Additional file 1: Figure S1. of UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data

1D-jury algorithm for geometric consensus-based model ranking with contact map profiles. Three models (rows) of a hypothetical protein consisting of just 4 amino acid residues are considered, with the upper triangle of the inter-residue contact map (i,j) arranged as a linear profile. Black squares indicate contacts, while yellow squares indicate pairs of residues that are not in contact. The calculation of the score for the best scoring M2 model that corresponds to the consensus state at 5 (out of 6) profile positions proceeds red arrows. Note that a vector of state counts in each column of the profile can be precomputed in linear time, allowing one to account for all pairwise similarities without the need for a loop over pairs of models. Figure S2. Assessment of protein model selection on TASSER benchmark using uQlust: Hash (K,F) with different choices of the number of clusters K, and fraction of data included F. Low (averaged over all TASSER targets) RMSD of the top ranking model with respect to the best model available indicates better results. Figure S3. Comparison between full (RMSD-based average linkage) and uQlust:Tree (approximate) hierarchical clustering of coarse-grained structures obtained using CABS-flex server (Jamroz et al., 2013). Three initial conformations of troponin C are used to generate 3 distinct clusters (each containing 3,000 models, and marked by red, green and blue bars, respectively). Figure S4. Hierarchical clustering of ribosomal RNAs (blue – 16S, red – 23S, green - 5S) using the fragment-based RNA-FragBag profile, uQlust:Tree in conjunction with profile hashing (using the default number of microclusters) and cosine distance. Table S1. Structural profiles implemented in uQlust. For each profile, its type (as defined by the macromolecule it applies to, i.e., either protein or RNA), the source of state assignment, the number of states and the size (length) of the profile are reported. (PDF 260 kb

Inhibition of Histo-blood Group Antigen Binding as a Novel Strategy to Block Norovirus Infections

<div><p>Noroviruses (NoVs) are the most important viral pathogens that cause epidemic acute gastroenteritis. NoVs recognize human histo-blood group antigens (HBGAs) as receptors or attachment factors. The elucidation of crystal structures of the HBGA-binding interfaces of a number of human NoVs representing different HBGA binding patterns opens a new strategy for the development of antiviral compounds against NoVs through rational drug design and computer-aided virtual screening methods. In this study, docking simulations and virtual screening were used to identify hit compounds targeting the A and B antigens binding sites on the surface of the capsid P protein of a GII.4 NoV (VA387). Following validation by re-docking of the A and B ligands, these structural models and AutoDock suite of programs were used to screen a large drug-like compound library (derived from ZINC library) for inhibitors blocking GII.4 binding to HBGAs. After screening >2 million compounds using multistage protocol, 160 hit compounds with best predicted binding affinities and representing a number of distinct chemical classes have been selected for subsequent experimental validation. Twenty of the 160 compounds were found to be able to block the VA387 P dimers binding to the A and/or B HBGAs at an IC₅₀<40.0 µM, with top 5 compounds blocking the HBGA binding at an IC₅₀<10.0 µM in both oligosaccharide- and saliva-based blocking assays. Interestingly, 4 of the top-5 compounds shared the basic structure of cyclopenta [a] dimethyl phenanthren, indicating a promising structural template for further improvement by rational design.</p></div

Parameters used for docking simulation.

<p>Parameters used for docking simulation.</p

Structures of the top 20 hit compounds against binding of VA387 to the A and B saliva.

<p>Structures of the top 20 hit compounds against binding of VA387 to the A and B saliva.</p

Distribution of the lowest Ki values of the top 255 compounds docked at the HBGA binding sites of the VA387 P dimer.

<p>Distribution of the lowest Ki values of the top 255 compounds docked at the HBGA binding sites of the VA387 P dimer.</p

Predicted docking poses for the A trisaccharides docked to the VA387 P dimer clusters at the proved HBGA binding site.

<p>The majority of the predicted poses (each represented by a magenta ball) docked to the experimentally resolved HBGA binding site that was formed by Ser343, Arg345, His347, Asp374, Gln376, Ser441 and Gly442 (circled by a yellow dashed line). Some of the poses docked to a nearby site that was previously suggested as an alternative binding site for HBGA (Tan et al., 2003). The structure of the P dimer of VA387 (2OBS) is shown using ribbon model, each monomer in green and blue, respectively. The amino acids that constitute the experimentally mapped HBGA binding site were shown using stick model and circled by a yellow dashed line, while amino acids forming the nearby site were also shown in stick model. The squared region containing the HBGA binding site is enlarged in the up-left panel.</p

The basic features of the 20 most inhibitory lead-like compounds.

a<p>determined by docking;</p>b<p>determined by blocking assays; the data were indicated by mean ± standard deviation.</p

Parameters used in the primary and secondary screening of the VHTS.

<p>Parameters used in the primary and secondary screening of the VHTS.</p

The crystal structures of the HBGA-binding interfaces of Norwalk virus (GI-1) and VA387 (GII-4).

<p>The surface models of the P dimers (top views) with indications of the HBGA-binding interfaces (colored regions) are shown in (A) and (B) with one monomer being shown in darker gray than another. Enlargements of the HBGA-binding interfaces are shown in (C) and (D) correspondingly with labels of individual amino acids, in which the prime symbol indicates a residue of another protomer. The three major components of the binding interfaces are colored in green (site I), red (site II), and orange (site III), respectively, while the trisaccharides binding to the interface are in yellow in (A) and (B) or in variable colors (C-cyans, O-red, and N-blue) in (C) and (D). The amino acids around the interface that affect the binding specificity are in light blue. (E) and (F) are schematic diagrams of hydrogen bonding network (dash lines) between the amino acids of the P dimers of Norwalk virus (E), or VA387 (F) and the A- or B- type trisaccharides. The water-bridged hydrogen bonds are indicated by W. (A) to (D) were prepared by software PyMOL version 1.0 (Delano Scientific), while (E) and (F) by software ChemDraw Pro version 11.0 (Adept Scientific). (E) is adapted from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0005058#pone.0005058-Bu1" target="_blank">[13]</a> with permission. The original data were published in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0005058#pone.0005058-Bu1" target="_blank">[13]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0005058#pone.0005058-Cao1" target="_blank">[14]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0005058#pone.0005058-Choi1" target="_blank">[15]</a>.</p

Primers used for cloning of P domain and site-directed mutagenesis to generate single mutation in the HBGA-binding interface and around regions.

<p>Primers used for cloning of P domain and site-directed mutagenesis to generate single mutation in the HBGA-binding interface and around regions.</p