Scaffold Matcher: A CMA-ES based algorithm for identifying hotspot aligned peptidomimetic scaffolds

The design of protein interaction inhibitors is a promising approach to address aberrant protein interactions that cause disease. One strategy in designing inhibitors is to use peptidomimetic scaffolds that mimic the natural interaction interface. A central challenge in using peptidomimetics as protein interaction inhibitors, however, is determining how best the molecular scaffold aligns to the residues of the interface it is attempting to mimic. Here we present the Scaffold Matcher algorithm that aligns a given molecular scaffold onto hotspot residues from a protein interaction interface. To optimize the degrees of freedom of the molecular scaffold we implement the covariance matrix adaptation evolution strategy (CMA-ES), a state-of-the-art derivative-free optimization algorithm in Rosetta. To evaluate the performance of the CMA-ES, we used 26 peptides from the FlexPepDock Benchmark and compared with three other algorithms in Rosetta, specifically, Rosetta's default minimizer, a Monte Carlo protocol of small backbone perturbations, and a Genetic algorithm. We test the algorithms' performance on their ability to align a molecular scaffold to a series of hotspot residues (i.e., constraints) along native peptides. Of the 4 methods, CMA-ES was able to find the lowest energy conformation for all 26 benchmark peptides. Additionally, as a proof of concept, we apply the Scaffold Match algorithm with CMA-ES to align a peptidomimetic oligooxopiperazine scaffold to the hotspot residues of the substrate of the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our implementation of CMA-ES into Rosetta allows for an alternative optimization method to be used on macromolecular modeling problems with rough energy landscapes. Finally, our Scaffold Matcher algorithm allows for the identification of initial conformations of interaction inhibitors that can be further designed and optimized as high-affinity reagents.

Come for the atmosphere, stay for the interactions: Deciphering small molecule partitioning into biomolecular condensates

Optimizing pharmacokinetic properties remains challenging but is generally guided by a set of structural rules. However, no such rule set exists for intracellular distribution. Kilgore et al.1 have examined small molecule partitioning within biomolecular condensates, yielding findings that could open a new window in the drug design and discovery process.

The protein organization of a red blood cell

Red blood cells (RBCs) (erythrocytes) are the simplest primary human cells, lacking nuclei and major organelles and instead employing about a thousand proteins to dynamically control cellular function and morphology in response to physiological cues. In this study, we define a canonical RBC proteome and interactome using quantitative mass spectrometry and machine learning. Our data reveal an RBC interactome dominated by protein homeostasis, redox biology, cytoskeletal dynamics, and carbon metabolism. We validate protein complexes through electron microscopy and chemical crosslinking and, with these data, build 3D structural models of the ankyrin/Band 3/Band 4.2 complex that bridges the spectrin cytoskeleton to the RBC membrane. The model suggests spring-like compression of ankyrin may contribute to the characteristic RBC cell shape and flexibility. Taken together, our study provides an in-depth view of the global protein organization of human RBCs and serves as a comprehensive resource for future research.

hu.MAP 2.0: integration of over 15,000 proteomic experiments builds a global compendium of human multiprotein assemblies

A general principle of biology is the self‐assembly of proteins into functional complexes. Characterizing their composition is, therefore, required for our understanding of cellular functions. Unfortunately, we lack knowledge of the comprehensive set of identities of protein complexes in human cells. To address this gap, we developed a machine learning framework to identify protein complexes in over 15,000 mass spectrometry experiments which resulted in the identification of nearly 7,000 physical assemblies. We show our resource, hu.MAP 2.0, is more accurate and comprehensive than previous state of the art high‐throughput protein complex resources and gives rise to many new hypotheses, including for 274 completely uncharacterized proteins. Further, we identify 253 promiscuous proteins that participate in multiple complexes pointing to possible moonlighting roles. We have made hu.MAP 2.0 easily searchable in a web interface (http://humap2.proteincomplexes.org/), which will be a valuable resource for researchers across a broad range of interests including systems biology, structural biology, and molecular explanations of disease.

Co-fractionation/mass spectrometry to identify protein complexes

Co-fractionation/mass spectrometry (CF/MS) is a flexible and powerful method to detect physical associations of proteins. CF/MS can be applied to any tissue or organism without the need for protein-specific antibodies or epitope tags. Here, we outline two alternate protocols for MS preparation of samples (containing low or high salt) and a computational pipeline (cfmsflow) that together allow the successful application of this approach. These protocols are based on CF/MS of over 16 diverse organisms including plants and animals.

For complete details on the use and execution of this protocol, please refer to McWhite et al. (2020).

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Co-fractionation/mass spectrometry (CF/MS) detects native protein associations

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Experimental methods for mass spec preparation of 96-well native fractions

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Computational pipeline to generate protein interaction maps from CF/MS data

Systematic Identification of Protein Phosphorylation-Mediated Interactions

Protein phosphorylation is a key regulatory mechanism involved in nearly every eukaryotic cellular process. Increasingly sensitive mass spectrometry approaches have identified hundreds of thousands of phosphorylation sites, but the functions of a vast majority of these sites remain unknown, with fewer than 5% of sites currently assigned a function. To increase our understanding of functional protein phosphorylation we developed an approach (phospho-DIFFRAC) for identifying the phosphorylation-dependence of protein assemblies in a systematic manner. A combination of nonspecific protein phosphatase treatment, size-exclusion chromatography, and mass spectrometry allowed us to identify changes in protein interactions after the removal of phosphate modifications. With this approach we were able to identify 316 proteins involved in phosphorylation-sensitive interactions. We recovered known phosphorylation-dependent interactors such as the FACT complex and spliceosome, as well as identified novel interactions such as the tripeptidyl peptidase TPP2 and the supraspliceosome component ZRANB2. More generally, we find phosphorylation-dependent interactors to be strongly enriched for RNA-binding proteins, providing new insight into the role of phosphorylation in RNA binding. By searching directly for phosphorylated amino acid residues in mass spectrometry data, we identified the likely regulatory phosphosites on ZRANB2 and FACT complex subunit SSRP1. This study provides both a method and resource for obtaining a better understanding of the role of phosphorylation in native macromolecular assemblies. All mass spectrometry data are available through PRIDE (accession #PXD021422).

Functional partitioning of a liquid-like organelle during assembly of axonemal dyneins

Ciliary motility is driven by axonemal dyneins that are assembled in the cytoplasm before deployment to cilia. Motile ciliopathy can result from defects in the dyneins themselves or from defects in factors required for their cytoplasmic pre-assembly. Recent work demonstrates that axonemal dyneins, their specific assembly factors, and broadly-acting chaperones are concentrated in liquid-like organelles in the cytoplasm called DynAPs (Dynein Axonemal Particles). Here, we use in vivo imaging in Xenopus to show that inner dynein arm (IDA) and outer dynein arm (ODA) subunits are partitioned into non-overlapping sub-regions within DynAPs. Using affinity- purification mass-spectrometry of in vivo interaction partners, we also identify novel partners for inner and outer dynein arms. Among these, we identify C16orf71/Daap1 as a novel axonemal dynein regulator. Daap1 interacts with ODA subunits, localizes specifically to the cytoplasm, is enriched in DynAPs, and is required for the deployment of ODAs to axonemes. Our work reveals a new complexity in the structure and function of a cell-type specific liquid-like organelle that is directly relevant to human genetic disease.

A systematic, label-free method for identifying RNA-associated proteins in vivo provides insights into vertebrate ciliary beating machinery

Cell-type specific RNA-associated proteins are essential for development and homeostasis in animals. Despite a massive recent effort to systematically identify RNA-associated proteins, we currently have few comprehensive rosters of cell-type specific RNA-associated proteins in vertebrate tissues. Here, we demonstrate the feasibility of determining the RNA-associated proteome of a defined vertebrate embryonic tissue using DIF-FRAC, a systematic and universal (i.e., label-free) method. Application of DIF-FRAC to cultured tissue explants of Xenopus mucociliary epithelium identified dozens of known RNA-associated proteins as expected, but also several novel RNA-associated proteins, including proteins related to assembly of the mitotic spindle and regulation of ciliary beating. In particular, we show that the inner dynein arm tether Cfap44 is an RNA-associated protein that localizes not only to axonemes, but also to liquid-like organelles in the cytoplasm called DynAPs. This result led us to discover that DynAPs are generally enriched for RNA. Together, these data provide a useful resource for a deeper understanding of mucociliary epithelia and demonstrate that DIF-FRAC will be broadly applicable for systematic identification of RNA-associated proteins from embryonic tissues.

A Pan-plant Protein Complex Map Reveals Deep Conservation and Novel Assemblies

Plants are foundational for global ecological and economic systems, but most plant proteins remain uncharacterized. Protein interaction networks often suggest protein functions and open new avenues to characterize genes and proteins. We therefore systematically determined protein complexes from 13 plant species of scientific and agricultural importance, greatly expanding the known repertoire of stable protein complexes in plants. By using co-fractionation mass spectrometry, we recovered known complexes, confirmed complexes predicted to occur in plants, and identified previously unknown interactions conserved over 1.1 billion years of green plant evolution. Several novel complexes are involved in vernalization and pathogen defense, traits critical for agriculture. We also observed plant analogs of animal complexes with distinct molecular assemblies, including a megadalton-scale tRNA multi-synthetase complex. The resulting map offers a cross-species view of conserved, stable protein assemblies shared across plant cells and provides a mechanistic, biochemical framework for interpreting plant genetics and mutant phenotypes.

Systematic Discovery of Endogenous Human Ribonucleoprotein Complexes

RNA-binding proteins (RBPs) play essential roles in biology and are frequently associated with human disease. Although recent studies have systematically identified individual RNA-binding proteins, their higher-order assembly into ribonucleoprotein (RNP) complexes has not been systematically investigated. Here, we describe a proteomics method for systematic identification of RNP complexes in human cells. We identify 1,428 protein complexes that associate with RNA, indicating that more than 20% of known human protein complexes contain RNA. To explore the role of RNA in the assembly of each complex, we identify complexes that dissociate, change composition, or form stable protein-only complexes in the absence of RNA. We use our method to systematically identify cell-type-specific RNA-associated proteins in mouse embryonic stem cells and finally, distribute our resource, rna.MAP, in an easy-to-use online interface (rna.proteincomplexes.org). Our system thus provides a methodology for explorations across human tissues, disease states, and throughout all domains of life.

An adaptive geometric search algorithm for macromolecular scaffold selection

A wide variety of protein and peptidomimetic design tasks require matching functional 3D motifs to potential oligomeric scaffolds. For example, during enzyme design, one aims to graft active-site patterns-typically consisting of 3-15 residues-onto new protein surfaces. Identifying protein scaffolds suitable for such active-site engraftment requires costly searches for protein folds that provide the correct side chain positioning to host the desired active site. Other examples of biodesign tasks that require similar fast exact geometric searches of potential side chain positioning include mimicking binding hotspots, design of metal binding clusters and the design of modular hydrogen binding networks for specificity. In these applications, the speed and scaling of geometric searches limits the scope of downstream design to small patterns. Here, we present an adaptive algorithm capable of searching for side chain take-off angles, which is compatible with an arbitrarily specified functional pattern and which enjoys substantive performance improvements over previous methods. We demonstrate this method in both genetically encoded (protein) and synthetic (peptidomimetic) design scenarios. Examples of using this method with the Rosetta framework for protein design are provided. Our implementation is compatible with multiple protein design frameworks and is freely available as a set of python scripts (https://github.com/JiangTian/adaptive-geometric-search-for-protein-design).

Identifying direct contacts between protein complex subunits from their conditional dependence in proteomics datasets

Determining the three dimensional arrangement of proteins in a complex is highly beneficial for uncovering mechanistic function and interpreting genetic variation in coding genes comprising protein complexes. There are several methods for determining co-complex interactions between proteins, among them co-fractionation / mass spectrometry (CF-MS), but it remains difficult to identify directly contacting subunits within a multi-protein complex. Correlation analysis of CF-MS profiles shows promise in detecting protein complexes as a whole but is limited in its ability to infer direct physical contacts among proteins in sub-complexes. To identify direct protein-protein contacts within human protein complexes we learn a sparse conditional dependency graph from approximately 3,000 CF-MS experiments on human cell lines. We show substantial performance gains in estimating direct interactions compared to correlation analysis on a benchmark of large protein complexes with solved three-dimensional structures. We demonstrate the method’s value in determining the three dimensional arrangement of proteins by making predictions for complexes without known structure (the exocyst and tRNA multi-synthetase complex) and by establishing evidence for the structural position of a recently discovered component of the core human EKC/KEOPS complex, GON7/C14ORF142, providing a more complete 3D model of the complex. Direct contact prediction provides easily calculable additional structural information for large-scale protein complex mapping studies and should be broadly applicable across organisms as more CF-MS datasets become available.

Proteins physically associate into complexes in order to carry out the essential functions of life. Knowing how proteins are physically arranged three dimensionally in these complexes provides clues towards how they work. In principle, the associations between proteins in large-scale proteomics datasets should often reflect direct physical contacts between proteins in each complex. Here, we describe a statistical method to discover which subunits within complexes directly contact each other based on their co-purification behavior in published co-fractionation mass spectrometry datasets. Within our predictions, we recover many known protein-protein contacts, serving to validate our method, as well as unknown contacts that can inform future studies of these complexes. Specifically, we observe confident contacts between subunits within the exocyst and tRNA multi-synthetase complexes, two complexes that have incomplete structural information. Using our method, we further provide structural information for a previously missing subunit of the EKC/KEOPS complex. We anticipate that this method and the associated predictions will help to better inform our understanding of the functions and structures of diverse protein complexes.

Integration of over 9,000 mass spectrometry experiments builds a global map of human protein complexes

Macromolecular protein complexes carry out many of the essential functions of cells, and many genetic diseases arise from disrupting the functions of such complexes. Currently, there is great interest in defining the complete set of human protein complexes, but recent published maps lack comprehensive coverage. Here, through the synthesis of over 9,000 published mass spectrometry experiments, we present hu.MAP, the most comprehensive and accurate human protein complex map to date, containing > 4,600 total complexes, > 7,700 proteins, and > 56,000 unique interactions, including thousands of confident protein interactions not identified by the original publications. hu.MAP accurately recapitulates known complexes withheld from the learning procedure, which was optimized with the aid of a new quantitative metric (k‐cliques) for comparing sets of sets. The vast majority of complexes in our map are significantly enriched with literature annotations, and the map overall shows improved coverage of many disease‐associated proteins, as we describe in detail for ciliopathies. Using hu.MAP, we predicted and experimentally validated candidate ciliopathy disease genes in vivo in a model vertebrate, discovering CCDC138, WDR90, and KIAA1328 to be new cilia basal body/centriolar satellite proteins, and identifying ANKRD55 as a novel member of the intraflagellar transport machinery. By offering significant improvements to the accuracy and coverage of human protein complexes, hu.MAP (http://proteincomplexes.org) serves as a valuable resource for better understanding the core cellular functions of human proteins and helping to determine mechanistic foundations of human disease.

Conformational preferences of peptide-peptoid hybrid oligomers

Peptomers are oligomeric molecules composed of both α-amino acids and N-substituted glycine monomers, thus creating a hybrid of peptide and peptoid units. Peptomers have been used in several applications such as antimicrobials, protease inhibitors, and antibody mimics. Despite the considerable promise of peptomers as chemically diverse molecular scaffolds, we know little about their conformational tendencies. This lack of knowledge limits the ability to implement computational approaches for peptomer design. Here we computationally evaluate the local structural propensities of the peptide-peptoid linkage. We find some general similarities between the peptide residue conformational preferences and the Ramachandran distribution of residues that precede proline in folded protein structures. However, there are notable differences. For example, several β-turn motifs are disallowed when the i+2 residue is also a peptoid monomer. Significantly, the lowest energy geometry, when dispersion forces are accounted for, corresponds to a "cis-Pro touch-turn" conformation, an unusual turn motif that has been observed at protein catalytic centers and binding sites. The peptomer touch-turn thus represents a useful design element for the construction of folded oligomers capable of molecular recognition and as modules in the assembly of structurally complex peptoid-protein hybrid macromolecules.

The ciliopathy-associated CPLANE proteins direct basal body recruitment of intraflagellar transport machinery

Cilia use microtubule-based intraflagellar transport (IFT) to organize intercellular signaling. Ciliopathies are a spectrum of human diseases resulting from defects in cilia structure or function. The mechanisms regulating the assembly of ciliary multiprotein complexes and the transport of these complexes to the base of cilia remain largely unknown. Combining proteomics, in vivo imaging and genetic analysis of proteins linked to planar cell polarity (Inturned, Fuzzy and Wdpcp), we identified and characterized a new genetic module, which we term CPLANE (ciliogenesis and planar polarity effector), and an extensive associated protein network. CPLANE proteins physically and functionally interact with the poorly understood ciliopathy-associated protein Jbts17 at basal bodies, where they act to recruit a specific subset of IFT-A proteins. In the absence of CPLANE, defective IFT-A particles enter the axoneme and IFT-B trafficking is severely perturbed. Accordingly, mutation of CPLANE genes elicits specific ciliopathy phenotypes in mouse models and is associated with ciliopathies in human patients.

Proteome-wide dataset supporting the study of ancient metazoan macromolecular complexes

Our analysis examines the conservation of multiprotein complexes among metazoa through use of high resolution biochemical fractionation and precision mass spectrometry applied to soluble cell extracts from 5 representative model organisms Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Strongylocentrotus purpuratus, and Homo sapiens. The interaction network obtained from the data was validated globally in 4 distant species (Xenopus laevis, Nematostella vectensis, Dictyostelium discoideum, Saccharomyces cerevisiae) and locally by targeted affinity-purification experiments. Here we provide details of our massive set of supporting biochemical fractionation data available via ProteomeXchange (PXD002319-PXD002328), PPIs via BioGRID (185267); and interaction network projections via (http://metazoa.med.utoronto.ca) made fully accessible to allow further exploration. The datasets here are related to the research article on metazoan macromolecular complexes in Nature [1].

Panorama of ancient metazoan macromolecular complexes

Macromolecular complexes are essential to conserved biological processes, but their prevalence across animals is unclear. By combining extensive biochemical fractionation with quantitative mass spectrometry, we directly examined the composition of soluble multiprotein complexes among diverse metazoan models. Using an integrative approach, we then generated a draft conservation map consisting of >1 million putative high-confidence co-complex interactions for species with fully sequenced genomes that encompasses functional modules present broadly across all extant animals. Clustering revealed a spectrum of conservation, ranging from ancient Eukaryal assemblies likely serving cellular housekeeping roles for at least 1 billion years, ancestral complexes that have accrued contemporary components, and rarer metazoan innovations linked to multicellularity. We validated these projections by independent co-fractionation experiments in evolutionarily distant species, by affinity-purification and by functional analyses. The comprehensiveness, centrality and modularity of these reconstructed interactomes reflect their fundamental mechanistic significance and adaptive value to animal cell systems.

Rational design of topographical helix mimics as potent inhibitors of protein-protein interactions

Protein–protein interactions encompass large surface areas, but often a handful of key residues dominate the binding energy landscape. Rationally designed small molecule scaffolds that reproduce the relative positioning and disposition of important binding residues, termed “hotspot residues”, have been shown to successfully inhibit specific protein complexes. Although this strategy has led to development of novel synthetic inhibitors of protein complexes, often direct mimicry of natural amino acid residues does not lead to potent inhibitors. Experimental screening of focused compound libraries is used to further optimize inhibitors but the number of possible designs that can be efficiently synthesized and experimentally tested in academic settings is limited. We have applied the principles of computational protein design to optimization of nonpeptidic helix mimics as ligands for protein complexes. We describe the development of computational tools to design helix mimetics from canonical and noncanonical residue libraries and their application to two therapeutically important protein–protein interactions: p53-MDM2 and p300-HIF1α. The overall study provides a streamlined approach for discovering potent peptidomimetic inhibitors of protein–protein interactions.

Extending RosettaDock with water, sugar, and pH for prediction of complex structures and affinities for CAPRI rounds 20-27

Rounds 20-27 of the Critical Assessment of PRotein Interactions (CAPRI) provided a testing platform for computational methods designed to address a wide range of challenges. The diverse targets drove the creation of and new combinations of computational tools. In this study, RosettaDock and other novel Rosetta protocols were used to successfully predict four of the 10 blind targets. For example, for DNase domain of Colicin E2-Im2 immunity protein, RosettaDock and RosettaLigand were used to predict the positions of water molecules at the interface, recovering 46% of the native water-mediated contacts. For α-repeat Rep4-Rep2 and g-type lysozyme-PliG inhibitor complexes, homology models were built and standard and pH-sensitive docking algorithms were used to generate structures with interface RMSD values of 3.3 Å and 2.0 Å, respectively. A novel flexible sugar-protein docking protocol was also developed and used for structure prediction of the BT4661-heparin-like saccharide complex, recovering 71% of the native contacts. Challenges remain in the generation of accurate homology models for protein mutants and sampling during global docking. On proteins designed to bind influenza hemagglutinin, only about half of the mutations were identified that affect binding (T55: 54%; T56: 48%). The prediction of the structure of the xylanase complex involving homology modeling and multidomain docking pushed the limits of global conformational sampling and did not result in any successful prediction. The diversity of problems at hand requires computational algorithms to be versatile; the recent additions to the Rosetta suite expand the capabilities to encompass more biologically realistic docking problems.

Adding diverse noncanonical backbones to rosetta: enabling peptidomimetic design

Peptidomimetics are classes of molecules that mimic structural and functional attributes of polypeptides. Peptidomimetic oligomers can frequently be synthesized using efficient solid phase synthesis procedures similar to peptide synthesis. Conformationally ordered peptidomimetic oligomers are finding broad applications for molecular recognition and for inhibiting protein-protein interactions. One critical limitation is the limited set of design tools for identifying oligomer sequences that can adopt desired conformations. Here, we present expansions to the ROSETTA platform that enable structure prediction and design of five non-peptidic oligomer scaffolds (noncanonical backbones), oligooxopiperazines, oligo-peptoids, -peptides, hydrogen bond surrogate helices and oligosaccharides. This work is complementary to prior additions to model noncanonical protein side chains in ROSETTA. The main purpose of our manuscript is to give a detailed description to current and future developers of how each of these noncanonical backbones was implemented. Furthermore, we provide a general outline for implementation of new backbone types not discussed here. To illustrate the utility of this approach, we describe the first tests of the ROSETTA molecular mechanics energy function in the context of oligooxopiperazines, using quantum mechanical calculations as comparison points, scanning through backbone and side chain torsion angles for a model peptidomimetic. Finally, as an example of a novel design application, we describe the automated design of an oligooxopiperazine that inhibits the p53-MDM2 protein-protein interaction. For the general biological and bioengineering community, several noncanonical backbones have been incorporated into web applications that allow users to freely and rapidly test the presented protocols (http://rosie.rosettacommons.org). This work helps address the peptidomimetic community's need for an automated and expandable modeling tool for noncanonical backbones.

Serverification of molecular modeling applications: the Rosetta Online Server that Includes Everyone (ROSIE)

The Rosetta molecular modeling software package provides experimentally tested and rapidly evolving tools for the 3D structure prediction and high-resolution design of proteins, nucleic acids, and a growing number of non-natural polymers. Despite its free availability to academic users and improving documentation, use of Rosetta has largely remained confined to developers and their immediate collaborators due to the code's difficulty of use, the requirement for large computational resources, and the unavailability of servers for most of the Rosetta applications. Here, we present a unified web framework for Rosetta applications called ROSIE (Rosetta Online Server that Includes Everyone). ROSIE provides (a) a common user interface for Rosetta protocols, (b) a stable application programming interface for developers to add additional protocols, (c) a flexible back-end to allow leveraging of computer cluster resources shared by RosettaCommons member institutions, and (d) centralized administration by the RosettaCommons to ensure continuous maintenance. This paper describes the ROSIE server infrastructure, a step-by-step 'serverification' protocol for use by Rosetta developers, and the deployment of the first nine ROSIE applications by six separate developer teams: Docking, RNA de novo, ERRASER, Antibody, Sequence Tolerance, Supercharge, Beta peptide design, NCBB design, and VIP redesign. As illustrated by the number and diversity of these applications, ROSIE offers a general and speedy paradigm for serverification of Rosetta applications that incurs negligible cost to developers and lowers barriers to Rosetta use for the broader biological community. ROSIE is available at http://rosie.rosettacommons.org.

Parametric Bayesian priors and better choice of negative examples improve protein function prediction

MOTIVATION

Computational biologists have demonstrated the utility of using machine learning methods to predict protein function from an integration of multiple genome-wide data types. Yet, even the best performing function prediction algorithms rely on heuristics for important components of the algorithm, such as choosing negative examples (proteins without a given function) or determining key parameters. The improper choice of negative examples, in particular, can hamper the accuracy of protein function prediction.

RESULTS

We present a novel approach for choosing negative examples, using a parameterizable Bayesian prior computed from all observed annotation data, which also generates priors used during function prediction. We incorporate this new method into the GeneMANIA function prediction algorithm and demonstrate improved accuracy of our algorithm over current top-performing function prediction methods on the yeast and mouse proteomes across all metrics tested.

AVAILABILITY

Code and Data are available at: http://bonneaulab.bio.nyu.edu/funcprop.html

The plant proteome folding project: structure and positive selection in plant protein families

Despite its importance, relatively little is known about the relationship between the structure, function, and evolution of proteins, particularly in land plant species. We have developed a database with predicted protein domains for five plant proteomes (http://pfp.bio.nyu.edu) and used both protein structural fold recognition and de novo Rosetta-based protein structure prediction to predict protein structure for Arabidopsis and rice proteins. Based on sequence similarity, we have identified ∼15,000 orthologous/paralogous protein family clusters among these species and used codon-based models to predict positive selection in protein evolution within 175 of these sequence clusters. Our results show that codons that display positive selection appear to be less frequent in helical and strand regions and are overrepresented in amino acid residues that are associated with a change in protein secondary structure. Like in other organisms, disordered protein regions also appear to have more selected sites. Structural information provides new functional insights into specific plant proteins and allows us to map positively selected amino acid sites onto protein structures and view these sites in a structural and functional context.

Rational design of temperature-sensitive alleles using computational structure prediction

Temperature-sensitive (ts) mutations are mutations that exhibit a mutant phenotype at high or low temperatures and a wild-type phenotype at normal temperature. Temperature-sensitive mutants are valuable tools for geneticists, particularly in the study of essential genes. However, finding ts mutations typically relies on generating and screening many thousands of mutations, which is an expensive and labor-intensive process. Here we describe an in silico method that uses Rosetta and machine learning techniques to predict a highly accurate "top 5" list of ts mutations given the structure of a protein of interest. Rosetta is a protein structure prediction and design code, used here to model and score how proteins accommodate point mutations with side-chain and backbone movements. We show that integrating Rosetta relax-derived features with sequence-based features results in accurate temperature-sensitive mutation predictions.

The Proteome Folding Project: proteome-scale prediction of structure and function

The incompleteness of proteome structure and function annotation is a critical problem for biologists and, in particular, severely limits interpretation of high-throughput and next-generation experiments. We have developed a proteome annotation pipeline based on structure prediction, where function and structure annotations are generated using an integration of sequence comparison, fold recognition, and grid-computing-enabled de novo structure prediction. We predict protein domain boundaries and three-dimensional (3D) structures for protein domains from 94 genomes (including human, Arabidopsis, rice, mouse, fly, yeast, Escherichia coli, and worm). De novo structure predictions were distributed on a grid of more than 1.5 million CPUs worldwide (World Community Grid). We generated significant numbers of new confident fold annotations (9% of domains that are otherwise unannotated in these genomes). We demonstrate that predicted structures can be combined with annotations from the Gene Ontology database to predict new and more specific molecular functions.

The coat morphogenetic protein SpoVID is necessary for spore encasement in Bacillus subtilis

Endospores formed by Bacillus subtilis are encased in a tough protein shell known as the coat, which consists of at least 70 different proteins. We investigated the process of spore coat morphogenesis using a library of 40 coat proteins fused to green fluorescent protein and demonstrate that two successive steps can be distinguished in coat assembly. The first step, initial localization of proteins to the spore surface, is dependent on the coat morphogenetic proteins SpoIVA and SpoVM. The second step, spore encasement, requires a third protein, SpoVID. We show that in spoVID mutant cells, most coat proteins assembled into a cap at one side of the developing spore but failed to migrate around and encase it. We also found that SpoIVA directly interacts with SpoVID. A domain analysis revealed that the N-terminus of SpoVID is required for encasement and is a structural homologue of a virion protein, whereas the C-terminus is necessary for the interaction with SpoIVA. Thus, SpoVM, SpoIVA and SpoVID are recruited to the spore surface in a concerted manner and form a tripartite machine that drives coat formation and spore encasement.

BioNetBuilder2.0: bringing systems biology to chicken and other model organisms

Background

Systems Biology research tools, such as Cytoscape, have greatly extended the reach of genomic research. By providing platforms to integrate data with molecular interaction networks, researchers can more rapidly begin interpretation of large data sets collected for a system of interest. BioNetBuilder is an open-source client-server Cytoscape plugin that automatically integrates molecular interactions from all major public interaction databases and serves them directly to the user's Cytoscape environment. Until recently however, chicken and other eukaryotic model systems had little interaction data available.

Results

Version 2.0 of BioNetBuilder includes a redesigned synonyms resolution engine that enables transfer and integration of interactions across species; this engine translates between alternate gene names as well as between orthologs in multiple species. Additionally, BioNetBuilder is now implemented to be part of the Gaggle, thereby allowing seamless communication of interaction data to any software implementing the widely used Gaggle software. Using BioNetBuilder, we constructed a chicken interactome possessing 72,000 interactions among 8,140 genes directly in the Cytoscape environment. In this paper, we present a tutorial on how to do so and analysis of a specific use case.

Conclusion

BioNetBuilder 2.0 provides numerous user-friendly systems biology tools that were otherwise inaccessible to researchers in chicken genomics, as well as other model systems. We provide a detailed tutorial spanning all required steps in the analysis. BioNetBuilder 2.0, the tools for maintaining its data bases, standard operating procedures for creating local copies of its back-end data bases, as well as all of the Gaggle and Cytoscape codes required, are open-source and freely available at http://err.bio.nyu.edu/cytoscape/bionetbuilder/.

A protein domain-based interactome network for C. elegans early embryogenesis

Many protein-protein interactions are mediated through independently folding modular domains. Proteome-wide efforts to model protein-protein interaction or "interactome" networks have largely ignored this modular organization of proteins. We developed an experimental strategy to efficiently identify interaction domains and generated a domain-based interactome network for proteins involved in C. elegans early-embryonic cell divisions. Minimal interacting regions were identified for over 200 proteins, providing important information on their domain organization. Furthermore, our approach increased the sensitivity of the two-hybrid system, resulting in a more complete interactome network. This interactome modeling strategy revealed insights into C. elegans centrosome function and is applicable to other biological processes in this and other organisms.

Investigating quantitation of phosphorylation using MALDI-TOF mass spectrometry

Despite advances in methods and instrumentation for analysis of phosphopeptides using mass spectrometry, it is still difficult to quantify the extent of phosphorylation of a substrate because of physiochemical differences between unphosphorylated and phosphorylated peptides. Here we report experiments to investigate those differences using MALDI-TOF mass spectrometry for a set of synthetic peptides by creating calibration curves of known input ratios of peptides/phosphopeptides and analyzing their resulting signal intensity ratios. These calibration curves reveal subtleties in sequence-dependent differences for relative desorption/ionization efficiencies that cannot be seen from single-point calibrations. We found that the behaviors were reproducible with a variability of 5-10% for observed phosphopeptide signal. Although these data allow us to begin addressing the issues related to modeling these properties and predicting relative signal strengths for other peptide sequences, it is clear that this behavior is highly complex and needs to be further explored.

BioNetBuilder: automatic integration of biological networks

BioNetBuilder is an open-source client-server Cytoscape plugin that offers a user-friendly interface to create biological networks integrated from several databases. Users can create networks for approximately 1500 organisms, including common model organisms and human. Currently supported databases include: DIP, BIND, Prolinks, KEGG, HPRD, The BioGrid and GO, among others. The BioNetBuilder plugin client is available as a Java Webstart, providing a platform-independent network interface to these public databases.

AVAILABILITY

http://err.bio.nyu.edu/cytoscape/bionetbuilder/

Colonoscopic resection of lateral spreading tumours: a prospective analysis of endoscopic mucosal resection

BACKGROUND

Lateral spreading tumours are superficial spreading neoplasms now increasingly diagnosed using chromoscopic colonoscopy. The clinicopathological features and safety of endoscopic mucosal resection for lateral spreading tumours (G-type "aggregate" and F-type "flat") has yet to be clarified in Western cohorts.

METHODS

Eighty two patients underwent magnification chromoscopic colonoscopy using the Olympus CF240Z by a single endoscopist. All patients had received a previous colonoscopy where an endoscopic diagnosis of lateral spreading tumour was made. All lesions were examined initially using indigo carmine chromoscopy to delineate contour followed by crystal violet for magnification crypt pattern analysis. A 20 MHz "mini probe" ultrasound was used if T2 disease was suspected. Following endoscopic mucosal resection, patients were followed up at 3, 6, 12, and 24 months using total colonoscopy.

RESULTS

Eighty two lateral spreading tumours were diagnosed in 80 patients (32% (26/82) F-type and 68% (56/82) G-type). G-type lesions were larger than F-type (G-type mean 42 (SD 14) mm v F-type 24 (6.4) mm; p<0.01). F-type lesions were more common in the right colon (F-type 77% (20/26) compared with G-type 39% (22/56); p<0.01) and more often associated with invasive disease (stage T2) (66% (10/15) v 33% (5/15); p<0.001). Fifty eight lesions underwent endoscopic mucosal resection (G-type 64% (37/58)/F-type 36% (21/58)). Local recurrent disease was detected in 17% of patients (10/58), all within six months of the index resection. Piecemeal resection and G-type morphology were significantly associated with recurrent disease (p<0.1). Overall "cure" rates for lateral spreading tumours using endoscopic mucosal resection at two years of follow-up was 96% (56/58).

CONCLUSIONS

Endoscopic mucosal resection for lateral spreading tumours, staged as T1, is a safe and effective treatment despite their large size. Endoscopic mucosal resection may be an alternative to surgery in selected patients.

An evaluation of colorectal endoscopic mucosal resection using high-magnification chromoscopic colonoscopy: a prospective study of 1000 colonoscopies

BACKGROUND AND STUDY AIMS

Endoscopic mucosal resection provides an alternative to surgery for resection of sessile and flat colorectal lesions. High-magnification chromoscopic colonoscopy may allow early detection and anticipate histological diagnosis by identifying colonic crypt patterns. The aim of the present study was to assess the efficacy and safety of en-bloc endoscopic mucosal resection with high-magnification chromoendoscopy in the management of sessile and flat colorectal lesions </= 20 mm.

PATIENTS AND METHODS

A single endoscopist using high-magnification chromoendoscopy prospectively examined 1000 patients attending for routine colonoscopy. Patients were selected for inclusion in the study if they were considered to be at high risk for underlying colorectal neoplasia or polyps. Within the study period, 1000 patients (29 %) qualified for entry from a total of 3480 colonoscopies conducted in our institution. Endoscopic mucosal resection was carried out in appropriate flat and sessile lesions.

RESULTS

Endoscopic mucosal resection was carried out in 599 lesions. Complete histological resection was confirmed in 576 (96 %). Perforation occurred in one patient (0.2 %) and bleeding in 12 (2 %). A total of 254 lesions (40 %; excluding hyperplasia/metaplasia) were flat or depressed, and 374 (60 %) were sessile. Fifty-eight flat lesions (23 %) contained high-grade dysplasia or beyond, compared to 33 sessile lesions (9.0 %; P = 0.001). After resection, 21 lesions were upgraded histologically, with 17 being defined as adenoma with high-grade dysplasia or beyond.

CONCLUSIONS

This study confirms that flat adenomas and carcinomas occur in the West and demonstrates the malignant potential of such lesions, which can be managed successfully using endoscopic techniques. Endoscopic mucosal resection with high-magnification chromoscopy is a safe and effective form of treatment for sessile or flat colorectal lesions. Complete resection can improve the accuracy of histopathological diagnosis. However, colonoscopists require training in these procedures in order to improve the rate of colorectal cancer detection.

Clinical indications for use of fresh frozen plasma in dogs: 74 dogs (October through December 1999)

OBJECTIVE

To document reasons for use of fresh frozen plasma (FFP) in dogs and determine variables that apparently triggered the decision to use FFP.

DESIGN

Retrospective study.

ANIMALS

74 dogs.

PROCEDURE

Medical records of dogs that received FFP at a veterinary teaching hospital during a 3-month period were reviewed.

RESULTS

The 74 dogs underwent 144 transfusion episodes (TE; a TE was defined as 1 day of transfusion therapy) and received 252 units (120 ml/unit) of FFP. Fresh frozen plasma was administered to provide coagulation factors (67 TE), albumin (91), alpha-macroglobulin (15), or immunoglobulins (19); for some TE, multiple clinical indications were identified. Variables that apparently triggered the decision to administer FFP included active hemorrhage with or without prolongation of coagulation times, low total plasma protein concentration, persistent vomiting associated with pancreatitis, and sepsis. Mean doses of FFP for each indication were between 8.5 and 9.4 ml/kg (3.9 and 4.3 ml/lb). Small dogs were generally given higher doses (mean dose, 13.9 ml/kg [6.3 ml/lb]) than large dogs (mean dose, 5.1 ml/kg [2.3 ml/lb]). Fifty (68%) dogs were alive at the time of discharge from the hospital.

CONCLUSIONS AND CLINICAL RELEVANCE

Results suggest that FFP plays an important role in the care of critically ill dogs. Because the supply of FFP is limited, guidelines for when administration of FFP may be clinically useful should be developed.

End-tidal carbon dioxide monitoring for weaning patients: a pilot study

This research pilot study evaluates the usefulness of capnography for patients being weaned from mechanical ventilation in a medical intensive care unit (MICU). The hypothesis that capnography would allow for more rapid weaning from mechanical ventilation, and require fewer arterial blood gases (ABGs) during the process, was found to be untrue. Several implications for critical care nursing practices were derived from the literature review and findings of this study.

What is colitis? Statistical approach to distinguishing clinically important inflammatory change in rectal biopsy specimens

Measurements of mucosal dimension, architecture, and cell counts in both lamina propria and epithelium were made on rectal biopsy specimens from 20 patients with irritable bowel syndrome ("normal" controls); 54 patients with ulcerative colitis, Crohn's disease, and non-specific proctitis; eight patients with small bowel Crohn's disease; and 34 in whom the rectal biopsy specimen was not diagnostic. Discriminant analysis was applied to multiple variables based on the measurements, and three variables were identified as of high predictive value. The most powerful discriminant was increased lamina propria cellularity in all forms of chronic colitis. The ratios of surface length to mucosal length and of surface epithelial height to crypt epithelial height also emerged as discriminants. Chronic inflammatory bowel disease was distinguished from normal in 95% of cases with a definite pathological diagnosis, and 85% of borderline cases were correctly classified as either normal or inflammatory when judged by the final diagnosis after follow up. This study provides a basis for automated diagnosis of rectal biopsy specimens and provides objectively validated criteria which can also be applied in routine histological diagnosis.

The use of an inexpensive, general purpose microcomputer in quantitative cytochemistry

A 32K Commodore Pet microcomputer has been interfaced with two Vickers microdensitometers. This system allows for the simultaneous logging of data from two densitometers being operated independently of each other. Software for the statistical analysis of data generated by the densitometers, and for use with the cytochemical bioassay of hormones, is described. The densitometer/Pet system is relatively cheap, reliable, and readily adaptable to other applications.