Desmond

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

Life Science: Desmond

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

Desmond is a GPU-powered high-performance molecular dynamics (MD) engine for simulating biological systems such as small protein, viral capsids, protein-ligand complexes, small molecules in mixed solvents, organic solids, and synthetic macromolecular complexes.

Benefits of Desmond

Speed time to market of new catalysts
GPU-accelerated perfomance

Achieves exceptional throughput on commodity Linux clusters with both typical and high-end networks and improves computing speed by 100x on general-purpose GPU (GPGPU) compared to single CPU

Superior accuracy
Superior accuracy

Constructed with a focus on numerical accuracy, stability, and rigor, Desmond’s performance enables the simulation of large-scale features of nanometer 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 force field models and is compatible with chemistries commonly used in biomolecular research

Realistic simulations
Realistic simulations

Performs explicit solvent simulations with periodic boundary conditions using simulation boxes with careful attention to the calculation of long-range electrostatics, and can be used to model protein and nucleic acid systems with explicit lipid membranes

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

Provides intelligent default settings and allows for rapid setup of computational experiments in an intuitive interface, while supporting automated simulation setup including system building, analysis tools, and force field assignment

Powerful analysis tools
Powerful analysis tools

Enables visualization and examination of computed results within the same Maestro modeling environment that connects to a comprehensive suite of modeling tools from quantum mechanics to machine learning

Applications

Use the left and right arrow keys to navigate between slides.

Mixed Solvent Molecular Dynamics (MxMD)

Improved cryptic pocket identification through enhanced sampling. Leverage MxMD with our new interface for simplified setup, analysis, and customizable visualization of cryptic binding pockets on protein surfaces.

Unbinding Kinetics

Characterize ligand-receptor interactions with unbinding kinetics analysis. Visualize unbinding pathways using enhanced sampling methods to identify and optimize promising lead compounds based on their dissociation rates.

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.

Materials Science Documentation

Desmond

Simulate biological systems with a GPU-powered high-performance molecular dynamics (MD) engine.

Life Science Documentation

Desmond

Simulate biological systems with a GPU-powered high-performance molecular dynamics (MD) engine.

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.

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

Maestro

Complete modeling environment for your molecular discovery

OPLS4 & OPLS5 Force Field

A modern, comprehensive force field for accurate molecular simulations

FEP+

High-performance free energy calculations for drug discovery

IFD-MD

Accurate ligand binding mode prediction for novel chemical matter, for on-targets and off-targets

Publications

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

Life Science Publication

STX-721, a Covalent EGFR/HER2 Exon 20 Inhibitor, Utilizes Exon 20–Mutant Dynamic Protein States and Achieves Unique Mutant Selectivity Across Human Cancer Models

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

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.