Prediction Of The Protein Complex Assembly Pathway Using Multiple Docking Algorithm

Proteins often function as a complex of multiple subunits, and the quaternary structure is important for proper function. An ordered assembly pathway is one of the strategies nature has developed to obtain the correct conformation: studies have shown a relationship between the assembly pathway and evolution of protein complexes. Identification of the assembly pathway and the intermediate structures helps drug development as well. Therefore, elucidation of the assembly pathway of protein complexes is important for understanding biochemical processes central to cellular function. Recent studies have demonstrated the assembly pathway of a protein complex can be predicted from its crystal structure by comparing the buried surface area (BSA) between each subunit. To our knowledge, this is the first and only work that has predicted the assembly pathways of protein complexes from their structure. In this work, we have developed four methods to predict the assembly pathway from the output of Multi-LZerD, a multiple docking algorithm for asymmetric protein complexes. We found that data from Multi-LZerD predicted not only the model of the complex but also suggested how the complex is assembled. The four methods were benchmarked, along with the BSA-based method, using a dataset of manually-curated protein complexes. In contrast with the data set used in the BSA-based method, which only contained homomeric and symmetric complexes, our data set includes asymmetric complexes varying in size, topology, and number of subunits. We confirmed that the BSA based-method also worked with asymmetric complexes as they predict the correct pathway in 68% of the cases in our data set. Although the success rate of our methods ranges from 40% to 52%, it improved to as high as 82% for the complexes where Multi-LZerD was successful in modeling near native structures. The results also showed that our method is capable of capturing some of the dimerization events in the assembly pathway, even if the overall pathway prediction was failing. Additionally, there was a case where the BSA-based method failed, but our method was successful, suggesting the limitations in the BSA-based method. These results demonstrate the ability of a multiple docking algorithm to predict the assembly pathway of protein complexes

PEPOP: Computational design of immunogenic peptides

© 2008 Moreau et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Protein-protein docking using region-based 3D Zernike descriptors

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur.</p> <p>Results</p> <p>We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-<it>α</it>RMSD ≤ 2.5 Å) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases.</p> <p>Conclusion</p> <p>We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.</p

Lys169 of Human Glucokinase Is a Determinant for Glucose Phosphorylation: Implication for the Atomic Mechanism of Glucokinase Catalysis

Glucokinase (GK), a glucose sensor, maintains plasma glucose homeostasis via phosphorylation of glucose and is a potential therapeutic target for treating maturity-onset diabetes of the young (MODY) and persistent hyperinsulinemic hypoglycemia of infancy (PHHI). To characterize the catalytic mechanism of glucose phosphorylation by GK, we combined molecular modeling, molecular dynamics (MD) simulations, quantum mechanics/molecular mechanics (QM/MM) calculations, experimental mutagenesis and enzymatic kinetic analysis on both wild-type and mutated GK. Our three-dimensional (3D) model of the GK-Mg2+-ATP-glucose (GMAG) complex, is in agreement with a large number of mutagenesis data, and elucidates atomic information of the catalytic site in GK for glucose phosphorylation. A 10-ns MD simulation of the GMAG complex revealed that Lys169 plays a dominant role in glucose phosphorylation. This prediction was verified by experimental mutagenesis of GK (K169A) and enzymatic kinetic analyses of glucose phosphorylation. QM/MM calculations were further used to study the role of Lys169 in the catalytic mechanism of the glucose phosphorylation and we found that Lys169 enhances the binding of GK with both ATP and glucose by serving as a bridge between ATP and glucose. More importantly, Lys169 directly participates in the glucose phosphorylation as a general acid catalyst. Our findings provide mechanistic details of glucose phorphorylation catalyzed by GK, and are important for understanding the pathogenic mechanism of MODY

Fibronectin Contributes To Notochord Intercalation In The Invertebrate Chordate, Ciona Intestinalis

Background: Genomic analysis has upended chordate phylogeny, placing the tunicates as the sister group to the vertebrates. This taxonomic rearrangement raises questions about the emergence of a tunicate/vertebrate ancestor. Results: Characterization of developmental genes uniquely shared by tunicates and vertebrates is one promising approach for deciphering developmental shifts underlying acquisition of novel, ancestral traits. The matrix glycoprotein Fibronectin (FN) has long been considered a vertebrate-specific gene, playing a major instructive role in vertebrate embryonic development. However, the recent computational prediction of an orthologous “vertebrate-like” Fn gene in the genome of a tunicate, Ciona savignyi, challenges this viewpoint suggesting that Fn may have arisen in the shared tunicate/vertebrate ancestor. Here we verify the presence of a tunicate Fn ortholog. Transgenic reporter analysis was used to characterize a Ciona Fn enhancer driving expression in the notochord. Targeted knockdown in the notochord lineage indicates that FN is required for proper convergent extension. Conclusions: These findings suggest that acquisition of Fn was associated with altered notochord morphogenesis in the vertebrate/tunicate ancestor

DmCatD, a cathepsin D-like peptidase of the hematophagous insect Dipetalogaster maxima (Hemiptera: Reduviidae): Purification, bioinformatic analyses and the significance of its interaction with lipophorin in the internalization by developing oocytes

DmCatD, a cathepsin D-like peptidase of the hematophagous insect Dipetalogaster maxima, is synthesized by the fat body and the ovary and functions as yolk protein precursor. Functionally, DmCatD is involved in vitellin proteolysis. In this work, we purified and sequenced DmCatD, performed bioinformatic analyses and investigated the events involved in its targeting and storage in developing oocytes. By ion exchange and gel filtration chromatography, DmCatD was purified from egg homogenates and its identity was confirmed by mass spectrometry. Approximately 73% of the full-length transcript was sequenced. The phylogeny indicated that DmCatD has features which suggest its distancing from “classical” cathepsins D. Bioinformatic analyses using a chimeric construct were employed to predict post-translational modifications. Structural modeling showed that DmCatD exhibited the expected folding for this type of enzyme, and an active site with conserved architecture. The interaction between DmCatD and lipophorin in the hemolymph was demonstrated by co-immunoprecipitation. Colocalization of both proteins in developing oocyte membranes and yolk bodies was detected by immunofluorescence. Docking assays favoring the interaction DmCatD-lipophorin were carried out after modeling lipophorin of a related triatomine species. Our results suggest that lipophorin acts as a carrier for DmCatD to facilitate its further internalization by the oocytes. The mechanisms involved in the uptake of peptidases within the oocytes of insects have not been reported. This is the first experimental work supporting the interaction between cathepsin D and lipophorin in an insect species, enabling us to propose a pathway for its targeting and storage in developing oocytes.Fil: Leyria, Jimena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Bioquímica Clínica; ArgentinaFil: Fruttero, Leonardo Luis. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Bioquímica Clínica; Argentina. Pontificia Universidade Católica do Rio Grande do Sul; Brasil. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; ArgentinaFil: Ligabue Braun, Rodrigo. Universidade Federal do Rio Grande do Sul; BrasilFil: Defferrari, Marina S.. University of Toronto; CanadáFil: Arrese, Estela L.. Oklahoma State University; Estados UnidosFil: Soulages, José L.. Oklahoma State University; Estados UnidosFil: Settembrini, Beatriz Patricia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales “Bernardino Rivadavia”; ArgentinaFil: Carlini, Célia Regina R S. Pontificia Universidade Católica do Rio Grande do Sul; BrasilFil: Canavoso, Lilian Etelvina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Bioquímica Clínica; Argentin

CD, UV, and In Silico Insights on the Effect of 1,3-Bis(1′-uracilyl)-2-propanone on Serum Albumin Structure

1,3-diaryl-2-propanone derivatives are synthetic compounds used as building blocks for the realization not only of antimicrobial drugs but also of new nanomaterials thanks to their ability to self-assemble in solution and interact with nucleopeptides. However, their ability to interact with proteins is a scarcely investigated theme considering the therapeutic importance that 1,3-diaryl-2-propanones could have in the modulation of protein-driven processes. Within this scope, we investigated the protein binding ability of 1,3-bis(1'-uracilyl)-2-propanone, which was previously synthesized in our laboratory utilizing a Dakin-West reaction and herein indicated as U2O, using bovine serum albumin (BSA) as the model protein. Through circular dichroism (CD) and UV spectroscopy, we demonstrated that the compound, but not the similar thymine derivative T2O, was able to alter the secondary structure of the serum albumin leading to significant consequences in terms of BSA structure with respect to the unbound protein (Δβ-turn + Δβ-sheet = +23.6%, Δα = -16.7%) as revealed in our CD binding studies. Moreover, molecular docking studies suggested that U2O is preferentially housed in the domain IIIB of the protein, and its affinity for the albumin is higher than that of the reference ligand HA 14-1 (HDOCK score (top 1-3 poses): -157.11 ± 1.38 (U2O); -129.80 ± 6.92 (HA 14-1); binding energy: -7.6 kcal/mol (U2O); -5.9 kcal/mol (HA 14-1)) and T2O (HDOCK score (top 1-3 poses): -149.93 ± 2.35; binding energy: -7.0 kcal/mol). Overall, the above findings suggest the ability of 1,3-bis(1'-uracilyl)-2-propanone to bind serum albumins and the observed reduction of the α-helix structure with the concomitant increase in the β-structure are consistent with a partial protein destabilization due to the interaction with U2O

Three-dimensional Structure of Victorivirus HvV190S Suggests Coat Proteins in Most Totiviruses Share a Conserved Core

Double-stranded (ds)RNA fungal viruses are currently assigned to six different families. Those from the family Totiviridae are characterized by nonsegmented genomes and single-layer capsids, 300–450 Å in diameter. Helminthosporium victoriae virus 190S (HvV190S), prototype of recently recognized genus Victorivirus, infects the filamentous fungus Helminthosporium victoriae (telomorph: Cochliobolus victoriae), which is the causal agent of Victoria blight of oats. The HvV190S genome is 5179 bp long and encompasses two large, slightly overlapping open reading frames that encode the coat protein (CP, 772 aa) and the RNA-dependent RNA polymerase (RdRp, 835 aa). To our present knowledge, victoriviruses uniquely express their RdRps via a coupled termination–reinitiation mechanism that differs from the well-characterized Saccharomyces cerevisiae virus L-A (ScV-L-A, prototype of genus Totivirus), in which the RdRp is expressed as a CP/RdRp fusion protein due to ribosomal frameshifting. Here, we used transmission electron cryomicroscopy and three-dimensional image reconstruction to determine the structures of HvV190S virions and two types of virus-like particles (capsids lacking dsRNA and capsids lacking both dsRNA and RdRp) at estimated resolutions of 7.1, 7.5, and 7.6 Å, respectively. The HvV190S capsid is thin and smooth, and contains 120 copies of CP arranged in a “T = 2” icosahedral lattice characteristic of ScV-L-A and other dsRNA viruses. For aid in our interpretations, we developed and used an iterative segmentation procedure to define the boundaries of the two, chemically identical CP subunits in each asymmetric unit. Both subunits have a similar fold, but one that differs from ScV-L-A in many details except for a core α-helical region that is further predicted to be conserved among many other totiviruses. In particular, we predict the structures of other victoriviruses to be highly similar to HvV190S and the structures of most if not all totiviruses including, Leishmania RNA virus 1, to be similar as well

In silico identification of new putative pathogenic variants in the NEU1 sialidase gene affecting enzyme function and subcellular localization

The NEU1 gene is the first identified member of the human sialidases, glycohydrolitic enzymes that remove the terminal sialic acid from oligosaccharide chains. Mutations in NEU1 gene are causative of sialidosis (MIM 256550), a severe lysosomal storage disorder showing autosomal recessive mode of inheritance. Sialidosis has been classified into two subtypes: sialidosis type I, a normomorphic, late-onset form, and sialidosis type II, a more severe neonatal or early-onset form. A total of 50 causative mutations are reported in HGMD database, most of which are missense variants. To further characterize the NEU1 gene and identify new functionally relevant protein isoforms, we decided to study its genetic variability in the human population using the data generated by two large sequencing projects: the 1000 Genomes Project (1000G) and the NHLBI GO Exome Sequencing Project (ESP). Together these two datasets comprise a cohort of 7595 sequenced individuals, making it possible to identify rare variants and dissect population specific ones. By integrating this approach with biochemical and cellular studies, we were able to identify new rare missense and frameshift alleles in NEU1 gene. Among the 9 candidate variants tested, only two resulted in significantly lower levels of sialidase activity (pC and c.700G>A. These two mutations give rise to the amino acid substitutions p.V217A and p.D234N, respectively. NEU1 variants including either of these two amino acid changes have 44% and 25% residual sialidase activity when compared to the wild-type enzyme, reduced protein levels and altered subcellular localization. Thus they may represent new, putative pathological mutations resulting in sialidosis type I. The in silico approach used in this study has enabled the identification of previously unknown NEU1 functional alleles that are widespread in the population and could be tested in future functional studies

Efficient search and comparison algorithms for 3D protein binding site retrieval and structure alignment from large-scale databases

Finding similar 3D structures is crucial for discovering potential structural, evolutionary, and functional relationships among proteins. As the number of known protein structures has dramatically increased, traditional methods can no longer provide the life science community with the adequate informatics capability needed to conduct large-scale and complex analyses. A suite of high-throughput and accurate protein structure search and comparison methods is essential. To meet the needs of the community, we develop several bioinformatics methods for protein binding site comparison and global structure alignment. First, we developed an efficient protein binding site search that is based on extracting geometric features both locally and globally. The main idea of this work was to capture spatial relationships among landmarks of binding site surfaces and bfuild a vocabulary of visual words to represent the characteristics of the surfaces. A vector model was then used to speed up the search of similar surfaces that share similar visual words with the query interface. Second, we developed an approach for accurate protein binding site comparison. Our algorithm provides an accurate binding site alignment by applying a two-level heuristic process which progressively refines alignment results from coarse surface point level to accurate residue atom level. This setting allowed us to explore different combinations of pairs of corresponding residues, thus improving the alignment quality of the binding site surfaces. Finally, we introduced a parallel algorithm for global protein structure alignment. Specifically, to speed up the time-consuming structure alignment process of protein 3D structures, we designed a parallel protein structure alignment framework to exploit the parallelism of Graphics Processing Units (GPUs). As a general-purpose GPU platform, the framework is capable of parallelizing traditional structure alignment algorithms. Our findings can be applied in various research areas, such as prediction of protein inte