS drug design.

Expert opinion: MD simulations are transforming psychedelic drug discovery from serendipity to precision design. While immediate impact lies in accelerating lead optimization through in silico screening of biased signaling and multimer-selective compounds, broader adoption requires closing the translational gap between simulation predictions and in vivo outcomes. Key advancements will come from AI-refined force fields, integrative structural modeling of receptor complexes, and coupling MD with kinetic pharmacology. The ultimate goal is a predictive 'digital pharmacology' platform. Within five years, cloud-based MD screening is expected to become standard, delivering safer, mechanism-based clinical candidates and paving the way for personalized neurotherapeutics.