XForce Field

Common Issues in the General Force Field of Drug Molecules

Molecular mechanics force fields of drug molecules are an essential component for many structure-based drug design predictions. Force fields provide an accurate description of intramolecular and intermolecular interactions by parameterizing a functional form to characterize the potential energy of molecules. At present, there are still some common issues in small molecular force fields, such as unsatisfactory accuracy and precision, insufficient chemical space coverage, and limited capability for customization. In addition, the general molecular mechanics force field has a tedious development process that requires many cumbersome human interventions that prevent its fast extension to new sets of molecules.

The Next-Generation Drug Molecular Force Field

XtalPi has developed a new and advanced molecular force field for drug discovery and development known as XForce field. Thanks to the concerted research efforts of XtalPi’s multi-disciplinary drug research and IT teams, its force field provides better accuracy, precision, and more comprehensive coverage of chemical space. This significantly improves its performance and reliability for drug molecular simulations and property predictions. Moreover, XtalPi has developed an automated cloud-computing-based parameterization platform for its large-scale molecule force field that can help its clients easily customize the force field parameters according to their target molecules.

Sufficient Chemical Space Coverage

XForce field has a more comprehensive chemical space coverage stemming from a variety of different training sets. It facilitates the exploration of chemical space in drug design and ensures a better success rate.

Accurate Prediction of Properties

XForce field is trained using large datasets of high-precision quantum chemistry and experimental data, and thus provides a more precise representation of molecular conformations, properties, intermolecular interactions, and molecular behavior in solution and in drug targets. As such, XForce Field can improve the accuracy of drug property predictions.

Automated Fitting Process and Toolsets

XtalPi has developed a user-friendly visualization software for the XForce field parameterization process. It supports an automated analysis of the target compound library, helps to construct the targeted training set, analyzes the compound conformation, generates the high-precision quantum chemical training data, and completes the parameter fitting as well as curation. Users can directly employ the existing parameter set for various applications, or re-parameterize the targeted molecular set based on their specific requirements.

Flexible Deployments, Customized Fitting Parameters

Both local and cloud deployment are available for users. XtalPi’s cloud deployment guarantees high information security, and provides users massive computing resources and quick deployment time, ensuring a fast verification and reparameterization process for users' target molecular sets.

Open Source Parameters and Toolsets Build Consortium for Force Field Development

XtalPi also plans to provide open-source parameters and toolsets for academia within the framework of written agreements, as we hope to create a healthy and beneficial research environment that could lead to more comprehensive testing and faster updates. XtalPi is dedicated to building and contributing to a consortium for force field development that fosters interactions and collaborations between academia and industry.

High Compatibility with Drug Development Tools

XtalPi has developed a series of drug discovery and development tools, including ligand-target based drug design tools, such as FEP-based high-precision affinity prediction, and other drug-based prediction tools, such as CSP and Solid-state property prediction tools. The XForce field for drug-like molecules has high compatibility with all these drug discovery and development tools. This greatly improves the accuracy and efficiency of drug design, and reduces the cost of drug research and development, thereby enhancing the success rate of drug development.