Prediction of Chameleonic Efficiency.

Area of Science:

• Computational chemistry
• Drug discovery
• Molecular modeling

Background:

• Chameleonic properties enable drug molecules to adapt their polarity for optimal permeability and solubility.
• High molecular weight (MW) drugs often face challenges with solubility and permeability.
• Understanding and quantifying molecular polarity in different environments is crucial for drug development.

Purpose of the Study:

• To develop predictive models for molecular polarity and chameleonic behavior.
• To introduce quantitative measures for chameleonic efficiency.
• To aid in the triage and prioritization of drug candidates with favorable physicochemical properties.

Main Methods:

• Molecular dynamics simulations to generate conformational ensembles in aqueous and non-polar solvents.
• Development of a linear regression model to predict chromatographic apparent polarity (EPSA).
• Calculation of solvent-accessible surface area (SASA) terms for donor, acceptor, and total polarity.

Main Results:

• A linear regression model predicted EPSA with a mean unsigned error of 10 Ų.
• Strong correlation (R² =0.92) observed between scaled hydrogen bond donor SASA and experimental hydrogen bond donor potential.
• Introduction of two novel chameleonic efficiency indices.

Conclusions:

• The developed models effectively quantify chameleonic behavior in drug molecules.
• The chameleonic efficiency indices can guide the design of molecules with improved permeability and solubility.
• These methods offer a valuable tool for early-stage drug discovery and candidate prioritization.