Structure from function: screening structural models with functional data
1994
Jin, L. | Cohen, F.E. | Wells, J.A.
Structural constraints derived from different antibody epitopes on human growth hormone (hGH) were used to screen three-dimensional models of hGH that were generated by computer algorithms. Previously, alanine-scanning mutagenesis defined the residues that modulate binding to 21 different monoclonal antibodies to hGH. These functional epitopes were composed of 4-14 side chains whose alpha-carbons clustered within 4-23 angstroms. Distance and topographic constraints for these functional epitopes were virtually the same as constraints derived from known X-ray structures of protein-antigen complexes. The constraints were used to evaluate about 1400 models of hGH that were computer-generated by a secondary-structure prediction and packing algorithm. On average each functional epitope reduced the number of models in the pool by a factor of 2, so that 8 monoclonal antibodies could reduce the number of possible models to <10. The average root-mean-square deviation of alpha-carbon coordinates between the X-ray structure and either the pool of starting models or final models ranged from 13 to 16 angstroms or 4 to 7 angstroms, respectively, depending on the pool of starting models and the level of constraints imposed. All of the final models had the correct folding topography, and the best model was within 3.8 angstroms, root-mean-square deviation of the X-ray coordinates. This model was as close as it could have been because the models were built by using ideal helices and those in the X-ray structure are not. Our studies suggest that epitope mapping data can effectively screen structural models and, when coupled to predictive algorithms, can help to generate low-resolution models of a protein.
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