Carlos J. Madrid-Aliste

M4T: a comparative protein structure modeling server

Multiple Mapping Method with Multiple Templates (M4T) (http://www.fiserlab.org/servers/m4t) is a fully automated comparative protein structure modeling server. The novelty of M4T resides in two of its major modules, Multiple Templates (MT) and Multiple Mapping Method (MMM). The MT module of M4T selects and optimally combines the sequences of multiple template structures through an iterative clustering approach that takes into account the ‘unique’ contribution of each template, its sequence similarity to other template sequences and to the target sequences, and the quality of its experimental resolution. MMM module is a sequence-to-structure alignment method that is aimed at improving the alignment accuracy, especially at lower sequence identity levels. The current implementation of MMM takes inputs from three profile-to-profile-based alignment methods and iteratively compares and ranks alternatively aligned regions according to their fit in the structural environment of the template structure. The performance of M4T was benchmarked on CASP6 comparative modeling target sequences and on a larger independent test set and showed a favorable performance to current state-of-the-art methods.

Trends in structural coverage of the protein universe and the impact of the Protein Structure Initiative

Significance The Protein Structure Initiative and related worldwide efforts are engaged in the large-scale structural annotation of proteins. In this work, we investigated the dynamic changes that have occurred in this complex race, where sequence databases double every 1.5 y but are becoming increasingly redundant and have exhibited profound changes in taxonomic composition over the last 5 y. Meanwhile, the number of known protein structures is approximately 200 times smaller, and the pace of discovery of new folds is slowing. Nevertheless, the overall structural coverage of proteins has increased from 30% to 40% over the last 10 y. Assuming current trends, ∼55% coverage will be achieved within 15 y, a level considered sufficient to fully characterize the metabolic network of an organism. The exponential growth of protein sequence data provides an ever-expanding body of unannotated and misannotated proteins. The National Institutes of Health-supported Protein Structure Initiative and related worldwide structural genomics efforts facilitate functional annotation of proteins through structural characterization. Recently there have been profound changes in the taxonomic composition of sequence databases, which are effectively redefining the scope and contribution of these large-scale structure-based efforts. The faster-growing bacterial genomic entries have overtaken the eukaryotic entries over the last 5 y, but also have become more redundant. Despite the enormous increase in the number of sequences, the overall structural coverage of proteins—including proteins for which reliable homology models can be generated—on the residue level has increased from 30% to 40% over the last 10 y. Structural genomics efforts contributed ∼50% of this new structural coverage, despite determining only ∼10% of all new structures. Based on current trends, it is expected that ∼55% structural coverage (the level required for significant functional insight) will be achieved within 15 y, whereas without structural genomics efforts, realizing this goal will take approximately twice as long.

The Histone Code of Toxoplasma gondii Comprises Conserved and Unique Posttranslational Modifications

ABSTRACT Epigenetic gene regulation has emerged as a major mechanism for gene regulation in all eukaryotes. Histones are small, basic proteins that constitute the major protein component of chromatin, and posttranslational modifications (PTM) of histones are essential for epigenetic gene regulation. The different combinations of histone PTM form the histone code for an organism, marking functional units of chromatin that recruit macromolecular complexes that govern chromatin structure and regulate gene expression. To characterize the repertoire of Toxoplasma gondii histone PTM, we enriched histones using standard acid extraction protocols and analyzed them with several complementary middle-down and bottom-up proteomic approaches with the high-resolution Orbitrap mass spectrometer using collision-induced dissociation (CID), higher-energy collisional dissociation (HCD), and/or electron transfer dissociation (ETD) fragmentation. We identified 249 peptides with unique combinations of PTM that comprise the T. gondii histone code. T. gondii histones share a high degree of sequence conservation with human histones, and many modifications are conserved between these species. In addition, T. gondii histones have unique modifications not previously identified in other species. Finally, T. gondii histones are modified by succinylation, propionylation, and formylation, recently described histone PTM that have not previously been identified in parasitic protozoa. The characterization of the T. gondii histone code will facilitate in-depth analysis of how epigenetic regulation affects gene expression in pathogenic apicomplexan parasites and identify a new model system for elucidating the biological functions of novel histone PTM. IMPORTANCE Toxoplasma gondii is among the most common parasitic infections in humans. The transition between the different stages of the T. gondii life cycle are essential for parasite virulence and survival. These differentiation events are accompanied by significant changes in gene expression, and the control mechanisms for these transitions have not been elucidated. Important mechanisms that are involved in the control of gene expression are the epigenetic modifications that have been identified in several eukaryotes. T. gondii has a full complement of histone-modifying enzymes, histones, and variants. In this paper, we identify over a hundred PTM and a full repertoire of PTM combinations for T. gondii histones, providing the first large-scale characterization of the T. gondii histone code and an essential initial step for understanding how epigenetic modifications affect gene expression and other processes in this organism. Toxoplasma gondii is among the most common parasitic infections in humans. The transition between the different stages of the T. gondii life cycle are essential for parasite virulence and survival. These differentiation events are accompanied by significant changes in gene expression, and the control mechanisms for these transitions have not been elucidated. Important mechanisms that are involved in the control of gene expression are the epigenetic modifications that have been identified in several eukaryotes. T. gondii has a full complement of histone-modifying enzymes, histones, and variants. In this paper, we identify over a hundred PTM and a full repertoire of PTM combinations for T. gondii histones, providing the first large-scale characterization of the T. gondii histone code and an essential initial step for understanding how epigenetic modifications affect gene expression and other processes in this organism.

Improved scoring function for comparative modeling using the M4T method

Improvements in comparative protein structure modeling for the remote target-template sequence similarity cases are possible through the optimal combination of multiple template structures and by improving the quality of target-template alignment. Recently developed MMM and M4T methods were designed to address these problems. Here we describe new developments in both the alignment generation and the template selection parts of the modeling algorithms. We set up a new scoring function in MMM to deliver more accurate target-template alignments. This was achieved by developing and incorporating into the composite scoring function a novel statistical pairwise potential that combines local and non-local terms. The non-local term of the statistical potential utilizes a shuffled reference state definition that helped to eliminate most of the false positive signal from the background distribution of pairwise contacts. The accuracy of the scoring function was further increased by using BLOSUM mutation table scores.

MMM: a sequence-to-structure alignment protocol

MOTIVATION Accurate alignment of a target sequence to a template structure continues to be a bottleneck in producing good quality comparative protein structure models. RESULTS Multiple Mapping Method (MMM) is a comparative protein structure modeling server with an emphasis on a novel alignment optimization protocol. MMM takes inputs from five profile-to-profile based alignment methods. The alternatively aligned regions from the input alignment set are combined according to their fit in the structural environment of the template structure. The resulting, optimally spliced MMM alignment is used as input to an automated comparative modeling module to produce a full atom model. AVAILABILITY The MMM server is freely accessible at http://www.fiserlab.org/servers/mmm

Computational Analysis and Experimental Validation of Gene Predictions in Toxoplasma gondii

Background Toxoplasma gondii is an obligate intracellular protozoan that infects 20 to 90% of the population. It can cause both acute and chronic infections, many of which are asymptomatic, and, in immunocompromized hosts, can cause fatal infection due to reactivation from an asymptomatic chronic infection. An essential step towards understanding molecular mechanisms controlling transitions between the various life stages and identifying candidate drug targets is to accurately characterize the T. gondii proteome. Methodology/Principal Findings We have explored the proteome of T. gondii tachyzoites with high throughput proteomics experiments and by comparison to publicly available cDNA sequence data. Mass spectrometry analysis validated 2,477 gene coding regions with 6,438 possible alternative gene predictions; approximately one third of the T. gondii proteome. The proteomics survey identified 609 proteins that are unique to Toxoplasma as compared to any known species including other Apicomplexan. Computational analysis identified 787 cases of possible gene duplication events and located at least 6,089 gene coding regions. Commonly used gene prediction algorithms produce very disparate sets of protein sequences, with pairwise overlaps ranging from 1.4% to 12%. Through this experimental and computational exercise we benchmarked gene prediction methods and observed false negative rates of 31 to 43%. Conclusions/Significance This study not only provides the largest proteomics exploration of the T. gondii proteome, but illustrates how high throughput proteomics experiments can elucidate correct gene structures in genomes.

EPIC-DB: A proteomics database for studying Apicomplexan organisms

BackgroundHigh throughput proteomics experiments are useful for analyzing the protein expression of an organism, identifying the correct gene structure of a genome, or locating possible post-translational modifications within proteins. High throughput methods necessitate publicly accessible and easily queried databases for efficiently and logically storing, displaying, and analyzing the large volume of data.DescriptionEPICDB is a publicly accessible, queryable, relational database that organizes and displays experimental, high throughput proteomics data for Toxoplasma gondii and Cryptosporidium parvum. Along with detailed information on mass spectrometry experiments, the database also provides antibody experimental results and analysis of functional annotations, comparative genomics, and aligned expressed sequence tag (EST) and genomic open reading frame (ORF) sequences. The database contains all available alternative gene datasets for each organism, which comprises a complete theoretical proteome for the respective organism, and all data is referenced to these sequences. The database is structured around clusters of protein sequences, which allows for the evaluation of redundancy, protein prediction discrepancies, and possible splice variants. The database can be expanded to include genomes of other organisms for which proteome-wide experimental data are available.ConclusionEPICDB is a comprehensive database of genome-wide T. gondii and C. parvum proteomics data and incorporates many features that allow for the analysis of the entire proteomes and/or annotation of specific protein sequences. EPICDB is complementary to other -genomics- databases of these organisms by offering complete mass spectrometry analysis on a comprehensive set of all available protein sequences.

Modularity of Protein Folds as a Tool for Template-Free Modeling of Structures.

Predicting the three-dimensional structure of proteins from their amino acid sequences remains a challenging problem in molecular biology. While the current structural coverage of proteins is almost exclusively provided by template-based techniques, the modeling of the rest of the protein sequences increasingly require template-free methods. However, template-free modeling methods are much less reliable and are usually applicable for smaller proteins, leaving much space for improvement. We present here a novel computational method that uses a library of supersecondary structure fragments, known as Smotifs, to model protein structures. The library of Smotifs has saturated over time, providing a theoretical foundation for efficient modeling. The method relies on weak sequence signals from remotely related protein structures to create a library of Smotif fragments specific to the target protein sequence. This Smotif library is exploited in a fragment assembly protocol to sample decoys, which are assessed by a composite scoring function. Since the Smotif fragments are larger in size compared to the ones used in other fragment-based methods, the proposed modeling algorithm, SmotifTF, can employ an exhaustive sampling during decoy assembly. SmotifTF successfully predicts the overall fold of the target proteins in about 50% of the test cases and performs competitively when compared to other state of the art prediction methods, especially when sequence signal to remote homologs is diminishing. Smotif-based modeling is complementary to current prediction methods and provides a promising direction in addressing the structure prediction problem, especially when targeting larger proteins for modeling.

Buprenorphine Decreases the CCL2-Mediated Chemotactic Response of Monocytes

Despite successful combined antiretroviral therapy, ∼60% of HIV-infected people exhibit HIV-associated neurocognitive disorders (HAND). CCL2 is elevated in the CNS of infected people with HAND and mediates monocyte influx into the CNS, which is critical in neuroAIDS. Many HIV-infected opiate abusers have increased neuroinflammation that may augment HAND. Buprenorphine is used to treat opiate addiction. However, there are few studies that examine its impact on HIV neuropathogenesis. We show that buprenorphine reduces the chemotactic phenotype of monocytes. Buprenorphine decreases the formation of membrane projections in response to CCL2. It also decreases CCL2-induced chemotaxis and mediates a delay in reinsertion of the CCL2 receptor, CCR2, into the cell membrane after CCL2-mediated receptor internalization, suggesting a mechanism of action of buprenorphine. Signaling pathways in CCL2-induced migration include increased phosphorylation of p38 MAPK and of the junctional protein JAM-A. We show that buprenorphine decreases these phosphorylations in CCL2-treated monocytes. Using DAMGO, CTAP, and Nor-BNI, we demonstrate that the effect of buprenorphine on CCL2 signaling is opioid receptor mediated. To identify additional potential mechanisms by which buprenorphine inhibits CCL2-induced monocyte migration, we performed proteomic analyses to characterize additional proteins in monocytes whose phosphorylation after CCL2 treatment was inhibited by buprenorphine. Leukosialin and S100A9 were identified and had not been shown previously to be involved in monocyte migration. We propose that buprenorphine limits CCL2-mediated monocyte transmigration into the CNS, thereby reducing neuroinflammation characteristic of HAND. Our findings underscore the use of buprenorphine as a therapeutic for neuroinflammation as well as for addiction.