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The proper choice of collective variables (CVs) is central to biased-sampling free energy reconstruction methods in molecular dynamics simulations. The PLUMED 2 library, for instance, provides several sophisticated CV choices, implemented in a C++ framework; however, developing new CVs is still time consuming due to the need to provide code for the analytical derivatives of all functions with respect to atomic coordinates. We present two solutions to this problem, namely (a) symbolic differentiation and code generation, and (b) automatic code differentiation, in both cases leveraging open-source libraries (SymPy and Stan Math, respectively). The two approaches are demonstrated and discussed in detail implementing a realistic example CV, the local radius of curvature of a polymer. Users may use the code as a template to streamline the implementation of their own CVs using high-level constructs and automatic gradient computation. Program summary Program Title: Practical approaches to the differentiation of collective variables in free energy codes: computer-algebra code generation and automatic differentiation Program Files doi: http://dx.doi.org/10.17632/r4r67bvkdn.1 Licensing provisions: GNU Lesser General Public License Version 3 (LGPL-3) Programming languages: C++, Python Nature of problem: The C++ implementation of collective variables (CVs, functions of atomic coordinates to be used in biased sampling applications) in biasing libraries for atomistic simulations, such as PLUMED [1], requires computation of both the variable and its gradient with respect to the atomic coordinates; coding and testing the analytical derivatives complicate the implementation of new CVs. Solution method: The paper shows two approaches to automate the computation of CV gradients, namely, symbolic differentiation with code generation and automatic code differentiation, demonstrating their implementation entirely with open-source software (respectively, SymPy and the Stan Math Library). Additional comments: The paper’s accompanying code serves as an example and template for the methods described in the paper; it is distributed as the two modules curvature_codegen and curvature_autodiff integrated in PLUMED 2’s source tree; the latest version is available at https://github.com/tonigi/plumed2-automatic-gradients . [1] Tribello GA, Bonomi M, Branduardi D, Camilloni C, Bussi G. PLUMED 2: New feathers for an old bird. Computer Physics Communications. 2014 Feb;185(2):604-13. [ABSTRACT FROM AUTHOR]

Molecular dynamics (MD) simulations allow the exploration of the phase space of biopolymers through the integration of equations of motion of their constituent atoms. The analysis of MD trajectories often relies on the choice of collective variables (CVs) along which the dynamics of the system is projected. We developed a graphical user interface (GUI) for facilitating the interactive choice of the appropriate CVs. The GUI allows: defining interactively new CVs; partitioning the configurations into microstates characterized by similar values of the CVs; calculating the free energies of the microstates for both unbiased and biased (metadynamics) simulations; clustering the microstates in kinetic basins; visualizing the free energy landscape as a function of a subset of the CVs used for the analysis. A simple mouse click allows one to quickly inspect structures corresponding to specific points in the landscape. Program summary Program Title: METAGUI 3 Program Files doi: http://dx.doi.org/10.17632/wyxjndwkbp.1 Licensing provisions: GPLv3 Programming language: Tcl/Tk, Fortran Journal reference of previous version: METAGUI [1] Does the new version supersede the previous version?: No Nature of problem: Choose the appropriate collective variables for describing the thermodynamics and kinetics of a biomolecular system through biased and unbiased molecular dynamics. Solution method: Provide an environment to compute and visualize free energy surfaces as a function of collective variables, interactively defined. Additional comments: METAGUI 3 is not a standalone program but a plugin that provides analysis features within VMD (version 1.9.2 or higher). [1] X. Biarnés, F. Pietrucci, F. Marinelli, A. Laio, METAGUI. A VMD interface for analyzing metadynamics and molecular dynamics simulations, Computer Physics Communications 183 (2012) 203–211. [ABSTRACT FROM AUTHOR]

PLUMED-GUI is an interactive environment to develop and test complex PLUMED scripts within the Visual Molecular Dynamics (VMD) environment. Computational biophysicists can take advantage of both PLUMED’s rich syntax to define collective variables (CVs) and VMD’s chemically-aware atom selection language, while working within a natural point-and-click interface. Pre-defined templates and syntax mnemonics facilitate the definition of well-known reaction coordinates. Complex CVs, e.g. involving reference snapshots used for RMSD or native contacts calculations, can be built through dialogs that provide a synoptic view of the available options. Scripts can be either exported for use in simulation programs, or evaluated on the currently loaded molecular trajectories. Script development takes place without leaving VMD, thus enabling an incremental try–see–modify development model for molecular metrics. Program summary: Program title: PLUMED-GUI (Collective variable analysis plugin) Catalogue identifier: AERU_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AERU_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: 3-clause BSD Open Source No. of lines in distributed program, including test data, etc.: 2651 No. of bytes in distributed program, including test data, etc.: 32359 Distribution format: tar.gz Programming language: TCL/TK. Computer: Workstations, PCs. Operating system: Linux/Unix, OSX, Windows. RAM: Sufficient to run PLUMED [1] and VMD [2]. Classification: 3, 23. Subprograms used: Nature of problem: Compute and visualize values of collective variables on molecular dynamics trajectories from within VMD, and interactively develop biasing scripts for the estimation of free-energy surfaces in PLUMED. Solution method: A graphical user interface is integrated in VMD and allows the user to interactively develop and run analysis scripts. Menus and dialogs provide mnemonics and documentation on the syntax to define complex CVs. Restrictions: Tested on systems up to 100,000 atoms. Unusual features: VMD–PLUMED is not a standalone program but a plugin that provides access to PLUMED’s analysis features from within VMD. Additional comments: Distributed with VMD since version 1.9.0. Manual update may be required to access the latest features. Running time: Computations of the values of collective variables, performed by the underlying PLUMED code, depends on the size of the system and the length of the trajectory; it is generally negligible with respect to simulation time. References: [[1]] G. A. Tribello, M. Bonomi, D. Branduardi, C. Camilloni, G. Bussi, PLUMED 2: New feathers for an old bird, Computer Physics Communications 185 (2014) 604. [[2]] W. Humphrey, A. Dalke, K. Schulten, VMD: visual molecular dynamics, J Mol Graph 14 (1996) 33–38. [ABSTRACT FROM AUTHOR]

Molecular dynamics simulations have a prominent role in biophysics and drug discovery due to the atomistic information they provide on the structure, energetics and dynamics of biomolecules. Specialized software packages are required to analyze simulated trajectories, either interactively or via scripts, to derive quantities of interest and provide insight for further experiments. This paper presents the Density Profile Tool, a package that enhances the Visual Molecular Dynamics environment with the ability to interactively compute and visualize 1-D projections of various density functions of molecular models. We describe how the plugin is used to perform computations both via a graphical interface and programmatically. Results are presented for realistic examples, all-atom bilayer models, showing how mass and electron densities readily provide measurements such as membrane thickness, location of structural elements, and how they compare to X-ray diffraction experiments. Program summary: Program title: Density Profile Tool Catalogue identifier: AEQM_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEQM_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: yes No. of lines in distributed program, including test data, etc.: 1742 No. of bytes in distributed program, including test data, etc.: 12764 Distribution format: tar.gz Programming language: TCL/TK. Computer: Any, with or without graphical display. Operating system: Linux/Unix, OSX, Windows. RAM: VMD should be able to hold the trajectory in memory. Classification: 3, 23. External routines: VMD (version 1.9 or higher) (http://www.ks.uiuc.edu/Research/vmd/). Nature of problem: Compute and visualize one-dimensional density profiles of molecular dynamics trajectories in the VMD environment, either interactively or programmatically. Solution method: Density profiles are computed by binning the simulation space into slabs of finite thickness. A graphical user interface allows the choice of the atomic property (number, mass, charge, electrons) and the details of the binning. Restrictions: The current version only supports orthorhombic cells. Unusual features: The Density Profile Tool is not a standalone program but a plug-in that enhances VMD’s analysis features. Running time: A contemporary PC completes the analysis of 500 frames of the example system discussed in the paper (35,000 atoms) in under 1 min. [ABSTRACT FROM AUTHOR]

Abstract: Distributed computing (DC) projects tackle large computational problems by exploiting the donated processing power of thousands of volunteered computers, connected through the Internet. To efficiently employ the computational resources of one of world''s largest DC efforts, GPUGRID, the project scientists require tools that handle hundreds of thousands of tasks which run asynchronously and generate gigabytes of data every day. We describe RBoinc, an interface that allows computational scientists to embed the DC methodology into the daily work-flow of high-throughput experiments. By extending the Berkeley Open Infrastructure for Network Computing (BOINC), the leading open-source middleware for current DC projects, with mechanisms to submit and manage large-scale distributed computations from individual workstations, RBoinc turns distributed grids into cost-effective virtual resources that can be employed by researchers in work-flows similar to conventional supercomputers. The GPUGRID project is currently using RBoinc for all of its in silico experiments based on molecular dynamics methods, including the determination of binding free energies and free energy profiles in all-atom models of biomolecules. [Copyright &y& Elsevier]