MOTIVATION: Knowledge graphs (KGs) are being adopted in industry, commerce and academia. Biomedical KG presents a challenge due to the complexity, size and heterogeneity of the underlying information. RESULTS: In this work, we present the Scalable Precision Medicine Open Knowledge Engine (SPOKE), a biomedical KG connecting millions of concepts via semantically meaningful relationships. SPOKE contains 27 million nodes of 21 different types and 53 million edges of 55 types downloaded from 41 databases. The graph is built on the framework of 11 ontologies that maintain its structure, enable mappings and facilitate navigation. SPOKE is built weekly by python scripts which download each resource, check for integrity and completeness, and then create a 'parent table' of nodes and edges. Graph queries are translated by a REST API and users can submit searches directly via an API or a graphical user interface. Conclusions/Significance: SPOKE enables the integration of seemingly disparate information to support precision medicine efforts. AVAILABILITY AND IMPLEMENTATION: The SPOKE neighborhood explorer is available at https://spoke.rbvi.ucsf.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Structural and biochemical constraints force some segments of proteins to evolve more slowly than others, often allowing identification of conserved structural or sequence motifs that can be associated with substrate binding properties, chemical mechanisms, and molecular functions. We have assessed the functional and structural constraints imposed by cofactors on the evolution of new functions in a superfamily of flavoproteins characterized by two-dinucleotide binding domains, the "two dinucleotide binding domains" flavoproteins (tDBDF) superfamily. Although these enzymes catalyze many different types of oxidation/reduction reactions, each is initiated by a stereospecific hydride transfer reaction between two cofactors, a pyridine nucleotide and flavin adenine dinucleotide (FAD). Sequence and structural analysis of more than 1,600 members of the superfamily reveals new members and identifies details of the evolutionary connections among them. Our analysis shows that in all of the highly divergent families within the superfamily, these cofactors adopt a conserved configuration optimal for stereospecific hydride transfer that is stabilized by specific interactions with amino acids from several motifs distributed among both dinucleotide binding domains. The conservation of cofactor configuration in the active site restricts the pyridine nucleotide to interact with FAD from the re-side, limiting the flow of electrons from the re-side to the si-side. This directionality of electron flow constrains interactions with the different partner proteins of different families to occur on the same face of the cofactor binding domains. As a result, superimposing the structures of tDBDFs aligns not only these interacting proteins, but also their constituent electron acceptors, including heme and iron-sulfur clusters. Thus, not only are specific aspects of the cofactor-directed chemical mechanism conserved across the superfamily, the constraints they impose are manifested in the mode of protein-protein interactions. Overlaid on this foundation of conserved interactions, nature has conscripted different protein partners to serve as electron acceptors, thereby generating diversification of function across the superfamily.

BACKGROUND: Comparing related structures and viewing the structures in the context of sequence alignments are important tasks in protein structure-function research. While many programs exist for individual aspects of such work, there is a need for interactive visualization tools that: (a) provide a deep integration of sequence and structure, far beyond mapping where a sequence region falls in the structure and vice versa; (b) facilitate changing data of one type based on the other (for example, using only sequence-conserved residues to match structures, or adjusting a sequence alignment based on spatial fit); (c) can be used with a researcher's own data, including arbitrary sequence alignments and annotations, closely or distantly related sets of proteins, etc.; and (d) interoperate with each other and with a full complement of molecular graphics features. We describe enhancements to UCSF Chimera to achieve these goals. RESULTS: The molecular graphics program UCSF Chimera includes a suite of tools for interactive analyses of sequences and structures. Structures automatically associate with sequences in imported alignments, allowing many kinds of crosstalk. A novel method is provided to superimpose structures in the absence of a pre-existing sequence alignment. The method uses both sequence and secondary structure, and can match even structures with very low sequence identity. Another tool constructs structure-based sequence alignments from superpositions of two or more proteins. Chimera is designed to be extensible, and mechanisms for incorporating user-specific data without Chimera code development are also provided. CONCLUSION: The tools described here apply to many problems involving comparison and analysis of protein structures and their sequences. Chimera includes complete documentation and is intended for use by a wide range of scientists, not just those in the computational disciplines. UCSF Chimera is free for non-commercial use and is available for Microsoft Windows, Apple Mac OS X, Linux, and other platforms from http://www.cgl.ucsf.edu/chimera.