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One algorithm to predict protein structure is the residual dipolar couplingbased residue assembly and filter tool (REDCRAFT). This algorithm exploits anexponential reduction of the search space of all possible structures to find astructure that best fits a set of experimental residual dipolar couplings.However, the minimum amount of data required to successfully determine aprotein's structure using REDCRAFT has not been previously investigated. Herewe explore the effect of reducing the amount of data used to fold proteins. Ourgoal is to reduce experimental data collection times while retaining theaccuracy levels previously achieved with larger amounts of data. We alsoinvestigate incorporating a priori secondary structure information intoREDCRAFT to improve its structure prediction ability.

Minimum Data Requirements and Supplemental Angle Constraints for Protein Structure Prediction with REDCRAFT