Kinematic Reconstruction of Cyclic Peptides and Protein Backbones from Partial Data

Area of Science:

• Computational Biology
• Structural Bioinformatics
• Biophysics

Background:

• Existing analytical methods for all-atom protein reconstruction from Cα traces often assume canonical planar trans peptide geometry.
• This assumption limits the accurate modeling of noncanonical cis-trans conformations and conformational flexibility.
• Addressing these limitations is crucial for improving protein structure analysis and comparison.

Purpose of the Study:

• To present Quaternary Backbone Kinematic Reconstruction (QBKR), a novel, fast, analytical method for all-atom protein and peptide backbone reconstruction from Cα coordinates.
• To incorporate noncanonical cis-trans peptide geometry naturally within a de novo kinematic model.
• To enhance conformational sampling and address limitations in Cα-based structure comparison by enabling alternative feasible conformations.

Main Methods:

• QBKR utilizes a kinematic model that naturally incorporates cis-trans geometry, allowing for perturbations and continuous changes.
• A spring-based objective function optimizes Cα-Cα distance variations beyond the cis-trans limit.
• The method combines kinematic construction with a ring closure algorithm for cyclic peptides and protein loops, requiring flexibility in one Cα atom for closure.

Main Results:

• QBKR successfully reconstructs all-atom protein and peptide backbones from Cα traces, handling both linear and cyclic structures.
• The method naturally incorporates noncanonical cis-trans geometry and allows for optimization of geometric variations.
• QBKR enriches conformational ensembles, producing alternative conformations with reversed H-bond orientations, and can be applied to noisy Cryo-EM data.

Conclusions:

• QBKR provides a fast and accurate method for all-atom backbone reconstruction, overcoming limitations of previous analytical approaches.
• The ability to model diverse peptide geometries and generate alternative conformations significantly improves structural analysis.
• QBKR offers a valuable tool for accelerating the generation of all-atom descriptions from experimental data, especially with suboptimal electron density maps.