Protein structure determination using protein threading and sparse NMR data (extended abstract)
It is well known that the NMR method for protein structure determination applies to small proteins and that its effectiveness decreases very rapidly as the molecular weight increases beyond about 30 kD. We have recently developed a method for protein structure determination that can fully utilize partial NMR data as calculation constraints. The core of the method is a threading algorithm that guarantees to find a globally optimal alignment between a query sequence and a template structure, under distance constraints specified by NMR/NOE data. Our preliminary tests have demonstrated that a small number of NMR/NOE distance restraints can significantly improve threading performance in both fold recognition and threading-alignment accuracy, and can possibly extend threading's scope of applicability from structural homologs to structural analogs. An accurate backbone structure generated by NMR-constrained threading can then provide a significant amount of structural information, equivalent to that provided by the NMR method with many NMR/NOE restraints; and hence can greatly reduce the amount of NMR data typically required for accurate structure determination. Our prelimenary study suggest that a small number of NOE restraints may suffice to determine adequately the all-atom structure when those restraints are incorporated in a procedure combining threading, modeling of loops and sidechains, and molecular dynamics simulation. Potentially, this new technique can expand NMR's capability to larger proteins.
accurate structure determination,nmr data,sparse nmr data,accurate backbone structure,all-atom structure,protein structure determination,fold recognition,small number,protein threading,partial nmr data,template structure,energy minimization,nmr,noe restraint,nmr method,molecular weight,global optimization,atomic structure
Small number,Biology,Threading (protein sequence),Threading (manufacturing),Molecular dynamics,Bioinformatics,Protein structure,Energy minimization