"We'll be able to take care of ourselves" - A qualitative study of client attitudes toward implementing buprenorphine treatment at syringe services programs.

Background: Syringe services programs (SSPs) complement substance use disorder treatment in providing services that improve the health of people who use drugs (PWUD). Buprenorphine treatment is an effective underutilized opioid use disorder treatment. Regulations allow buprenorphine prescribing from office-based settings, potentially including SSPs although few studies have examined this approach. Our objective was to assess the attitudes among PWUD toward the potential introduction of buprenorphine treatment in an SSP. Methods: In this qualitative study, we recruited 34 participants who were enrolled at a New York City-based SSP to participate in one of seven focus group sessions. The focus group facilitators prompted participants to share their thoughts in five domains: attitudes toward (1) medical clinics; (2) harm reduction in general; (3) SSP-based buprenorphine treatment; (4) potential challenges of SSP-based treatment; and (5) logistical considerations of an SSP-based buprenorphine treatment program. Four researchers analyzed focus group transcripts using thematic analysis. Results: Of the 34 participants, most were white (68%), over the age of 40 years old (56%), and had previously tried buprenorphine (89%). Common themes were: 1) The SSP is a supportive community for people who use drugs; 2) Participants felt less stigmatized at the SSP than in general medical settings; 3) Offering buprenorphine treatment could change the SSP's culture; and 4) SSP participants receiving buprenorphine may be tempted to divert their medication. Participants offered suggestions for a slow intentional introduction of buprenorphine treatment at the SSP including structured appointments, training medical providers in harm reduction, and program eligibility criteria. Conclusion: Overall, participants expressed enthusiasm for onsite buprenorphine treatment at SSPs. Research on SSP-based buprenorphine treatment should investigate standard buprenorphine treatment outcomes but also any effects on the program itself and medication diversion. Implementation should consider cultural and environmental aspects of the SSP and consult program staff and participants.

A strategy for large-scale comparison of evolutionary- and reaction-based classifications of enzyme function.

Determining the molecular function of enzymes discovered by genome sequencing represents a primary foundation for understanding many aspects of biology. Historically, classification of enzyme reactions has used the enzyme nomenclature system developed to describe the overall reactions performed by biochemically characterized enzymes, irrespective of their associated sequences. In contrast, functional classification and assignment for the millions of protein sequences of unknown function now available is largely done in two computational steps, first by similarity-based assignment of newly obtained sequences to homologous groups, followed by transferring to them the known functions of similar biochemically characterized homologs. Due to the fundamental differences in their etiologies and practice, `how' these chemistry- and evolution-centric functional classification systems relate to each other has been difficult to explore on a large scale. To investigate this issue in a new way, we integrated two published ontologies that had previously described each of these classification systems independently. The resulting infrastructure was then used to compare the functional assignments obtained from each classification system for the well-studied and functionally diverse enolase superfamily. Mapping these function assignments to protein structure and reaction similarity networks shows a profound and complex disconnect between the homology- and chemistry-based classification systems. This conclusion mirrors previous observations suggesting that except for closely related sequences, facile annotation transfer from small numbers of characterized enzymes to the huge number uncharacterized homologs to which they are related is problematic. Our extension of these comparisons to large enzyme superfamilies in a computationally intelligent manner provides a foundation for new directions in protein function prediction for the huge proportion of sequences of unknown function represented in major databases. Interactive sequence, reaction, substrate and product similarity networks computed for this work for the enolase and two other superfamilies are freely available for download from the Structure Function Linkage Database Archive (http://sfld.rbvi.ucsf.edu).

Structural Basis for the Asymmetry of a 4-Oxalocrotonate Tautomerase Trimer.

Tautomerase superfamily (TSF) members are constructed from a single ß-α-ß unit or two consecutively joined ß-α-ß units. This pattern prevails throughout the superfamily consisting of more than 11000 members where homo- or heterohexamers are localized in the 4-oxalocrotonate tautomerase (4-OT) subgroup and trimers are found in the other four subgroups. One exception is a subset of sequences that are double the length of the short 4-OTs in the 4-OT subgroup, where the coded proteins form trimers. Characterization of two members revealed an interesting dichotomy. One is a symmetric trimer, whereas the other is an asymmetric trimer. One monomer is flipped 180° relative to the other two monomers so that three unique protein-protein interfaces are created that are composed of different residues. A bioinformatics analysis of the fused 4-OT subset shows a further division into two clusters with a total of 133 sequences. The analysis showed that members of one cluster (86 sequences) have more salt bridges if the asymmetric trimer forms, whereas the members of the other cluster (47 sequences) have more salt bridges if the symmetric trimer forms. This hypothesis was examined by the kinetic and structural characterization of two proteins within each cluster. As predicted, all four proteins function as 4-OTs, where two assemble into asymmetric trimers (designated R7 and F6) and two form symmetric trimers (designated W0 and Q0). These findings can be extended to the other sequences in the two clusters in the fused 4-OT subset, thereby annotating their oligomer properties and activities.

Structural, Kinetic, and Mechanistic Analysis of an Asymmetric 4-Oxalocrotonate Tautomerase Trimer.

A 4-oxalocrotonate tautomerase (4-OT) trimer has been isolated from Burkholderia lata, and a kinetic, mechanistic, and structural analysis has been performed. The enzyme is the third described oligomer state for 4-OT along with a homo- and heterohexamer. The 4-OT trimer is part of a small subset of sequences (133 sequences) within the 4-OT subgroup of the tautomerase superfamily (TSF). The TSF has two distinct features: members are composed of a single ß-α-ß unit (homo- and heterohexamer) or two consecutively joined ß-α-ß units (trimer) and generally have a catalytic amino-terminal proline. The enzyme, designated as fused 4-OT, functions as a 4-OT where the active site groups (Pro-1, Arg-39, Arg-76, Phe-115, Arg-127) mirror those in the canonical 4-OT from Pseudomonas putida mt-2. Inactivation by 2-oxo-3-pentynoate suggests that Pro-1 of fused 4-OT has a low p Ka enabling the prolyl nitrogen to function as a general base. A remarkable feature of the fused 4-OT is the absence of P3 rotational symmetry in the structure (1.5 Å resolution). The asymmetric arrangement of the trimer is not due to the fusion of the two ß-α-ß building blocks because an engineered "unfused" variant that breaks the covalent bond between the two units (to generate a heterohexamer) assumes the same asymmetric oligomerization state. It remains unknown how the different active site configurations contribute to the observed overall activities and whether the asymmetry has a biological purpose or role in the evolution of TSF members.

InterPro in 2019: improving coverage, classification and access to protein sequence annotations.

The InterPro database (http://www.ebi.ac.uk/interpro/) classifies protein sequences into families and predicts the presence of functionally important domains and sites. Here, we report recent developments with InterPro (version 70.0) and its associated software, including an 18% growth in the size of the database in terms on new InterPro entries, updates to content, the inclusion of an additional entry type, refined modelling of discontinuous domains, and the development of a new programmatic interface and website. These developments extend and enrich the information provided by InterPro, and provide greater flexibility in terms of data access. We also show that InterPro's sequence coverage has kept pace with the growth of UniProtKB, and discuss how our evaluation of residue coverage may help guide future curation activities.

Atlas of the Radical SAM Superfamily: Divergent Evolution of Function Using a "Plug and Play" Domain.

The radical SAM superfamily contains over 100,000 homologous enzymes that catalyze a remarkably broad range of reactions required for life, including metabolism, nucleic acid modification, and biogenesis of cofactors. While the highly conserved SAM-binding motif responsible for formation of the key 5'-deoxyadenosyl radical intermediate is a key structural feature that simplifies identification of superfamily members, our understanding of their structure-function relationships is complicated by the modular nature of their structures, which exhibit varied and complex domain architectures. To gain new insight about these relationships, we classified the entire set of sequences into similarity-based subgroups that could be visualized using sequence similarity networks. This superfamily-wide analysis reveals important features that had not previously been appreciated from studies focused on one or a few members. Functional information mapped to the networks indicates which members have been experimentally or structurally characterized, their known reaction types, and their phylogenetic distribution. Despite the biological importance of radical SAM chemistry, the vast majority of superfamily members have never been experimentally characterized in any way, suggesting that many new reactions remain to be discovered. In addition to 20 subgroups with at least one known function, we identified additional subgroups made up entirely of sequences of unknown function. Importantly, our results indicate that even general reaction types fail to track well with our sequence similarity-based subgroupings, raising major challenges for function prediction for currently identified and new members that continue to be discovered. Interactive similarity networks and other data from this analysis are available from the Structure-Function Linkage Database.

Biocuration in the structure-function linkage database: the anatomy of a superfamily.

With ever-increasing amounts of sequence data available in both the primary literature and sequence repositories, there is a bottleneck in annotating molecular function to a sequence. This article describes the biocuration process and methods used in the structure-function linkage database (SFLD) to help address some of the challenges. We discuss how the hierarchy within the SFLD allows us to infer detailed functional properties for functionally diverse enzyme superfamilies in which all members are homologous, conserve an aspect of their chemical function and have associated conserved structural features that enable the chemistry. Also presented is the Enzyme Structure-Function Ontology (ESFO), which has been designed to capture the relationships between enzyme sequence, structure and function that underlie the SFLD and is used to guide the biocuration processes within the SFLD. Database URL: http://sfld.rbvi.ucsf.edu/.

An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results.

Molecular Diversity of Terpene Synthases in the Liverwort Marchantia polymorpha.

Marchantia polymorpha is a basal terrestrial land plant, which like most liverworts accumulates structurally diverse terpenes believed to serve in deterring disease and herbivory. Previous studies have suggested that the mevalonate and methylerythritol phosphate pathways, present in evolutionarily diverged plants, are also operative in liverworts. However, the genes and enzymes responsible for the chemical diversity of terpenes have yet to be described. In this study, we resorted to a HMMER search tool to identify 17 putative terpene synthase genes from M. polymorpha transcriptomes. Functional characterization identified four diterpene synthase genes phylogenetically related to those found in diverged plants and nine rather unusual monoterpene and sesquiterpene synthase-like genes. The presence of separate monofunctional diterpene synthases for ent-copalyl diphosphate and ent-kaurene biosynthesis is similar to orthologs found in vascular plants, pushing the date of the underlying gene duplication and neofunctionalization of the ancestral diterpene synthase gene family to >400 million years ago. By contrast, the mono- and sesquiterpene synthases represent a distinct class of enzymes, not related to previously described plant terpene synthases and only distantly so to microbial-type terpene synthases. The absence of a Mg2+ binding, aspartate-rich, DDXXD motif places these enzymes in a noncanonical family of terpene synthases.

Determinants of the CmoB carboxymethyl transferase utilized for selective tRNA wobble modification.

Enzyme-mediated modifications at the wobble position of tRNAs are essential for the translation of the genetic code. We report the genetic, biochemical and structural characterization of CmoB, the enzyme that recognizes the unique metabolite carboxy-S-adenosine-L-methionine (Cx-SAM) and catalyzes a carboxymethyl transfer reaction resulting in formation of 5-oxyacetyluridine at the wobble position of tRNAs. CmoB is distinctive in that it is the only known member of the SAM-dependent methyltransferase (SDMT) superfamily that utilizes a naturally occurring SAM analog as the alkyl donor to fulfill a biologically meaningful function. Biochemical and genetic studies define the in vitro and in vivo selectivity for Cx-SAM as alkyl donor over the vastly more abundant SAM. Complementary high-resolution structures of the apo- and Cx-SAM bound CmoB reveal the determinants responsible for this remarkable discrimination. Together, these studies provide mechanistic insight into the enzymatic and non-enzymatic feature of this alkyl transfer reaction which affords the broadened specificity required for tRNAs to recognize multiple synonymous codons.

Covalent docking predicts substrates for haloalkanoate dehalogenase superfamily phosphatases.

Enzyme function prediction remains an important open problem. Though structure-based modeling, such as metabolite docking, can identify substrates of some enzymes, it is ill-suited to reactions that progress through a covalent intermediate. Here we investigated the ability of covalent docking to identify substrates that pass through such a covalent intermediate, focusing particularly on the haloalkanoate dehalogenase superfamily. In retrospective assessments, covalent docking recapitulated substrate binding modes of known cocrystal structures and identified experimental substrates from a set of putative phosphorylated metabolites. In comparison, noncovalent docking of high-energy intermediates yielded nonproductive poses. In prospective predictions against seven enzymes, a substrate was identified for five. For one of those cases, a covalent docking prediction, confirmed by empirical screening, and combined with genomic context analysis, suggested the identity of the enzyme that catalyzes the orphan phosphatase reaction in the riboflavin biosynthetic pathway of Bacteroides.

Using the structure-function linkage database to characterize functional domains in enzymes.

The Structure-Function Linkage Database (SFLD; http://sfld.rbvi.ucsf.edu/) is a Web-accessible database designed to link enzyme sequence, structure, and functional information. This unit describes the protocols by which a user may query the database to predict the function of uncharacterized enzymes and to correct misannotated functional assignments. The information in this unit is especially useful in helping a user discriminate functional capabilities of a sequence that is only distantly related to characterized sequences in publicly available databases.

New insights about enzyme evolution from large scale studies of sequence and structure relationships.

Understanding how enzymes have evolved offers clues about their structure-function relationships and mechanisms. Here, we describe evolution of functionally diverse enzyme superfamilies, each representing a large set of sequences that evolved from a common ancestor and that retain conserved features of their structures and active sites. Using several examples, we describe the different structural strategies nature has used to evolve new reaction and substrate specificities in each unique superfamily. The results provide insight about enzyme evolution that is not easily obtained from studies of one or only a few enzymes.

Prediction and characterization of enzymatic activities guided by sequence similarity and genome neighborhood networks.

Metabolic pathways in eubacteria and archaea often are encoded by operons and/or gene clusters (genome neighborhoods) that provide important clues for assignment of both enzyme functions and metabolic pathways. We describe a bioinformatic approach (genome neighborhood network; GNN) that enables large scale prediction of the in vitro enzymatic activities and in vivo physiological functions (metabolic pathways) of uncharacterized enzymes in protein families. We demonstrate the utility of the GNN approach by predicting in vitro activities and in vivo functions in the proline racemase superfamily (PRS; InterPro IPR008794). The predictions were verified by measuring in vitro activities for 51 proteins in 12 families in the PRS that represent ∼85% of the sequences; in vitro activities of pathway enzymes, carbon/nitrogen source phenotypes, and/or transcriptomic studies confirmed the predicted pathways. The synergistic use of sequence similarity networks3 and GNNs will facilitate the discovery of the components of novel, uncharacterized metabolic pathways in sequenced genomes.

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.

Discovery of new enzymes and metabolic pathways by using structure and genome context.

Assigning valid functions to proteins identified in genome projects is challenging: overprediction and database annotation errors are the principal concerns. We and others are developing computation-guided strategies for functional discovery with 'metabolite docking' to experimentally derived or homology-based three-dimensional structures. Bacterial metabolic pathways often are encoded by 'genome neighbourhoods' (gene clusters and/or operons), which can provide important clues for functional assignment. We recently demonstrated the synergy of docking and pathway context by 'predicting' the intermediates in the glycolytic pathway in Escherichia coli. Metabolite docking to multiple binding proteins and enzymes in the same pathway increases the reliability of in silico predictions of substrate specificities because the pathway intermediates are structurally similar. Here we report that structure-guided approaches for predicting the substrate specificities of several enzymes encoded by a bacterial gene cluster allowed the correct prediction of the in vitro activity of a structurally characterized enzyme of unknown function (PDB 2PMQ), 2-epimerization of trans-4-hydroxy-L-proline betaine (tHyp-B) and cis-4-hydroxy-D-proline betaine (cHyp-B), and also the correct identification of the catabolic pathway in which Hyp-B 2-epimerase participates. The substrate-liganded pose predicted by virtual library screening (docking) was confirmed experimentally. The enzymatic activities in the predicted pathway were confirmed by in vitro assays and genetic analyses; the intermediates were identified by metabolomics; and repression of the genes encoding the pathway by high salt concentrations was established by transcriptomics, confirming the osmolyte role of tHyp-B. This study establishes the utility of structure-guided functional predictions to enable the discovery of new metabolic pathways.

Consequences of domain insertion on sequence-structure divergence in a superfold.

Although the universe of protein structures is vast, these innumerable structures can be categorized into a finite number of folds. New functions commonly evolve by elaboration of existing scaffolds, for example, via domain insertions. Thus, understanding structural diversity of a protein fold evolving via domain insertions is a fundamental challenge. The haloalkanoic dehalogenase superfamily serves as an excellent model system wherein a variable cap domain accessorizes the ubiquitous Rossmann-fold core domain. Here, we determine the impact of the cap-domain insertion on the sequence and structure divergence of the core domain. Through quantitative analysis on a unique dataset of 154 core-domain-only and cap-domain-only structures, basic principles of their evolution have been uncovered. The relationship between sequence and structure divergence of the core domain is shown to be monotonic and independent of the corresponding type of domain insert, reflecting the robustness of the Rossmann fold to mutation. However, core domains with the same cap type share greater similarity at the sequence and structure levels, suggesting interplay between the cap and core domains. Notably, results reveal that the variance in structure maps to α-helices flanking the central ß-sheet and not to the domain-domain interface. Collectively, these results hint at intramolecular coevolution where the fold diverges differentially in the context of an accessory domain, a feature that might also apply to other multidomain superfamilies.

Structure-guided discovery of the metabolite carboxy-SAM that modulates tRNA function.

The identification of novel metabolites and the characterization of their biological functions are major challenges in biology. X-ray crystallography can reveal unanticipated ligands that persist through purification and crystallization. These adventitious protein-ligand complexes provide insights into new activities, pathways and regulatory mechanisms. We describe a new metabolite, carboxy-S-adenosyl-l-methionine (Cx-SAM), its biosynthetic pathway and its role in transfer RNA modification. The structure of CmoA, a member of the SAM-dependent methyltransferase superfamily, revealed a ligand consistent with Cx-SAM in the catalytic site. Mechanistic analyses showed an unprecedented role for prephenate as the carboxyl donor and the involvement of a unique ylide intermediate as the carboxyl acceptor in the CmoA-mediated conversion of SAM to Cx-SAM. A second member of the SAM-dependent methyltransferase superfamily, CmoB, recognizes Cx-SAM and acts as a carboxymethyltransferase to convert 5-hydroxyuridine into 5-oxyacetyl uridine at the wobble position of multiple tRNAs in Gram-negative bacteria, resulting in expanded codon-recognition properties. CmoA and CmoB represent the first documented synthase and transferase for Cx-SAM. These findings reveal new functional diversity in the SAM-dependent methyltransferase superfamily and expand the metabolic and biological contributions of SAM-based biochemistry. These discoveries highlight the value of structural genomics approaches in identifying ligands within the context of their physiologically relevant macromolecular binding partners, and in revealing their functions.

Homology models guide discovery of diverse enzyme specificities among dipeptide epimerases in the enolase superfamily.

The rapid advance in genome sequencing presents substantial challenges for protein functional assignment, with half or more of new protein sequences inferred from these genomes having uncertain assignments. The assignment of enzyme function in functionally diverse superfamilies represents a particular challenge, which we address through a combination of computational predictions, enzymology, and structural biology. Here we describe the results of a focused investigation of a group of enzymes in the enolase superfamily that are involved in epimerizing dipeptides. The first members of this group to be functionally characterized were Ala-Glu epimerases in Eschericiha coli and Bacillus subtilis, based on the operon context and enzymological studies; these enzymes are presumed to be involved in peptidoglycan recycling. We have subsequently studied more than 65 related enzymes by computational methods, including homology modeling and metabolite docking, which suggested that many would have divergent specificities;, i.e., they are likely to have different (unknown) biological roles. In addition to the Ala-Phe epimerase specificity reported previously, we describe the prediction and experimental verification of: (i) a new group of presumed Ala-Glu epimerases; (ii) several enzymes with specificity for hydrophobic dipeptides, including one from Cytophaga hutchinsonii that epimerizes D-Ala-D-Ala; and (iii) a small group of enzymes that epimerize cationic dipeptides. Crystal structures for certain of these enzymes further elucidate the structural basis of the specificities. The results highlight the potential of computational methods to guide experimental characterization of enzymes in an automated, large-scale fashion.