On the estimation of ligand binding affinities

A method to accurately estimate the binding affinity of a small molecule to a receptor would be indispensable in numerous fields. For instance, most drugs exert their action by binding to a macromolecule target. Thus, a lot of time and resources could be saved in drug design by predicting affinities by computer programs.

In a series of 15 papers, we have tested, compared, and improved the most popular methods to estimate binding affinities. We have used for instance molecular mechanics with generalized Born and surface area solvation (MM/GBSA), linear interaction energy (LIE), and alchemical perturbation methods. Some of the topics covered are:

* How the precision of MM/GBSA estimates are affected by the simulation protocol
* If semiempirical quantum-mechanical methods can improve affinity estimates
* A comparison of different polar solvation methods in MM/GBSA
* If non-polar solvation methods can model different degrees of active-site hydration
* How to obtain normal-mode entropies accurately and efficiently
* What method is more efficient: LIE or MM/GBSA
* A comparison of several end-point continuum-solvation methods
* What charge model to use in simulations of host–guest complexes
* The performance of end-point methods in a binding-affinity blind test
* How we can make alchemical methods more useful for drug design
* If a single-reference state can be used to simulate several ligands
* What properties calculated from molecular dynamics simulations do converge

Together, these studies clearly show what methods to use and what methods to avoid. We conclude that approximate methods are not very accurate and the results are highly system dependent. On the other hand, using alchemical methods, affinity differences between similar ligands can be accurately estimated both quickly and with a high precision.