Ramy Farid

Integrated Modeling Program, Applied Chemical Theory (IMPACT)

We provide an overview of the IMPACT molecular mechanics program with an emphasis on recent developments and a description of its current functionality. With respect to core molecular mechanics technologies we include a status report for the fixed charge and polarizable force fields that can be used with the program and illustrate how the force fields, when used together with new atom typing and parameter assignment modules, have greatly expanded the coverage of organic compounds and medicinally relevant ligands. As we discuss in this review, explicit solvent simulations have been used to guide our design of implicit solvent models based on the generalized Born framework and a novel nonpolar estimator that have recently been incorporated into the program. With IMPACT it is possible to use several different advanced conformational sampling algorithms based on combining features of molecular dynamics and Monte Carlo simulations. The program includes two specialized molecular mechanics modules: Glide, a high‐throughput docking program, and QSite, a mixed quantum mechanics/molecular mechanics module. These modules employ the IMPACT infrastructure as a starting point for the construction of the protein model and assignment of molecular mechanics parameters, but have then been developed to meet specialized objectives with respect to sampling and the energy function.

Role of the active-site solvent in the thermodynamics of factor Xa ligand binding.

Understanding the underlying physics of the binding of small-molecule ligands to protein active sites is a key objective of computational chemistry and biology. It is widely believed that displacement of water molecules from the active site by the ligand is a principal (if not the dominant) source of binding free energy. Although continuum theories of hydration are routinely used to describe the contributions of the solvent to the binding affinity of the complex, it is still an unsettled question as to whether or not these continuum solvation theories describe the underlying molecular physics with sufficient accuracy to reliably rank the binding affinities of a set of ligands for a given protein. Here we develop a novel, computationally efficient descriptor of the contribution of the solvent to the binding free energy of a small molecule and its associated receptor that captures the effects of the ligand displacing the solvent from the protein active site with atomic detail. This descriptor quantitatively predicts (R(2) = 0.81) the binding free energy differences between congeneric ligand pairs for the test system factor Xa, elucidates physical properties of the active-site solvent that appear to be missing in most continuum theories of hydration, and identifies several features of the hydration of the factor Xa active site relevant to the structure-activity relationship of its inhibitors.

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

Designing tight-binding ligands is a primary objective of small-molecule drug discovery. Over the past few decades, free-energy calculations have benefited from improved force fields and sampling algorithms, as well as the advent of low-cost parallel computing. However, it has proven to be challenging to reliably achieve the level of accuracy that would be needed to guide lead optimization (∼5× in binding affinity) for a wide range of ligands and protein targets. Not surprisingly, widespread commercial application of free-energy simulations has been limited due to the lack of large-scale validation coupled with the technical challenges traditionally associated with running these types of calculations. Here, we report an approach that achieves an unprecedented level of accuracy across a broad range of target classes and ligands, with retrospective results encompassing 200 ligands and a wide variety of chemical perturbations, many of which involve significant changes in ligand chemical structures. In addition, we have applied the method in prospective drug discovery projects and found a significant improvement in the quality of the compounds synthesized that have been predicted to be potent. Compounds predicted to be potent by this approach have a substantial reduction in false positives relative to compounds synthesized on the basis of other computational or medicinal chemistry approaches. Furthermore, the results are consistent with those obtained from our retrospective studies, demonstrating the robustness and broad range of applicability of this approach, which can be used to drive decisions in lead optimization.

Use of an Induced Fit Receptor Structure in Virtual Screening

Structured‐based drug design has traditionally relied on a single receptor structure as a target for docking and screening studies. However, it has become increasingly clear that in many cases where protein flexibility is an issue, it is critical to accurately model ligand‐induced receptor movement in order to obtain high enrichment factors. We present a novel protein‐ligand docking method that accounts for both ligand and receptor flexibility and accurately predicts the conformation of protein‐ligand binding complexes. This method can generate viable receptor ensembles that can be used in virtual database screens.

Contribution of explicit solvent effects to the binding affinity of small-molecule inhibitors in blood coagulation factor serine proteases.

The prevention of blood coagulation is important in treating thromboembolic disorders, and several serine proteases involved in the coagulation cascade have been classified as pharmaceutically relevant. Whereas structure‐based drug design has contributed to the development of some serine protease inhibitors, traditional computational methods have not been able to fully describe structure–activity relationships (SAR). Here, we study the SAR for a number of serine proteases by using a method that calculates the thermodynamic properties (enthalpy and entropy) of the water that solvates the active site. We show that the displacement of water from specific subpockets (such as S1–4 and the ester binding pocket) of the active site by the ligand can govern potency, especially for cases in which small chemical changes (i.e., a methyl group or halogen) result in a substantial increase in potency. Furthermore, we describe how relative binding free energies can be estimated by combining the water displacement energy with complementary terms from an implicit solvent molecular mechanics description binding.

High‐energy water sites determine peptide binding affinity and specificity of PDZ domains

PDZ domains have well known binding preferences for distinct C‐terminal peptide motifs. For most PDZ domains, these motifs are of the form [S/T]‐W‐[I/L/V]. Although the preference for S/T has been explained by a specific hydrogen bond interaction with a histidine in the PDZ domain and the (I/L/V) is buried in a hydrophobic pocket, the mechanism for Trp specificity at the second to last position has thus far remained unknown. Here, we apply a method to compute the free energies of explicit water molecules and predict that potency gained by Trp binding is due to a favorable release of high‐energy water molecules into bulk. The affinities of a series of peptides for both wild‐type and mutant forms of the PDZ domain of Erbin correlate very well with the computed free energy of binding of displaced waters, suggesting a direct relationship between water displacement and peptide affinity. Finally, we show a correlation between the magnitude of the displaced water free energy and the degree of Trp‐sensitivity among subtypes of the HTRA PDZ family, indicating a water‐mediated mechanism for specificity of peptide binding.

Understanding Kinase Selectivity Through Energetic Analysis of Binding Site Waters

Kinases remain an important drug target class within the pharmaceutical industry; however, the rational design of kinase inhibitors is plagued by the complexity of gaining selectivity for a small number of proteins within a family of more than 500 related enzymes. Herein we show how a computational method for identifying the location and thermodynamic properties of water molecules within a protein binding site can yield insight into previously inexplicable selectivity and structure–activity relationships. Four kinase systems (Src family, Abl/c‐Kit, Syk/ZAP‐70, and CDK2/4) were investigated, and differences in predicted water molecule locations and energetics were able to explain the experimentally observed binding selectivity profiles. The successful predictions across the range of kinases studied here suggest that this methodology could be generally applicable for predicting selectivity profiles in related targets.

Docking Covalent Inhibitors: A Parameter Free Approach To Pose Prediction and Scoring

Although many popular docking programs include a facility to account for covalent ligands, large-scale systematic docking validation studies of covalent inhibitors have been sparse. In this paper, we present the development and validation of a novel approach for docking and scoring covalent inhibitors, which consists of conventional noncovalent docking, heuristic formation of the covalent attachment point, and structural refinement of the protein-ligand complex. This approach combines the strengths of the docking program Glide and the protein structure modeling program Prime and does not require any parameter fitting for the study of additional covalent reaction types. We first test this method by predicting the native binding geometry of 38 covalently bound complexes. The average RMSD of the predicted poses is 1.52 Å, and 76% of test set inhibitors have an RMSD of less than 2.0 Å. In addition, the apparent affinity score constructed herein is tested on a virtual screening study and the characterization of the SAR properties of two different series of congeneric compounds with satisfactory success.

Improving database enrichment through ensemble docking

While it may seem intuitive that using an ensemble of multiple conformations of a receptor in structure-based virtual screening experiments would necessarily yield improved enrichment of actives relative to using just a single receptor, it turns out that at least in the p38 MAP kinase model system studied here, a very large majority of all possible ensembles do not yield improved enrichment of actives. However, there are combinations of receptor structures that do lead to improved enrichment results. We present here a method to select the ensembles that produce the best enrichments that does not rely on knowledge of active compounds or sophisticated analyses of the 3D receptor structures. In the system studied here, the small fraction of ensembles of up to 3 receptors that do yield good enrichments of actives were identified by selecting ensembles that have the best mean GlideScore for the top 1% of the docked ligands in a database screen of actives and drug-like “decoy” ligands. Ensembles of two receptors identified using this mean GlideScore metric generally outperform single receptors, while ensembles of three receptors identified using this metric consistently give optimal enrichment factors in which, for example, 40% of the known actives outrank all the other ligands in the database.

The translocation kinetics of antibiotics through porin OmpC: Insights from structure-based solvation mapping using WaterMap

Poor permeability of the lipopolysaccharide‐based outer membrane of Gram‐negative bacteria is compensated by the existence of protein channels (porins) that selectively admit low molecular weight substrates, including many antibiotics. Improved understanding of the translocation mechanisms of porin substrates could help guide the design of antibiotics capable of achieving high intracellular exposure. Energy barriers to channel entry and exit govern antibiotic fluxes through porins. We have previously reported a hypothesis that the costs of transferring protein solvation to and from bulk medium underlie the barriers to protein‐ligand association and dissociation, respectively, concomitant with the gain and loss of protein‐ligand interactions during those processes. We have now applied this hypothesis to explain the published rates of entry (association) and exit (dissociation) of six antibiotics to/from reconstituted E. coli porin OmpC. WaterMap was used to estimate the total water transfer energies resulting from transient occupation by each antibiotic. Our results suggest that solvation within the porin cavity is highly energetically favorable, and the observed moderately fast entry rates of the antibiotics are consistent with replacement of protein‐water H‐bonds. The observed ultrafast exit kinetics is consistent with the lack of intrachannel solvation sites that convey unfavorable resolvation during antibiotic dissociation. These results are aligned with known general relationships between antibiotic efficacy and physicochemical properties, namely unusually low logP, reflecting an abundance of H‐bond partners. We conclude that antibiotics figuratively “melt” their way through porin solvation at a rate determined by the cost of exchanging protein‐solvent for protein‐antibiotic H‐bonds. Proteins 2013.