Molecular dynamics (MD) is a computer simulation method for analyzing the physical movements of atoms and molecules. The atoms and molecules are allowed to interact for a fixed period of time, giving a view of the dynamic "evolution" of the system. In the most common version, the trajectories of atoms and molecules are determined by numerically solving Newton's equations of motion for a system of interacting particles, where forces between the particles and their potential energies are often calculated using interatomic potentials or molecular mechanical force fields. The method is applied mostly in chemical physics, materials science, and biophysics.
Assisted Model Building with Energy Refinement (AMBER) is the name of a widely-used molecular dynamics software package originally developed by Peter Kollman's group at the University of California, San Francisco. It has also, subsequently, come to designate a family of force fields for molecular dynamics of biomolecules that can be used both within the AMBER software suite and with many modern computational platforms.
Chemistry at Harvard Macromolecular Mechanics (CHARMM) is the name of a widely used set of force fields for molecular dynamics, and the name for the molecular dynamics simulation and analysis computer software package associated with them. The CHARMM Development Project involves a worldwide network of developers working with Martin Karplus and his group at Harvard to develop and maintain the CHARMM program. Licenses for this software are available, for a fee, to people and groups working in academia.
Molecular mechanics uses classical mechanics to model molecular systems. The Born–Oppenheimer approximation is assumed valid and the potential energy of all systems is calculated as a function of the nuclear coordinates using force fields. Molecular mechanics can be used to study molecule systems ranging in size and complexity from small to large biological systems or material assemblies with many thousands to millions of atoms.
Visual Molecular Dynamics (VMD) is a molecular modelling and visualization computer program. VMD is developed mainly as a tool to view and analyze the results of molecular dynamics simulations. It also includes tools for working with volumetric data, sequence data, and arbitrary graphics objects. Molecular scenes can be exported to external rendering tools such as POV-Ray, RenderMan, Tachyon, Virtual Reality Modeling Language (VRML), and many others. Users can run their own Tcl and Python scripts within VMD as it includes embedded Tcl and Python interpreters. VMD runs on Unix, Apple Mac macOS, and Microsoft Windows. VMD is available to non-commercial users under a distribution-specific license which permits both use of the program and modification of its source code, at no charge.
Molecular modelling encompasses all methods, theoretical and computational, used to model or mimic the behaviour of molecules. The methods are used in the fields of computational chemistry, drug design, computational biology and materials science to study molecular systems ranging from small chemical systems to large biological molecules and material assemblies. The simplest calculations can be performed by hand, but inevitably computers are required to perform molecular modelling of any reasonably sized system. The common feature of molecular modelling methods is the atomistic level description of the molecular systems. This may include treating atoms as the smallest individual unit, or explicitly modelling protons and neutrons with its quarks, anti-quarks and gluons and electrons with its photons.
Molden is a general molecular and electronic structure processing program.
In the field of molecular modeling, docking is a method which predicts the preferred orientation of one molecule to a second when a ligand and a target are bound to each other to form a stable complex. Knowledge of the preferred orientation in turn may be used to predict the strength of association or binding affinity between two molecules using, for example, scoring functions.
In the context of chemistry, molecular physics, physical chemistry, and molecular modelling, a force field is a computational model that is used to describe the forces between atoms within molecules or between molecules as well as in crystals. Force fields are a variety of interatomic potentials. More precisely, the force field refers to the functional form and parameter sets used to calculate the potential energy of a system on the atomistic level. Force fields are usually used in molecular dynamics or Monte Carlo simulations. The parameters for a chosen energy function may be derived from classical laboratory experiment data, calculations in quantum mechanics, or both. Force fields utilize the same concept as force fields in classical physics, with the main difference being that the force field parameters in chemistry describe the energy landscape on the atomistic level. From a force field, the acting forces on every particle are derived as a gradient of the potential energy with respect to the particle coordinates.
BALL is a C++ class framework and set of algorithms and data structures for molecular modelling and computational structural bioinformatics, a Python interface to this library, and a graphical user interface to BALL, the molecule viewer BALLView.
UTOPIA is a suite of free tools for visualising and analysing bioinformatics data. Based on an ontology-driven data model, it contains applications for viewing and aligning protein sequences, rendering complex molecular structures in 3D, and for finding and using resources such as web services and data objects. There are two major components, the protein analysis suite and UTOPIA documents.
This is a list of computer programs that are predominantly used for molecular mechanics calculations.
WHAT IF is a computer program used in a wide variety of computational macromolecular structure research fields. The software provides a flexible environment to display, manipulate, and analyze small and large molecules, proteins, nucleic acids, and their interactions.
Molecular modeling on GPU is the technique of using a graphics processing unit (GPU) for molecular simulations.
Desmond is a software package developed at D. E. Shaw Research to perform high-speed molecular dynamics simulations of biological systems on conventional computer clusters. The code uses novel parallel algorithms and numerical methods to achieve high performance on platforms containing multiple processors, but may also be executed on a single computer.
Ascalaph Designer is a computer program for general purpose molecular modelling for molecular design and simulations. It provides a graphical environment for the common programs of quantum and classical molecular modelling ORCA, NWChem, Firefly, CP2K and MDynaMix . The molecular mechanics calculations cover model building, energy optimizations and molecular dynamics. Firefly covers a wide range of quantum chemistry methods. Ascalaph Designer is free and open-source software, released under the GNU General Public License, version 2 (GPLv2).
MacroModel is a computer program for molecular modelling of organic compounds and biopolymers. It features various chemistry force fields, plus energy minimizing algorithms, to predict geometry and relative conformational energies of molecules. MacroModel is maintained by Schrödinger, LLC.
FoldX is a protein design algorithm that uses an empirical force field. It can determine the energetic effect of point mutations as well as the interaction energy of protein complexes. FoldX can mutate protein and DNA side chains using a probability-based rotamer library, while exploring alternative conformations of the surrounding side chains.
In biochemistry, a backbone-dependent rotamer library provides the frequencies, mean dihedral angles, and standard deviations of the discrete conformations of the amino acid side chains in proteins as a function of the backbone dihedral angles φ and ψ of the Ramachandran map. By contrast, backbone-independent rotamer libraries express the frequencies and mean dihedral angles for all side chains in proteins, regardless of the backbone conformation of each residue type. Backbone-dependent rotamer libraries have been shown to have significant advantages over backbone-independent rotamer libraries, principally when used as an energy term, by speeding up search times of side-chain packing algorithms used in protein structure prediction and protein design.
