Yeast cytochrome c oxidase: a model system to study mitochondrial forms of the haem-copper oxidase superfamily.

The known subunits of yeast mitochondrial cytochrome c oxidase are reviewed. The structures of all eleven of its subunits are explored by building homology models based on the published structures of the homologous bovine subunits and similarities and differences are highlighted, particularly of the core functional subunit I. Yeast genetic techniques to enable introduction of mutations into the three core mitochondrially-encoded subunits are reviewed

Co-Expression Network Models Suggest that Stress Increases Tolerance to Mutations

Network models are a well established tool for studying the robustness of complex systems, including modelling the effect of loss of function mutations in protein interaction networks. Past work has concentrated on average damage caused by random node removal, with little attention to the shape of the damage distribution. In this work, we use fission yeast co-expression networks before and after exposure to stress to model the effect of stress on mutational robustness. We find that exposure to stress decreases the average damage from node removal, suggesting stress induces greater tolerance to loss of function mutations. The shape of the damage distribution is also changed upon stress, with a greater incidence of extreme damage after exposure to stress. We demonstrate that the change in shape of the damage distribution can have considerable functional consequences, highlighting the need to consider the damage distribution in addition to average behaviour

An integrated approach to the interpretation of Single Amino Acid Polymorphisms within the framework of CATH and Gene3D

Background: The phenotypic effects of sequence variations in protein-coding regions come about primarily via their effects on the resulting structures, for example by disrupting active sites or affecting structural stability. In order better to understand the mechanisms behind known mutant phenotypes, and predict the effects of novel variations, biologists need tools to gauge the impacts of DNA mutations in terms of their structural manifestation. Although many mutations occur within domains whose structure has been solved, many more occur within genes whose protein products have not been structurally characterized.Results: Here we present 3DSim (3D Structural Implication of Mutations), a database and web application facilitating the localization and visualization of single amino acid polymorphisms (SAAPs) mapped to protein structures even where the structure of the protein of interest is unknown. The server displays information on 6514 point mutations, 4865 of them known to be associated with disease. These polymorphisms are drawn from SAAPdb, which aggregates data from various sources including dbSNP and several pathogenic mutation databases. While the SAAPdb interface displays mutations on known structures, 3DSim projects mutations onto known sequence domains in Gene3D. This resource contains sequences annotated with domains predicted to belong to structural families in the CATH database. Mappings between domain sequences in Gene3D and known structures in CATH are obtained using a MUSCLE alignment. 1210 three-dimensional structures corresponding to CATH structural domains are currently included in 3DSim; these domains are distributed across 396 CATH superfamilies, and provide a comprehensive overview of the distribution of mutations in structural space.Conclusion: The server is publicly available at http://3DSim.bioinfo.cnio.es/. In addition, the database containing the mapping between SAAPdb, Gene3D and CATH is available on request and most of the functionality is available through programmatic web service access

Control químico de las malezas en ajíes dulces

Two herbicide experiments with sweet cherry peppers were conducted in a Fraternidad clay at Lajas Substation from 1989 to 1990. In the first experiment, clomazone at 1.68 and 3.36 kg ai/ha applied pre-plant and incorporated, as well as fluazifop at 0.42 and 0.84 applied postemergence, gave excellent control of most grasses. Oxyfluorfen at 0.20 kg ai/ha as a pre-plant followed by bentazon at 1.12 kg ai/ha and fluazifop at 0.42 kg ai/ha also provided excellent weed control. The highest sweet cherry pepper yield was obtained with the hand-weeded control. It was then followed by oxyfluorfen at 0,20 kg ai/ha, then followed by bentazon + fluazifop mixture. The treatment with fluazifop at 0.42 kg ai/ha as a postemergence + one supplementary handweeding ranked third in yield. The above treatments did not differ significantly in yield. In the second experiment, colmazone at 2.24 kg ai/ha as a pre-plant, followed by three post directed application of paraquat at 0.56 kg ai/ha, gave the best weed control. Oxyfluorfen at 0.56 kg ai/ha as a pre-plant followed by bentazon at 1.12 kg ai/ha and fluazifop at 0.42 kg ai/ha mixture, also gave excellent weed control. The highest cherry pepper yield was obtained with clomazone at 2.24 kg ai/ha plus three applications of paraquat at 0.56kg ai/ha. This yield was followed by that with oxyfluorfen at 0.56 kg ai/ha followed by bentazone and fluazifop mixture. Napropamide at 2.24 kg ai/ha as a pre-plant, followed by three post directed applications of paraquat at 0.56 kg ai/ha, was ranked third. A good yield was also obtained with Napropamide at 2.24 kg ai/ha as a pre-plant followed by bentazon at 2.24 kg ai/ha and fluazifop at 0.42 kg ai/ha mixture. Yields did not differ significantly with these treatments.En un suelo Fraternidad de la Substación Experimental Agrícola de Lajas se realizaron dos experimentos con herbicidas en ají dulce de 1989 a 1990. En el primer experimento se encontró que clomazone a razón de 1.68 y 3.36 kg. p.a./ha. aplicado presiembra e incorporado como el fluazifop-P a razón de 0.42 y 0.84 kg. p.a./ha. como posemergente reprimieron las gramíneas eficazmente hasta 6 semanas después del trasplante. El oxyfiuorfen a razón de 0.20 kg. p.a./ha. como presiembra seguido por la mezcla bentazon a 1.12 kg. p.a./ha. proveyó un control excelente de la mayoría de las malezas. El rendimiento más alto de ajíes se obtuvo con el desyerbo a mano. A este rendimiento le seguió el del tratamiento de oxifluorfen a razón de 0.20 kg. p.a./ha. como presiembra + la mezcla de bentazon a 1.12 kg. p.a./ha. y fluazifop-P a 0.42 kg. p.a./ha. como posemergente. El fluazifop-P a razón de 0.42 kg. p.a./ha. + un desyerbo suplementario a mano fue tercero en rendimiento. No hubo diferencias estadísticamente significativas (0.05) de probabilidad con estos tres tratamientos. En el segundo experimento, clomazone a razón de 2.24 kg. p.a./ha. como presiembra seguido por el paraquat a razón de 0.56 kg. p.a./ha. (tres veces dirigidos) controló excelentemente la mayoría de las malezas. Oxifluorfen a razón de 0.56 kg. p.a./ha. como presiembra seguido por la mezcla de bentazon a 2.24 kg. p.a./ha. y fluazifop-P a 0.42 kg. p.a./ha. como posemergente controló eficientemente. El rendimiento más alto se obtuvo con el clomazone a razón de 2.24 kg. p.a./ha. como presiembra seguido por la aplicación dirigida de paraquat a razón de 0.56 kg p.a./ha. A este rendimiento le siguió el de oxifluorfen a razón de 0.56 kg. p.a./ha. Napropamide a razón de 2.24 kg. p.a./ha. seguido por paraquat a 0.56 kg. p.a./ha. ocupó el tercer lugar. Napropamide a razón de 2.24 kg. p.a./ha. seguido por la mezcla de bentazon a 2.24 kg. p.a./ha. y fluazifop-P a 0.42 kg. p.a./ha. obtuvo el cuarto lugar. En estos cuatro tratamientos no hubo diferencias significativas (P = 0.05) en rendimiento

The history of the CATH structural classification of protein domains

This article presents a historical review of the protein structure classification database CATH. Together with the SCOP database, CATH remains comprehensive and reasonably up-to-date with the now more than 100,000 protein structures in the PDB. We review the expansion of the CATH and SCOP resources to capture predicted domain structures in the genome sequence data and to provide information on the likely functions of proteins mediated by their constituent domains. The establishment of comprehensive function annotation resources has also meant that domain families can be functionally annotated allowing insights into functional divergence and evolution within protein families

CATHEDRAL: A Fast and Effective Algorithm to Predict Folds and Domain Boundaries from Multidomain Protein Structures

We present CATHEDRAL, an iterative protocol for determining the location of previously observed protein folds in novel multidomain protein structures. CATHEDRAL builds on the features of a fast secondary-structure–based method (using graph theory) to locate known folds within a multidomain context and a residue-based, double-dynamic programming algorithm, which is used to align members of the target fold groups against the query protein structure to identify the closest relative and assign domain boundaries. To increase the fidelity of the assignments, a support vector machine is used to provide an optimal scoring scheme. Once a domain is verified, it is excised, and the search protocol is repeated in an iterative fashion until all recognisable domains have been identified. We have performed an initial benchmark of CATHEDRAL against other publicly available structure comparison methods using a consensus dataset of domains derived from the CATH and SCOP domain classifications. CATHEDRAL shows superior performance in fold recognition and alignment accuracy when compared with many equivalent methods. If a novel multidomain structure contains a known fold, CATHEDRAL will locate it in 90% of cases, with <1% false positives. For nearly 80% of assigned domains in a manually validated test set, the boundaries were correctly delineated within a tolerance of ten residues. For the remaining cases, previously classified domains were very remotely related to the query chain so that embellishments to the core of the fold caused significant differences in domain sizes and manual refinement of the boundaries was necessary. To put this performance in context, a well-established sequence method based on hidden Markov models was only able to detect 65% of domains, with 33% of the subsequent boundaries assigned within ten residues. Since, on average, 50% of newly determined protein structures contain more than one domain unit, and typically 90% or more of these domains are already classified in CATH, CATHEDRAL will considerably facilitate the automation of protein structure classification

CATH functional families predict functional sites in proteins

MOTIVATION: Identification of functional sites in proteins is essential for functional characterization, variant interpretation and drug design. Several methods are available for predicting either a generic functional site, or specific types of functional site. Here, we present FunSite, a machine learning predictor that identifies catalytic, ligand-binding and protein-protein interaction functional sites using features derived from protein sequence and structure, and evolutionary data from CATH functional families (FunFams). RESULTS: FunSite's prediction performance was rigorously benchmarked using cross-validation and a holdout dataset. FunSite outperformed other publicly-available functional site prediction methods. We show that conserved residues in FunFams are enriched in functional sites. We found FunSite's performance depends greatly on the quality of functional site annotations and the information content of FunFams in the training data. Finally, we analyse which structural and evolutionary features are most predictive for functional sites. AVAILABILITY: https://github.com/UCL/cath-funsite-predictor. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Three-dimensional Structure Databases of Biological Macromolecules

Databases of three-dimensional structures of proteins (and their associated molecules) provide: (a)Curated repositories of coordinates of experimentally determined structures, including extensive metadata; for instance information about provenance, details about data collection and interpretation, and validation of results.(b)Information-retrieval tools to allow searching to identify entries of interest and provide access to them.(c)Links among databases, especially to databases of amino-acid and genetic sequences, and of protein function; and links to software for analysis of amino-acid sequence and protein structure, and for structure prediction.(d)Collections of predicted three-dimensional structures of proteins. These will become more and more important after the breakthrough in structure prediction achieved by AlphaFold2. The single global archive of experimentally determined biomacromolecular structures is the Protein Data Bank (PDB). It is managed by wwPDB, a consortium of five partner institutions: the Protein Data Bank in Europe (PDBe), the Research Collaboratory for Structural Bioinformatics (RCSB), the Protein Data Bank Japan (PDBj), the BioMagResBank (BMRB), and the Electron Microscopy Data Bank (EMDB). In addition to jointly managing the PDB repository, the individual wwPDB partners offer many tools for analysis of protein and nucleic acid structures and their complexes, including providing computer-graphic representations. Their collective and individual websites serve as hubs of the community of structural biologists, offering newsletters, reports from Task Forces, training courses, and “helpdesks,” as well as links to external software. Many specialized projects are based on the information contained in the PDB. Especially important are SCOP, CATH, and ECOD, which present classifications of protein domains

Tracing Evolution Through Protein Structures: Nature Captured in a Few Thousand Folds

This article is dedicated to the memory of Cyrus Chothia, who was a leading light in the world of protein structure evolution. His elegant analyses of protein families and their mechanisms of structural and functional evolution provided important evolutionary and biological insights and firmly established the value of structural perspectives. He was a mentor and supervisor to many other leading scientists who continued his quest to characterise structure and function space. He was also a generous and supportive colleague to those applying different approaches. In this article we review some of his accomplishments and the history of protein structure classifications, particularly SCOP and CATH. We also highlight some of the evolutionary insights these two classifications have brought. Finally, we discuss how the expansion and integration of protein sequence data into these structural families helps reveal the dark matter of function space and can inform the emergence of novel functions in Metazoa. Since we cover 25 years of structural classification, it has not been feasible to review all structure based evolutionary studies and hence we focus mainly on those undertaken by the SCOP and CATH groups and their collaborators