Predicting the binding free energy between a ligand and a protein is crucial for drug discovery. Alchemical free energy calculations have emerged as the go-to tools for this purpose, offering immense potential in hit-to-lead and lead optimization stages. Both academia and the pharmaceutical industry have witnessed the development of various commercial and free tools over the past few years, increasing their accuracy and reliability.
One commonly employed approach for alchemical calculations is Free Energy Perturbation (FEP). This method involves conducting numerous equilibrium MD simulations along a lambda coordinate to transform ligand A into ligand B through an alchemical process, making use of softcore potentials to prevent clashes and instabilities. Custom alchemical topologies and the requirement for multiple simulations of distinct systems (receptor complex and ligand in solvent) can pose challenges and demand specialized user expertise. Moreover, these methods are often unsuitable for ligand pairs with different net charges, potentially leading to difficulties in accurately treating long-range electrostatic interactions and introducing artifacts in the estimation of free energy unless complex correction factors are incorporated.
A new and innovative method called the Alchemical Transfer Method (ATM) [1,2] has recently been introduced for performing alchemical calculations. It offers a protocol to estimate relative binding free energies by swapping the positions of two ligands using a coordinate transformation. Unlike other popular approaches that involve splitting the calculation into multiple steps, ATM simplifies the process by being able to perform everything in a single solvent box. As a consequence, ATM does not require the use of softcore pair potentials, making it more straightforward to implement and use. The method is integrated into the free and open-source OpenMM molecular simulation package, which makes it easily accessible for large-scale automated deployments. With ATM, researchers have the flexibility to employ any potential energy function, offering a versatile and efficient solution for studying molecular interactions.
In our latest publication , we put ATM up to a test and validate it against other popular, state-of-the-art methodologies, such as FEP+, Amber, and pmx, comparing their performance on relative binding free energy predictions. To do so, we use the widely recognized benchmark dataset provided by Wang et al . This dataset is renowned for its extensive evaluation of relative binding free energy protocols and provides free energy differences for 330 ligand pairs across eight distinct protein systems.
Results on the method comparison reveal that ATM is a highly competitive method for predicting relative binding affinities, often exceeding the performance of other state-of-the-art techniques in terms of Pearson correlation. Although there were slightly higher mean absolute errors compared to alternative methods, ATM shows great promise for estimating relative binding free energies.
Overall, ATM stands out as a competitive and promising approach for predicting protein-ligand binding affinities. Its ability to achieve results on par with or even surpass other advanced techniques, combined with its simplicity and flexibility, positions ATM as a valuable new contender for accurately estimating relative binding free energies in drug discovery.
 Wu, J. Z., Azimi, S., Khuttan, S., Deng, N., & Gallicchio, E. (2021). Alchemical transfer approach to absolute binding free energy estimation. Journal of Chemical Theory and Computation, 17(6), 3309-3319.
 Azimi, S., Khuttan, S., Wu, J. Z., Pal, R. K., & Gallicchio, E. (2022). Relative binding free energy calculations for ligands with diverse scaffolds with the alchemical transfer method. Journal of Chemical Information and Modeling, 62(2), 309-323.
 Sabanés Zariquiey, F., Pérez, A., Majewski, M., Gallicchio, E., & De Fabritiis, G. (2023). Validation of the Alchemical Transfer Method for the Estimation of Relative Binding Affinities of Molecular Series. Journal of Chemical Information and Modeling.
 Wang, L., Wu, Y., Deng, Y., Kim, B., Pierce, L., Krilov, G., ... & Nicholls, A. (2015). Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field. Journal of the American Chemical Society, 137(7), 2695-2703.
Receive important news, updates, tutorials, and the latest by the Acellera team.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.