CholMine: Determinants and Prediction of Cholesterol and Cholate Binding Across Nonhomologous Protein Structures.

Identifying physiological ligands is necessary for annotating new protein structures, yet this presents a significant challenge to biologists and pharmaceutical chemists. Here we develop a predictor of cholesterol and cholate binding that works across diverse protein families, extending beyond sequence motif-based prediction. This approach combines SimSite3D site comparison with the detection of conserved interactions in cholesterol/cholate bound crystal structures to define three-dimensional interaction motifs. The resulting predictor identifies cholesterol sites with an ∼82% unbiased true positive rate in both membrane and soluble proteins, with a very low false positive rate relative to other predictors. The CholMine Web server can analyze users' structures, detect those likely to bind cholesterol/cholate, and predict the binding mode and key interactions. By deciphering the determinants of binding for these important steroids, CholMine may also aid in the design of selective inhibitors and detergents for targets such as G protein coupled receptors and bile acid receptors.

Computational prediction and in vitro analysis of potential physiological ligands of the bile acid binding site in cytochrome c oxidase.

A conserved bile acid site has been crystallographically defined in the membrane domain of mammalian and Rhodobacter sphaeroides cytochrome c oxidase (RsCcO). Diverse amphipathic ligands were shown previously to bind to this site and affect the electron transfer equilibrium between heme a and a3 cofactors by blocking the K proton uptake path. Current studies identify physiologically relevant ligands for the bile acid site using a novel three-pronged computational approach: ROCS comparison of ligand shape and electrostatics, SimSite3D comparison of ligand binding site features, and SLIDE screening of potential ligands by docking. Identified candidate ligands include steroids, nicotinamides, flavins, nucleotides, retinoic acid, and thyroid hormones, which are predicted to make key protein contacts with the residues involved in bile acid binding. In vitro oxygen consumption and ligand competition assays on RsCcO wildtype and its Glu101Ala mutant support regulatory activity and specificity of some of these ligands. An ATP analog and GDP inhibit RsCcO under low substrate conditions, while fusidic acid, cholesteryl hemisuccinate, retinoic acid, and T3 thyroid hormone are more potent inhibitors under both high and low substrate conditions. The sigmoidal kinetics of RsCcO inhibition in the presence of certain nucleotides is reminiscent of previously reported ATP inhibition of mammalian CcO, suggesting regulation involving the conserved core subunits of both mammalian and bacterial oxidases. Ligand binding to the bile acid site is noncompetitive with respect to cytochrome c and appears to arrest CcO in a semioxidized state with some resemblance to the "resting" state of the enzyme.

Searching for likeness in a database of macromolecular complexes.

A software tool and workflow based on distance geometry is presented that can be used to search for local similarity in substructures in a comprehensive database of experimentally derived macromolecular structure. The method does not rely on fold annotation, specific secondary structure assignments, or sequence homology and may be used to locate compound substructures of multiple segments spanning different macromolecules that share a queried backbone geometry. This generalized substructure searching capability is intended to allow users to play an active part in exploring the role specific substructures play in larger protein domains, quaternary assemblies of proteins, and macromolecular complexes of proteins and polynucleotides. The user may select any portion or portions of an existing structure or complex to serve as a template for searching, and other structures that share the same structural features are identified, retrieved and overlaid to emphasize substructural likeness. Matching structures may be compared using a variety of integrated tools including molecular graphics for structure visualization and matching substructure sequence logos. A number of examples are provided that illustrate how generalized substructure searching may be used to understand both the similarity, and individuality of specific macromolecular structures. Web-based access to our substructure searching services is freely available at https://drugsite.msi.umn.edu.

Conserved core substructures in the overlay of protein-ligand complexes.

The method of conserved core substructure matching (CSM) for the overlay of protein-ligand complexes is described. The method relies upon distance geometry to align structurally similar substructures without regard to sequence similarity onto substructures from a reference protein empirically selected to include key determinants of binding site location and geometry. The error in ligand position is reduced in reoriented ensembles generated with CSM when compared to other overlay methods. Since CSM can only succeed when the selected core substructure is geometrically conserved, misalignments only rarely occur. The method may be applied to reliably overlay large numbers of protein-ligand complexes in a way that optimizes ligand position at a specific binding site or subsite or to align structures from large and diverse protein families where the conserved binding site is localized to only a small portion of either protein. Core substructures may be complex and must be chosen with care. We have created a database of empirically selected core substructures to demonstrate the utility of CSM alignment of ligand binding sites in important drug targets. A Web-based interface can be used to apply CSM to align large collections of protein-ligand complexes for use in drug design using these substructures or to evaluate the use of alternative core substructures that may then be shared with the larger user community. Examples show the benefit of CSM in the practice of structure-based drug design.

Scoring ligand similarity in structure-based virtual screening.

Scoring to identify high-affinity compounds remains a challenge in virtual screening. On one hand, protein-ligand scoring focuses on weighting favorable and unfavorable interactions between the two molecules. Ligand-based scoring, on the other hand, focuses on how well the shape and chemistry of each ligand candidate overlay on a three-dimensional reference ligand. Our hypothesis is that a hybrid approach, using ligand-based scoring to rank dockings selected by protein-ligand scoring, can ensure that high-ranking molecules mimic the shape and chemistry of a known ligand while also complementing the binding site. Results from applying this approach to screen nearly 70 000 National Cancer Institute (NCI) compounds for thrombin inhibitors tend to support the hypothesis. EON ligand-based ranking of docked molecules yielded the majority (4/5) of newly discovered, low to mid-micromolar inhibitors from a panel of 27 assayed compounds, whereas ranking docked compounds by protein-ligand scoring alone resulted in one new inhibitor. Since the results depend on the choice of scoring function, an analysis of properties was performed on the top-scoring docked compounds according to five different protein-ligand scoring functions, plus EON scoring using three different reference compounds. The results indicate that the choice of scoring function, even among scoring functions measuring the same types of interactions, can have an unexpectedly large effect on which compounds are chosen from screening. Furthermore, there was almost no overlap between the top-scoring compounds from protein-ligand versus ligand-based scoring, indicating the two approaches provide complementary information. Matchprint analysis, a new addition to the SLIDE (Screening Ligands by Induced-fit Docking, Efficiently) screening toolset, facilitated comparison of docked molecules' interactions with those of known inhibitors. The majority of interactions conserved among top-scoring compounds for a given scoring function, and from the different scoring functions, proved to be conserved interactions in known inhibitors. This was particularly true in the S1 pocket, which was occupied by all the docked compounds.