Desmond for Materials Science

High-performance molecular dynamics (MD) engine providing high scalability, throughput, and scientific accuracy

Desmond for Materials Science

Understand and predict key properties of materials with fast, accurate molecular dynamics

Desmond is a GPU-powered high-performance molecular dynamics (MD) engine for predicting bulk properties of materials, such as thermophysical properties, elastic constants, stress/strain relationships, diffusion coefficients, viscosity, persistence length, free energy of solvation, and more. Desmond also characterizes structure and properties in complex systems involving non-equilibrium systems as well as interfaces or self-assembled structures.

Comprehensive molecular dynamics capabilities

Speed time to market of new catalysts
Exceptional performance

Achieve exceptional throughput on commodity Linux clusters with both typical and high-end networks. Improve computing speed by 100x on general-purpose GPU (GPGPU) versus single CPU.

Superior accuracy
Superior accuracy

Constructed with a focus on numerical accuracy, stability, and rigor. Enables the simulation of large scale features of nanometers to micron size over time scales of picoseconds to microseconds.

Trusted energetics
Trusted energetics

Provides a robust framework for the calculation of energies and forces for atomistic and coarse grained force field models. Compatible with chemistries commonly used in both biomolecular and condensed-matter research.

Realistic simulations
Realistic simulations

Perform explicit solvent simulations with periodic boundary conditions using cubic, orthorhombic, truncated octahedron, rhombic dodecahedron, and arbitrary triclinic simulation boxes with careful attention to the efficient and accurate calculation of long-range electrostatics, and can be used to model explicit membrane systems, complex mixtures, polymers, and interfaces under various conditions.

Easy-to-use interface
Easy-to-use interface

Support automated simulation setup, including multistage MD simulations with built-in simulation protocols, prediction of equation of states (EOS) at multiple temperatures, and prediction of dynamic responses at non-equilibrium states. An intuitive interface provides intelligent default settings and allows for rapid setup of computational experiments. 

Powerful analysis tools
Powerful analysis tools

Visualize and examine computed results within the same MS Maestro modeling environment that connects to a comprehensive suite of modeling tools from quantum mechanics to machine learning.

Case Studies

Discover how Schrödinger technology is being used to solve real-world research challenges.

Molecular dynamics and coarse-grained simulations facilitate design new eco-friendly cosmetic formulations

Prediction of moisture adsorption and effects on amorphous starch

Molecular dynamics simulations accelerate the development and optimization of recyclable tire materials

Broad applications across materials science research areas

Get more from your ideas by harnessing the power of large-scale chemical exploration and accurate in silico molecular prediction.

Polymeric Materials
Pharmaceutical Formulations & Delivery
Energy Capture & Storage
Organic Electronics
Consumer Packaged Goods

Official NVIDIA Partner

Schrödinger has a strategic partnership with NVIDIA to optimize our computational drug discovery platform for NVIDIA GPU technology.

Documentation & Tutorials

Get answers to common questions and learn best practices for using Schrödinger’s software.

Life Science Quick Reference Sheet

MxMD

Setting up and analyzing mixed-solvent MD simulations in a nutshell.

Materials Science Tutorial

Nanoemulsions with Automated DPD Parameterization

Learn how to automatically build a coarse-grained force field for dissipative particle dynamics (DPD) from a nanoemulsions system with water and perform a molecular dynamics simulation.

Materials Science Tutorial

Umbrella Sampling

Learn to calculate the free energy profile for butanol permeation through a DMPC membrane using umbrella sampling.

Life Science Tutorial

Exploring Protein Binding Sites with Mixed-Solvent Molecular Dynamics

Identify and characterize binding sites with mixed solvent molecular dynamics.

Materials Science Tutorial

Thermal Conductivity

Learn to use the Thermal Conductivity Calculation and Results panels to calculate thermal conductivity.

Life Science Documentation

Learning Path: Computational Target Analysis

A structured overview of tools and workflows for analyzing and understanding the behavior of target proteins.

Life Science Tutorial

Protein pKa Prediction with Constant pH Molecular Dynamics

Determine pKa values and protonation states for protein residues.

Life Science Tutorial

Thin Plane Shear

Learn to calculate the thin plane shear viscosity and friction coefficient.

Materials Science Tutorial

Disordered System Building and Molecular Dynamics Multistage Workflows

Learn to use the Disordered System Builder and Molecular Dynamics Multistage Workflow panels to build and equilibrate model systems.

Life Science Tutorial

Introduction to MD Simulations with Desmond

Prepare, run, and perform simple analysis on an all-atom MD simulation with Desmond.

Related Products

Learn more about the related computational technologies available to progress your research projects.

Virtual Cluster

Secure, scalable environment for running simulations on the cloud

MS Maestro

Complete modeling environment for your materials discovery

OPLS4 & OPLS5 Force Field

A modern, comprehensive force field for accurate molecular simulations

MS CG

Efficient coarse-grained (CG) molecular dynamics (MD) simulations for large systems over long time scales

MS Morph

Efficient modeling tool for organic crystal habit prediction

MS Penetrant Loading

Molecular dynamics (MD) modeling for predicting water loading and small molecule gas adsorption capacity of a condensed system

MS Transport

Efficient molecular dynamics (MD) simulation tool for predicting liquid viscosity and diffusions of atoms and molecules

Publications

Browse the list of peer-reviewed publications using Schrödinger technology in related application areas.

Life Science Publication

A robust crystal structure prediction method to support small molecule drug development with large scale validation and blind study

Materials Science Publication

Uncovering the light absorption mechanism of the blue natural colorant allophycocyanin from Arthrospira platensis using molecular dynamics

Materials Science Publication

Evaluating the Binding Potential and Stability of Drug-like Compounds with the Monkeypox Virus VP39 Protein Using Molecular Dynamics Simulations and Free Energy Analysis

Materials Science Publication

Predicting Drug-Polymer Compatibility in Amorphous Solid Dispersions by MD Simulation: On the Trap of Solvation Free Energie

Materials Science Publication

Designing the Next Generation of Polymers with Machine Learning and Physics-Based Models

Materials Science Publication

Modelling of Prednisolone Drug Encapsulation in Poly Lactic-co-Glycolic Acid Polymer Carrier Using Molecular Dynamics Simulations

Materials Science Publication

Cu-TiO2/Zeolite/PMMA Tablets for Efficient Dye Removal: A Study of Photocatalytic Water Purification

Life Science Publication

Predicting the Release Mechanism of Amorphous Solid Dispersions: A Combination of Thermodynamic Modeling and In Silico Molecular Simulation

Materials Science Publication

Coarse-Grained Simulation of mRNA-Loaded Lipid Nanoparticle Self-Assembly

Life Science Publication

Coarse-grained simulation of mRNA-loaded lipid nanoparticle self-assembly

Training & Resources

Online certification courses

Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.

Tutorials

Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.