An easy-to-use pharmacophore modeling solution for ligand- and structure-based drug design
The Advantages of Pharmacophore Modeling
Pharmacophore modeling has demonstrated its value in drug design over the last 25 years with success in hit identification, core hopping, patent busting, and lead optimization. By determining the spatial arrangement of chemical features that interact with a receptor, pharmacophore modeling helps create understanding of an unknown binding site in the absence of a protein structure. These spatial relationships can arise from ligand-based information, protein-based information, or a mixture of both. Virtual screening against these features can then identify novel compounds and chemotypes that are likely to bind to the target receptor more efficiently than docking experiments.
Easy-to-use yet powerful graphical interface:
A new, intuitive interface designed by UX experts working closely with our users provides powerful yet easy-to-use access to setup, execute, and analyze pharmacophore modeling experiments. A user can move seamlessly between hypotheses creation from protein-ligand complexes or only ligands, validation, modification, and screening with expert-level control as desired.
Universally applicable - Create Hypotheses from one or more ligands, protein-ligand complexes, and apo proteins:
Phase is well suited to drug discovery projects with and without receptor structures. Create hypotheses from protein-ligand complexes and apo proteins with Schrödinger's unique e-Pharmacophores technology or via observed interactions. For ligand based projects create hypotheses through common pharmacophore perception, from aligned known actives/inactives, or from particular ligands. Selectively merge hypotheses features from protein-ligand complexes and ligand-only to create hybrid models. Add your own features to hypothesis for complete control.
A unique common pharmacophore perception algorithm designed for use in both lead optimization and virtual screening:
Phase employs a newly developed common pharmacophore perception algorithm that flips the old paradigm by identifying ligand alignments first and then perceiving hypothesis. Using pharmacophore-based shape alignments, It quickly creates high-quality hypothesis from a handful to hundreds of known active ligands. A new scoring function, PhaseHypoScore, rank-orders hypotheses by their likely performance in virtual screening as well as the quality of ligand alignment. Easily recognize multiple binding modes in hypotheses from common pharmacophore perception when training against diverse known actives.
Many opportunities to introduce experimental data or user preferences:
While Phase can be used “out of the box" to quickly design and execute pharmacophore modeling experiments, it also allows users the option to exercise precise control over job settings at all steps, including pharmacophore creation, and screening. This enables users to fine-tune hypotheses creation and screening to bias results toward experimental observables.
Flexible creation and application of compound databases:
Phase uses Schrödinger's ConfGen and Epik for rapid and thorough sampling of conformational, ionization, and tautomeric space, with optional minimization using the best-in-class OPLS3 force field. Generation and updating of Phase databases can be efficiently distributed over all available computational resources. Phase databases can be used with all Schrödinger virtual screening methods including Glide, Phase, and Shape Screening. Multiple databases can be used in a single Phase screening calculation.
A fully prepared database of purchasable compounds from eMolecules:
Schrödinger has partnered with eMolecules® to provide a Phase database of fragment, lead-like, and drug-like compounds available from eMolecules. The database can be updated monthly to ensure compound availability and enables out-of-the-box virtual screening. Top-ranked compounds from a virtual screen can be easily purchased by ID directly from eMolecules.
Citations and Acknowledgements
Schrödinger Release 2016-4: Phase, Schrödinger, LLC, New York, NY, 2016.
ö Dixon, S.L.; Smondyrev, A.M.; Knoll, E.H.; Rao, S.N.; Shaw, D.E.; Friesner, R.A., "PHASE: A New Engine for Pharmacophore Perception, 3D QSAR Model Development, and 3D Database Screening. 1. Methodology and Preliminary Results," J. Comput. Aided Mol. Des., 2006, 20, 647-671
ö Dixon, S.L.; Smondyrev, A.M.; Rao, S.N., "PHASE: A Novel Approach to Pharmacophore Modeling and 3D Database Searching," Chem. Biol. Drug Des., 2006, 67, 370-372