ProtPOS: a python package for the prediction of protein preferred orientation on a surface.
ABSTRACT: Atomistic molecular dynamics simulation is a promising technique to investigate the energetics and dynamics in the protein-surface adsorption process which is of high relevance to modern biotechnological applications. To increase the chance of success in simulating the adsorption process, favorable orientations of the protein at the surface must be determined. Here, we present ProtPOS which is a lightweight and easy-to-use python package that can predict low-energy protein orientations on a surface of interest. It combines a fast conformational sampling algorithm with the energy calculation of GROMACS. The advantage of ProtPOS is it allows users to select any force fields suitable for the system at hand and provide structural output readily available for further simulation studies.ProtPOS is freely available for academic and non-profit uses at http://cbbio.cis.umac.mo/software/protposSupplementary data are available at Bioinformatics email@example.com.
Project description:In this paper, we introduce JGromacs, a Java API (Application Programming Interface) that facilitates the development of cross-platform data analysis applications for Molecular Dynamics (MD) simulations. The API supports parsing and writing file formats applied by GROMACS (GROningen MAchine for Chemical Simulations), one of the most widely used MD simulation packages. JGromacs builds on the strengths of object-oriented programming in Java by providing a multilevel object-oriented representation of simulation data to integrate and interconvert sequence, structure, and dynamics information. The easy-to-learn, easy-to-use, and easy-to-extend framework is intended to simplify and accelerate the implementation and development of complex data analysis algorithms. Furthermore, a basic analysis toolkit is included in the package. The programmer is also provided with simple tools (e.g., XML-based configuration) to create applications with a user interface resembling the command-line interface of GROMACS applications.JGromacs and detailed documentation is freely available from http://sbcb.bioch.ox.ac.uk/jgromacs under a GPLv3 license .
Project description:Two-dimensional molybdenum disulfide (MoS2) has attracted intense interest owing to its unique properties and promising biosensor applications. To develop effective biocompatible platforms, it is crucial to understand the interactions between MoS2 and biological molecules such as proteins, but little knowledge exists on the orientation and conformation of proteins on the MoS2 surface at the molecular level. In this work, the lysozyme adsorption on the MoS2 surface was studied by molecular dynamics simulations, wherein six different orientations were selected based on the different faces of lysozyme. Simulation results showed that lysozyme tends to adsorb on the MoS2 surface in an "end-on" orientation, indicating that orientations within this range are favorable for stable adsorption. The end-on orientation could be further categorized into "bottom end-on" and "top end-on" orientations. The driving forces responsible for the adsorption were dominated by van der Waals interactions and supplemented by electrostatic interactions. Further, the conformations of the lysozyme adsorbed on the MoS2 surface were basically preserved. This simulation study promotes the fundamental understanding of interactions between MoS2 and proteins and can guide the development of future biomedical applications of MoS2.
Project description:As the amount of data generated by biomolecular simulations dramatically increases, new tools need to be developed to help manage this data at the individual investigator or small research group level. In this paper, we introduce iBIOMES Lite, a lightweight tool for biomolecular simulation data indexing and summarization. The main goal of iBIOMES Lite is to provide a simple interface to summarize computational experiments in a setting where the user might have limited privileges and limited access to IT resources. A command-line interface allows the user to summarize, publish, and search local simulation data sets. Published data sets are accessible via static hypertext markup language (HTML) pages that summarize the simulation protocols and also display data analysis graphically. The publication process is customized via extensible markup language (XML) descriptors while the HTML summary template is customized through extensible stylesheet language (XSL). iBIOMES Lite was tested on different platforms and at several national computing centers using various data sets generated through classical and quantum molecular dynamics, quantum chemistry, and QM/MM. The associated parsers currently support AMBER, GROMACS, Gaussian, and NWChem data set publication. The code is available at https://github.com/jcvthibault/ibiomes .
Project description:We present here a free, open source Python 3D graphics library called Ratcave that extends existing Python psychology stimulus software by allowing scientists to load, display, and transform 3D stimuli created in 3D modeling software. This library makes 3D programming intuitive to new users by providing 3D graphics engine concepts (Mesh, Scene, Light, and Camera classes) that can be manipulated using an interface similar to existing 2D stimulus libraries. In addition, the use of modern OpenGL constructs by Ratcave helps scientists create fast, hardware-accelerated dynamic stimuli using the same intuitive high-level, lightweight interface. Because Ratcave supplements, rather than replaces, existing Python stimulus libraries, scientists can continue to use their preferred libraries by simply adding Ratcave graphics to their existing experiments. We hope this tool will be useful both as a stimulus library and as an example of how tightly-focused libraries can add quality to the existing scientific open-source software ecosystem.
Project description:Free energy calculations based on molecular dynamics (MD) simulations have seen a tremendous growth in the last decade. However, it is still difficult and tedious to set them up in an automated manner, as the majority of the present-day MD simulation packages lack that functionality. Relative free energy calculations are a particular challenge for several reasons, including the problem of finding a common substructure and mapping the transformation to be applied. Here we present a tool, alchemical-setup.py, that automatically generates all the input files needed to perform relative solvation and binding free energy calculations with the MD package GROMACS. When combined with Lead Optimization Mapper (LOMAP; Liu et al. in J Comput Aided Mol Des 27(9):755-770, 2013), recently developed in our group, alchemical-setup.py allows fully automated setup of relative free energy calculations in GROMACS. Taking a graph of the planned calculations and a mapping, both computed by LOMAP, our tool generates the topology and coordinate files needed to perform relative free energy calculations for a given set of molecules, and provides a set of simulation input parameters. The tool was validated by performing relative hydration free energy calculations for a handful of molecules from the SAMPL4 challenge (Mobley et al. in J Comput Aided Mol Des 28(4):135-150, 2014). Good agreement with previously published results and the straightforward way in which free energy calculations can be conducted make alchemical-setup.py a promising tool for automated setup of relative solvation and binding free energy calculations.
Project description:The use of standard molecular dynamics simulation methods to predict the interactions of a protein with a material surface have the inherent limitations of lacking the ability to determine the most likely conformations and orientations of the adsorbed protein on the surface and to determine the level of convergence attained by the simulation. In addition, standard mixing rules are typically applied to combine the nonbonded force field parameters of the solution and solid phases the system to represent interfacial behavior without validation. As a means to circumvent these problems, the authors demonstrate the application of an efficient advanced sampling method (TIGER2A) for the simulation of the adsorption of hen egg-white lysozyme on a crystalline (110) high-density polyethylene surface plane. Simulations are conducted to generate a Boltzmann-weighted ensemble of sampled states using force field parameters that were validated to represent interfacial behavior for this system. The resulting ensembles of sampled states were then analyzed using an in-house-developed cluster analysis method to predict the most probable orientations and conformations of the protein on the surface based on the amount of sampling performed, from which free energy differences between the adsorbed states were able to be calculated. In addition, by conducting two independent sets of TIGER2A simulations combined with cluster analyses, the authors demonstrate a method to estimate the degree of convergence achieved for a given amount of sampling. The results from these simulations demonstrate that these methods enable the most probable orientations and conformations of an adsorbed protein to be predicted and that the use of our validated interfacial force field parameter set provides closer agreement to available experimental results compared to using standard CHARMM force field parameterization to represent molecular behavior at the interface.
Project description:Many biochemical systems require stochastic descriptions. Unfortunately these can only be solved for the simplest cases and their direct simulation can become prohibitively expensive, precluding thorough analysis. As an alternative, moment closure approximation methods generate equations for the time-evolution of the system's moments and apply a closure ansatz to obtain a closed set of differential equations; that can become the basis for the deterministic analysis of the moments of the outputs of stochastic systems.We present a free, user-friendly tool implementing an efficient moment expansion approximation with parametric closures that integrates well with the IPython interactive environment. Our package enables the analysis of complex stochastic systems without any constraints on the number of species and moments studied and the type of rate laws in the system. In addition to the approximation method our package provides numerous tools to help non-expert users in stochastic analysis.https://firstname.lastname@example.org or email@example.comSupplementary data are available at Bioinformatics online.
Project description:Molecular dynamics (MD) simulation engines use a variety of different approaches for modeling molecular systems with force fields that govern their dynamics and describe their topology. These different approaches introduce incompatibilities between engines, and previously published software bridges the gaps between many popular MD packages, such as between CHARMM and AMBER or GROMACS and LAMMPS. While there are many structure building tools available that generate topologies and structures in CHARMM format, only recently have mechanisms been developed to convert their results into GROMACS input. We present an approach to convert CHARMM-formatted topology and parameters into a format suitable for simulation with GROMACS by expanding the functionality of TopoTools, a plugin integrated within the widely used molecular visualization and analysis software VMD. The conversion process was diligently tested on a comprehensive set of biological molecules in vacuo. The resulting comparison between energy terms shows that the translation performed was lossless as the energies were unchanged for identical starting configurations. By applying the conversion process to conventional benchmark systems that mimic typical modestly sized MD systems, we explore the effect of the implementation choices made in CHARMM, NAMD, and GROMACS. The newly available automatic conversion capability breaks down barriers between simulation tools and user communities and allows users to easily compare simulation programs and leverage their unique features without the tedium of constructing a topology twice.
Project description:Molecular dynamics simulation studies were employed to investigate the microscopic behaviors of CH<sub>4</sub> and CO<sub>2</sub> molecules in slit-nanopores (SNPs) with various surfaces and different compositions. Three kinds of SNPs were constructed by a pair-wise combination of graphene, silica, and the calcite surface. The grand canonical Monte Carlo and molecular dynamics simulation methods were used to investigate the adsorption and self-diffusion of the gases in the nanopores. It is found that in all three cases, the CH<sub>4</sub> molecules prefer to adsorb onto the graphene surface, whereas the CO<sub>2</sub> molecules prefer to adsorb onto the calcite surface. The adsorption intensity of gases adsorbed onto various surfaces, the adsorption distances, along with the details of adsorption orientations of CH<sub>4</sub> and CO<sub>2</sub> molecules on various surfaces are calculated. The surface characteristics, such as surface roughness and charge distribution, are analyzed to help understand the microscopic adsorption behaviors of the gases on the specific surface. It was found that competitive adsorptions of CO<sub>2</sub> over CH<sub>4</sub> broadly occurred, especially in the SNPs containing calcite, because of the strong adsorption interactions between the CO<sub>2</sub> molecules and the calcite surface. This work provides the microbehaviors of CH<sub>4</sub> and CO<sub>2</sub> in SNPs with various surfaces in different compositions to provide useful guidance for better understanding about the microstate of gases in complex nanoporous shale formation and to give out useful guidance for enhancing shale gas recovery by injecting CO<sub>2</sub>.
Project description:LOOS (Lightweight Object Oriented Structure-analysis) is a C++ library designed to facilitate making novel tools for analyzing molecular dynamics simulations by abstracting out the repetitive tasks, allowing developers to focus on the scientifically relevant part of the problem. LOOS supports input using the native file formats of most common biomolecular simulation packages, including CHARMM, NAMD, Amber, Tinker, and Gromacs. A dynamic atom selection language based on the C expression syntax is included and is easily accessible to the tool-writer. In addition, LOOS is bundled with over 140 prebuilt tools, including suites of tools for analyzing simulation convergence, three-dimensional histograms, and elastic network models. Through modern C++ design, LOOS is both simple to develop with (requiring knowledge of only four core classes and a few utility functions) and is easily extensible. A python interface to the core classes is also provided, further facilitating tool development.