Computational study of protein secondary structure elements: Ramachandran plots revisited

Area of Science:

• Computational Chemistry
• Molecular Modeling
• Biophysics

Background:

• Understanding amino acid intrinsic properties is crucial for molecular modeling.
• Previous studies often overlook individual amino acid characteristics, focusing on larger polypeptide models.
• Computational methods offer insights into conformational preferences.

Purpose of the Study:

• To construct and analyze potential energy surfaces (PES) for nineteen amino acids.
• To identify common conformational patterns and global minima within amino acid groups.
• To correlate these intrinsic properties with structural and pharmacophoric features.

Main Methods:

• Utilized density functional theory (DFT) with PW91 and M062X/6-311** functionals.
• Calculated PES by examining energy as a function of φ/ψ dihedral angles.
• Analyzed allowed regions of the Ramachandran plot for conformational analysis.

Main Results:

• Identified distinct groups of amino acids sharing common PES patterns and global minima.
• Observed partial correlation between identified patterns and amino acid structural/pharmacophoric features.
• Rationalized discrepancies between computational and experimental conformations via non-covalent interactions.

Conclusions:

• Amino acid intrinsic properties, revealed through PES analysis, exhibit group-specific conformational patterns.
• These intrinsic properties influence overall polypeptide behavior and should be considered in molecular modeling.
• The study provides a foundation for understanding amino acid behavior independent of larger biological contexts.