Request demo
  • Science

Free Energy Perturbation

Free Energy Perturbation (FEP) methods in drug discovery enable in silico testing of ligand binding affinity. Calculation of binding affinities helps prioritize compounds for synthesis, and greatly reduces the time and cost involved in a drug discovery project.
REQUEST EVALUATION, DEMO OR DISCUSSION
FEP calculation results typically fall within 1kcal/ mol from experimental data enabling accurately informed decisions on which ligand modifications can achieve the best results, with new molecule designs often significantly different from the initial molecular structure and with enhanced potency. Free energy perturbation software supports scientists in making known actives more potent, without having to synthesize hundreds or thousands of compounds, eliminating the time wasted on synthesizing non-potent molecules.

Lead optimization or hit to lead?

Whether you’re refining a promising hit or comparing multiple candidates, relative and absolute FEP offer powerful insights at different stages of drug discovery:

Relative FEP

Relative Binding Free Energy (RBFE) Perturbation calculates the relative free energy of binding between two ligands and the target

  • Best for lead optimization: Quickly compare small modifications in a chemical series
  • Highly efficient: Requires shorter simulations, making it fast and cost-effective
  • Great for ranking analogs: Determine which modifications improve binding affinity
  • Excellent for fine-tuning: Make data-driven decisions on subtle molecular changes
Absolute Binding Free Energy (ABFE) Perturbation calculates the binding strength of a ligand into a protein target

Absolute FEP

Absolute Binding Free Energy (ABFE) Perturbation calculates the binding strength of a ligand into a protein target

  • Best for hit-to-lead: Accurately predict binding affinities of new chemotypes
  • Essential for early-stage drug discovery: Identify promising starting points with confidence
  • Absolute binding free energy predictions: Directly assess compound-target interactions without the need of a congeneric ligand series

Stages of an FEP Project

There are two phases of an FEP project. Benchmarking FEP experiments can be used to gain confidence that your system is prepared correctly, confirming the predictivity of the method on the target and ligand series of interest. Then production FEP experiments yield predicted binding free energies for new molecular designs.

Benchmark

The validation process also known as ‘benchmark’ mode, uses known active molecules in their defined binding mode to assess the stability of the protein-ligand complex and the accuracy of the FEP calculation using the specific target and ligand binding mode. This phase is a critical factor for a successful FEP calculation as it allows for early identification of problematic regions of the molecular systems and localized redevelopment of the protein-ligand model to improve the calculation in these regions.

Production

Once the required level of accuracy is reached in the set of compounds used in the validation phase, the production phase can begin. New compounds with unknown activities are imported, and additional FEP calculations are deployed to predict their activity and hence rank them for synthesis or purchase.

What are the data requirements to run an FEP project?

 The three ideal data requirements for an effective FEP project can be summarised as:

The availability of a high-quality crystal structure with a relevant ligand – a crystal structure to a resolution below 2.2 Å is ideal

The quantity and quality of a dataset of ligands for validating the experiment set up and model

The generation of an appropriate ligand set for prediction

What our customers say

“As a global computational chemistry team within a contract research organisation (CRO), we aimed to improve the consistency, scalability, and scientific rigor of our molecular modelling workflows across a wide range of client projects. Cresset supported a smooth transition from a previously used commercial tool and helped address key limitations around accessibility and deployment at scale. A differentiated licensing model has enabled broad access across chemistry and biology teams while reserving advanced capabilities for computational chemistry specialists. This approach has helped balance accessibility, scientific depth, and efficient use of resources, enabling wider engagement without compromising rigor. The Cresset team have been highly responsive and knowledgeable, working closely with us to support adoption across a global user base. Training was organised according to user needs, with regular office hours providing an open forum for questions and ongoing support.

Overall, Cresset has become a valuable part of our computational chemistry toolkit, strengthening consistency, productivity, and confidence in decision-making across our organisation.”

Nicola Porta, Senior Scientist, Evotec

We are pleased to be working with Cresset’s software. This provides us with intuitive molecule design, a powerful ability to understand SAR and design plus a fresh way for generating novel and diverse structures for our projects.

Dr Kristian Birchall, Medical Research Council Technology, UK

We really like the powerful combination of excellent software tools and molecular design expertise which we get from working with Cresset.

Dr Graham Sibley, Head of Chemistry, F2G, UK

We wanted to use computational methods to suggest alternative substructures which could replace part of one of our key leads. We’d looked at other tools previously, without success, then turned to the Spark™ field-based approach. We looked at the top 50 hits from Spark and selected a subset to synthesise. Whilst the synthesised compounds exhibited a broad range of activities, we were delighted to observe that a number turned out to be nanomolar hits – with several even more potent than the original lead. One of these compounds is now our key lead against this target and further analogue synthesis is underway. Spark has certainly helped direct us towards some novel and very useful SAR on this occasion.

Laurent Rigoreau, Group Leader Medicinal Chemistry, Cancer Research Technology Discovery Laboratories

Cresset Discovery’s computational experience and high standard of scientific support is ideally suited to help drive the next stage of this project.

Dr Richard Boyce, Senior Director of Research, PhoreMost

The protein interaction potential capability [in Flare] highlighted common features across the family of targets of interest that we had not been able to visualize before. We used this information to drive ligand design into a direction we have not explored before.

Dr Martin Quibell, MAQU Chemistry Consulting, UK

We sought the scientific expertise within the Cresset Discovery team to utilize their novel field and shape-based virtual screening methods in Blaze™, and their proprietary Electrostatic Complementarity™ technique to help identify a backup series for our target effectively and efficiently. Ultimately we identified 9 novel chemotypes that were clearly distinct to those arising from docking and pharmacophore virtual screening approaches, which was an exciting outcome for us.

Dr Zara Sands, Head of CADD and Informatics, Confo Therapeutics, Belgium

Working closely with the Cresset Discovery team we aimed to identify a putative binding pose for a lead series in published PDB coordinates that was not only consistent with the kinetically deduced MOA but explained the established SAR as well. The furnished results were able to satisfy these goals and then be applied prophetically for ligand design purposes.

Twentyeight-Seven Therapeutics, USA

Medicinal chemists in my team find the covalent docking feature in Flare™ very intuitive to use.

Matthias Bauer, AstraZeneca, UK