Fragment based drug design (FBDD) starts with finding fragment-sized compounds that are highly ligand efficient and can serve as a core moiety for developing high affinity leads. Although the core-bound structure of a protein facilitates the construction of leads, effective design is far from straightforward. We show that protein mapping, a computational method developed to find binding hot spots and implemented as the FTMap server, provides information that complements the fragment screening results and can drive the evolution of core fragments into larger leads with a minimal loss or, in some cases, even a gain in ligand efficiency. The method places small molecular probes, the size of organic solvents, on a dense grid around the protein, and identifies the hot spots as consensus clusters formed by clusters of several probes. The hot spots are ranked based on the number of probe clusters, which predicts the binding propensity of the subsites and hence their importance for drug design. Accordingly, with a single exception the main hot spot identified by FTMap binds the core compound found by fragment screening. The most useful information is provided by the neighboring secondary hot spots, indicating the regions where the core can be extended to increase its affinity. To quantify this information, we calculate the density of probes from mapping, which describes the binding propensity at each point, and show that the change in the correlation between a ligand position and the probe density upon extending or repositioning the core moiety predicts the expected change in ligand efficiency.

Motivation: Binding site identification is a classical problem that is important for a range of applications, including the structure-based prediction of function, the elucidation of functional relationships among proteins, protein engineering and drug design. We describe an accurate method of binding site identification, namely FTSite. This method is based on experimental evidence that ligand binding sites also bind small organic molecules of various shapes and polarity. The FTSite algorithm does not rely on any evolutionary or statistical information, but achieves near experimental accuracy: it is capable of identifying the binding sites in over 94% of apo proteins from established test sets that have been used to evaluate many other binding site prediction methods.

Availability: FTSite is freely available as a web-based server at http://ftsite.bu.edu.

Contact: vajda@bu.edu; midas@bu.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Background

In the savannahs of East and Southern Africa, tsetse flies (Glossina spp.) transmit Trypanosoma brucei rhodesiense which causes Rhodesian sleeping sickness, the zoonotic form of human African trypanosomiasis. The flies feed mainly on wild and domestic animals and are usually repelled by humans. However, this innate aversion to humans can be undermined by environmental stresses on tsetse populations, so increasing disease risk. To monitor changes in risk, we need traps designed specifically to quantify the responsiveness of savannah tsetse to humans, but the traps currently available are designed to simulate other hosts.

Methodology/Principal Findings

In Zimbabwe, two approaches were made towards developing a man-like trap for savannah tsetse: either modifying an ox-like trap or creating new designs. Tsetse catches from a standard ox-like trap used with and without artificial ox odor were reduced by two men standing nearby, by an average of 34% for Glossina morsitans morsitans and 56% for G. pallidipes, thus giving catches more like those made by hand-nets from men. Sampling by electrocuting devices suggested that the men stopped flies arriving near the trap and discouraged trap-entering responses. Most of human repellence was olfactory, as evidenced by the reduction in catches when the trap was used with the odor of hidden men. Geranyl acetone, known to occur in human odor, and dispensed at 0.2 mg/h, was about as repellent as human odor but not as powerfully repellent as wood smoke. New traps looking and smelling like men gave catches like those from men.

Conclusion/Significance

Catches from the completely new man-like traps seem too small to give reliable indices of human repellence. Better indications would be provided by comparing the catches of an ox-like trap either with or without artificial human odor. The chemistry and practical applications of the repellence of human odor and smoke deserve further study.

Author Summary

In savannah areas of Africa the incidence of sleeping sickness is commonly low because the species of tsetse fly that spread the disease there feed mainly on wild and domestic animals, and are strongly repelled by humans. Environmental stresses can make the flies less responsive to the repellence, so threatening to increase greatly the disease risk. Man-like traps for tsetse could monitor the repellence, but the only traps available are ox-like. Hence, we tried two approaches to developing man-like traps: first, the modification of an existing ox-like trap, and second, the creation of entirely new traps that look and smell somewhat like people. The new traps caught very few tsetse, giving unreliable indices of disease risk. A better index is provided by monitoring the catches from an ox-like trap, to assess tsetse abundance, and comparing such catches with those from an ox-like trap provided with artificial human odor, to assess repellency. Geranyl acetone seems to be an important repellent in human odor, but it is not as effective as wood smoke. The chemistry and practical uses of repellents need further study.

Summary

Computational solvent mapping globally samples the surface of target proteins using molecular probes – small molecules or functional groups – to identify potentially favorable binding positions. The method is based on X-ray and NMR screening studies showing that the binding sites of proteins also bind a large variety of fragment-sized molecules. We have developed the multi-stage mapping algorithm FTMap (available as a server at http://ftmap.bu.edu/) based on the fast Fourier transform (FFT) correlation approach. Identifying regions of low free energy rather than individual low energy conformations, FTMap reproduces the available experimental mapping results. Applications to a variety of proteins show that the probes always cluster in important subsites of the binding site, and the amino acid residues that interact with many probes also bind the specific ligands of the protein. The “consensus” sites at which a number of different probes cluster are likely to be “druggable” sites, capable of binding drug-size ligands with high affinity. Due to its sensitivity to conformational changes the method can also be used for comparing the binding sites in different structures of a protein.

Formaldehyde has long been recognized as a hazardous environmental agent highly reactive with DNA. Recently, it has been realized that due to the activity of histone demethylation enzymes within the cell nucleus, formaldehyde is produced endogenously, in direct vicinity of genomic DNA. Should it lead to extensive DNA damage? We address this question with the aid of a computational mapping method, analogous to X-ray and nuclear magnetic resonance techniques for observing weakly specific interactions of small organic compounds with a macromolecule in order to establish important functional sites. We concentrate on the leading reaction of formaldehyde with free bases: hydroxymethylation of cytosine amino groups. Our results show that in B-DNA, cytosine amino groups are totally inaccessible for the formaldehyde attack. Then, we explore the effect of recently discovered transient flipping of Watson–Crick (WC) pairs into Hoogsteen (HG) pairs (HG breathing). Our results show that the HG base pair formation dramatically affects the accessibility for formaldehyde of cytosine amino nitrogens within WC base pairs adjacent to HG base pairs. The extensive literature on DNA interaction with formaldehyde is analyzed in light of the new findings. The obtained data emphasize the significance of DNA HG breathing.

Binding hot spots, protein sites with high-binding affinity, can be identified using X-ray crystallography or NMR by screening libraries of small organic molecules that tend to cluster at such regions. FTMAP, a direct computational analog of the experimental screening approaches, globally samples the surface of a target protein using small organic molecules as probes, finds favorable positions, clusters the conformations and ranks the clusters on the basis of the average energy. The regions that bind several probe clusters predict the binding hot spots, in good agreement with experimental results. Small molecules discovered by fragment-based approaches to drug design also bind at the hot spot regions. To identify such molecules and their most likely bound positions, we extend the functionality of FTMAP (http://ftmap.bu.edu/param) to accept any small molecule as an additional probe. In its updated form, FTMAP identifies the hot spots based on a standard set of probes, and for each additional probe shows representative structures of nearby low energy clusters. This approach helps to predict bound poses of the user-selected molecules, detects if a compound is not likely to bind in the hot spot region, and provides input for the design of larger ligands.

Coronaviruses are a family of enveloped single-stranded positive-sense RNA viruses causing respiratory, enteric, and neurologic diseases in mammals and fowl. Human coronaviruses are recognized to cause up to a third of common colds and are suspected to be involved in enteric and neurologic diseases. Coronavirus replication involves the generation of nested subgenomic mRNAs (sgmRNAs) with a common capped 5′ leader sequence. The translation of most of the sgmRNAs is thought to be cap dependent and displays a requirement for eukaryotic initiation factor 4F (eIF4F), a heterotrimeric complex needed for the recruitment of 40S ribosomes. We recently reported on an ultrahigh-throughput screen to discover compounds that inhibit eIF4F activity by blocking the interaction of two of its subunits (R. Cencic et al., Proc. Natl. Acad. Sci. U. S. A. 108:1046–1051, 2011). Herein we describe a molecule from this screen that prevents the interaction between eIF4E (the cap-binding protein) and eIF4G (a large scaffolding protein), inhibiting cap-dependent translation. This inhibitor significantly decreased human coronavirus 229E (HCoV-229E) replication, reducing the percentage of infected cells and intra- and extracellular infectious virus titers. Our results support the strategy of targeting the eIF4F complex to block coronavirus infection.

Our approach to protein-protein docking includes three main steps. First we run PIPER, a rigid body docking program based on the Fast Fourier Transform (FFT) correlation approach, extended to use pairwise interactions potentials. Next, the 1000 best energy conformations are clustered, and the 30 largest clusters are retained for refinement. Third, the stability of the clusters is analyzed by short Monte Carlo simulations, and the structures are refined by the medium-range optimization method SDU. The first two steps of this approach are implemented in the ClusPro 2.0 protein-protein docking server. Despite being fully automated, the last step is computationally too expensive to be included in the server. Comparing the models obtained in CAPRI rounds 13–19 by ClusPro, by the refinement of the ClusPro predictions, and by all predictor groups, we arrived at three conclusions. First, for the first time in the CAPRI history, our automated ClusPro server was able to compete with the best human predictor groups. Second, selecting the top ranked models, our current protocol reliably generates high quality structures of protein-protein complexes from the structures of separately crystallized proteins, even in the absence of biological information, provided that there is limited backbone conformational change. Third, despite occasional successes, homology modeling requires further improvement to achieve reliable docking results.

MxCuBE is a beamline control environment optimized for the needs of macromolecular crystallography. This paper describes the design of the software and the features that MxCuBE currently provides.

The design and features of a beamline control software system for macromolecular crystallography (MX) experiments developed at the European Synchrotron Radiation Facility (ESRF) are described. This system, MxCuBE, allows users to easily and simply interact with beamline hardware components and provides automated routines for common tasks in the operation of a synchrotron beamline dedicated to experiments in MX. Additional functionality is provided through intuitive interfaces that enable the assessment of the diffraction characteristics of samples, experiment planning, automatic data collection and the on-line collection and analysis of X-ray emission spectra. The software can be run in a tandem client-server mode that allows for remote control and relevant experimental parameters and results are automatically logged in a relational database, ISPyB. MxCuBE is modular, flexible and extensible and is currently deployed on eight macromolecular crystallography beamlines at the ESRF. Additionally, the software is installed at MAX-lab beamline I911-3 and at BESSY beamline BL14.1.

Proteins that catalyse homologous recombination have been identified in all living organisms and are essential for the repair of damaged DNA as well as for the generation of genetic diversity. In bacteria homologous recombination is performed by the RecA protein, whereas in the eukarya a related protein called Rad51 is required to catalyse recombination and repair. More recently, archaeal homologues of RecA/Rad51 (RadA) have been identified and isolated. In this work we have cloned and purified the RadA protein from the hyperthermophilic, sulphate-reducing archaeon Archaeoglobus fulgidus and characterised its in vitro activities. We show that (i) RadA protein forms ring structures in solution and binds single- but not double-stranded DNA to form nucleoprotein filaments, (ii) RadA is a single-stranded DNA-dependent ATPase at elevated temperatures, and (iii) RadA catalyses efficient D-loop formation and strand exchange at temperatures of 60–70°C. Finally, we have used electron microscopy to visualise RadA-mediated joint molecules, the intermediates of homologous recombination. Intriguingly, RadA shares properties of both the bacterial RecA and eukaryotic Rad51 recombinases.