OPLS4

A modern, comprehensive force field for accurate molecular simulations

OPLS4

Improve the quality of your computational predictions with OPLS4

Force fields are used in molecular simulations to describe the interactions between atoms in a system. Having an accurate force field is at the heart of obtaining useful molecular structures and predicting relative energies, and yet many in silico programs employ force fields that are years, if not decades, old, and suffer from lack of sufficient coverage for many common molecular motifs.

OPLS4 is a highly accurate, modern force field with comprehensive coverage of chemical space for both drug discovery and materials science applications. It builds upon the extensive coverage and accuracy achieved in previous OPLS versions by improving the accuracy of functional groups that have presented significant modeling challenges in the past, such as charged groups and sulfur-containing moieties.

Key Benefits

Continuous scientific development by leading force field experts
Backed by state of the art quantum engine (Jaguar) and extensive experimental validation
Broad coverage of chemical space for small molecules, biologics and materials science applications
Easily extendible into novel project-specific chemistry with Force Field Builder

Applications of OPLS4 for Materials Science

Generate accurate parameters for advanced molecular materials

OPLS4 significantly improved structural stabilization during long MD simulations due to improved parameters for molecular materials composed of small-molecule and macromolecule constituents.

Perform accurate property predictions

OPLS4 produces accurate predictions of solvation free energies, density, glass transition, radius of gyration, cohesive energy, and other properties with Desmond, leading to more accurate rank ordering among compounds.

Model challenging interactions accurately

OPLS4 accurately models challenging organicinteractions including heterocycles, halogen bonds, sulfur-oxygen interactions and salt-bridge formation enabling reliable predictions of small molecules, organics, polymers, OLEDs, silicates, and more. 

Improve conformational analyses

OPLS4 provides a more accurate description of torsional energies and leads to improved conformational analyses and more accurate molecular flexibility.

Documentation & Tutorials

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

Materials Science Documentation

OPLS4 and OPLS5 Force Field

A force field that is a model of the potential energy of a chemical system – a set of functions and parameters used to model the potential energy of the system, and thereby to calculate the forces on each particle.

Life Science Documentation

OPLS4 and OPLS5 Force Field

A force field that is a model of the potential energy of a chemical system – a set of functions and parameters used to model the potential energy of the system, and thereby to calculate the forces on each particle.

Life Science Tutorial

Exploring Protein Binding Sites with Mixed-Solvent Molecular Dynamics

Identify and characterize binding sites with mixed solvent molecular dynamics.

Materials Science Documentation

Materials Science Panel Explorer

Quickly learn which Schrödinger tools are the best fit for your research.

Related Products

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

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

Desmond

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

Force Field Builder

Efficient tool for optimizing custom torsion parameters in OPLS4

MS Transport

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

MS CG

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

MS Penetrant Loading

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

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

Life Science Publication

Towards automated physics-based absolute drug residence time predictions

Life Science Publication

Accurate physics-based prediction of binding affinities of RNA- and DNA-targeting ligands

Materials Science Publication

Gaining molecular insights towards inhibition of foodborne fungi Aspergillus fumigatus by a food colourant violacein via computational approach

Materials Science Publication

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

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

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

Life Science Publication

OPLS5: Addition of polarizability and improved treatment of metals

Materials Science Publication

Computational and Machine Learning-Assisted Discovery and Experimental Validation of Conjugated Sulfonamide Cathodes for Lithium-Ion Batteries

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.