Optibrium Enhances Drug Discovery with AI-Powered Affinity Prediction via New PyMOL Plugin
Optibrium, a leading developer of software and AI solutions for molecular design, has announced the release of a new QuanSA™ plugin for PyMOL. This plugin provides an intuitive Graphical User Interface (GUI) for its ligand-based binding affinity prediction method, integrated within the BioPharmics 3D molecular modelling platform. The new interface aims to streamline the process for chemists, offering more accurate predictions to guide the design of potent compounds and reduce the need for extensive synthesis and testing during lead optimization.
From Command-Line to Accessible Interface
Originally developed as a command-line tool for expert computational users, QuanSA (Quantitative Surface-Field Analysis) is now more accessible to a broader range of chemists through the new PyMOL plugin. The plugin’s visualizations highlight key molecular interactions that drive binding affinity, providing crucial insights for optimizing molecule potency.
Accuracy and Efficiency in Affinity Prediction
QuanSA is a validated method for predicting the affinity of potential drug molecules to their biological targets. Its machine learning approach, grounded in physical principles, models the factors governing molecular recognition and binding. According to Optibrium, this delivers accuracy comparable to simulation-based methods like free energy perturbation (FEP), but at a significantly reduced computational cost and without requiring a protein structure. [Optibrium News] This allows for earlier and more widespread application of accurate affinity predictions in drug discovery projects.
Expanding the BioPharmics Platform
The QuanSA plugin builds upon Optibrium’s recent introduction of a PyMOL interface for Surflex-Dock 2, its molecular docking method. [Optibrium News] This reflects the company’s commitment to making advanced 3D modelling techniques more readily available. The command-line interface for QuanSA will continue to be supported for expert users and large-scale screening applications.
“Early-phase drug discovery relies on accurate predictions of binding affinity. QuanSA has been proven to deliver accuracy equivalent to the most advanced simulation-based methods, but at a fraction of the computational cost and even when a protein structure is not available. Putting this capability into the hands of the wider scientific community through an intuitive, visual interface is an important step. The more widely these predictions can be applied, the greater the impact they can have on drug discovery.”
Ann Cleves, VP of Application Science, BioPharmics Division, Optibrium
Matthew Segall, Chief Executive Officer of Optibrium, added: “Understanding why a molecule binds to a target and not just how strongly, is highly valuable in lead optimisation. With the new PyMOL plugin, teams can now visualize the key interactions driving affinity alongside QuanSA’s proven predictions, giving them the insight to produce better, more confident design decisions. The result is a more informed and efficient path to a pre-clinical candidate.” [Optibrium LinkedIn]
The QuanSA plugin for PyMOL is available at no additional cost to existing BioPharmics license holders.