Identification of sequence changes in myosin II that adjust muscle contraction velocity.

The speed of muscle contraction is related to body size; muscles in larger species contract at slower rates. Since contraction speed is a property of the myosin isoform expressed in a muscle, we investigated how sequence changes in a range of muscle myosin II isoforms enable this slower rate of muscle contraction. We considered 798 sequences from 13 mammalian myosin II isoforms to identify any adaptation to increasing body mass. We identified a correlation between body mass and sequence divergence for the motor domain of the 4 major adult myosin II isoforms (β/Type I, IIa, IIb, and IIx), suggesting that these isoforms have adapted to increasing body mass. In contrast, the non-muscle and developmental isoforms show no correlation of sequence divergence with body mass. Analysis of the motor domain sequence of β-myosin (predominant myosin in Type I/slow and cardiac muscle) from 67 mammals from 2 distinct clades identifies 16 sites, out of 800, associated with body mass (padj 0.05). Both clades change the same small set of amino acids, in the same order from small to large mammals, suggesting a limited number of ways in which contraction velocity can be successfully manipulated. To test this relationship, the 9 sites that differ between human and rat were mutated in the human β-myosin to match the rat sequence. Biochemical analysis revealed that the rat-human β-myosin chimera functioned like the native rat myosin with a 2-fold increase in both motility and in the rate of ADP release from the actin-myosin crossbridge (the step that limits contraction velocity). Thus, these sequence changes indicate adaptation of β-myosin as species mass increased to enable a reduced contraction velocity and heart rate

PDBe-KB: collaboratively defining the biological context of structural data

The Protein Data Bank in Europe - Knowledge Base (PDBe-KB, https://pdbe-kb.org) is an open collaboration between world-leading specialist data resources contributing functional and biophysical annotations derived from or relevant to the Protein Data Bank (PDB). The goal of PDBe-KB is to place macromolecular structure data in their biological context by developing standardised data exchange formats and integrating functional annotations from the contributing partner resources into a knowledge graph that can provide valuable biological insights. Since we described PDBe-KB in 2019, there have been significant improvements in the variety of available annotation data sets and user functionality. Here, we provide an overview of the consortium, highlighting the addition of annotations such as predicted covalent binders, phosphorylation sites, effects of mutations on the protein structure and energetic local frustration. In addition, we describe a library of reusable web-based visualisation components and introduce new features such as a bulk download data service and a novel superposition service that generates clusters of superposed protein chains weekly for the whole PDB archive

PDBe-KB: a community-driven resource for structural and functional annotations.

The Protein Data Bank in Europe-Knowledge Base (PDBe-KB, https://pdbe-kb.org) is a community-driven, collaborative resource for literature-derived, manually curated and computationally predicted structural and functional annotations of macromolecular structure data, contained in the Protein Data Bank (PDB). The goal of PDBe-KB is two-fold: (i) to increase the visibility and reduce the fragmentation of annotations contributed by specialist data resources, and to make these data more findable, accessible, interoperable and reusable (FAIR) and (ii) to place macromolecular structure data in their biological context, thus facilitating their use by the broader scientific community in fundamental and applied research. Here, we describe the guidelines of this collaborative effort, the current status of contributed data, and the PDBe-KB infrastructure, which includes the data exchange format, the deposition system for added value annotations, the distributable database containing the assembled data, and programmatic access endpoints. We also describe a series of novel web-pages-the PDBe-KB aggregated views of structure data-which combine information on macromolecular structures from many PDB entries. We have recently released the first set of pages in this series, which provide an overview of available structural and functional information for a protein of interest, referenced by a UniProtKB accession

Steroid drugs inhibit bacterial respiratory oxidases and are lethal towards methicillin-resistant Staphylococcus aureus

Background: Cytochrome bd complexes are respiratory oxidases found exclusively in prokaryotes that are important during infection for numerous bacterial pathogens. Methods: In silico docking was employed to screen approved drugs for their ability to bind to the quinol site of Escherichia coli cytochrome bd-I. Respiratory inhibition was assessed with oxygen electrodes using membranes isolated from E. coli and Methicillin-resistant Staphylococcus aureus strains expressing single respiratory oxidases (i.e., cytochromes bd, bo or aa3). Growth/viability assays were used to measure bacteriostatic and bactericidal effects. Results: The steroid drugs ethinylestradiol and quinestrol inhibited E. coli bd-I activity with IC50 values of 47 ± 28.9 µg/mL (158 ± 97.2 µM) and 0.2 ± 0.04 µg/mL (0.5 ± 0.1 µM), respectively. Quinestrol inhibited growth of an E. coli ‘bd-I only’ strain with an IC50 of 0.06 ± 0.02 µg/mL (0.2 ± 0.07 µM). Growth of a S. aureus ‘bd only’ strain was inhibited by quinestrol with an IC50 of 2.2 ± 0.43 µg/mL (6.0 ± 1.2 µM). Quinestrol exhibited potent bactericidal effects against S. aureus but not E. coli. Conclusions: Quinestrol inhibits cytochrome bd in E. coli and S. aureus membranes and inhibits the growth of both species yet is only bactericidal towards S. aureus

PDBe-KB: a community-driven resource for structural and functional annotations

The Protein Data Bank in Europe-Knowledge Base (PDBe-KB, https://pdbe-kb.org) is a community-driven, collaborative resource for literature-derived, manually curated and computationally predicted structural and functional annotations of macromolecular structure data, contained in the Protein Data Bank (PDB). The goal of PDBe-KB is two-fold: (i) to increase the visibility and reduce the fragmentation of annotations contributed by specialist data resources, and to make these data more findable, accessible, interoperable and reusable (FAIR) and (ii) to place macromolecular structure data in their biological context, thus facilitating their use by the broader scientific community in fundamental and applied research. Here, we describe the guidelines of this collaborative effort, the current status of contributed data, and the PDBe-KB infrastructure, which includes the data exchange format, the deposition system for added value annotations, the distributable database containing the assembled data, and programmatic access endpoints. We also describe a series of novel web-pages—the PDBe-KB aggregated views of structure data—which combine information on macromolecular structures from many PDB entries. We have recently released the first set of pages in this series, which provide an overview of available structural and functional information for a protein of interest, referenced by a UniProtKB accession

PDBe-KB: collaboratively defining the biological context of structural data

none71: The Protein Data Bank in Europe - Knowledge Base (PDBe-KB, https://pdbe-kb.org) is an open collaboration between world-leading specialist data resources contributing functional and biophysical annotations derived from or relevant to the Protein Data Bank (PDB). The goal of PDBe-KB is to place macromolecular structure data in their biological context by developing standardised data exchange formats and integrating functional annotations from the contributing partner resources into a knowledge graph that can provide valuable biological insights. Since we described PDBe-KB in 2019, there have been significant improvements in the variety of available annotation data sets and user functionality. Here, we provide an overview of the consortium, highlighting the addition of annotations such as predicted covalent binders, phosphorylation sites, effects of mutations on the protein structure and energetic local frustration. In addition, we describe a library of reusable web-based visualisation components and introduce new features such as a bulk download data service and a novel superposition service that generates clusters of superposed protein chains weekly for the whole PDB archive.noneVaradi, Mihaly; Anyango, Stephen; Armstrong, David; Berrisford, John; Choudhary, Preeti; Deshpande, Mandar; Nadzirin, Nurul; Nair, Sreenath S; Pravda, Lukas; Tanweer, Ahsan; Al-Lazikani, Bissan; Andreini, Claudia; Barton, Geoffrey J; Bednar, David; Berka, Karel; Blundell, Tom; Brock, Kelly P; Carazo, Jose Maria; Damborsky, Jiri; David, Alessia; Dey, Sucharita; Dunbrack, Roland; Recio, Juan Fernandez; Fraternali, Franca; Gibson, Toby; Helmer-Citterich, Manuela; Hoksza, David; Hopf, Thomas; Jakubec, David; Kannan, Natarajan; Krivak, Radoslav; Kumar, Manjeet; Levy, Emmanuel D; London, Nir; Macias, Jose Ramon; Srivatsan, Madhusudhan M; Marks, Debora S; Martens, Lennart; McGowan, Stuart A; McGreig, Jake E; Modi, Vivek; Parra, R Gonzalo; Pepe, Gerardo; Piovesan, Damiano; Prilusky, Jaime; Putignano, Valeria; Radusky, Leandro G; Ramasamy, Pathmanaban; Rausch, Atilio O; Reuter, Nathalie; Rodriguez, Luis A; Rollins, Nathan J; Rosato, Antonio; Rubach, Paweł; Serrano, Luis; Singh, Gulzar; Skoda, Petr; Sorzano, Carlos Oscar S; Stourac, Jan; Sulkowska, Joanna I; Svobodova, Radka; Tichshenko, Natalia; Tosatto, Silvio C E; Vranken, Wim; Wass, Mark N; Xue, Dandan; Zaidman, Daniel; Thornton, Janet; Sternberg, Michael; Orengo, Christine; Velankar, SameerVaradi, Mihaly; Anyango, Stephen; Armstrong, David; Berrisford, John; Choudhary, Preeti; Deshpande, Mandar; Nadzirin, Nurul; Nair, Sreenath S; Pravda, Lukas; Tanweer, Ahsan; Al-Lazikani, Bissan; Andreini, Claudia; Barton, Geoffrey J; Bednar, David; Berka, Karel; Blundell, Tom; Brock, Kelly P; Carazo, Jose Maria; Damborsky, Jiri; David, Alessia; Dey, Sucharita; Dunbrack, Roland; Recio, Juan Fernandez; Fraternali, Franca; Gibson, Toby; Helmer-Citterich, Manuela; Hoksza, David; Hopf, Thomas; Jakubec, David; Kannan, Natarajan; Krivak, Radoslav; Kumar, Manjeet; Levy, Emmanuel D; London, Nir; Macias, Jose Ramon; Srivatsan, Madhusudhan M; Marks, Debora S; Martens, Lennart; Mcgowan, Stuart A; Mcgreig, Jake E; Modi, Vivek; Parra, R Gonzalo; Pepe, Gerardo; Piovesan, Damiano; Prilusky, Jaime; Putignano, Valeria; Radusky, Leandro G; Ramasamy, Pathmanaban; Rausch, Atilio O; Reuter, Nathalie; Rodriguez, Luis A; Rollins, Nathan J; Rosato, Antonio; Rubach, Paweł; Serrano, Luis; Singh, Gulzar; Skoda, Petr; Sorzano, Carlos Oscar S; Stourac, Jan; Sulkowska, Joanna I; Svobodova, Radka; Tichshenko, Natalia; Tosatto, Silvio C E; Vranken, Wim; Wass, Mark N; Xue, Dandan; Zaidman, Daniel; Thornton, Janet; Sternberg, Michael; Orengo, Christine; Velankar, Samee