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Judging if a protein is able to bind orally available molecules with high affinity, i.e. if a protein is druggable, is an important step in target assessment. In order to derive a structure-based method to predict protein druggability, a comprehensive, nonredundant data set containing crystal structures of 71 druggable and 44 less druggable proteins was compiled by literature search and data mining. This data set was subsequently used to train a structure-based druggability predictor (DrugPred) using partial least-squares projection to latent structures discriminant analysis (PLS-DA). DrugPred performed well in discriminating druggable from less druggable binding sites for both internal and external predictions. The method is robust against conformational changes in the binding site and outperforms previously published methods. The superior performance of DrugPred is likely due to the size and composition of the training set which, in contrast to most previously developed methods, only contains cavities that have evolved to bind a natural ligand.

The scope of the current work is to investigate whether structurally similar ligands bind in a similar fashion by exhaustively analyzing experimental data from the protein database (PDB). The complete PDB was searched for pairs of structurally similar ligands binding to the same biological target. The binding sites of the pairs of proteins complexing structurally similar ligands were found to differ in 83% of the cases. The most recurrent structural change among the pairs involves different water molecule architecture. Side-chain movements are observed in half of the pairs, whereas backbone movements rarely occurred. However, two structurally similar ligands generally confirm a high degree of structural conservation. That is, a majority of the ligand pairs occupy the same region in the binding sites, providing support for the use of shape matching in the drug design process. We allow ourselves to draw general conclusions because our data set consists of ligands with drug-like physicochemical properties complexed to a broad spectrum of different protein classes.

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A new assessment criterion for docking poses is proposed in which experimental electron density is taken into account when evaluating the ability of docking programs to reproduce experimentally observed binding modes. Three docking programs (Gold, Glide, and Fred) were used to generate poses for a set of 88 protein-ligand complexes for which the crystal structure is known. The new criterion is based on the real space R-factor (RSR), which measures how well a group of atoms-in our case the ligand-fits the experimental electron density by comparing that density to the expected density, calculated from the model (i.e., the predicted ligand pose). The RSR-based measure is compared to the traditional criterion, the root-mean-square distance (RMSD) between the docking pose and the binding configuration in the crystallographic model. The results highlight several shortcomings of the RMSD criterion that do not affect the RSR-based measure. Examples illustrate that the RSR-derived approach allows a more meaningful a posteriori assessment of docking methods and results. Practical implications for docking evaluations and for methodological development work in this field are discussed.

In this contribution, the classification of protein binding sites using the physicochemical properties exposed to their pockets is presented. We recently introduced Cavbase, a method for describing and comparing protein binding pockets on the basis of the geometrical and physicochemical properties of their active sites. Here, we present algorithmic and methodological enhancements in the Cavbase property description and in the cavity comparison step. We give examples of the Cavbase similarity analysis detecting pronounced similarities in the binding sites of proteins unrelated in sequence. A similarity search using SARS M(pro) protease subpockets as queries retrieved ligands and ligand fragments accommodated in a physicochemical environment similar to that of the query. This allowed the characterization of the protease recognition pockets and the identification of molecular building blocks that can be incorporated into novel antiviral compounds. A cluster analysis procedure for the functional classification of binding pockets was implemented and calibrated using a diverse set of enzyme binding sites. Two relevant protein families, the alpha-carbonic anhydrases and the protein kinases, are used to demonstrate the scope of our cluster approach. We propose a relevant classification of both protein families, on the basis of the binding motifs in their active sites. The classification provides a new perspective on functional properties across a protein family and is able to highlight features important for potency and selectivity. Furthermore, this information can be used to identify possible cross-reactivities among proteins due to similarities in their binding sites.

The epitaxial growth of graphene by chemical vapor deposition of ethylene on a Ru(0001) surface was monitored by high-temperature scanning tunneling microscopy. The in situ data show that at low pressures and high temperatures the metal surface facets into large terraces, leading to much better ordered graphene layers than resulting from the known growth mode. Density functional theory calculations show that the single terrace growth mode can be understood from the energetics of the graphene-metal interaction.

It is well established that certain chemotherapeutic agents have potent antiangiogenic properties which may be part of their antitumor activity. Temozolomide (TMZ) is a lipophilic methylating agent used in the therapy of malignant melanoma and other tumors. We sought to determine whether TMZ is capable of inhibiting angiogenesis or influencing endothelial function. We used the in vivo chorioallantoic membrane (CAM) assay, and HUVEC-based in vitro Matrigel, adhesion and proliferation assays to determine the antiangiogenic effects of different doses of TMZ. In the CAM assay, angiogenesis was significantly inhibited by 5 microM TMZ, a concentration also found to be effective in interfering with in vitro angiogenesis as measured by the Matrigel assay. For the inhibition of basic fibroblast growth factor (bFGF)-, vascular endothelial growth factor (VEGF)- or beta-phorbol 12-myristate-13-acetate (PMA)-induced endothelial cell proliferation or endothelial cell adhesion to fibronectin, TMZ concentrations of at least 25 microM were necessary, indicating that bFGF-, VEGF- or protein kinase C-mediated pathways may not primarily be involved in the observed antiangiogenic effect. Thus, we could demonstrate that TMZ inhibits angiogenesis at low, non-toxic doses that correspond to the plasma concentrations achieved by an oral application of 20 mg/m2 every 8 h. This 'metronomic' scheduling has already been used in phase I studies and has produced antitumor effects. Therefore, the antitumor activity of TMZ may, at least in part, be due to its antiangiogenic properties. The precise mechanism of its antiangiogenic action remains to be elucidated.