Unlock your protein target and ligand series of interest for rigorous structure-based design
We’re in the midst of a revolution in structural biology, with a proliferation of available structures across protein classes due to advances in cryo-EM, low sequence identity homology modeling, and machine learning technologies such as AlphaFold. However, significant protein structure refinement and accurate ligand placement is required to use these structures for accurate physics-based simulations, including free energy calculations with FEP+.
Free up your time and resources — let us prepare your protein-ligand system of interest for structurebased design. Whether you are starting from experimental X-ray structures, cryo-EM structures, AlphaFold predicted structures, or homology models, Schrödinger scientists will leverage our unique technologies and expertise to optimize and validate protein-ligand complexes for highly predictive structure-based design.
Propel your discovery program with unrivaled technologies and expertise
Case Study I
Challenge:
Despite a ~3.2Å cryo-EM structure of the target in complex with a ligand from the series of interest, known SAR could not be explained and the program was, effectively, not structurally enabled.
Result:
Our ensemble trial-and-error approach allowed us to identify an alternate ligand binding mode, as well as small but important protein adjustments necessary for binding. Although the binding mode was flipped compared to the model proposed by the structural biology team, it also fit the experimental density and, importantly, was predictive of all known SAR available.
Case Study II
Challenge:
A series of small molecule inhibitors against a flexible protein target was reaching its limits due to the lack of structural insights to guide the design, as well as off-target activity on a homologue.
Result:
Schrödinger enabled accurate FEP+ predictions for the series of interest both on the target and the anti-target. Importantly, it revealed specific loop and side-chain motions that were necessary for the ligands to bind, and remarkably, the results were counterintuitive as they revealed different binding modes in the two proteins despite their high similarity.
Enable FEP+ starting from all levels of structural information
Whether you are starting with template-based homology and AlphaFold models or if you have incomplete cryo-EM or experimental X-ray structures, Schrödinger’s team has the scientific expertise and computational resources needed to structurally enable your unique project.
Scientifically-validated solutions for structure-based drug discovery
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Using AlphaFold and experimental structures for the prediction of the structure and binding affinities of GPCR complexes via induced fit docking and free energy perturbation.
Coskun D, et al. J. Chem. Theory Comput. December 15, 2023.
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Benchmarking refined and unrefined AlphaFold2 structures for hit discovery.
Zhang Y, et al. J. Chem. Inf. Model. 2023, 63, 6, 1656–1667.
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Induced-fit docking enables accurate free energy perturbation calculations in homology models.
Xu T, et al. J. Chem. Theory Comput. 2022, 18, 9, 5710–5724.
Enabling digital technologies to drive discovery programs
IFD-MD
Accurate ligand binding mode prediction for novel chemical matter, for on-targets and off-targets
Software and services to meet your organizational needs
Software Platform
Deploy digital drug discovery workflows using a comprehensive and user-friendly platform for molecular modeling, design, and collaboration.
Modeling Services
Leverage Schrödinger’s computational expertise and technology at scale to advance your projects through key stages in the drug discovery process.
Support & Training
Access expert support, educational materials, and training resources designed for both novice and experienced users.