A novel scoring function to estimate protein-ligand binding affinities has been developed and implemented as the Glide 4.0 XP scoring function and docking protocol. In addition to unique water desolvation energy terms, protein-ligand structural motifs leading to enhanced binding affinity are included: (1) hydrophobic enclosure where groups of lipophilic ligand atoms are enclosed on opposite faces by lipophilic protein atoms, (2) neutral-neutral single or correlated hydrogen bonds in a hydrophobically enclosed environment, and (3) five categories of charged-charged hydrogen bonds. The XP scoring function and docking protocol have been developed to reproduce experimental binding affinities for a set of 198 complexes (RMSDs of 2.26 and 1.73 kcal/mol over all and well-docked ligands, respectively) and to yield quality enrichments for a set of fifteen screens of pharmaceutical importance. Enrichment results demonstrate the importance of the novel XP molecular recognition and water scoring in separating active and inactive ligands and avoiding false positives.

Glide's ability to identify active compounds in a database screen is characterized by applying Glide to a diverse set of nine protein receptors. In many cases, two, or even three, protein sites are employed to probe the sensitivity of the results to the site geometry. To make the database screens as realistic as possible, the screens use sets of "druglike" decoy ligands that have been selected to be representative of what we believe is likely to be found in the compound collection of a pharmaceutical or biotechnology company. Results are presented for releases 1.8, 2.0, and 2.5 of Glide. The comparisons show that average measures for both "early" and "global" enrichment for Glide 2.5 are 3 times higher than for Glide 1.8 and more than 2 times higher than for Glide 2.0 because of better results for the least well-handled screens. This improvement in enrichment stems largely from the better balance of the more widely parametrized GlideScore 2.5 function and the inclusion of terms that penalize ligand-protein interactions that violate established principles of physical chemistry, particularly as it concerns the exposure to solvent of charged protein and ligand groups. Comparisons to results for the thymidine kinase and estrogen receptors published by Rognan and co-workers (J. Med. Chem. 2000, 43, 4759-4767) show that Glide 2.5 performs better than GOLD 1.1, FlexX 1.8, or DOCK 4.01.

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 (~5X 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 based on 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.3

Epik is a computer program for predicting pK(a) values for drug-like molecules. Epik can use this capability in combination with technology for tautomerization to adjust the protonation state of small drug-like molecules to automatically generate one or more of the most probable forms for use in further molecular modeling studies. Many medicinal chemicals can exchange protons with their environment, resulting in various ionization and tautomeric states, collectively known as protonation states. The protonation state of a drug can affect its solubility and membrane permeability. In modeling, the protonation state of a ligand will also affect which conformations are predicted for the molecule, as well as predictions for binding modes and ligand affinities based upon protein-ligand interactions. Despite the importance of the protonation state, many databases of candidate molecules used in drug development do not store reliable information on the most probable protonation states. Epik is sufficiently rapid and accurate to process large databases of drug-like molecules to provide this information. Several new technologies are employed. Extensions to the well-established Hammett and Taft approaches are used for pK(a) prediction, namely, mesomer standardization, charge cancellation, and charge spreading to make the predicted results reflect the nature of the molecule itself rather just for the particular Lewis structure used on input. In addition, a new iterative technology for generating, ranking and culling the generated protonation states is employed.

We have cloned the Saccharomyces cerevisiae C-4 sterol methyl oxidase ERG25 gene. The sterol methyl oxidase performs the first of three enzymic steps required to remove the two C-4 methyl groups leading to cholesterol (animal), ergosterol (fungal), and stigmasterol (plant) biosynthesis. An ergosterol auxotroph, erg25, which fails to demethylate and concomitantly accumulates 4,4-dimethylzymosterol, was isolated after mutagenesis. A complementing clone consisting of a 1.35-kb Dra I fragment encoded a 309-amino acid polypeptide (calculated molecular mass, 36.48 kDa). The amino acid sequence shows a C-terminal endoplasmic reticulum retrieval signal KKXX and three histidine-rich clusters found in eukaryotic membrane desaturases and in a bacterial alkane hydroxylase and xylene monooxygenase. The sterol profile of an ERG25 disruptant was consistent with the erg25 allele obtained by mutagenesis.In the synthesis of sterols, required components of eukaryotic membranes, an initial sterol (lanosterol in animals and fungi and cycloartenol in plants) undergoes three demethylations prior to formation of the end product sterol. The first demethylation occurs directly with lanosterol or cycloartenol and results in removal of the C-14 methyl group. The fungal demethylation is performed by the product of the ERG11 gene (Fig.

The binding site on the lymphocyte function-associated antigen-1 (LFA-1) of a class of hydantoin-based antagonists of leukocyte cell adhesion has been identified. This site resides in the inserted-domain (I-domain) of the CD11a chain at a location that is distal to residues known to be required for interactions with the intercellular adhesion molecules. This finding supports the hypothesis that the molecules are antagonizing cell adhesion via an allosteric modification of LFA-1. The binding site was identified using an integrated immunochemical, chemical, and molecular modeling approach. Antibodies that map to epitopes on the I-domain were blocked from binding to the purified protein by the hydantoins, indicating that the hydantoin-binding site resides on the I-domain. Photoaffinity labeling of the I-domain followed by LC/MS and LC/MS/MS analysis of the enzymatic digest identified proline 281 as the primary amino acid residue covalently attached to the photoprobe. Distance constraints derived from this study coupled with known SAR considerations allowed for the construction of a molecular model of the I-domain/inhibitor complex. The atomic details of the protein/antagonist interaction were accurately predicted by this model, as subsequently confirmed by the X-ray crystal structure of the complex.

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The specificity of the immune response relies on processing of foreign proteins and presentation of antigenic peptides at the cell surface. Inhibition of antigen presentation, and the subsequent activation of T-cells, should, in theory, modulate the immune response. The cysteine protease Cathepsin S performs a fundamental step in antigen presentation and therefore represents an attractive target for inhibition. Herein, we report a series of potent and reversible Cathepsin S inhibitors based on dipeptide nitriles. These inhibitors show nanomolar inhibition of the target enzyme as well as cellular potency in a human B cell line. The first X-ray crystal structure of a reversible inhibitor cocrystallized with Cathepsin S is also reported.