Prime

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.

Unmatched accuracy:
Prime combines improved science with new methods and algorithms to provide the highest accuracy in predicted structures.

Advanced simulation:
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.

Full integration:
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.

Easy-to-use interface:
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 2023-3: Prime, Schrödinger, LLC, New York, NY, 2023.

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"Disulfide Bond Engineering of an Endoglucanase from Penicillium verruculosum to Improve Its Thermostability"

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· "Target-template relationships in protein structure prediction and their effect on the accuracy of thermostability calculations"

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· "A novel method for in silico assessment of Methionine oxidation risk in monoclonal antibodies: Improvement over the 2-shell model"

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· "A Descriptor Set for Quantitative Structure-Property Relationship Prediction in Biologics"

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· "Relative Binding Affinity Prediction of Charge-Changing Sequence Mutations with FEP in Protein–Protein Interfaces"

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· "Improving Accuracy, Diversity, and Speed with Prime Macrocycle Conformational Sampling"

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· "Relative Binding Free Energy Calculations Applied to Protein Homology Models"

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· "Docking covalent inhibitors: A parameter free approach to pose prediction and scoring"

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· "Prediction of Long Loops with Embedded Secondary Structure Using the Protein Local Optimization Program"

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· "Improved docking of polypeptides with Glide"

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· "Consensus Induced Fit Docking (cIFD): Methodology, validation, and application to the discovery of novel Crm1 inhibitors"

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· "Successful prediction of the intra- and extracellular loops of four G-protein-coupled receptors"

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"Further Characterization of the [Fe-Fe]-Hydrogenase Maturase  HydG"

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· "Towards better refinement of comparative models: predicting loops in inexact environments"

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"Exploring Structural Variability in X-Ray Crystallographic Models Using Protein Local Optimization by Torsion-Angle Sampling"

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· "Improved Methods for Side Chain and Loop Predictions via the Protein Local Optimization Program: Variable Dielectric Model for Implicitly Improving the Treatment of Polarization Effects"

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"Prediction and assignment of function for a divergent N-succinyl amino acid racemase"

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· "Multiscale Optimization of a Truncated Newton Minimizer and Application to Proteins and Protein-Ligand Complexes"

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"Molecular mechanics methods for predicting protein-ligand binding"

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· "What role do surfaces play in GB models? A new generation of surface-generalized Born model based on a novel Gaussian surface for biomolecules"

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· "Long Loop Prediction Using the Protein Local Optimization Program"

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"Conformational flexibility, internal hydrogen bonding, and passive membrane permeability: Successful in silico prediction of the relative permeabilities of cyclic peptides"

Rezai, T.; Bock, J. E.; Vong, M.; Lokey, R. S.; Jacobson, M. P., J. Am. Chem. Soc, 2006, 128, 14073-14080

"Accurate Prediction of the Relative Potencies of Members of a Series of Kinase Inhibitors Using Molecular Docking and MM-GBSA Scoring"

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"Conformational Changes in Protein Loops and Helices Induced by Post-Translational Phosphorylation"

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· "First-Shell Solvation of Ion Pairs: Correction of Systematic Errors in Implicit Solvent Models"

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· "A Hierarchical Approach to All-Atom Protein Loop Prediction"

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· "Computational Modeling of the Catalytic Reaction in Triosephosphate Isomerase"

Guallar, V.; Jacobson, M. P.; McDermott, A.; Friesner, R. A., J. Mol. Biol., 2004, 337, 227-239

· "Complete Protein Structure Determination Using Backbone Residual Dipolar Couplings and Sidechain Rotamer Predication"

Andrec, M.; Harano, Y.; Jacobson, M. P.; Friesner, R. A; Levy, R. M., J. of Structural and Functional Genomics, 2002, 2, 103-111

· "Force Field Validation Using Protein Side Chain Prediction"

Jacobson, M. P.; Kaminski, G. A.; Friesner, R. A; Rapp, C. S., J. Phys. Chem. B., 2002, 106, 11673-11680

· "On the Role of Crystal Packing Forces in Determining Protein Sidechain Conformations"

Jacobson, M. P.; Friesner, R.A.; Xiang, Z.; Honig, B., J. Mol. Biol., 2002, 320, 597-608
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