High-performance free energy calculations for drug discovery

Life Science: FEP+

Discover better quality molecules, faster with FEP+

FEP+ is Schrödinger’s proprietary, physics-based free energy perturbation technology for computationally predicting protein-ligand binding at an accuracy matching experimental methods, across broad chemical space.

Explore vast chemical space and reduce costs

Explore vast chemical space and reduce costs

Leverage FEP+ as an accurate in silico binding affinity assay to drive rapid virtual design cycles and focus experimental efforts on only the highest quality ideas

Improve molecular profiles, efficiently

Improve molecular profiles, efficiently

Optimize multiple properties simultaneously, including potency, selectivity, and solubility, to improve the profile and developability of small and large molecules

Pursue novel chemistry with confidence

Pursue novel chemistry with confidence

Synthesize novel and challenging chemistry with a high degree of confidence through prospective application of FEP+

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Continuously pushing the state of the art in free energy methods

Gold standard accuracy

Predictive accuracy approaching experiment (1 kcal/mol) as demonstrated in large-scale validation studies across diverse ligands and protein classes

Proven impact in drug discovery

Widely adopted by leading pharma and biotech companies, with several drug candidates in the clinic driven by FEP+

Highly versatile

Supports the broadest range of applications and perturbation types common in drug discovery scenarios and consistently expanded through active R&D

Apply FEP+ to diverse applications across the drug discovery process

Structure Prediction & Target Enablement

Structure Prediction & Target Enablement

  • Check greenValidate protein models without experimental structures or from low resolution structures using IFD-MD with FEP+
  • Check greenStructurally enable off-targets and design out common ADMET liabilities
Hit Discovery

Hit Discovery

  • Check greenRescore hits from virtual screens to prioritize synthesis lists and improve using absolute binding FEP+

  • Check greenLeverage available chemical matter to efficiently discover novel cores via core hopping 

  • Check greenPerform large-scale in silico fragment screens using absolute binding FEP+ and solubility FEP+
Hit-to-Lead & Lead Optimization

Hit-to-Lead & Lead Optimization

  • Check greenRapidly optimize on-target potency by leveraging FEP+ as an in silico binding affinity assay

  • Check greenOptimize selectivity to known off-targets and across large gene families

  • Check greenMaintain on-target potency and selectivity while optimizing ADMET properties
In Silico Protein Engineering

In Silico Protein Engineering

  • Check greenRefine antibody candidate selection with accuracy that reproduces experimentally determined relative free energies
  • Check greenPredict predict binding affinity, selectivity, and thermostability of peptides
  • Check greenEngineer enzymes for substrate selectivity and specificity
Accelerate FEP+ calculations across large compound libraries with Active Learning

Accelerate FEP+ calculations across large compound libraries with Active Learning

Leverage a well-validated, automated workflow which trains a machine learning model on project-specific FEP+ data to allow processing of up to millions of compounds with highly accurate FEP+ calculations efficiently.

Technology in action

With FEP+, “The Experiment is the Limit.” Blog Life Science
With FEP+, “The Experiment is the Limit.”

High-performance free energy calculations for drug discovery

Tackling Drug Solubility: AbbVie and Schrödinger Collaborate to Advance Accurate Prediction Methods (FEP) Blog Life Science
Can AlphaFold Models be Used for Structure-Based Drug Design? A Perspective Two Years In Blog Life Science
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Featured CourseFree energy calculations for drug design with FEP+

Learn how to apply FEP+ to your project with our online certification course

Level-up your FEP+ skills and enroll in our online molecular modeling course, Free Energy Calculations for Drug Design with FEP+.

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Case Studies

Discover how Schrödinger’s technology is being used to solve real-world research challenges.

Hit to development candidate in 10 months: Rapid discovery of a novel, potent MALT1 inhibitor

Digital chemistry platform provides scale and accuracy to drive high precision molecular design

Morphic Therapeutic leverages digital chemistry strategy to design a novel small molecule inhibitor of α4β7 integrin

Collaborative enterprise platform and physics-based digital assays empower a team of experts to tackle a challenging target

Accelerating DMTA cycles with fast, push-button free energy calculations available to whole project teams

Single-edge FEP+ integrated in LiveDesign

Official NVIDIA Partner

Schrödinger has a strategic partnership with NVIDIA to optimize our computational drug discovery platform for NVIDIA GPU technology.

Related Products

Learn more about the related computational technologies available to progress your research projects.

Active Learning Applications

Accelerate discovery with machine learning

De Novo Design Workflow

Fully-integrated, cloud-based design system for ultra-large scale chemical space exploration and refinement

OPLS4 & OPLS5 Force Field

A modern, comprehensive force field for accurate molecular simulations


Accurate ligand binding mode prediction for novel chemical matter, for on-targets and off-targets


Complete modeling environment for your molecular discovery


Your complete digital molecular design lab


Browse the list of peer-reviewed publications using Schrödinger technology in related application areas.

Life Science
Pathfinder-Driven Chemical Space Exploration and Multiparameter Optimization in Tandem with Glide/IFD and QSAR-Based Active Learning Approach to Prioritize Design Ideas for FEP+ Calculations of SARS-CoV-2 PLpro Inhibitors
Life Science
Robust prediction of relative binding energies for protein-protein complex mutations using free energy perturbation calculations
Life Science
In silico enabled discovery of KAI-11101, a preclinical DLK inhibitor for the treatment of neurodegenerative disease and neuronal injury
Life Science
Enabling Structure-Based Drug Discovery Utilizing Predicted Models
Life Science
The maximal and current accuracy of rigorous protein-ligand binding free energy calculations
Life Science
Is the Functional Response of a Receptor Determined by the Thermodynamics of Ligand Binding?
Life Science
Exploiting high-energy hydration sites for the discovery of potent peptide aldehyde inhibitors of the SARS-CoV-2 main protease with cellular antiviral activity
Life Science
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
Life Science
Basic Residues at Position 11 of α-Conotoxin LvIA Influence Subtype Selectivity between α3β2 and α3β4 Nicotinic Receptors via an Electrostatic Mechanism
Life Science
Free Energy Perturbation Approach for Accurate Crystalline Aqueous Solubility Predictions

Training & Resources

Online certification courses

Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.


Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.