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In rational drug design approaches two major properties of a drug candidate are exploited during the optimization cycles: affinity and selectivity. Computational approaches play an increasingly important role for the analysis and prediction of selectivity profiles. As most of the successfully administered small molecule drugs bind in depressions on the surface of proteins, physicochemical properties of the pocket-exposed aminoacids play a central role in ligand recognition during the binding event. Cavbase is a methodology to describe binding sites in terms of the exposed physicochemical properties and to compare them independent of the sequence and fold homology. Classification of proteins by means of their binding site properties is a promising approach to achieve relevant information for selectivity modeling. For this purpose, a novel workflow has been developed to explore the important parameters of a clustering procedure, which will allow an accurate classification of proteins. For a given data set a similarity matrix can be generated and subsequently utilized as input for a clustering procedure. It has been successfully applied on two diverse and challenging data sets. The predicted number of clusters, suggested by the clustering methods, and the subsequent clustering of proteins are in agreement with considered expert classifications. In case of the human proteases data set, the binding site-based classification leads to significant groups of proteins independent from sequence information. As a consequence, the cross-reactivity between calpain-1 and cysteine cathepsins on the structural level could be detected, which so far has only been described for the ligand data. In a benchmark study using ligand topology, binding site, and sequence information of eleven serine proteases the emerged clusters indicate a pronounced correlation between the cavity and ligand data. These results emphasize the importance of the binding site information which should be considered for ligand design during lead optimization cycles.
The increasing number of resistances to currently applied antimalarial and antibacterial drugs give rise to an urgent need for the development of new and affordable antiinfectives. A promising candidate should exhibit a mode of action differing from the available drugs for which pronounced resistance has been described.
For the Plasmodium parasites, the pathogen of malaria, the key enzyme of the type II fatty acid biosynthesis, enoyl ACP reductase (ENR), has been suggested as a target. We performed a virtual screening for novel scaffolds of Plasmodium falciparum ENR using an in-house fragment-like virtual library and selected eight promising hits for synthesis and subsequent biological evaluation as multistage inhibitors by our project partners. A salicylamide derivative inhibited erythrocytic parasite growth in a cell-based assay and was considered for further optimization. A comprehensive analysis of the structure-activity relationships and the docking results of a combinatorial library of salicylamides resulted in two highly active structures. Both compounds comprise low cell-toxicity and display at one-digit micromolar concentrations potent inhibition of the parasitic growth in erythrocytic stage as well as superior inhibition profile compared to the gold-standard primaquine in pre-erythrocytic stages.
Biosynthesis of tetrahydrofolate is an essential pathway in almost all living organisms. Pyruvoyltetrahydropterin synthase of Plasmodiun falciparum (PfPTPS) has been found to fill the gap in the folate biosynthetic pathway in Plasmodium parasites, since dihydroneopterin aldolase could not be identified in the genome. Integration of PfPTPS in the folate metabolism qualifies the protein for inhibitor design, as antifolates are well established and effective agents for prophylaxis and treatment of malaria. A focused library of compounds comprising zinc binding groups has been created and docked into the binding site of the protein. Nine virtual screening hits have been selected for synthesis and will be subjected further biological testing by our project partners.
Many pathogenic organisms rely on the synthesis of isoprenoids via the non-mevalonate pathway (DXP/MEP). Inhibition of this pathway is a promising strategy for the development of potent antiinfective agents, as it has been shown for the IspC inhibitor fosmidomycin. IspD catalyzes the third reaction step in the DXP/MEP pathway and has been selected for our study as model protein to elucidate the structural determinants for structure-based drug design. Virtual screening of the lead-like subset retrieved from the ZINC database resulted in the selection of seven promising hits. Six molecules were purchased and subsequently tested in an experimental enzyme binding assay. Two compounds showed weak and one compound moderate binding affinity.