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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 and analysis tools

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

Official NVIDIA Partner

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

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

Materials Science
Early cure analysis to inform direct ink writing of HTPB Polyurethane: Insights from spectroscopy, rheology, and molecular simulations
Materials Science
Probabilistic approach to low strain rate atomistic simulations of ultimate tensile strength of polymer crystals
Materials Science
Drug aggregation of sparingly-soluble ionizable drugs: Molecular dynamics simulations of Papaverine and Prostaglandin F2α
Materials Science
Toward a combined molecular dynamics and quantum mechanical approach to understanding solvent effects on chemical processes in the pharmaceutical industry: The case of a Lewis acid-mediated SNAr reaction
Materials Science
Hop bitterness in beer evaluated by computational analysis
Materials Science
Molecular mechanisms of caramel-like odorant-olfactory receptor interactions based on a computational chemistry approach
Materials Science
Brewers’ spent hop revalorization for the production of high added-value cosmetics ingredients with elastase inhibition capacity
Materials Science
Molecular-scale exploration of mechanical properties and interactions of poly(lactic acid) with cellulose and chitin
Materials Science
Physics-based molecular modeling of biosurfactants
Life Science
Atomistic simulations of the Escherichia coli ribosome provide selection criteria for translationally active substrates

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.


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.