Exploring the Conformational Landscape of Bioactive Small Molecules

Area of Science:

• Computational chemistry
• Drug discovery
• Structural biology

Background:

• Understanding drug-target interactions is crucial for drug discovery.
• The energy cost of adopting a bioactive conformation can influence drug efficacy.
• Protein Data Bank (PDB) structures provide valuable insights into bound ligand conformations.

Purpose of the Study:

• To investigate the energy cost associated with drug-like molecules binding to macromolecules.
• To determine the accessibility of bioactive conformations for drug-like molecules.
• To assess the reliability of computational methods for predicting drug conformations.

Main Methods:

• Utilized classical Hamiltonian replica exchange simulations.
• Employed high-level quantum mechanical calculations (DFT/SCRF).
• Analyzed over one hundred drug-like molecules from the Protein Data Bank (PDB).

Main Results:

• 73% of drug-like molecules in PDB are within 3kBT of their most stable solution conformation.
• Large conformational differences were observed for ligands with ionic contacts or extensive protein interactions.
• Identified cases with experimental structure uncertainties in the PDB.
• A coarse force field provided reasonable estimates of drug conformational ensembles in solution.

Conclusions:

• Drug-like molecules generally access their bioactive conformation with minimal energy cost.
• The computational protocol can effectively estimate the conformational energy cost.
• Findings support the feasibility of predicting drug binding conformations for improved drug design.