Fine grained sampling of residue characteristics using molecular dynamics simulation.

Area of Science:

• Computational biology
• Structural bioinformatics
• Protein dynamics

Background:

• Understanding protein structure-function relationships requires detailed knowledge of residue interactions.
• Existing structural databases like the Protein Data Bank (PDB) may not fully represent all biologically relevant protein conformations.

Purpose of the Study:

• To computationally investigate the intricate relationships between protein backbone conformations and side-chain packing/conformations.
• To explore how these relationships are influenced by amino acid identity and their local environment.
• To provide high-resolution insights into protein dynamics beyond PDB-represented states.

Main Methods:

• Utilized molecular dynamics simulations on a comprehensive set of protein folds (dynameome dataset).
• Analyzed the interplay between backbone dihedral angles (phi, psi) and the first side-chain torsion angle (chi(1)).
• Quantified the volumes occupied by side-chains and their dependence on backbone structure and location (surface vs. interior).

Main Results:

• Residue volumes are conformation-dependent, with denser packing observed in beta-sheet structures compared to alpha-helices.
• Side-chain packing is less dense on protein surfaces than in the protein interior.
• High-resolution analysis confirmed backbone-dependent rotamer preferences for chi(1), with deviations from canonical values to alleviate steric strain.

Conclusions:

• Dynameomic modeling offers a powerful approach to study native protein ensembles.
• Revealed detailed interplay between backbone conformation, residue volume, and side-chain conformation.
• Highlights the importance of considering underrepresented states in structural databases for a complete understanding of protein behavior.