Csaba Hetényi

Mechanism of Blebbistatin Inhibition of Myosin II

Blebbistatin is a recently discovered small molecule inhibitor showing high affinity and selectivity toward myosin II. Here we report a detailed investigation of its mechanism of inhibition. Blebbistatin does not compete with nucleotide binding to the skeletal muscle myosin subfragment-1. The inhibitor preferentially binds to the ATPase intermediate with ADP and phosphate bound at the active site, and it slows down phosphate release. Blebbistatin interferes neither with binding of myosin to actin nor with ATP-induced actomyosin dissociation. Instead, it blocks the myosin heads in a products complex with low actin affinity. Blind docking molecular simulations indicate that the productive blebbistatin-binding site of the myosin head is within the aqueous cavity between the nucleotide pocket and the cleft of the actin-binding interface. The property that blebbistatin blocks myosin II in an actin-detached state makes the compound useful both in muscle physiology and in exploring the cellular function of cytoplasmic myosin II isoforms, whereas the stabilization of a specific myosin intermediate confers a great potential in structural studies.

Efficient docking of peptides to proteins without prior knowledge of the binding site

Reliability in docking of ligand molecules to proteins or other targets is an important challenge for molecular modeling. Applications of the docking technique include not only prediction of the binding mode of novel drugs, but also other problems like the study of protein‐protein interactions. Here we present a study on the reliability of the results obtained with the popular AutoDock program. We have performed systematical studies to test the ability of AutoDock to reproduce eight different protein/ligand complexes for which the structure was known, without prior knowledge of the binding site. More specifically, we look at factors influencing the accuracy of the final structure, such as the number of torsional degrees of freedom in the ligand. We conclude that the Autodock program package is able to select the correct complexes based on the energy without prior knowledge of the binding site. We named this application blind docking, as the docking algorithm is not able to “see” the binding site but can still find it. The success of blind docking represents an important finding in the era of structural genomics.

The autoimmune regulator PHD finger binds to non-methylated histone H3K4 to activate gene expression

Mutations in the gene autoimmune regulator (AIRE) cause autoimmune polyendocrinopathy candidiasis ectodermal dystrophy. AIRE is expressed in thymic medullary epithelial cells, where it promotes the expression of tissue‐restricted antigens. By the combined use of biochemical and biophysical methods, we show that AIRE selectively interacts with histone H3 through its first plant homeodomain (PHD) finger (AIRE–PHD1) and preferentially binds to non‐methylated H3K4 (H3K4me0). Accordingly, in vivo AIRE binds to and activates promoters containing low levels of H3K4me3 in human embryonic kidney 293 cells. We conclude that AIRE–PHD1 is an important member of a newly identified class of PHD fingers that specifically recognize H3K4me0, thus providing a new link between the status of histone modifications and the regulation of tissue‐restricted antigen expression in thymus.

Blind docking of drug-sized compounds to proteins with up to a thousand residues

Blind docking was introduced for the detection of possible binding sites and modes of peptide ligands by scanning the entire surface of protein targets. In the present study, the method is tested on a group of drug‐sized compounds and proteins with up to a thousand amino acid residues. Both proteins from complex structures and ligand‐free proteins were used as targets. Robustness, limitations and future perspectives of the method are discussed. It is concluded that blind docking can be used for unbiased mapping of the binding patterns of drug candidates.

A new easy-to-prepare homogeneous continuous electrochromatographic bed for enantiomer recognition

Completely homogeneous polyacrylamide‐based gels were used for capillary electrochromatography (CEC) of drug enantiomers. Like continuous beds (also called continuous polymer rods, silica rods, monoliths) they do not require frits to support the bed because it is covalently linked to the capillary wall. A long lifetime is an important feature of the beds. The gel matrices can be prepared in any laboratory and for specific interactions they can be derivatized with appropriate ligands. The application range is, therefore, broad. For chiral electrochromatography, negatively and positively charged polyacrylamide gels copolymerized with 2‐hydroxy‐3‐allyloxy‐propyl‐β‐cyclodextrin (allyl‐β‐CD) were prepared. The latter monomer was synthesized from β‐CD and allylglycidyl ether by a very simple one‐step procedure. Eight acidic, neutral and basic drug compounds were resolved into their enantiomers, most of them with baseline separation. Interestingly, the resolution is independent of the electroendosmotic velocity, i.e., rapid analyses will not give low resolution. Upon increasing this velocity, the plate height for the fast enantiomer did not change (or decreased slightly), whereas that for the slow enantiomer increased. Only the last term in the van Deemter equation contributed significantly to the total plate height. The composition of the gel was chosen such that the „pores”︁ became large enough to guarantee a satisfactory electroendosmotic flow (EOF). This open gel structure explains why acetone diffused as in free solution, i.e., independently of the presence of the gel matrix. This finding also indicates that the separation of small molecules in polyacrylamide gels cannot be explained by „molecular‐sieving”︁, but rather by some type of adsorption (”︁aromatic adsorption”︁?).

Drug Effect Prediction by Polypharmacology-Based Interaction Profiling

Most drugs exert their effects via multitarget interactions, as hypothesized by polypharmacology. While these multitarget interactions are responsible for the clinical effect profiles of drugs, current methods have failed to uncover the complex relationships between them. Here, we introduce an approach which is able to relate complex drug-protein interaction profiles with effect profiles. Structural data and registered effect profiles of all small-molecule drugs were collected, and interactions to a series of nontarget protein binding sites of each drug were calculated. Statistical analyses confirmed a close relationship between the studied 177 major effect categories and interaction profiles of ca. 1200 FDA-approved small-molecule drugs. On the basis of this relationship, the effect profiles of drugs were revealed in their entirety, and hitherto uncovered effects could be predicted in a systematic manner. Our results show that the prediction power is independent of the composition of the protein set used for interaction profile generation.

Ribosomal intersubunit bridge B2a is involved in factor-dependent translation initiation and translational processivity.

Intersubunit bridges are important for holding together subunits in the 70S ribosome. Moreover, a number of intersubunit bridges have a role in modulating the activity of the ribosome during translation. Ribosomal intersubunit bridge B2a is formed by the interaction between the conserved 23S rRNA helix-loop 69 (H69) and the top of the 16S rRNA helix 44. Within the 70S ribosome, bridge B2a contacts translation factors and the A-site tRNA. In addition to bridging the subunits, bridge B2a has been invoked in a number of other ribosomal functions from initiation to termination. In the present work, single-nucleotide substitutions were inserted at positions 1912 and 1919 of Escherichia coli 23S rRNA (helix 69), which are involved in important intrahelical and intersubunit tertiary interactions in bridge B2a. The resulting ribosomes had a severely reduced activity in a cell-free translation elongation assay, but displayed a nearly wild-type-level peptidyl transferase activity. In vitro reassociation efficiency decreased with all of the H69 variant 50S subunits, but was severest with the A1919C and DeltaH69 variants. The mutations strongly affected initiation-factor-dependent 70S initiation complex formation, but exhibited a minor effect on the nonenzymatic initiation process. The mutations decreased ribosomal processivity in vitro and caused a progressive depletion of 50S subunits in polysomal fractions in vivo. Mutations at position 1919 decreased the stability of a dipeptidyl-tRNA in the A-site, whereas the binding of the dipeptidyl-tRNA was rendered more stable with 1912 and DeltaH69 mutations. Our results suggest that the H69 of 23S rRNA functions as a control element during enzymatic steps of translation.

Toward prediction of functional protein pockets using blind docking and pocket search algorithms.

Location of functional binding pockets of bioactive ligands on protein molecules is essential in structural genomics and drug design projects. If the experimental determination of ligand‐protein complex structures is complicated, blind docking (BD) and pocket search (PS) calculations can help in the prediction of atomic resolution binding mode and the location of the pocket of a ligand on the entire protein surface. Whereas the number of successful predictions by these methods is increasing even for the complicated cases of exosites or allosteric binding sites, their reliability has not been fully established. For a critical assessment of reliability, we use a set of ligand‐protein complexes, which were found to be problematic in previous studies. The robustness of BD and PS methods is addressed in terms of success of the selection of truly functional pockets from among the many putative ones identified on the surfaces of ligand‐bound and ligand‐free (holo and apo) protein forms. Issues related to BD such as effect of hydration, existence of multiple pockets, and competition of subsidiary ligands are considered. Practical cases of PS are discussed, categorized and strategies are recommended for handling the different situations. PS can be used in conjunction with BD, as we find that a consensus approach combining the techniques improves predictive power.

Drug efficiency indices for improvement of molecular docking scoring functions.

A dataset of protein‐drug complexes with experimental binding energy and crystal structure were analyzed and the performance of different docking engines and scoring functions (as well as components of these) for predicting the free energy of binding and several ligand efficiency indices were compared. The aim was not to evaluate the best docking method, but to determine the effect of different efficiency indices on the experimental and predicted free energy. Some ligand efficiency indices, such as ΔG/W (Wiener index), ΔG/NoC (number of carbons), and ΔG/P (partition coefficient), improve the correlation between experimental and calculated values. This effect was shown to be valid across the different scoring functions and docking programs. It also removes the common bias of scoring functions in favor of larger ligands. For all scoring functions, the efficiency indices effectively normalize the free energy derived indices, to give values closer to experiment. Compound collection filtering can be done prior or after docking, using pharmacokinetic as well as pharmacodynamic profiles. Achieving these better correlations with experiment can improve the ability of docking scoring functions to predict active molecules in virtual screening.

Mapping of Possible Binding Sequences of Two Beta-Sheet Breaker Peptides on Beta Amyloid Peptide of Alzheimer's Disease

Aggregation of amyloid peptide (Abeta) has been identified as a major feature of the pathogenesis of Alzheimers disease. Increased risk for disease is associated with increased formation of polymerized Abeta. Inhibition of formation of toxic (aggregated) form of Abeta is one of the therapeutic possibilities. Beta sheet breaker peptides (BSBs) fulfill the requirements of an effective inhibitor. After having attached to the Abeta molecules, BSBs can prevent aggregation of Abeta to polymeric forms (aggregates). In the present study, we performed molecular modelling of complex formation between Abeta and two BSB peptides. Our aim was to find proper binding sequences for the BSB peptides on Abeta and characterize them. A dimeric model of Abeta was also used to study the interaction of BSBs with the aggregated forms of Abeta and find the sequences responsible for the polymerization process. A fast and efficient computational method: molecular docking was used for the afore-mentioned purposes.