Exhaustive enumeration of protein conformations using experimental restraints

Area of Science:

• Computational Biology
• Structural Biology
• Biophysics

Background:

• Determining protein structures is crucial for understanding biological function.
• Experimental techniques like NMR and NOESY provide distance restraints for structure determination.
• Existing methods may require extensive data or computational resources.

Purpose of the Study:

• To develop an efficient algorithm for enumerating protein conformations based on distance restraints.
• To assess the sufficiency of limited distance restraints in defining protein folds.
• To explore a novel approach for protein structure prediction and analysis.

Main Methods:

• An efficient algorithm for enumerating self-avoiding conformations on a diamond lattice was developed.
• The algorithm was applied to proteins like crambin, pancreatic trypsin inhibitor, and ubiquitin.
• Analysis of conformational families using pairwise Root Mean Square Deviation (RMSD) was performed.

Main Results:

• The algorithm efficiently enumerates all possible protein conformations satisfying distance restraints.
• As few as 1-2 contacts per monomer are sufficient to reduce candidate structures to ~1,000.
• These conformations cluster into approximately 25 distinct structural families.

Conclusions:

• Limited distance restraints can significantly narrow down the possibilities for protein folds.
• This approach offers a new strategy for assessing alternative protein structures.
• The method is particularly relevant for utilizing Nuclear Overhauser Effect Spectroscopy (NOESY)-derived restraints.