A powerful and innovative package for accurate protein structure predictions
The Advantages of Accurate Receptor Models
Rational drug design has proven to be an effective and cost-saving approach to drug development. Lead discovery using virtual screening and lead optimization through detailed understanding of ligand-receptor interactions are now indispensable components of pharmaceutical research. An accurate model of the receptor, particularly of the active site, is central to all structure-based drug design efforts. While the recent explosion in genomic data has elucidated many protein sequences, there remain many pharmaceutically relevant targets for which no accurate 3D model exist.
An accurate protein structure prediction can not only provide a model where an experimental structure is unavailable, but can also refine experimental structures obtained through X-ray crystallography or NMR, providing an even more accurate and detailed starting point for subsequent simulations and computational analyses.
Prime combines improved science with new methods and algorithms to provide the highest accuracy in predicted structures.
Prime's ligand-induced fit analysis refines active site geometries in the presence of ligands. Induced-fit modeling simulates flexibility of protein targets and identifies alternate binding modes of different ligand chemotypes.
Prime incorporates homology modeling and fold recognition into one package. Comparative modeling is used to generate accurate homology models for further structure-based studies. Threading and fold recognition techniques are used to create backbone models for early structural investigations or functional annotation in cases of low or no-sequence identity.
Prime includes an intuitive step-by-step interface that takes a novice user through the workflow of structure prediction by supplying helpful default settings for each stage of the process. At the same time, Prime allows the expert user to specify and adjust parameters to optimize the quality of predictions. The Maestro interface provides additional structural and sequence visualization and analyses tools.
Citations and Acknowledgements
Schrödinger Release 2017-1: Prime, Schrödinger, LLC, New York, NY, 2017.
ö Jacobson, M. P.; Pincus, D. L.; Rapp, C. S.; Day, T. J. F.; Honig, B.; Shaw, D. E.; Friesner, R. A., "A Hierarchical Approach to All-Atom Protein Loop Prediction," Proteins: Structure, Function and Bioinformatics, 2004, 55, 351-367
ö Jacobson, M. P.; Friesner, R.A.; Xiang, Z.; Honig, B., "On the Role of Crystal Packing Forces in Determining Protein Sidechain Conformations," J. Mol. Biol., 2002, 320, 597-608