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Detecting micro domains in model membranes with APL@VORO

1/26/2015

APL@Voro is a program developed to aid in the analysis of Molecular dynamics trajectories of lipid bilayer simulations. Initially designed to work with GROMACS trajectory files, it may be used also with other trajectories if they are converted to Gromacs format (needed are the Gromacs trajectory file, PDB coordinate files and a GROMACS index files) to create a two dimensional geometric representation of a bilayer. The analysis of the bilayer is supported by using the Voronoi diagrams and Delaunay triangulations generated for different selection models of lipids. The values calculated on the geometric structures can be visualized in an interactive environment, plotted and exported to different file types. APL@Voro supports complex bilayers with a mix of various lipids and proteins and calculates the area per lipid and the bilayer thickness. The program is written in C++, open source and published under the GPL 3.0 License.

Download the software here.

For the algorithms used click here.

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SQUEEZE-E: How to make a simulation cell based on the shape of the molecule

10/11/2013

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Read below on how the authors below made a method to define a box which is based on the shape of the molecule. This should drastically recude the number of atoms and hence simulation time! i(if the rotation is constrained)

SQUEEZE-E: The Optimal Solution for Molecular Simulations with Periodic Boundary Conditions
by Tsjerk A. Wassenaar *†‡, Sjoerd de Vries ‡, Alexandre M. J. J. Bonvin ‡, and Henk Bekker §

In molecular simulations of macromolecules, it is desirable to limit the amount of solvent in the system to avoid spending computational resources on uninteresting solvent–solvent interactions. As a consequence, periodic boundary conditions are commonly used, with a simulation box chosen as small as possible, for a given minimal distance between images. Here, we describe how such a simulation cell can be set up for ensembles, taking into account a priori available or estimable information regarding conformational flexibility. Doing so ensures that any conformation present in the input ensemble will satisfy the distance criterion during the simulation. This helps avoid periodicity artifacts due to conformational changes. The method introduces three new approaches in computational geometry: (1) The first is the derivation of an optimal packing of ensembles, for which the mathematical framework is described. (2) A new method for approximating the α-hull and the contact body for single bodies and ensembles is presented, which is orders of magnitude faster than existing routines, allowing the calculation of packings of large ensembles and/or large bodies. 3. A routine is described for searching a combination of three vectors on a discretized contact body forming a reduced base for a lattice with minimal cell volume. The new algorithms reduce the time required to calculate packings of single bodies from minutes or hours to seconds. The use and efficacy of the method is demonstrated for ensembles obtained from NMR, MD simulations, and elastic network modeling. An implementation of the method has been made available online at http://haddock.chem.uu.nl/services/SQUEEZE/ and has been made available as an option for running simulations through the weNMR GRID MD server at http://haddock.science.uu.nl/enmr/services/GROMACS/main.php.

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Computational Drug Discovery and Design volume from @SpringerPub

3/1/2013

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Riccardo Baron also put together a great computational methods volume you should have access to:http://link.springer.com/book/10.1007/978-1-61779-465-0/page/1
Here's the list of contents:

Drug Binding Site Prediction, Design, and Descriptors
A Molecular Dynamics Ensemble-Based Approach for the Mapping of Druggable Binding Sites

Anthony Ivetac, J. Andrew McCammon Look Inside Get Access

Analysis of Protein Binding Sites by Computational Solvent Mapping

David R. Hall, Dima Kozakov, Sandor Vajda

Evolutionary Trace for Prediction and Redesign of Protein Functional Sites

Angela Wilkins,Serkan Erdin,Rhonald Lua,Olivier Lichtarge

Information Entropic Functions for Molecular Descriptor Profiling

Anne Mai Wassermann,Britta Nisius,Martin Vogt,Jürgen Bajorath

Virtual Screening of Large Compound Libraries: Including Molecular Flexibility
Expanding the Conformational Selection Paradigm in Protein-Ligand Docking

Guray Kuzu,Ozlem Keskin,Attila Gursoy,Ruth Nussinov Look Inside Get Access

Flexibility Analysis of Biomacromolecules with Application to Computer-Aided Drug Design

Simone Fulle,Holger Gohlke

On the Use of Molecular Dynamics Receptor Conformations for Virtual Screening

Sara E. Nichols,Riccardo Baron,J. Andrew McCammon

Virtual Ligand Screening Against Comparative Protein Structure Models

Hao Fan,John J. Irwin,Andrej Sali

AMMOS Software: Method and Application

T. Pencheva,D. Lagorce,I. Pajeva,B. O. Villoutreix,M. A. Miteva

Rosetta Ligand Docking with Flexible XML Protocols

Gordon Lemmon,Jens Meiler

Normal Mode-Based Approaches in Receptor Ensemble Docking

Claudio N. Cavasotto

Application of Conformational Clustering in Protein–Ligand Docking

Giovanni Bottegoni,Walter Rocchia,Andrea Cavalli

How to Benchmark Methods for Structure-Based Virtual Screening of Large Compound Libraries

Andrew J. Christofferson,Niu Huang

Prediction of Protein-Protein Docking and Interactions
AGGRESCAN: Method, Application, and Perspectives for Drug Design

Natalia S. de Groot,Virginia Castillo,Ricardo Graña-Montes,Salvador Ventura

ATTRACT and PTOOLS: Open Source Programs for Protein–Protein Docking

Sebastian Schneider,Adrien Saladin,Sébastien Fiorucci,Chantal Prévost

Prediction of Interacting Protein Residues Using Sequence and Structure Data

Vedran Franke,Mile Šikić,Kristian Vlahoviček

Rescoring Docking Predictions
MM-GB/SA Rescoring of Docking Poses

Cristiano R. W. Guimarães

A Case Study of Scoring and Rescoring in Peptide Docking

Zunnan Huang, Chung F. Wong

The Solvated Interaction Energy Method for Scoring Binding Affinities

Traian Sulea, Enrico O. Purisima

Linear Interaction Energy: Method and Applications in Drug Design

Hugo Gutiérrez-de-Terán, Johan Åqvist

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Analysis of MD simulations using GROMACS tools

11/7/2012

3 Comments

I just came across this presentation which very nicely summarises the most important analysis tools for proteins available in Gromacs: Definitely worth reading and very good as a reference for experienced gromacs users.

Analysis tools that you can find in the presentation include:
- Looking at your trajectory
- Groups in analysis
- Root mean square deviations and fluctuations
- Radius of gyration and distances
- Hydrogen bonds
- Secondary structure analysis
- Free energy surfaces
- Principal component analysis: using Cartesian coordinates or dihedral angles
- Clustering

Evi

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Detecting micro domains in model membranes with APL@VORO

SQUEEZE-E: How to make a simulation cell based on the shape of the molecule

Computational Drug Discovery and Design volume from @SpringerPub

Analysis of MD simulations using GROMACS tools

Alexis, Giannis, Melina, Sofia, Eleftheria, Isidora, Zoi, Dimitris, Michalis, Danae, Themis, George, Katerina, Aspasia, Zoe

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