Since it would have expected benefits for the drug discovery process, precise prediction of receptor-ligand binding affinity has become a key objective in structure-based drug design in recent years. Relative binding free energy (RBFE) computations, which depend on statistical mechanics and physics-based molecular simulations, have recently showed promise in delivering reliable predictions for drug discovery efforts. This development is the result of years of work on sampling algorithms and force fields, as well as a significant boost in computational resources.
The RBFE simulation service from Alfa Chemistry can forecast homologous ligand affinity differences with enough precision and throughput to be very helpful in lead and hit rate optimization projects. Since the predicted RBFE between reference and virtual molecules can be used to order synthetic molecules, we are particularly interested in RBFE calculations because they require less computing power than absolute binding free energy (ABFE) calculations and map directly to hit rate and lead optimization processes.
Our Computational Method
Fig 1. Thermodynamic cycle of the RBFE calculation. The RBFE difference between molecules A and B can be calculated by two possible paths. (Cournia Z, et al. 2017)
By calculating the free energy differences between homologous molecules using molecular simulations and statistical mechanics, RBFE calculations offer an appealing method to forecast protein receptor-ligand binding affinities. Because of its accurate modeling of biological systems (such as protein flexibility, explicit solvents, cofactors, ions, co-motion, and entropy, etc.) and direct application to real-world issues, RBFE simulations are of particular interest from a computational standpoint (e.g., hit rate and lead optimization).
The ability to run RBFE simulations on a modest GPU cluster processing hundreds of ligands per week provides the opportunity to explore a larger chemical space through virtual libraries, where the best predicted compounds can be prioritized for experimental synthesis and detection, thus greatly impacting drug discovery programs.
|Ligand-Receptor Binding Calculation
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Ligand-Receptor Binding Calculation Service
- System Preparation
Protein preparation; treatment of kinetic retention water; force field selection
- Sampling Considerations
Handling of protein flexibility (backbone flexibility, side chain flexibility, equilibrium protocols); handling of ligands (selection of reference ligands, pose placement, multiple bound poses, reciprocal isomers/ionized states, charged mutations, atomic mapping between ligands, size of perturbations, covalently bound and metal-bound ligands, generation of perturbation maps)
Fig 2. Example of computed poses for a congeneric series of ligands. (A) Docking tends to produce poses that fit well into the receptor structure but do not have a high overlap of the common core. (B) Poses after alignment to a reference crystal structure ligand using maximum common substructure (MCS) superposition produce a perfect overlap of the common core atoms but may contain clashes with the protein. (Cournia Z, et al. 2017)
Free energy simulations can also be used to determine the difference in relative free energy between two endpoints of a system, which should be possible as long as two endpoints of a system can be identified. Solubility (solid phase vs. aqueous phase), protein-protein interactions (bound vs. unbound), permeability (aqueous phase vs. embedded in a membrane), and many more applications are made possible as a result. As the cost of computer resources declines and the expense of drug research rises, the use of free energy simulation approaches will increase.
Our ligand-receptor binding calculation services significantly reduce costs, facilitate further experimentation, and accelerate the drug design process for our global customers. Our personalized, full-service approach will meet your innovative learning needs. If you are interested in our services, please feel free to contact us. We would be happy to work with you and see you succeed!
- Cournia Z, et al. (2017). "Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations." J. Chem. Inf. Model. 57(12): 2911-2937.