HorA web server to infer homology between proteins using sequence and structural similarity

Structural Basis for Regulation of GPR56/ADGRG1 by Its Alternatively Spliced Extracellular Domains

Adhesion G protein-coupled receptors (aGPCRs) play critical roles in diverse neurobiological processes including brain development, synaptogenesis, and myelination. aGPCRs have large alternatively spliced extracellular regions (ECRs) that likely mediate intercellular signaling; however, the precise roles of ECRs remain unclear. The aGPCR GPR56/ADGRG1 regulates both oligodendrocyte and cortical development. Accordingly, human GPR56 mutations cause myelination defects and brain malformations. Here, we determined the crystal structure of the GPR56 ECR, the first structure of any complete aGPCR ECR, in complex with an inverse-agonist monobody, revealing a GPCR-Autoproteolysis-Inducing domain and a previously unidentified domain that we term Pentraxin/Laminin/neurexin/sex-hormone-binding-globulin-Like (PLL). Strikingly, PLL domain deletion caused increased signaling and characterizes a GPR56 splice variant. Finally, we show that an evolutionarily conserved residue in the PLL domain is critical for oligodendrocyte development in vivo. Thus, our results suggest that the GPR56 ECR has unique and multifaceted regulatory functions, providing novel insights into aGPCR roles in neurobiology.

A vocabulary of ancient peptides at the origin of folded proteins

The seemingly limitless diversity of proteins in nature arose from only a few thousand domain prototypes, but the origin of these themselves has remained unclear. We are pursuing the hypothesis that they arose by fusion and accretion from an ancestral set of peptides active as co-factors in RNA-dependent replication and catalysis. Should this be true, contemporary domains may still contain vestiges of such peptides, which could be reconstructed by a comparative approach in the same way in which ancient vocabularies have been reconstructed by the comparative study of modern languages. To test this, we compared domains representative of known folds and identified 40 fragments whose similarity is indicative of common descent, yet which occur in domains currently not thought to be homologous. These fragments are widespread in the most ancient folds and enriched for iron-sulfur- and nucleic acid-binding. We propose that they represent the observable remnants of a primordial RNA-peptide world.

Manual classification strategies in the ECOD database

ECOD (Evolutionary Classification Of protein Domains) is a comprehensive and up-to-date protein structure classification database. The majority of new structures released from the PDB (Protein Data Bank) each week already have close homologs in the ECOD hierarchy and thus can be reliably partitioned into domains and classified by software without manual intervention. However, those proteins that lack confidently detectable homologs require careful analysis by experts. Although many bioinformatics resources rely on expert curation to some degree, specific examples of how this curation occurs and in what cases it is necessary are not always described. Here, we illustrate the manual classification strategy in ECOD by example, focusing on two major issues in protein classification: domain partitioning and the relationship between homology and similarity scores. Most examples show recently released and manually classified PDB structures. We discuss multi-domain proteins, discordance between sequence and structural similarities, difficulties with assessing homology with scores, and integral membrane proteins homologous to soluble proteins. By timely assimilation of newly available structures into its hierarchy, ECOD strives to provide a most accurate and updated view of the protein structure world as a result of combined computational and expert-driven analysis.

ECOD: an evolutionary classification of protein domains

Understanding the evolution of a protein, including both close and distant relationships, often reveals insight into its structure and function. Fast and easy access to such up-to-date information facilitates research. We have developed a hierarchical evolutionary classification of all proteins with experimentally determined spatial structures, and presented it as an interactive and updatable online database. ECOD (Evolutionary Classification of protein Domains) is distinct from other structural classifications in that it groups domains primarily by evolutionary relationships (homology), rather than topology (or "fold"). This distinction highlights cases of homology between domains of differing topology to aid in understanding of protein structure evolution. ECOD uniquely emphasizes distantly related homologs that are difficult to detect, and thus catalogs the largest number of evolutionary links among structural domain classifications. Placing distant homologs together underscores the ancestral similarities of these proteins and draws attention to the most important regions of sequence and structure, as well as conserved functional sites. ECOD also recognizes closer sequence-based relationships between protein domains. Currently, approximately 100,000 protein structures are classified in ECOD into 9,000 sequence families clustered into close to 2,000 evolutionary groups. The classification is assisted by an automated pipeline that quickly and consistently classifies weekly releases of PDB structures and allows for continual updates. This synchronization with PDB uniquely distinguishes ECOD among all protein classifications. Finally, we present several case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies.

Conserved evolutionary units in the heme-copper oxidase superfamily revealed by novel homologous protein families

The heme-copper oxidase (HCO) superfamily includes HCOs in aerobic respiratory chains and nitric oxide reductases (NORs) in the denitrification pathway. The HCO/NOR catalytic subunit has a core structure consisting of 12 transmembrane helices (TMHs) arranged in three-fold rotational pseudosymmetry, with six conserved histidines for heme and metal binding. Using sensitive sequence similarity searches, we detected a number of novel HCO/NOR homologs and named them HCO Homology (HCOH) proteins. Several HCOH families possess only four TMHs that exhibit the most pronounced similarity to the last four TMHs (TMHs 9-12) of HCOs/NORs. Encoded by independent genes, four-TMH HCOH proteins represent a single evolutionary unit (EU) that relates to each of the three homologous EUs of HCOs/NORs comprising TMHs 1-4, TMHs 5-8, and TMHs 9-12. Single-EU HCOH proteins could form homotrimers or heterotrimers to maintain the general structure and ligand-binding sites defined by the HCO/NOR catalytic subunit fold. The remaining HCOH families, including NnrS, have 12-TMHs and three EUs. Most three-EU HCOH proteins possess two conserved histidines and could bind a single heme. Limited experimental studies and genomic context analysis suggest that many HCOH proteins could function in the denitrification pathway and in detoxification of reactive molecules such as nitric oxide. HCO/NOR catalytic subunits exhibit remarkable structural similarity to the homotrimers of MAPEG (membrane-associated proteins in eicosanoid and glutathione metabolism) proteins. Gene duplication, fusion, and fission likely play important roles in the evolution of HCOs/NORs and HCOH proteins.

In silico investigation and structural characterization of virulent factor and a metallo peptidase present in Helicobacter pylori strain J99

VacA is a high-molecular weight multimeric pore-forming protein encoded by the chromosomal gene vacA of Helicobacter pylori J99 strian. It plays a significant role in the development of gastric cancer in human by inducing the formation of vacuoles. Genomics and proteomics features of an organism have provided a plethora of potential drug targets. The crystal structure of VacA is not available in any structural database; hence a 3D structure is very essential for structural studies and discovery of potential inhibitors against proteins. In this study 3D structure of VacA is modelled a by using Bhageerath: an energy based web enabled computer software suite. According to our study VacA steriochemical validation shows 91.7% residues are in allowed region of Ramachandran plot. Further validation was done by WHAT CHECK to provide evidence that the distribution of the main chain bond lengths and omega bond angles were within limits with Z-score 1.0 and error values are negligible. The modelled protein was submitted to Protein Model Database and can be downloaded with PMDID PM0077963. Further we found that metallo peptidase "M3" cleaves VacA and helps in import mechanism in mitochondria. Structure of metallo peptidase is also not available in any structural database so we modelled and validated its structure. With the help of docking studies we blocked the active site of metallo peptidase by ligand LA3 and 294 with binding energy -5.9 and -5.2 KJ/mol respectively, thus prevented import mechanism of VacA in mitochondria. The inhibitors identified from our study were LA3 and 294 ligands. The investigation concluded that these drugs could be used as the potential inhibitors against the damage of stomach and duodenum, which ultimately reduces the likelihood of ulcer as well as gastric cancer.

CASP9 target classification

The Critical assessment of protein structure prediction round 9 (CASP9) aimed to evaluate predictions for 129 experimentally determined protein structures. To assess tertiary structure predictions, these target structures were divided into domain-based evaluation units that were then classified into two assessment categories: template based modeling (TBM) and template free modeling (FM). CASP9 targets were split into domains of structurally compact evolutionary modules. For the targets with more than one defined domain, the decision to split structures into domains for evaluation was based on server performance. Target domains were categorized based on their evolutionary relatedness to existing templates as well as their difficulty levels indicated by server performance. Those target domains with sequence-related templates and high server prediction performance were classified as TMB, whereas those targets without identifiable templates and low server performance were classified as FM. However, using these generalizations for classification resulted in a blurred boundary between CASP9 assessment categories. Thus, the FM category included those domains without sequence detectable templates (25 target domains) as well as some domains with difficult to detect templates whose predictions were as poor as those without templates (five target domains). Several interesting examples are discussed, including targets with sequence related templates that exhibit unusual structural differences, targets with homologous or analogous structure templates that are not detectable by sequence, and targets with new folds.

iPBA: a tool for protein structure comparison using sequence alignment strategies

With the immense growth in the number of available protein structures, fast and accurate structure comparison has been essential. We propose an efficient method for structure comparison, based on a structural alphabet. Protein Blocks (PBs) is a widely used structural alphabet with 16 pentapeptide conformations that can fairly approximate a complete protein chain. Thus a 3D structure can be translated into a 1D sequence of PBs. With a simple Needleman–Wunsch approach and a raw PB substitution matrix, PB-based structural alignments were better than many popular methods. iPBA web server presents an improved alignment approach using (i) specialized PB Substitution Matrices (SM) and (ii) anchor-based alignment methodology. With these developments, the quality of ∼88% of alignments was improved. iPBA alignments were also better than DALI, MUSTANG and GANGSTA⁺ in >80% of the cases. The webserver is designed to for both pairwise comparisons and database searches. Outputs are given as sequence alignment and superposed 3D structures displayed using PyMol and Jmol. A local alignment option for detecting subs-structural similarity is also embedded. As a fast and efficient ‘sequence-based’ structure comparison tool, we believe that it will be quite useful to the scientific community. iPBA can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/ipba/.

Crystal structure of CCM3, a cerebral cavernous malformation protein critical for vascular integrity

CCM3 mutations are associated with cerebral cavernous malformation (CCM), a disease affecting 0.1-0.5% of the human population. CCM3 (PDCD10, TFAR15) is thought to form a CCM complex with CCM1 and CCM2; however, the molecular basis for these interactions is not known. We have determined the 2.5 A crystal structure of CCM3. This structure shows an all alpha-helical protein containing two domains, an N-terminal dimerization domain with a fold not previously observed, and a C-terminal focal adhesion targeting (FAT)-homology domain. We show that CCM3 binds CCM2 via this FAT-homology domain and that mutation of a highly conserved FAK-like hydrophobic pocket (HP1) abrogates CCM3-CCM2 interaction. This CCM3 FAT-homology domain also interacts with paxillin LD motifs using the same surface, and partial CCM3 co-localization with paxillin in cells is lost on HP1 mutation. Disease-related CCM3 truncations affect the FAT-homology domain suggesting a role for the FAT-homology domain in the etiology of CCM.