Approaches to the Description and Prediction of the Binding Affinity of Small-Molecule Ligands to Macromolecular Receptors

Abstract

The influence of a xenobiotic compound on an organism is usually summarized by the expression biological activity. If a controlled, therapeutically relevant, and regulatory action is observed the compound has potential as a drug, otherwise its toxicity on the biological system is of interest. However, what do we understand by the biological activity? In principle, the overall effect on an organism has to be considered. However, because of the complexity of the interrelated processes involved, as a simplification primarily the "main action" on the organism is taken into consideration. On the molecular level, biological activity corresponds to the binding of a (low-molecular weight) compound to a macromolecular receptor, usually a protein. Enzymatic reactions or signal-transduction cascades are thereby influenced with respect to their function for the organism. We regard this binding as a process under equilibrium conditions; thus, binding can be described as an association or dissociation process. Accordingly, biological activity is expressed as the affinity of both partners for each other, as a thermodynamic equilibrium quantity. How well do we understand these terms and how well are they theoretically predictable today? The holy grail of rational drug design is the prediction of the biological activity of a compound. The processes involving ligand binding are extremely complicated, both ligand and protein are flexible molecules, and the energy inventory between the bound and unbound states must be considered in aqueous solution. How sophisticated and reliable are our experimental approaches to obtaining the necessary insight? The present review summarizes our current understanding of the binding affinity of a small-molecule ligand to a protein. Both theoretical and empirical approaches for predicting binding affinity, starting from the three-dimensional structure of a protein-ligand complex, will be described and compared. Experimental methods, primarily microcalorimetry, will be discussed. As a perspective, our own knowledge-based approach towards affinity prediction and experimental data on factorizing binding contributions to protein-ligand binding will be presented.

Free-energy perturbation and quantum mechanical study of SAMPL4 octa-acid host–guest binding energies

“…These were estimated using a thermodynamic cycle that relates ∆∆Gbind to the free energy of alchemically transforming G1 into G2 when they are either bound to the host, ∆Gbound, or are free in solution, ∆Gfree [37] ∆∆Gbind = ∆Gbind(G2) -∆Gbind(G1) = ∆Gbound -∆Gfree (1) ∆Gbound and ∆Gfree were estimated by the Bennett acceptance-ratio method [38,39] (BAR). In this approach, a finite number of λ values is selected between 0 and 1, and for each λ, an MD simulation is run with the potential…”

“…a drug candidate to its receptor protein [1,2,3,4,5,6]. Therefore, a large number of methods have been suggested with this aim, ranging from statistical knowledge-and regression-based methods to force-field-based simulations and free-energy perturbation methods.…”

The impact of accelerator processors for high-throughput molecular modeling and simulation

“…It is, however, very difficult for such methods to account correctly for the many phenomena involved in complex formation, such as the subtle interplay between entropy and enthalpy, conformational changes of the ligand or the substrate, presence of water molecules in the binding sites and limited resolution of structures [39,40]. We advocate that high-throughput molecularbased methods aimed at a detailed, systematic and physically-sound quantitative description of the binding site can now be used thanks to accelerator processors.…”

“…We advocate that high-throughput molecularbased methods aimed at a detailed, systematic and physically-sound quantitative description of the binding site can now be used thanks to accelerator processors. Methods using atomistic force-fields and dynamical molecular simulations can provide enough level of detail to achieve accurate virtual screening performance [39]. In fact, such approaches potentially take into account system specific interactions involved in complex formation.…”

Protein–Ligand Binding Free Energies from Exhaustive Docking

“…A number of approaches have been developed over the years that range from the more empirical and knowledge-based to the more force field-based methods. 1 Among the latter, the end-point methods 2 are attractive in terms of their simplicity and computational efficiency relative to more rigorous perturbation or alchemical simulations. 3 In our own lab we have previously developed one such end-point method, the solvated interaction energy (SIE) model, 4,5 which has been moderately successful in predicting protein−ligand binding affinities.…”