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Motivation: An effective docking algorithm for antibody-protein antigen complex prediction is an important first step toward design of biologics and vaccines. We have recently developed a new class of knowledge-based interaction potentials called Decoys as the Reference State (DARS) and incorporated DARS into the docking program PIPER based on the fast Fourier transform correlation approach. Although PIPER was the best performer in the latest rounds of the CAPRI protein docking experiment, it is much less accurate for docking antibody-protein antigen pairs than other types of complexes, in spite of incorporating sequence-based information on the location of the paratope. Analysis of antibody-protein antigen complexes has revealed an inherent asymmetry within these interfaces. Specifically, phenylalanine, tryptophan and tyrosine residues highly populate the paratope of the antibody but not the epitope of the antigen., Results: Since this asymmetry cannot be adequately modeled using a symmetric pairwise potential, we have removed the usual assumption of symmetry. Interaction statistics were extracted from antibody-protein complexes under the assumption that a particular atom on the antibody is different from the same atom on the antigen protein. The use of the new potential significantly improves the performance of docking for antibody-protein antigen complexes, even without any sequence information on the location of the paratope. We note that the asymmetric potential captures the effects of the multi-body interactions inherent to the complex environment in the antibody-protein antigen interface., Availability: The method is implemented in the ClusPro protein docking server, available at http://cluspro.bu.edu.

Motivation: N-linked glycosylation occurs predominantly at the N-X-T/S motif, where X is any amino acid except proline. Not all N-X-T/S sequons are glycosylated, and a number of web servers for predicting N-linked glycan occupancy using sequence and/or residue pattern information have been developed. None of the currently available servers, however, utilizes protein structural information for the prediction of N-glycan occupancy., Results: Here, we describe a novel classifier algorithm, NGlycPred, for the prediction of glycan occupancy at the N-X-T/S sequons. The algorithm utilizes both structural as well as residue pattern information and was trained on a set of glycosylated protein structures using the Random Forest algorithm. The best predictor achieved a balanced accuracy of 0.687 under 10-fold cross-validation on a curated dataset of 479 N-X-T/S sequons and outperformed sequence-based predictors when evaluated on the same dataset. The incorporation of structural information, including local contact order, surface accessibility/composition and secondary structure thus improves the prediction accuracy of glycan occupancy at the N-X-T/S consensus sequon., Availability and Implementation: NGlycPred is freely available to non-commercial users as a web-based server at http://exon.niaid.nih.gov/nglycpred/.

Antibody PG9 is a prototypical member of a class of V1/V2-directed antibodies that effectively neutralizes diverse strains of HIV-1. We analyzed strain-specific resistance to PG9 using sequence and structural information. For multiply resistant strains, mutations in a short segment of V1/V2 resulted in gain of sensitivity to PG9 and related V1/V2 neutralizing antibodies, suggesting both a common mechanism of HIV-1 resistance to and a common mode of recognition by this class of antibodies.

Human noroviruses bind with their capsid-protruding domains to histo-blood-group antigens (HBGAs), an interaction thought to direct their entry into cells. Although human noroviruses are the major cause of gastroenteritis outbreaks, development of antivirals has been lacking, mainly because human noroviruses cannot be cultivated. Here we use X-ray crystallography and saturation transfer difference nuclear magnetic resonance (STD NMR) to analyze the interaction of citrate with genogroup II (GII) noroviruses. Crystals of citrate in complex with the protruding domain from norovirus GII.10 Vietnam026 diffracted to 1.4 Å and showed a single citrate bound at the site of HBGA interaction. The citrate interaction was coordinated with a set of capsid interactions almost identical to that involved in recognizing the terminal HBGA fucose, the saccharide which forms the primary conserved interaction between HBGAs and GII noroviruses. Citrate and a water molecule formed a ring-like structure that mimicked the pyranoside ring of fucose. STD NMR showed the protruding domain to have weak affinity for citrate (460 μM). This affinity, however, was similar to the affinities of the protruding domain for fucose (460 μM) and H type 2 trisaccharide (390 μM), an HBGA shown previously to be specifically recognized by human noroviruses. Importantly, competition STD NMR showed that citrate could compete with HBGA for norovirus binding. Together, the results suggest that citrate and other glycomimetics have the potential to block human noroviruses from binding to HBGAs.

Variable regions 1 and 2 (V1/V2) of human immunodeficiency virus-1 (HIV-1) gp120 envelope glycoprotein are critical for viral evasion of antibody neutralization, and are themselves protected by extraordinary sequence diversity and N-linked glycosylation. Human antibodies such as PG9 nonetheless engage V1/V2 and neutralize 80% of HIV-1 isolates. Here we report the structure of V1/V2 in complex with PG9. V1/V2 forms a four-stranded β-sheet domain, in which sequence diversity and glycosylation are largely segregated to strand-connecting loops. PG9 recognition involves electrostatic, sequence-independent and glycan interactions: the latter account for over half the interactive surface but are of sufficiently weak affinity to avoid autoreactivity. The structures of V1/V2-directed antibodies CH04 and PGT145 indicate that they share a common mode of glycan penetration by extended anionic loops. In addition to structurally defining V1/V2, the results thus identify a paradigm of antibody recognition for highly glycosylated antigens, which-with PG9-involves a site of vulnerability comprising just two glycans and a strand.

Classically, the estrogen signaling system has two core components: cytochrome P450 aromatase (CYP19), the enzyme complex that catalyzes the rate limiting step in estrogen biosynthesis; and estrogen receptors (ERs), ligand activated transcription factors that interact with the regulatory region of target genes to mediate the biological effects of estrogen. While the importance of estrogens for regulation of reproduction, development and physiology has been well-documented in gnathostome vertebrates, the evolutionary origins of estrogen as a hormone are still unclear. As invertebrates within the phylum Chordata, cephalochordates (e.g., the amphioxus of the genus Branchiostoma) are among the closest invertebrate relatives of the vertebrates and can provide critical insight into the evolution of vertebrate-specific molecules and pathways. To address this question, this paper briefly reviews relevant earlier studies that help to illuminate the history of the aromatase and ER genes, with a particular emphasis on insights from amphioxus and other invertebrates. We then present new analyses of amphioxus aromatase and ER sequence and function, including an in silico model of the amphioxus aromatase protein, and CYP19 gene analysis. CYP19 shares a conserved gene structure with vertebrates (9 coding exons) and moderate sequence conservation (40% amino acid identity with human CYP19). Modeling of the amphioxus aromatase substrate binding site and simulated docking of androstenedione in comparison to the human aromatase shows that the substrate binding site is conserved and predicts that androstenedione could be a substrate for amphioxus CYP19. The amphioxus ER is structurally similar to vertebrate ERs, but differs in sequence and key residues of the ligand binding domain. Consistent with results from other laboratories, amphioxus ER did not bind radiolabeled estradiol, nor did it modulate gene expression on an estrogen-responsive element (ERE) in the presence of estradiol, 4-hydroxytamoxifen, diethylstilbestrol, bisphenol A or genistein. Interestingly, it has been shown that a related gene, the amphioxus "steroid receptor" (SR), can be activated by estrogens and that amphioxus ER can repress this activation. CYP19, ER and SR are all primarily expressed in gonadal tissue, suggesting an ancient paracrine/autocrine signaling role, but it is not yet known how their expression is regulated and, if estrogen is actually synthesized in amphioxus, whether it has a role in mediating any biological effects. Functional studies are clearly needed to link emerging bioinformatics and in vitro molecular biology results with organismal physiology to develop an understanding of the evolution of estrogen signaling. This article is part of a Special Issue entitled 'Marine organisms'., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Despite the growing number of examples of small-molecule inhibitors that disrupt protein-protein interactions (PPIs), the origin of druggability of such targets is poorly understood. To identify druggable sites in protein-protein interfaces we combine computational solvent mapping, which explores the protein surface using a variety of small "probe" molecules, with a conformer generator to account for side-chain flexibility. Applications to unliganded structures of 15 PPI target proteins show that the druggable sites comprise a cluster of binding hot spots, distinguishable from other regions of the protein due to their concave topology combined with a pattern of hydrophobic and polar functionality. This combination of properties confers on the hot spots a tendency to bind organic species possessing some polar groups decorating largely hydrophobic scaffolds. Thus, druggable sites at PPI are not simply sites that are complementary to particular organic functionality, but rather possess a general tendency to bind organic compounds with a variety of structures, including key side chains of the partner protein. Results also highlight the importance of conformational adaptivity at the binding site to allow the hot spots to expand to accommodate a ligand of drug-like dimensions. The critical components of this adaptivity are largely local, involving primarily low energy side-chain motions within 6 Å of a hot spot. The structural and physicochemical signature of druggable sites at PPI interfaces is sufficiently robust to be detectable from the structure of the unliganded protein, even when substantial conformational adaptation is required for optimal ligand binding.

The aim of this article is to analyze conformational changes by comparing 10 different structures of Pseudomonas aeruginosa phosphomannomutase/phosphoglucomutase (PMM/PGM), a four-domain enzyme in which both substrate binding and catalysis require substantial movement of the C-terminal domain. We focus on changes in interdomain and active site crevices using a method called computational solvent mapping rather than superimposing the structures. The method places molecular probes (i.e., small organic molecules containing various functional groups) around the protein to find hot spots. One of the most important hot spots is in the active site, consistent with the ability of the enzyme to bind both glucose and mannose phosphosugar substrates. The protein has eight additional hot spots at domain-domain interfaces and hinge regions. The locations and nature of six of these hot spots vary between the open, half-open, and closed conformers of the enzyme, in good agreement with the ligand-induced conformational changes. In the closed structures the number of probe clusters at the hinge region significantly depends on the position of the phosphorylated oxygen in the substrate (e.g., glucose 1-phosphate versus glucose 6-phosphate), but the protein remains almost unchanged in terms of the overall RMSD, indicating that computational solvent mapping is a more sensitive approach to detect changes in binding sites and interdomain crevices. Focusing on multidomain proteins we show that the subresolution conformational differences revealed by the mapping are in fact significant, and present a general statistical method of analysis to determine the significance of rigid body domain movements in X-ray structures., (Copyright © 2010 The Protein Society.)

Structures of the influenza A virus M2 proton channel in the open conformation have been determined by X-ray crystallography, and in the closed conformation by NMR. Whereas the X-ray structure shows a single inhibitor molecule in the middle of the channel, four inhibitor molecules bind the channel's outer surface in the NMR structure. In both structures, the strongest hot spots (i.e., regions that contribute substantially to the free energy of binding any potential ligand) lie inside the pore, and other hot spots are found at exterior locations. By considering all available models, we propose the primary drug binding site is inside the pore, but that exterior binding occurs under appropriate conditions., (Copyright (c) 2010 Elsevier Ltd. All rights reserved.)

Structures of truncated versions of the influenza A virus M2 proton channel have been determined recently by x-ray crystallography in the open conformation of the channel, and by NMR in the closed state. The structures differ in the position of the bound inhibitors. The x-ray structure shows a single amantadine molecule in the middle of the channel, whereas in the NMR structure four drug molecules bind at the channel's outer surface. To study this controversy we applied computational solvent mapping, a technique developed for the identification of the most druggable binding hot spots of proteins. The method moves molecular probes--small organic molecules containing various functional groups--around the protein surface, finds favorable positions using empirical free energy functions, clusters the conformations, and ranks the clusters on the basis of the average free energy. The results of the mapping show that in both structures the primary hot spot is an internal cavity overlapping the amantadine binding site seen in the x-ray structure. However, both structures also have weaker hot spots at the exterior locations that bind rimantadine in the NMR structure, although these sites are partially due to the favorable interactions with the interfacial region of the lipid bilayer. As confirmed by docking calculations, the open channel binds amantadine at the more favorable internal site, in good agreement with the x-ray structure. In contrast, the NMR structure is based on a peptide/micelle construct that is able to accommodate the small molecular probes used for the mapping, but has a too narrow pore for the rimantadine to access the internal hot spot, and hence the drug can bind only at the exterior sites.

The identification of hot spots, i.e., binding regions that contribute substantially to the free energy of ligand binding, is a critical step for structure-based drug design. Here we present the application of two fragment-based methods to the detection of hot spots for DJ-1 and glucocerebrosidase (GCase), targets for the development of therapeutics for Parkinson's and Gaucher's diseases, respectively. While the structures of these two proteins are known, binding information is lacking. In this study we employ the experimental multiple solvent crystal structures (MSCS) method and computational fragment mapping (FTMap) to identify regions suitable for the development of pharmacological chaperones for DJ-1 and GCase. Comparison of data derived via MSCS and FTMap also shows that FTMap, a computational method for the identification of fragment binding hot spots, is an accurate and robust alternative to the performance of expensive and difficult crystallographic experiments.

Motivation: The binding sites of proteins generally contain smaller regions that provide major contributions to the binding free energy and hence are the prime targets in drug design. Screening libraries of fragment-sized compounds by NMR or X-ray crystallography demonstrates that such 'hot spot' regions bind a large variety of small organic molecules, and that a relatively high 'hit rate' is predictive of target sites that are likely to bind drug-like ligands with high affinity. Our goal is to determine the 'hot spots' computationally rather than experimentally., Results: We have developed the FTMAP algorithm that performs global search of the entire protein surface for regions that bind a number of small organic probe molecules. The search is based on the extremely efficient fast Fourier transform (FFT) correlation approach which can sample billions of probe positions on dense translational and rotational grids, but can use only sums of correlation functions for scoring and hence is generally restricted to very simple energy expressions. The novelty of FTMAP is that we were able to incorporate and represent on grids a detailed energy expression, resulting in a very accurate identification of low-energy probe clusters. Overlapping clusters of different probes are defined as consensus sites (CSs). We show that the largest CS is generally located at the most important subsite of the protein binding site, and the nearby smaller CSs identify other important subsites. Mapping results are presented for elastase whose structure has been solved in aqueous solutions of eight organic solvents, and we show that FTMAP provides very similar information. The second application is to renin, a long-standing pharmaceutical target for the treatment of hypertension, and we show that the major CSs trace out the shape of the first approved renin inhibitor, aliskiren., Availability: FTMAP is available as a server at http://ftmap.bu.edu/.

Decoys As the Reference State (DARS) is a simple and natural approach to the construction of structure-based intermolecular potentials. The idea is generating a large set of docked conformations with good shape complementarity but without accounting for atom types, and using the frequency of interactions extracted from these decoys as the reference state. In principle, the resulting potential is ideal for finding near-native conformations among structures obtained by docking, and can be combined with other energy terms to be used directly in docking calculations. We investigated the performance of various DARS versions for docking enzyme-inhibitor, antigen-antibody, and other type of complexes. For enzyme-inhibitor pairs, DARS provides both excellent discrimination and docking results, even with very small decoy sets. For antigen-antibody complexes, DARS is slightly better than a number of interaction potentials tested, but results are worse than for enzyme-inhibitor complexes. With a few exceptions, the DARS docking results are also good for the other complexes, despite poor discrimination, and we show that the latter is not a correct test for docking accuracy. The analysis of interactions in antigen-antibody pairs reveals that, in constructing pairwise potentials for such complexes, one should account for the asymmetry of hydrophobic patches on the two sides of the interface. Similar asymmetry does occur in the few other complexes with poor DARS docking results.