MACiE (Mechanism, Annotation and Classification in Enzymes): novel tools for searching catalytic mechanisms

MACiE (Mechanism, Annotation and Classification in Enzymes) is a database of enzyme reaction mechanisms, and is publicly available as a web-based data resource. This paper presents the first release of a web-based search tool to explore enzyme reaction mechanisms in MACiE. We also present Version 2 of MACiE, which doubles the dataset available (from Version 1). MACiE can be accessed fro

MACiE: exploring the diversity of biochemical reactions

MACiE (which stands for Mechanism, Annotation and Classification in Enzymes) is a database of enzyme reaction mechanisms, and can be accessed from http://www.ebi.ac.uk/thornton-srv/databases/MACiE/. This article presents the release of Version 3 of MACiE, which not only extends the dataset to 335 entries, covering 182 of the EC sub-subclasses with a crystal structure available (∼90%), but also incorporates greater chemical and structural detail. This version of MACiE represents a shift in emphasis for new entries, from non-homologous representatives covering EC reaction space to enzymes with mechanisms of interest to our users and collaborators with a view to exploring the chemical diversity of life. We present new tools for exploring the data in MACiE and comparing entries as well as new analyses of the data and new searches, many of which can now be accessed via dedicated Perl scripts

Digital Therapeutics Care Utilizing Genetic and Gut Microbiome Signals for the Management of Functional Gastrointestinal Disorders: Results From a Preliminary Retrospective Study

Diet and lifestyle-related illnesses including functional gastrointestinal disorders (FGIDs) and obesity are rapidly emerging health issues worldwide. Research has focused on addressing FGIDs via in-person cognitive-behavioral therapies, diet modulation and pharmaceutical intervention. Yet, there is paucity of research reporting on digital therapeutics care delivering weight loss and reduction of FGID symptom severity, and on modeling FGID status and symptom severity reduction including personalized genomic SNPs and gut microbiome signals. Our aim for this study was to assess how effective a digital therapeutics intervention personalized on genomic SNPs and gut microbiome signals was at reducing symptomatology of FGIDs on individuals that successfully lost body weight. We also aimed at modeling FGID status and FGID symptom severity reduction using demographics, genomic SNPs, and gut microbiome variables. This study sought to train a logistic regression model to differentiate the FGID status of subjects enrolled in a digital therapeutics care program using demographic, genetic, and baseline microbiome data. We also trained linear regression models to ascertain changes in FGID symptom severity of subjects at the time of achieving 5% or more of body weight loss compared to baseline. For this we utilized a cohort of 177 adults who reached 5% or more weight loss on the Digbi Health personalized digital care program, who were retrospectively surveyed about changes in symptom severity of their FGIDs and other comorbidities before and after the program. Gut microbiome taxa and demographics were the strongest predictors of FGID status. The digital therapeutics program implemented, reduced the summative severity of symptoms for 89.42% (93/104) of users who reported FGIDs. Reduction in summative FGID symptom severity and IBS symptom severity were best modeled by a mixture of genomic and microbiome predictors, whereas reduction in diarrhea and constipation symptom severity were best modeled by microbiome predictors only. This preliminary retrospective study generated diagnostic models for FGID status as well as therapeutic models for reduction of FGID symptom severity. Moreover, these therapeutic models generate testable hypotheses for associations of a number of biomarkers in the prognosis of FGIDs symptomatology

The Structure-Function Linkage Database

The Structure–Function Linkage Database (SFLD, http://sfld.rbvi.ucsf.edu/) is a manually curated classification resource describing structure–function relationships for functionally diverse enzyme superfamilies. Members of such superfamilies are diverse in their overall reactions yet share a common ancestor and some conserved active site features associated with conserved functional attributes such as a partial reaction. Thus, despite their different functions, members of these superfamilies ‘look alike’, making them easy to misannotate. To address this complexity and enable rational transfer of functional features to unknowns only for those members for which we have sufficient functional information, we subdivide superfamily members into subgroups using sequence information, and lastly into families, sets of enzymes known to catalyze the same reaction using the same mechanistic strategy. Browsing and searching options in the SFLD provide access to all of these levels. The SFLD offers manually curated as well as automatically classified superfamily sets, both accompanied by search and download options for all hierarchical levels. Additional information includes multiple sequence alignments, tab-separated files of functional and other attributes, and sequence similarity networks. The latter provide a new and intuitively powerful way to visualize functional trends mapped to the context of sequence similarity

Non-Proportional Medical Interventions at the End of Life in a High Complexity Hospital in Colombia

Objetivo: Analizar las intervenciones realizadas en una cohorte de pacientes fallecidos en un hospital universitario de alta complejidad y definir la proporcionalidad terapéutica de las mismas, a partir del estudio de la prevalencia de “tratamientos no benéficos”. Metodología Estudio observacional descriptivo retrospectivo, basado en la revisión de historias clínicas de los pacientes fallecidos en el periodo de dos años en un hospital universitario de alta complejidad Resultados: Se analizaron 931 historias de pacientes fallecidos y en la categorización de acuerdo con el criterio de “proporcionalidad terapéutica” se encontró que en el 54,7% de los pacientes se realizaron intervenciones diagnosticas o terapéuticas clasificadas como “desproporcionadas” de acuerdo con la definición aplicada. Conclusión: En la práctica las intervenciones no proporcionales o no benéficas al final de la vida son prevalentes, lo que constituye un problema mayor y persistente, a pesar de sus repercusiones negativas sobre los pacientes, las familias, los profesionales de la salud y el sistema de saludPurpose: To analyze the interventions carried out in a cohort of patients who died in a university hospital of highcomplexity and define their therapeutic proportionality, based on the study of the prevalence of "non-beneficialtreatments". Methodology: Retrospective descriptive observational study, based on the review of medical records of patients who died in a two-year period in a highly complex university hospital. Results: 931 records of deceased patients were analyzed and categorized according to the criteria of “ therapeutic proportionality ”. It was found that 54.7% of the patients underwent diagnostic or therapeutic interventions classified as “disproportionate” according to the applied definition. Conclusion: In practice, non-proportional or non-beneficial end-of-lifeinterventions are prevalent, which is a major and persistent problem, despite the negative impact on patients,families, health professionals and the health system.Revista Nacional - Indexad

The chemistry of protein catalysis

We report, for the first time, on the statistics of chemical mechanisms and amino acid residue functions that occur in enzyme reaction sequences using the MAGE database of 202 distinct enzyme reaction mechanisms as a knowledge base. MAGE currently holds representatives from each Enzyme Commission sub-subclass where there is an available crystal structure and sufficient evidence in the primary literature for a mechanism. Each catalytic step of every reaction sequence in MAGE is fully annotated, so that it includes the function of the catalytic residues involved in the reaction and the chemical mechanisms by which substrates are transformed into products. We show that the most catalytic amino acid residues are histidine, cysteine and aspartate, which are also the residues whose side-chains are more likely to serve as reactants, and that have the greatest versatility of function. We show that electrophilic reactions in enzymes are very rare, and the majority of enzyme reactions rely upon nucleophilic and general acid/base chemistry. However, although rare, radical (homolytic) reactions are much more common than electrophilic reactions. Thus, the majority of amino acid residues perform stabilisation roles (as spectators) or proton shuttling roles (as reactants). The analysis presented provides a better understanding of the mechanisms of enzyme catalysis and may act as an initial step in the validation and prediction of mechanism in an enzyme active site. (c) 2007 Elsevier Ltd. All rights reserved.</p

Using reaction mechanism to measure enzyme similarity

The concept of reaction similarity has been well-studied in terms of the overall transformation associated with a reaction, but not in terms of mechanism. We present the first method to give a quantitative measure of the similarity of reactions based upon their explicit mechanisms. Two approaches are presented to measure the similarity between individual steps of mechanisms: a fingerprint-based approach which incorporates relevant information on each mechanistic step, and an approach based only on bond formation, cleavage and changes in order. The overall similarity for two reaction mechanisms is then calculated using the Needleman-Wunsch alignment algorithm. An analysis of MACiE, a database of enzyme mechanisms, using our measure of similarity identifies some examples of convergent evolution of chemical mechanism. In many cases mechanism similarity is not reflected by similarity according to the EC system of enzyme classification. In particular, little mechanistic information is conveyed by the class level of the EC

A semiempirical approach to the intra-phycocyanin and inter-phycocyanin fluorescence resonance energy-transfer pathways in phycobilisomes.

A semiempirical methodology to model the intra-phycocyanin and inter-phycocyanin fluorescence resonance energy-transfer (FRET) pathways in the rods of the phycobilisomes (PBSs) from Fremyella diplosiphon is presented. Using the Forster formulation of FRET and combining experimental data and PM3 calculation of the dipole moments of the aromatic portions of the chromophores, transfer constants between pairs of chromophores in the phycocyanin (PC) structure were obtained. Protein docking of two PC hexamers was used to predict the optimal distance and axial rotation angle for the staked PCs in the PBSs' rods. Using the distance obtained by the docking process, transfer constants between pairs of chromophores belonging to different PC hexamers were calculated as a function of the angle of rotation. We show that six preferential FRET pathways within the PC hexameric ring and 15 pathways between hexamers exist, with transfer constants consistent with experimental results. Protein docking predicted the quaternary structure for PCs in rods with inter-phycocyanin distance of 55.6 A and rotation angle of 20.5 degrees . The inter-phycocyanin FRET constant between chromophores at positions beta(155) is maximized at the rotation angle predicted by docking revealing the crucial role of this specific inter-phycocyanin channel in defining the complete set of FRET pathways in the system