Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.

Integrated computational approaches for Mycobacterium tuberculosis (Mtb) are useful to identify new molecules that could lead to future tuberculosis (TB) drugs. Our approach uses information derived from the TBCyc pathway and genome database, the Collaborative Drug Discovery TB database combined with 3D pharmacophores and dual event Bayesian models of whole-cell activity and lack of cytotoxicity. We have prioritized a large number of molecules that may act as mimics of substrates and metabolites in the TB metabolome. We computationally searched over 200,000 commercial molecules using 66 pharmacophores based on substrates and metabolites from Mtb and further filtering with Bayesian models. We ultimately tested 110 compounds in vitro that resulted in two compounds of interest, BAS 04912643 and BAS 00623753 (MIC of 2.5 and 5 µg/mL, respectively). These molecules were used as a starting point for hit-to-lead optimization. The most promising class proved to be the quinoxaline di-N-oxides, evidenced by transcriptional profiling to induce mRNA level perturbations most closely resembling known protonophores. One of these, SRI58 exhibited an MIC = 1.25 µg/mL versus Mtb and a CC50 in Vero cells of >40 µg/mL, while featuring fair Caco-2 A-B permeability (2.3 x 10-6 cm/s), kinetic solubility (125 µM at pH 7.4 in PBS) and mouse metabolic stability (63.6% remaining after 1 h incubation with mouse liver microsomes). Despite demonstration of how a combined bioinformatics/cheminformatics approach afforded a small molecule with promising in vitro profiles, we found that SRI58 did not exhibit quantifiable blood levels in mice.

Machine Learning Models and Pathway Genome Data Base for Trypanosoma cruzi Drug Discovery.

BACKGROUND: Chagas disease is a neglected tropical disease (NTD) caused by the eukaryotic parasite Trypanosoma cruzi. The current clinical and preclinical pipeline for T. cruzi is extremely sparse and lacks drug target diversity. METHODOLOGY/PRINCIPAL FINDINGS: In the present study we developed a computational approach that utilized data from several public whole-cell, phenotypic high throughput screens that have been completed for T. cruzi by the Broad Institute, including a single screen of over 300,000 molecules in the search for chemical probes as part of the NIH Molecular Libraries program. We have also compiled and curated relevant biological and chemical compound screening data including (i) compounds and biological activity data from the literature, (ii) high throughput screening datasets, and (iii) predicted metabolites of T. cruzi metabolic pathways. This information was used to help us identify compounds and their potential targets. We have constructed a Pathway Genome Data Base for T. cruzi. In addition, we have developed Bayesian machine learning models that were used to virtually screen libraries of compounds. Ninety-seven compounds were selected for in vitro testing, and 11 of these were found to have EC50 < 10 µM. We progressed five compounds to an in vivo mouse efficacy model of Chagas disease and validated that the machine learning model could identify in vitro active compounds not in the training set, as well as known positive controls. The antimalarial pyronaridine possessed 85.2% efficacy in the acute Chagas mouse model. We have also proposed potential targets (for future verification) for this compound based on structural similarity to known compounds with targets in T. cruzi. CONCLUSIONS/ SIGNIFICANCE: We have demonstrated how combining chemoinformatics and bioinformatics for T. cruzi drug discovery can bring interesting in vivo active molecules to light that may have been overlooked. The approach we have taken is broadly applicable to other NTDs.

Crystal structure of nonstructural protein 10 from the severe acute respiratory syndrome coronavirus reveals a novel fold with two zinc-binding motifs.

The severe acute respiratory syndrome coronavirus (SARS-CoV) possesses a large 29.7-kb positive-stranded RNA genome. The first open reading frame encodes replicase polyproteins 1a and 1ab, which are cleaved to generate 16 "nonstructural" proteins, nsp1 to nsp16, involved in viral replication and/or RNA processing. Among these, nsp10 plays a critical role in minus-strand RNA synthesis in a related coronavirus, murine hepatitis virus. Here, we report the crystal structure of SARS-CoV nsp10 at a resolution of 1.8 A as determined by single-wavelength anomalous dispersion using phases derived from hexatantalum dodecabromide. nsp10 is a single domain protein consisting of a pair of antiparallel N-terminal helices stacked against an irregular beta-sheet, a coil-rich C terminus, and two Zn fingers. nsp10 represents a novel fold and is the first structural representative of this family of Zn finger proteins found so far exclusively in coronaviruses. The first Zn finger coordinates a Zn2+ ion in a unique conformation. The second Zn finger, with four cysteines, is a distant member of the "gag-knuckle fold group" of Zn2+-binding domains and appears to maintain the structural integrity of the C-terminal tail. A distinct clustering of basic residues on the protein surface suggests a nucleic acid-binding function. Gel shift assays indicate that in isolation, nsp10 binds single- and double-stranded RNA and DNA with high-micromolar affinity and without obvious sequence specificity. It is possible that nsp10 functions within a larger RNA-binding protein complex. However, its exact role within the replicase complex is still not clear.

Coiled coils at the edge of configurational heterogeneity. Structural analyses of parallel and antiparallel homotetrameric coiled coils reveal configurational sensitivity to a single solvent-exposed amino acid substitution.

A detailed understanding of the mechanisms by which particular amino acid sequences can give rise to more than one folded structure, such as for proteins that undergo large conformational changes or misfolding, is a long-standing objective of protein chemistry. Here, we describe the crystal structures of a single coiled-coil peptide in distinct parallel and antiparallel tetrameric configurations and further describe the parallel or antiparallel crystal structures of several related peptide sequences; the antiparallel tetrameric assemblies represent the first crystal structures of GCN4-derived peptides exhibiting such a configuration. Intriguingly, substitution of a single solvent-exposed residue enabled the parallel coiled-coil tetramer GCN4-pLI to populate the antiparallel configuration, suggesting that the two configurations are close enough in energy for subtle sequence changes to have important structural consequences. We present a structural analysis of the small changes to the helix register and side-chain conformations that accommodate the two configurations and have supplemented these results using solution studies and a molecular dynamics energetic analysis using a replica exchange methodology. Considering the previous examples of structural nonspecificity in coiled-coil peptides, the findings reported here not only emphasize the predisposition of the coiled-coil motif to adopt multiple configurations but also call attention to the associated risk that observed crytstal structures may not represent the only (or even the major) species present in solution.

Structure-based engineering of internal cavities in coiled-coil peptides.

Cavities and clefts are frequently important sites of interaction between natural enzymes or receptors and their corresponding substrate or ligand molecules and exemplify the types of molecular surfaces that would facilitate engineering of artificial catalysts and receptors. Even so, structural characterizations of designed cavities are rare. To address this issue, we performed a systematic study of the structural effects of single-amino acid substitutions within the hydrophobic cores of tetrameric coiled-coil peptides. Peptides containing single glycine, serine, alanine, or threonine amino acid substitutions at the buried L9, L16, L23, and I26 hydrophobic core positions of a GCN4-based sequence were synthesized and studied by solution-phase and crystallographic techniques. All peptides adopt the expected tetrameric state and contain tunnels or internal cavities ranging in size from 80 to 370 A(3). Two closely related sequences containing an L16G substitution, one of which adopts an antiparallel configuration and one of which adopts a parallel configuration, illustrate that cavities of different volumes and shapes can be engineered from identical core substitutions. Finally, we demonstrate that two of the peptides (L9G and L9A) bind the small molecule iodobenzene when present during crystallization, leaving the general peptide quaternary structure intact but altering the local peptide conformation and certain superhelical parameters. These high-resolution descriptions of varied molecular surfaces within solvent-occluded internal cavities illustrate the breadth of design space available in even closely related peptides and offer valuable models for the engineering of de novo helical proteins.

In situ data collection and structure refinement from microcapillary protein crystallization.

In situ X-ray data collection has the potential to eliminate the challenging task of mounting and cryocooling often fragile protein crystals, reducing a major bottleneck in the structure determination process. An apparatus used to grow protein crystals in capillaries and to compare the background X-ray scattering of the components, including thin-walled glass capillaries against Teflon, and various fluorocarbon oils against each other, is described. Using thaumatin as a test case at 1.8 Å resolution, this study demonstrates that high-resolution electron density maps and refined models can be obtained from in situ diffraction of crystals grown in microcapillaries.

Heterocyclic peptide backbone modifications in an alpha-helical coiled coil.

In this paper, we present 1,2,3-triazole epsilon2-amino acids incorporated as a dipeptide surrogate at three positions in the sequence of a known alpha-helical coiled coil. Biophysical characterization indicates that the modified peptides retain much of the helical structure of the parent sequence, and that the thermodynamic stability of the coiled coil depends on the position of the incorporation of the epsilon-residue. Crystal structures obtained for each peptide give insight into the chemical behavior and conformational preferences of the non-natural amino acid and show that the triazole ring can participate in the backbone hydrogen bonding of the alpha-helix as well as template an interhelical crossing between chains in the bundle.

Design of a directed molecular network.

An ability to rationally design complex networks from the bottom up can offer valuable quantitative model systems for use in gaining a deeper appreciation for the principles governing the self-organization and functional characteristics of complex systems. We report herein the de novo design, graph prediction, experimental analysis, and characterization of simple self-organized, nonlinear molecular networks. Our approach makes use of the sequence-dependent auto- and cross-catalytic functional characteristics of template-directed peptide fragment condensation reactions in neutral aqueous solutions. Starting with an array of 81 sequence similar 32-residue coiled-coil peptides, we estimated the relative stability difference between all plausible A(2)B-type coiled-coil ensembles and used this information to predict the auto- and cross-catalysis pathways and the resulting plausible network motif and connectivities. Similar to most complex systems, the generated graph displays clustered nodes with an overall hierarchical architecture. To test the validity of the design principles used, nine nodes composing a main segment of the graph were experimentally analyzed for their capacity in establishing the predicted network connectivity. The resulting self-organized chemical network is shown to display 25 directed edges in good agreement with the graph analysis estimations. Moreover, we show that by varying the system parameters (presence or absence of certain substrates or templates), its operating network motif can be altered, even to the extremes of turning pathways on or off. We suggest that this approach can be expanded for the construction of large-scale networks, offering a means to study and to understand better the emergent, collective behaviors of networks.