Drug and gut microbe relationships: Moving beyond antibiotics.

Our understanding of drug-microbe relationships has evolved from viewing microbes as mere drug producers to a dynamic, modifiable system where they can serve as drugs or targets of precision pharmacology. This review highlights recent findings on the gut microbiome, particularly focusing on four aspects of research: (i) drugs for bugs, covering recent strategies for targeting gut pathogens; (ii) bugs as drugs, including probiotics; (iii) drugs from bugs, including postbiotics; and (iv) bugs and drugs, discussing additional types of drug-microbe interactions. This review provides a perspective on future translational research, including efficient companion diagnostics in pharmaceutical interventions.

Mental Health Symptom Reduction Using Digital Therapeutics Care Informed by Genomic SNPs and Gut Microbiome Signatures.

Neuropsychiatric diseases and obesity are major components of morbidity and health care costs, with genetic, lifestyle, and gut microbiome factors linked to their etiology. Dietary and weight-loss interventions can help improve mental health, but there is conflicting evidence regarding their efficacy; and moreover, there is substantial interindividual heterogeneity that needs to be understood. We aimed to identify genetic and gut microbiome factors that explain interindividual differences in mental health improvement after a dietary and lifestyle intervention for weight loss. We recruited 369 individuals participating in Digbi Health's personalized digital therapeutics care program and evaluated the association of 23 genetic scores, the abundance of 178 gut microbial genera, and 42 bacterial pathways with mental health. We studied the presence/absence of anxiety or depression, or sleep problems at baseline and improvement on anxiety, depression, and insomnia after losing at least 2% body weight. Participants lost on average 5.4% body weight and >95% reported improving mental health symptom intensity. There were statistically significant correlations between: (a) genetic scores with anxiety or depression at baseline, gut microbial functions with sleep problems at baseline, and (b) genetic scores and gut microbial taxa and functions with anxiety, depression, and insomnia improvement. Our results are concordant with previous findings, including the association between anxiety or depression at baseline with genetic scores for alcohol use disorder and major depressive disorder. As well, our results uncovered new associations in line with previous epidemiological literature. As evident from previous literature, we also observed associations of gut microbial signatures with mental health including short-chain fatty acids and bacterial neurotoxic metabolites specifically with depression. Our results also show that microbiome and genetic factors explain self-reported mental health status and improvement better than demographic variables independently. The genetic and microbiome factors identified in this study provide the basis for designing and personalizing dietary interventions to improve mental health.

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.

Local Network Properties of Soil and Rhizosphere Microbial Communities in Potato Plantations Treated with a Biological Product Are Important Predictors of Crop Yield.

Understanding the effectiveness and potential mechanism of action of agricultural biological products under different soil profiles and crops will allow more precise product recommendations based on local conditions and will ultimately result in increased crop yield. This study aimed to use bulk soil and rhizosphere microbial composition and structure to evaluate the potential effect of a Bacillus amyloliquefaciens inoculant (strain QST713) on potatoes and to explore its relationship with crop yield. We implemented next-generation sequencing (NGS) and bioinformatics approaches to assess the bacterial and fungal biodiversity in 185 soil samples, distributed over four different time points-from planting to harvest-from three different geographical locations in the United States. In addition to location and sampling time (which includes the difference between bulk soil and rhizosphere) as the main variables defining the microbiome composition, the microbial inoculant applied as a treatment also had a small but significant effect in fungal communities and a marginally significant effect in bacterial communities. However, treatment preserved the native communities without causing a detectable long-lasting effect on the alpha- and beta-diversity patterns after harvest. Using information about the application of the microbial inoculant and considering microbiome composition and structure data, we were able to train a Random Forest model to estimate if a bulk soil or rhizosphere sample came from a low- or high-yield block with relatively high accuracy (84.6%), concluding that the structure of fungal communities gives us more information as an estimator of potato yield than the structure of bacterial communities. IMPORTANCE Our results reinforce the notion that each cultivar on each location recruits a unique microbial community and that these communities are modulated by the vegetative growth stage of the plant. Moreover, inoculation of a Bacillus amyloliquefaciens strain QST713-based product on potatoes also changed the abundance of specific taxonomic groups and the structure of local networks in those locations where the product caused an increase in the yield. The data obtained, from in-field assays, allowed training a predictive model to estimate the yield of a certain block, identifying microbiome variables-especially those related to microbial community structure-even with a higher predictive power than the geographical location of the block (that is, the principal determinant of microbial beta-diversity). The methods described here can be replicated to fit new models in any other crop and to evaluate the effect of any agricultural input in the composition and structure of the soil microbiome.

Gut microbiome composition and risk factors in a large cross-sectional IBS cohort.

Objective: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is difficult to diagnose and treat due to its inherent heterogeneity and unclear aetiology. Although there is evidence suggesting the importance of the microbiome in IBS, this association remains poorly defined. In the current study, we aimed to characterise a large cross-sectional cohort of patients with self-reported IBS in terms of microbiome composition, demographics, and risk factors. Design: Individuals who had previously submitted a stool sample for 16S microbiome sequencing were sent a comprehensive survey regarding IBS diagnosis, demographics, health history, comorbidities, family history, and symptoms. Log ratio-transformed abundances of microbial taxa were compared between individuals reporting a diagnosis of IBS without any comorbidities and individuals reporting no health conditions. Univariable testing was followed by a multivariable logistic regression model controlling for relevant confounders. Results: Out of 6386 respondents, 1692 reported a diagnosis of IBS without comorbidities and 1124 reported no health conditions. We identified 3 phyla, 15 genera, and 19 species as significantly associated with IBS after adjustment for confounding factors. Demographic risk factors include a family history of gut disorders and reported use of antibiotics in the last year. Conclusion: The results of this study confirm important IBS risk factors in a large cohort and support a connection for microbiome compositional changes in IBS pathogenesis. The results also suggest clinical relevance in monitoring and investigating the microbiome in patients with IBS. Further, the exploratory models described here provide a foundation for future studies.

Draft Genome Sequence of Blautia luti DSM 14534T, Isolated from Human Stool.

Here, we report the draft sequence of Blautia luti strain DSM 14534T, originally isolated from human feces. This draft contains 74 contigs, comprising 3,718,760 bp with a G+C content of 42.87%. The annotated draft contains 3,338 coding sequences (CDSs) and 110 RNA genes.

A novel sequencing-based vaginal health assay combining self-sampling, HPV detection and genotyping, STI detection, and vaginal microbiome analysis.

The composition of the vaginal microbiome, including both the presence of pathogens involved in sexually transmitted infections (STI) as well as commensal microbiota, has been shown to have important associations for a woman's reproductive and general health. Currently, healthcare providers cannot offer comprehensive vaginal microbiome screening, but are limited to the detection of individual pathogens, such as high-risk human papillomavirus (hrHPV), the predominant cause of cervical cancer. There is no single test on the market that combines HPV, STI, and microbiome screening. Here, we describe a novel inclusive vaginal health assay that combines self-sampling with sequencing-based HPV detection and genotyping, vaginal microbiome analysis, and STI-associated pathogen detection. The assay includes genotyping and detection of 14 hrHPV types, 5 low-risk HPV types (lrHPV), as well as the relative abundance of 31 bacterial taxa of clinical importance, including Lactobacillus, Sneathia, Gardnerella, and 3 pathogens involved in STI, with high sensitivity, specificity, and reproducibility. For each of these taxa, reference ranges were determined in a group of 50 self-reported healthy women. The HPV sequencing portion of the test was evaluated against the digene High-Risk HPV HC2 DNA test. For hrHPV genotyping, agreement was 95.3% with a kappa of 0.804 (601 samples); after removal of samples in which the digene hrHPV probe showed cross-reactivity with lrHPV types, the sensitivity and specificity of the hrHPV genotyping assay were 94.5% and 96.6%, respectively, with a kappa of 0.841. For lrHPV genotyping, agreement was 93.9% with a kappa of 0.788 (148 samples), while sensitivity and specificity were 100% and 92.9%, respectively. This novel assay could be used to complement conventional cervical cancer screening, because its self-sampling format can expand access among women who would otherwise not participate, and because of its additional information about the composition of the vaginal microbiome and the presence of pathogens.

Correction: 16S rRNA gene sequencing and healthy reference ranges for 28 clinically relevant microbial taxa from the human gut microbiome.

[This corrects the article DOI: 10.1371/journal.pone.0176555.].

The role of a sequencing-based clinical intestinal screening test in patients at high-risk for Clostridium difficile and other pathogens: a case report.

BACKGROUND: Hospitalization and antibiotic treatment can put patients at high risk for Clostridium difficile infection, where a disturbance of the gut microbiome allows for Clostridium difficile proliferation and associated symptoms, including mild, moderate, or severe diarrhea. Clostridium difficile infection is challenging to treat, often recurrent, and leads to almost 30,000 annual deaths in the USA alone. Here we present a case where SmartGut™, an at-home, self-administered sequencing-based clinical intestinal screening test, was used to identify the presence of Clostridium difficile in a patient with worsening diarrhea. Identification of this pathogen and subsequent treatment led to a significant improvement in symptoms. CASE PRESENTATION: The patient is a 29-year-old white woman with a history of severe irritable bowel syndrome with diarrhea, hemorrhoidectomy, and anal sphincterotomy complicated by a perianal fistula and perirectal abscesses that required extended courses of broad-spectrum antibiotics. In June 2016, she developed intermittent Clostridium difficile infections, which required continued antibiotic use. Months later she used an at-home, self-administered, intestinal microbial test, the first of which was negative for the presence of Clostridium difficile, but it detected the relative abundance of microbes associated with irritable bowel syndrome outside the healthy reference ranges. In the subsequent 2 months after the negative Clostridium difficile result, her gastrointestinal symptoms worsened dramatically. A second microbiome test resulted in a positive Clostridium difficile finding and continued abnormal microbial parameters, which led the treating physician to refer her to a gastroenterologist. Additional testing confirmed the presence of Clostridium difficile with a toxin-positive strain. She received treatment immediately and her gastrointestinal symptoms improved significantly over the next week. CONCLUSIONS: This case report suggests that more frequent DNA testing for Clostridium difficile infections may be indicated in patients that are at high-risk for Clostridium difficile infection, especially for patients with irritable bowel syndrome, and those who undergo gastrointestinal surgery and/or an extended antibiotic treatment. This report also shows that such testing could be effectively performed using at-home, self-administered sequencing-based clinical intestinal microbial screening tests. Further research is needed to investigate whether the observations reported here extrapolate to a larger cohort of patients.

Self-Sampling for Human Papillomavirus Testing: Increased Cervical Cancer Screening Participation and Incorporation in International Screening Programs.

In most industrialized countries, screening programs for cervical cancer have shifted from cytology (Pap smear or ThinPrep) alone on clinician-obtained samples to the addition of screening for human papillomavirus (HPV), its main causative agent. For HPV testing, self-sampling instead of clinician-sampling has proven to be equally accurate, in particular for assays that use nucleic acid amplification techniques. In addition, HPV testing of self-collected samples in combination with a follow-up Pap smear in case of a positive result is more effective in detecting precancerous lesions than a Pap smear alone. Self-sampling for HPV testing has already been adopted by some countries, while others have started trials to evaluate its incorporation into national cervical cancer screening programs. Self-sampling may result in more individuals willing to participate in cervical cancer screening, because it removes many of the barriers that prevent women, especially those in low socioeconomic and minority populations, from participating in regular screening programs. Several studies have shown that the majority of women who have been underscreened but who tested HPV-positive in a self-obtained sample will visit a clinic for follow-up diagnosis and management. In addition, a self-collected sample can also be used for vaginal microbiome analysis, which can provide additional information about HPV infection persistence as well as vaginal health in general.

Novel Insights for Inhibiting Mutant Heterodimer IDH1wt-R132H in Cancer: An In-Silico Approach.

BACKGROUND: Isocitrate dehydrogenase 1 (IDH1) is a dimeric enzyme responsible for supplying the cell's nicotinamide adenine dinucleotide phosphate (NADPH) reserves via dehydrogenation of isocitrate (ICT) and reduction of NADP+. Mutations in position R132 trigger cancer by enabling IDH1 to produce D-2-hydroxyglutarate (2-HG) and reduce inhibition by ICT. Mutant IDH1 can be found as a homodimer or a heterodimer. OBJECTIVE: We propose a novel strategy to inhibit IDH1 R132 variants as a means not to decrease the concentration of 2-HG but to provoke a cytotoxic effect, as the cell malignancy at this point no longer depends on 2-HG. We aim to inhibit the activity of the mutant heterodimer to block the wild-type subunit. Limiting the NADPH reserves in a cancerous cell will enhance its susceptibility to the oxidative stress provoked by chemotherapy. METHODS: We performed a virtual screening using all US FDA-approved drugs to replicate the loss of inhibition of mutant IDH1 by ICT. We characterized our results based on molecular interactions and correlated them with the described phenotypes. RESULTS: We replicated the loss of inhibition by ICT in mutant IDH1. We identified 20 drugs with the potential to inhibit the heterodimeric isoform. Six of them are used in cancer treatment. CONCLUSIONS: We present 20 FDA-approved drugs with the potential to inhibit IDH1 wild-type activity in mutated cells. We believe this work may provide important insights into current and new approaches to dealing with IDH1 mutations. In addition, it may be used as a basis for additional studies centered on drugs presenting differential sensitivities to different IDH1 isoforms.

Increasing the intracellular isoprenoid pool in Saccharomyces cerevisiae by structural fine-tuning of a bifunctional farnesyl diphosphate synthase.

Farnesyl diphosphate synthase (FPPS) is a key enzyme responsible for the supply of isoprenoid precursors for several essential metabolites, including sterols, dolichols and ubiquinone. In Saccharomyces cerevisiae, FPPS catalyzes the sequential condensation of two molecules of isopentenyl diphosphate (IPP) with dimethylallyl diphosphate (DMAPP), producing geranyl diphosphate (GPP) and farnesyl diphosphate (FPP). Critical amino acid residues that determine product chain length were determined by a comparative study of strict GPP synthases versus strict FPPS. In silico ΔΔG, i.e. differential binding energy between a protein and two different ligands-of yeast FPPS mutants was evaluated, and F96, A99 and E165 residues were identified as key determinants for product selectivity. A99X variants were evaluated in vivo, S. cerevisiae strains carrying A99R and A99H variants showed significant differences on GPP concentrations and specific growth rates. The FPPS A99T variant produced unquantifiable amounts of FPP and no effect on GPP production was observed. Strains carrying A99Q, A99Y and A99K FPPS accumulated high amounts of DMAPP-IPP, with a decrease in GPP and FPP. Our results demonstrated the relevance of the first residue before FARM (First Aspartate Rich Motif) over substrate consumption and product specificity of S. cerevisiae FPPS in vivo. The presence of A99H significantly modified product selectivity and appeared to be relevant for GPP synthesis.

16S rRNA gene sequencing and healthy reference ranges for 28 clinically relevant microbial taxa from the human gut microbiome.

Changes in the relative abundances of many intestinal microorganisms, both those that naturally occur in the human gut microbiome and those that are considered pathogens, have been associated with a range of diseases. To more accurately diagnose health conditions, medical practitioners could benefit from a molecular, culture-independent assay for the quantification of these microorganisms in the context of a healthy reference range. Here we present the targeted sequencing of the microbial 16S rRNA gene of clinically relevant gut microorganisms as a method to provide a gut screening test that could assist in the clinical diagnosis of certain health conditions. We evaluated the possibility of detecting 46 clinical prokaryotic targets in the human gut, 28 of which could be identified with high precision and sensitivity by a bioinformatics pipeline that includes sequence analysis and taxonomic annotation. These targets included 20 commensal, 3 beneficial (probiotic), and 5 pathogenic intestinal microbial taxa. Using stool microbiome samples from a cohort of 897 healthy individuals, we established a reference range defining clinically relevant relative levels for each of the 28 targets. Our assay quantifies 28 targets in the context of a healthy reference range and correctly reflected 38/38 verification samples of real and synthetic stool material containing known gut pathogens. Thus, we have established a method to determine microbiome composition with a focus on clinically relevant taxa, which has the potential to contribute to patient diagnosis, treatment, and monitoring. More broadly, our method can facilitate epidemiological studies of the microbiome as it relates to overall human health and disease.

Biomimetics: From Bioinformatics to Rational Design of Dendrimers as Gene Carriers.

Biomimetics, or the use of principles of Nature for developing new materials, is a paradigm that could help Nanomedicine tremendously. One of the current challenges in Nanomedicine is the rational design of new efficient and safer gene carriers. Poly(amidoamine) (PAMAM) dendrimers are a well-known class of nanoparticles, extensively used as non-viral nucleic acid carriers, due to their positively charged end-groups. Yet, there are still several aspects that can be improved for their successful application in in vitro and in vivo systems, including their affinity for nucleic acids as well as lowering their cytotoxicity. In the search of new functional groups that could be used as new dendrimer-reactive groups, we followed a biomimetic approach to determine the amino acids with highest prevalence in protein-DNA interactions. Then we introduced them individually as terminal groups of dendrimers, generating a new class of nanoparticles. Molecular dynamics studies of two systems: PAMAM-Arg and PAMAM-Lys were also performed in order to describe the formation of complexes with DNA. Results confirmed that the introduction of amino acids as terminal groups in a dendrimer increases their affinity for DNA and the interactions in the complexes were characterized at atomic level. We end up by briefly discussing additional modifications that can be made to PAMAM dendrimers to turned them into promising new gene carriers.

A transient receptor potential ion channel in Chlamydomonas shares key features with sensory transduction-associated TRP channels in mammals.

Sensory modalities are essential for navigating through an ever-changing environment. From insects to mammals, transient receptor potential (TRP) channels are known mediators for cellular sensing. Chlamydomonas reinhardtii is a motile single-celled freshwater green alga that is guided by photosensory, mechanosensory, and chemosensory cues. In this type of alga, sensory input is first detected by membrane receptors located in the cell body and then transduced to the beating cilia by membrane depolarization. Although TRP channels seem to be absent in plants, C. reinhardtii possesses genomic sequences encoding TRP proteins. Here, we describe the cloning and characterization of a C. reinhardtii version of a TRP channel sharing key features present in mammalian TRP channels associated with sensory transduction. In silico sequence-structure analysis unveiled the modular design of TRP channels, and electrophysiological experiments conducted on Human Embryonic Kidney-293T cells expressing the Cr-TRP1 clone showed that many of the core functional features of metazoan TRP channels are present in Cr-TRP1, suggesting that basic TRP channel gating characteristics evolved early in the history of eukaryotes.

Participation of the Salmonella OmpD porin in the infection of RAW264.7 macrophages and BALB/c mice.

Salmonella Typhimurium is the etiological agent of gastroenteritis in humans and enteric fever in mice. Inside these hosts, Salmonella must overcome hostile conditions to develop a successful infection, a process in which the levels of porins may be critical. Herein, the role of the Salmonella Typhimurium porin OmpD in the infection process was assessed for adherence, invasion and proliferation in RAW264.7 mouse macrophages and in BALB/c mice. In cultured macrophages, a ΔompD strain exhibited increased invasion and proliferation phenotypes as compared to its parental strain. In contrast, overexpression of ompD caused a reduction in bacterial proliferation but did not affect adherence or invasion. In the murine model, the ΔompD strain showed increased ability to survive and replicate in target organs of infection. The ompD transcript levels showed a down-regulation when Salmonella resided within cultured macrophages and when it colonized target organs in infected mice. Additionally, cultured macrophages infected with the ΔompD strain produced lower levels of reactive oxygen species, suggesting that down-regulation of ompD could favor replication of Salmonella inside macrophages and the subsequent systemic dissemination, by limiting the reactive oxygen species response of the host.

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.

Prediction of function for the polyprenyl transferase subgroup in the isoprenoid synthase superfamily.

The number of available protein sequences has increased exponentially with the advent of high-throughput genomic sequencing, creating a significant challenge for functional annotation. Here, we describe a large-scale study on assigning function to unknown members of the trans-polyprenyl transferase (E-PTS) subgroup in the isoprenoid synthase superfamily, which provides substrates for the biosynthesis of the more than 55,000 isoprenoid metabolites. Although the mechanism for determining the product chain length for these enzymes is known, there is no simple relationship between function and primary sequence, so that assigning function is challenging. We addressed this challenge through large-scale bioinformatics analysis of >5,000 putative polyprenyl transferases; experimental characterization of the chain-length specificity of 79 diverse members of this group; determination of 27 structures of 19 of these enzymes, including seven cocrystallized with substrate analogs or products; and the development and successful application of a computational approach to predict function that leverages available structural data through homology modeling and docking of possible products into the active site. The crystallographic structures and computational structural models of the enzyme-ligand complexes elucidate the structural basis of specificity. As a result of this study, the percentage of E-PTS sequences similar to functionally annotated ones (BLAST e-value ≤ 1e(-70)) increased from 40.6 to 68.8%, and the percentage of sequences similar to available crystal structures increased from 28.9 to 47.4%. The high accuracy of our blind prediction of newly characterized enzymes indicates the potential to predict function to the complete polyprenyl transferase subgroup of the isoprenoid synthase superfamily computationally.

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.

Toward mechanistic classification of enzyme functions.

Classification of enzyme function should be quantitative, computationally accessible, and informed by sequences and structures to enable use of genomic information for functional inference and other applications. Large-scale studies have established that divergently evolved enzymes share conserved elements of structure and common mechanistic steps and that convergently evolved enzymes often converge to similar mechanisms too, suggesting that reaction mechanisms could be used to develop finer-grained functional descriptions than provided by the Enzyme Commission (EC) system currently in use. Here we describe how evolution informs these structure-function mappings and review the databases that store mechanisms of enzyme reactions along with recent developments to measure ligand and mechanistic similarities. Together, these provide a foundation for new classifications of enzyme function.