Better Drug Design Decisions using
Molecular Interaction Fields
Our proprietary GRID forcefield comprehensively describes molecules from the perspective of their interaction partner. From Hit Finding, through Lead Optimisation, to Pharmacokinetic and Metabolism prediction, using Molecular Interaction Fields has been demonstrated to be highly effective in all aspects of Drug Discovery.
Lead Hop to different scaffolds to improve chemical diversity and intellectual property. Find Hits that complement receptor interaction fields. Combine with statistical approaches to understand which field regions are more critical for your target. Explore the hydrophobic and water interaction fields to model solubility and permeation. Use receptor complementarity combined with chemical reactivity for metabolism prediction.
Aug. 2, 2024, 1:19 p.m.
We are pleased to announce the immediate availability of MetaSite 7
Our flagship product for predicting Cytochrome P450-mediated biotransformations just got a massive upgrade with the inclusion of combined prediction of phase I and phase II metabolism, SoM Heatmap visualization, Metabolite Pathways Analysis, non-CYP metabolic reactions and much more.
More information about MetaSite 7 can be found in the product page.
May 2, 2022, midnight
We are pleased to announce the release of BioGPS 22.01, for drug-repurposing, off-targeting prediction, ligand selectivity and many other applications.
BioGPS enables pocket-pocket comparison by aligning the sites and directly comparing the Molecular Interaction Fields. Chemometric approaches are included to reduce the complexity of the resulting data on large datasets, enabling users to focus on the most relevant information.
BioGPS comes with a curated database of ~800,000 pockets. Precomputed Molecular Interaction Fields (MIFs) are ready for large scale virtual screening, and pockets biological annotation (i.e. biochemical pathways) are useful for filtering dataset and results.
More info about BioGPS on the product page.
Dec. 15, 2021, 9:39 a.m.
We are proud to announce the immediate availability of the next major release of MoKa, our pKa prediction tool.
Along with the usual improvements on the pKa prediction engine (39 out of 55 models have seen additions and refinements) this release marks the introduction of a completely new solubility model providing both intrinsic (logS0) and pH dependant values.
All of pKa, solubility, and lipophilicity (logP) models are now completely trainable with in-house experimental data; please refer to the documentation for details.
More info about MoKa on the product page
Aug. 2, 2021, 10:10 a.m.
We are pleased to announce the release of Lipostar2, a new enhanced version of the Molecular
Discovery software for lipidomics.
Lipostar2 is a comprehensive, vendor-neutral software for LC-MS/MS-based lipidomics (DDA and
DIA), which includes a large number of features including: raw data import and peak detection,
identification, quantification, statistical analysis, trend analysis and biopathways analysis.
Please check out the product page for more information about the product
