NMR-guided molecular docking of a protein-peptide complex based on ant colony optimization

Abstract

Standard docking approaches used for the prediction of protein ligand complexes in the drug development process have problems identifying the correct binding mode of large flexible ligands. Herein we show how additional experimental data from NMR experiments can be used to predict the binding mode of a mucin1 (MUC-1) pentapeptide recognized by the breast-cancer-selective monoclonal antibody SM3. Distance constraints derived from trNOE and saturation transfer difference NMR experiments are combined with the docking approach PLANTS. The resulting complex structures show excellent agreement with the NMR data and with a published X-ray crystal structure. The method was then further tested on two complexes in order to demonstrate its more general applicability: T-antigen disaccharide bound to Maclura pomifera agglutinin, and the inhibitor SBi279 bound to S100B protein. Our new approach has the advantages of being fully automatic, rapid, and unbiased; moreover, it is based on relatively easily obtainable experimental data and can greatly increase the reliability of the generated structures.