Predictions from First-Principles of Membrane Permeability to Small Molecules: How Useful Are They in Practice?
Christophe J ChipotPublished in: Journal of chemical information and modeling (2023)
Predicting from first-principles the rate of passive permeation of small molecules across the biological membrane represents a promising strategy for screening lead compounds upstream in the drug-discovery and development pipeline. One popular avenue for the estimation of permeation rates rests on computer simulations in conjunction with the inhomogeneous solubility-diffusion model, which requires the determination of the free-energy change and position-dependent diffusivity of the substrate along the translocation pathway through the lipid bilayer. In this Perspective, we will clarify the physical meaning of the membrane permeability inferred from such computer simulations, and how theoretical predictions actually relate to what is commonly measured experimentally. We will also examine why these calculations remain both technically challenging and overly computationally expensive, which has hitherto precluded their routine use in nonacademic settings. We finally synopsize possible research directions to meet these challenges, increase the predictive power of physics-based rates of passive permeation, and, by ricochet, improve their practical usefulness.
Keyphrases
- drug discovery
- molecular dynamics
- monte carlo
- deep learning
- endothelial cells
- healthcare
- primary care
- physical activity
- mental health
- density functional theory
- machine learning
- molecular dynamics simulations
- fatty acid
- quality improvement
- palliative care
- molecularly imprinted
- mass spectrometry
- data analysis
- advanced cancer
- simultaneous determination