A case of behavioural diversification in male floral function – the evolution of thigmonastic pollen presentation

The authors gratefully acknowledge funding provided by an Else-Neumann-Stipendium (http://www.fu-berlin.de/sites/promovieren/drs/nachwuchs/nachwuchs/nafoeg.html), Deutscher Akademischer Austausch Dienst (DAAD) and botconsult GmbH at different stages of data acquisition. We thank Tobias Grass, Joana Bergmann and Franziska Weber (Freie Universität Berlin) for help with data collection in the field and in the greenhouse. Nicole Schmandt, Federico Luebert, Juliana Chacón and Dietmar Quant (Universität Bonn) provided help in the molecular laboratory and the edition of the molecular dataset. We furthermore thank Markus Ackermann (Koblenz) for providing photographs, Philipp Klein (Berlin) for editing the video and Katy Jones (Berlin) for helpful comments on an earlier version of the manuscript. Rafael Acuña has been supported by the ALECOSTA scholarship program. Coverage of the article processing charge by the German Research Foundation via the Open Access Publication Fund of the Freie Universität Berlin is gratefully acknowledged.Peer reviewedPublisher PD

Efficient Characterization of Protein Cavities within Molecular Simulation Trajectories: <i>trj_cavity</i>

Protein cavities and tunnels are critical in determining phenomena such as ligand binding, molecular transport, and enzyme catalysis. Molecular dynamics (MD) simulations enable the exploration of the flexibility and conformational plasticity of protein cavities, extending the information available from static experimental structures relevant to, for example, drug design. Here, we present a new tool (<i>trj_cavity</i>) implemented within the GROMACS (www.gromacs.org) framework for the rapid identification and characterization of cavities detected within MD trajectories. <i>trj_cavity</i> is optimized for usability and computational efficiency and is applicable to the time-dependent analysis of any cavity topology, and optional specialized descriptors can be used to characterize, for example, protein channels. Its novel grid-based algorithm performs an efficient neighbor search whose calculation time is linear with system size, and a comparison of performance with other widely used cavity analysis programs reveals an orders-of-magnitude improvement in the computational cost. To demonstrate its potential for revealing novel mechanistic insights, <i>trj_cavity</i> has been used to analyze long-time scale simulation trajectories for three diverse protein cavity systems. This has helped to reveal, respectively, the lipid binding mechanism in the deep hydrophobic cavity of a soluble mite-allergen protein, Der p 2; a means for shuttling carbohydrates between the surface-exposed substrate-binding and catalytic pockets of a multidomain, membrane-proximal pullulanase, PulA; and the structural basis for selectivity in the transmembrane pore of a voltage-gated sodium channel (NavMs), embedded within a lipid bilayer environment. <i>trj_cavity</i> is available for download under an open-source license (http://sourceforge.net/projects/trjcavity). A simplified, GROMACS-independent version may also be compiled