Protein Structure Determination by Assembling Super-Secondary Structure Motifs Using Pseudocontact Shifts.

Area of Science:

• Structural biology
• Computational biology
• Biophysics

Background:

• Hybrid computational and nuclear magnetic resonance (NMR) methods are effective for small protein 3D structure determination.
• Existing algorithms face challenges in accurately modeling larger protein structures.

Purpose of the Study:

• To develop a novel computational algorithm for assembling 3D protein structures from super-secondary structural motifs (Smotifs).
• To address the limitations of current methods in determining structures of larger proteins.

Main Methods:

• The DINGO-PCS (3D assembly of Individual Smotifs to Near-native Geometry as Orchestrated by PCSs) algorithm was developed.
• It utilizes pseudocontact shift (PCS) restraints from metal centers to recognize, orient, and assemble Smotifs.
• A universal Smotif database is employed for exhaustive Smotif enumeration.

Main Results:

• The DINGO-PCS algorithm was benchmarked on ten protein targets (100–220 residues) with diverse topologies.
• Near-native Smotifs were successfully identified for nine out of ten protein targets.
• The method demonstrated efficacy without requiring additional experimental data or computational force fields.

Conclusions:

• DINGO-PCS offers a robust computational approach for 3D protein structure determination, particularly for larger proteins.
• The algorithm effectively leverages PCS restraints for accurate Smotif assembly.
• This method advances the capabilities of computational structural biology.