To investigate biophysics problems at the atomic and subatomic level, our group develops computational tools for Molecular Dynamics, both at the classical and the quantum level. Additionally, our group is part of the NIH Center for Macromolecular Modeling and Visualization, which is known worldwide for the development of both NAMD and VMD software. Particularly, we are on the main development team of VMD's QwikMD, a tool that simplifies the use of Molecular Dynamics tools, and the hybrid QM/MM implementation of NAMD. More recently we also started to work on combining artificial intelligence tools to both NAMD and VMD.
NAMD, recipient of a 2002 Gordon Bell Award, a 2012 Sidney Fernbach Award, and a 2020 Gordon Bell Prize, is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. Based on Charm++ parallel objects, NAMD scales to hundreds of cores for typical simulations and beyond 500,000 cores for the largest simulations. NAMD uses the popular molecular graphics program VMD for simulation setup and trajectory analysis, but is also file-compatible with AMBER, CHARMM, and X-PLOR. NAMD is distributed free of charge with source code. You can build NAMD yourself or download binaries for a wide variety of platforms. Our tutorials show you how to use NAMD and VMD for biomolecular modeling.
VMD is designed for modeling, visualization, and analysis of biological systems such as proteins, nucleic acids, lipid bilayer assemblies, etc. It may be used to view more general molecules, as VMD can read standard Protein Data Bank (PDB) files and display the contained structure. VMD provides a wide variety of methods for rendering and coloring a molecule: simple points and lines, CPK spheres and cylinders, licorice bonds, backbone tubes and ribbons, cartoon drawings, and others. VMD can be used to animate and analyze the trajectory of a molecular dynamics (MD) simulation. In particular, VMD can act as a graphical front end for an external MD program by displaying and animating a molecule undergoing simulation on a remote computer.
NAMD QM/MM interface extends existing NAMD features to the quantum mechanical level, presenting features that are not yet available in any QM/MM implementation. The first is the ability to execute multiple QM regions in parallel, thorough independent executions of your choice of quantum chemistry code. This allows one to account for multiple reaction centers that are known to work synergistically, for example, or even distant allosteric regulation sites and a reaction center. Investigation of processes occurring on a timescale usually not accessible by QM/MM methods can now be performed by a combination of temperature replica exchange molecular dynamics and QM/MM molecular dynamics. Taking advantage of its integration to VMD, NAMD QM/MM is an easy-to-use platform for hybrid simulations.
QwikMD is a VMD plugin to help to start and analyze MD simulations. The plugin helps, specially scientists that are starting to perform MD simulations, to prepare the necessary files to run these simulations in desktop machines all the way to large supercomputers. All the necessary steps, from the PDB to the configuration file is created with simple procedures so the user one can use the plugin to learn how to prepare MD simulations. The live simulation option allows for the visualization and analysis of the simulation on the fly, helping new users to learn more about MD simulations and expert users to test their simulations before submitting it to run in a supercomputer.
QwikFold is graphical interface plugin for artificial intelligence (AI) based structural biology tools, such as AlphaFold.
The Generalized Network Analysis tool allows its users to study allostery and signaling through network models. It can be used to display and manipulate representations of the networks projected onto the underlying molecular structures. Networks stored in simple formats can be loaded and mapped onto molecular structures.
Analyzing large sets of Molecular Dynamics (MD) trajectories is a major problem in computational biophysics. Combining extensive MD simulations to create a unique database allow us to link protein dynamics to mechanostability and binding affinity. We are using this database to inform the development and optimization of artificial intelligence (AI) models for optimization of protein interfaces.
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