GS-align for glycan structure alignment and similarity measurement.

MOTIVATION: Glycans play critical roles in many biological processes, and their structural diversity is key for specific protein-glycan recognition. Comparative structural studies of biological molecules provide useful insight into their biological relationships. However, most computational tools are designed for protein structure, and despite their importance, there is no currently available tool for comparing glycan structures in a sequence order- and size-independent manner. RESULTS: A novel method, GS-align, is developed for glycan structure alignment and similarity measurement. GS-align generates possible alignments between two glycan structures through iterative maximum clique search and fragment superposition. The optimal alignment is then determined by the maximum structural similarity score, GS-score, which is size-independent. Benchmark tests against the Protein Data Bank (PDB) N-linked glycan library and PDB homologous/non-homologous N-glycoprotein sets indicate that GS-align is a robust computational tool to align glycan structures and quantify their structural similarity. GS-align is also applied to template-based glycan structure prediction and monosaccharide substitution matrix generation to illustrate its utility. AVAILABILITY AND IMPLEMENTATION: http://www.glycanstructure.org/gsalign. CONTACT: wonpil@ku.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Following Natures Lead: On the Construction of Membrane-Inserted Toxins in Lipid Bilayer Nanodiscs.

Bacterial toxin or viral entry into the cell often requires cell surface binding and endocytosis. The endosomal acidification induces a limited unfolding/refolding and membrane insertion reaction of the soluble toxins or viral proteins into their translocation competent or membrane inserted states. At the molecular level, the specific orientation and immobilization of the pre-transitioned toxin on the cell surface is often an important prerequisite prior to cell entry. We propose that structures of some toxin membrane insertion complexes may be observed through procedures where one rationally immobilizes the soluble toxin so that potential unfolding â†” refolding transitions that occur prior to membrane insertion orientate away from the immobilization surface in the presence of lipid micelle pre-nanodisc structures. As a specific example, the immobilized prepore form of the anthrax toxin pore translocon or protective antigen can be transitioned, inserted into a model lipid membrane (nanodiscs), and released from the immobilized support in its membrane solubilized form. This particular strategy, although unconventional, is a useful procedure for generating pure membrane-inserted toxins in nanodiscs for electron microscopy structural analysis. In addition, generating a similar immobilized platform on label-free biosensor surfaces allows one to observe the kinetics of these acid-induced membrane insertion transitions. These platforms can facilitate the rational design of inhibitors that specifically target the toxin membrane insertion transitions that occur during endosomal acidification. This approach may lead to a new class of direct anti-toxin inhibitors.

Predicting nucleic acid binding interfaces from structural models of proteins.

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure.

Functional implications of structural predictions for alternative splice proteins expressed in Her2/neu-induced breast cancers.

Alternative splicing allows a single gene to generate multiple mRNA transcripts, which can be translated into functionally diverse proteins. However, experimentally determined structures of protein splice isoforms are rare, and homology modeling methods are poor at predicting atomic-level structural differences because of high sequence identity. Here we exploit the state-of-the-art structure prediction method I-TASSER to analyze the structural and functional consequences of alternative splicing of proteins differentially expressed in a breast cancer model. We first successfully benchmarked the I-TASSER pipeline for structure modeling of all seven pairs of protein splice isoforms, which are known to have experimentally solved structures. We then modeled three cancer-related variant pairs reported to have opposite functions. In each pair, we observed structural differences in regions where the presence or absence of a motif can directly influence the distinctive functions of the variants. Finally, we applied the method to five splice variants overexpressed in mouse Her2/neu mammary tumor: anxa6, calu, cdc42, ptbp1, and tax1bp3. Despite >75% sequence identity between the variants, structural differences were observed in biologically important regions of these protein pairs. These results demonstrate the feasibility of integrating proteomic analysis with structure-based conformational predictions of differentially expressed alternative splice variants in cancers and other conditions.

MM-align: a quick algorithm for aligning multiple-chain protein complex structures using iterative dynamic programming.

Structural comparison of multiple-chain protein complexes is essential in many studies of protein-protein interactions. We develop a new algorithm, MM-align, for sequence-independent alignment of protein complex structures. The algorithm is built on a heuristic iteration of a modified Needleman-Wunsch dynamic programming (DP) algorithm, with the alignment score specified by the inter-complex residue distances. The multiple chains in each complex are first joined, in every possible order, and then simultaneously aligned with cross-chain alignments prevented. The alignments of interface residues are enhanced by an interface-specific weighting factor. MM-align is tested on a large-scale benchmark set of 205 x 3897 non-homologous multiple-chain complex pairs. Compared with a naïve extension of the monomer alignment program of TM-align, the alignment accuracy of MM-align is significantly higher as judged by the average TM-score of the physically-aligned residues. MM-align is about two times faster than TM-align because of omitting the cross-alignment zone of the DP matrix. It also shows that the enhanced alignment of the interfaces helps in identifying biologically relevant protein complex pairs.

QAUST: Protein Function Prediction Using Structure Similarity, Protein Interaction, and Functional Motifs.

The number of available protein sequences in public databases is increasing exponentially. However, a significant percentage of these sequences lack functional annotation, which is essential for the understanding of how biological systems operate. Here, we propose a novel method, Quantitative Annotation of Unknown STructure (QAUST), to infer protein functions, specifically Gene Ontology (GO) terms and Enzyme Commission (EC) numbers. QAUST uses three sources of information: structure information encoded by global and local structure similarity search, biological network information inferred by protein-protein interaction data, and sequence information extracted from functionally discriminative sequence motifs. These three pieces of information are combined by consensus averaging to make the final prediction. Our approach has been tested on 500 protein targets from the Critical Assessment of Functional Annotation (CAFA) benchmark set. The results show that our method provides accurate functional annotation and outperforms other prediction methods based on sequence similarity search or threading. We further demonstrate that a previously unknown function of human tripartite motif-containing 22 (TRIM22) protein predicted by QAUST can be experimentally validated.

Revisiting the Plasmodium falciparum RIFIN family: from comparative genomics to 3D-model prediction.

BACKGROUND: Subtelomeric RIFIN genes constitute the most abundant multigene family in Plasmodium falciparum. RIFIN products are targets for the human immune response and contribute to the antigenic variability of the parasite. They are transmembrane proteins grouped into two sub-families (RIF_A and RIF_B). Although recent data show that RIF_A and RIF_B have different sub-cellular localisations and possibly different functions, the same structural organisation has been proposed for members of the two sub-families. Despite recent advances, our knowledge of the regulation of RIFIN gene expression is still poor and the biological role of the protein products remain obscure. RESULTS: Comparative studies on RIFINs in three clones of P. falciparum (3D7, HB3 and Dd2) by Multidimensional scaling (MDS) showed that gene sequences evolve differently in the 5'upstream, coding, and 3'downstream regions, and suggested a possible role of highly conserved 3' downstream sequences. Despite the expected polymorphism, we found that the overall structure of RIFIN repertoires is conserved among clones suggesting a balance between genetic drift and homogenisation mechanisms which guarantees emergence of novel variants but preserves the functionality of genes. Protein sequences from a bona fide set of 3D7 RIFINs were submitted to predictors of secondary structure elements. In contrast with the previously proposed structural organisation, no signal peptide and only one transmembrane helix were predicted for the majority of RIF_As. Finally, we developed a strategy to obtain a reliable 3D-model for RIF_As. We generated 265 possible structures from 53 non-redundant sequences, from which clustering and quality assessments selected two models as the most representative for putative RIFIN protein structures. CONCLUSION: First, comparative analyses of RIFIN repertoires in different clones of P. falciparum provide insights on evolutionary mechanisms shaping the multigene family. Secondly, we found that members of the two sub-families RIF_As and RIF_Bs have different structural organization in accordance with recent experimental results. Finally, representative models for RIF_As have an "Armadillo-like" fold which is known to promote protein-protein interactions in diverse contexts.

Asymmetric Cryo-EM Structure of Anthrax Toxin Protective Antigen Pore with Lethal Factor N-Terminal Domain.

The anthrax lethal toxin consists of protective antigen (PA) and lethal factor (LF). Understanding both the PA pore formation and LF translocation through the PA pore is crucial to mitigating and perhaps preventing anthrax disease. To better understand the interactions of the LF-PA engagement complex, the structure of the LFN-bound PA pore solubilized by a lipid nanodisc was examined using cryo-EM. CryoSPARC was used to rapidly sort particle populations of a heterogeneous sample preparation without imposing symmetry, resulting in a refined 17 Å PA pore structure with 3 LFN bound. At pH 7.5, the contributions from the three unstructured LFN lysine-rich tail regions do not occlude the Phe clamp opening. The open Phe clamp suggests that, in this translocation-compromised pH environment, the lysine-rich tails remain flexible and do not interact with the pore lumen region.

How many protein-protein interactions types exist in nature?

"Protein quaternary structure universe" refers to the ensemble of all protein-protein complexes across all organisms in nature. The number of quaternary folds thus corresponds to the number of ways proteins physically interact with other proteins. This study focuses on answering two basic questions: Whether the number of protein-protein interactions is limited and, if yes, how many different quaternary folds exist in nature. By all-to-all sequence and structure comparisons, we grouped the protein complexes in the protein data bank (PDB) into 3,629 families and 1,761 folds. A statistical model was introduced to obtain the quantitative relation between the numbers of quaternary families and quaternary folds in nature. The total number of possible protein-protein interactions was estimated around 4,000, which indicates that the current protein repository contains only 42% of quaternary folds in nature and a full coverage needs approximately a quarter century of experimental effort. The results have important implications to the protein complex structural modeling and the structure genomics of protein-protein interactions.

Protein-protein complex structure predictions by multimeric threading and template recombination.

The total number of protein-protein complex structures currently available in the Protein Data Bank (PDB) is six times smaller than the total number of tertiary structures in the PDB, which limits the power of homology-based approaches to complex structure modeling. We present a threading-recombination approach, COTH, to boost the protein complex structure library by combining tertiary structure templates with complex alignments. The query sequences are first aligned to complex templates using a modified dynamic programming algorithm, guided by ab initio binding-site predictions. The monomer alignments are then shifted to the multimeric template framework by structural alignments. COTH was tested on 500 nonhomologous dimeric proteins, which can successfully detect correct templates for 50% of the cases after homologous templates are excluded, which significantly outperforms conventional homology modeling algorithms. It also shows a higher accuracy in interface modeling than rigid-body docking of unbound structures from ZDOCK although with lower coverage. These data demonstrate new avenues to model complex structures from nonhomologous templates.