Through high-resolution 3D visualization and in-depth analysis of target structures and potential ligands, Flare enables users to optimize and prioritize new molecules efficiently and effectively

 

Accelerating small molecule discovery
Flare customers, typically computational and medicinal chemists across pharmaceuticals, biotechnology, academia, and other industries, value the platform as their ‘computational toolbox’. The software enables them to closely inspect the detail of their ligand-protein complexes, using a variety of methods to gain useful insights into their protein targets and ligand series. As our most feature-packed software package, both ligand-based and structure-based drug designers are supported to progress their lead optimization, with confidence.

By closely examining a wide portfolio of ideas and applying a large variety of methods, a large number of molecules can be reduced to a small collection, allowing only the very best molecules to be handed over for lab experiments. The outcome is not only a great reduction in time, energy, and lab resources, but also the greatest chances of success in later-stage drug development.

 

Flare™ V9 released: Spark™ bioisostere replacement, Homology Modeling, ensemble MM/GBSA and more in the latest release of Cresset’s CADD solution
 

 

Version 9 of Flare, Cresset’s CADD solution, brings new and enhanced scientific features and methods for all users. These include Homology Modeling to create reliable 3D models for protein targets for which crystallographic information is not available, ensemble Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) on dynamics trajectories for estimating binding free energy, a full integration of Spark in Flare, and enhanced protein preparation.

 

In this release, we have also further expanded and enhanced the choice of visual tools to investigate the results of Flare FEP experiments and analyze dynamics trajectories, and added many new options for fine-tuning the experiments.

 

Furthermore, the enhanced Extension Manager provides a streamlined workflow for the installation of Flare Python Extensions.

 

Create reliable 3D structures for your protein targets with Homology Modeling
Experimental information about the 3D protein structure may not be available for many interesting biological targets, for example, many GPCRs, ion channels and novel targets. In all these cases, Homology Modeling can be used to create a reliable 3D structure to use in structure-based studies, from docking and scoring to molecular dynamics.

Homology Modeling in Flare uses the robust ProMod31 algorithm, deployed on a secure server hosted by Cresset. This enables Flare to build reliable homology models in just a few minutes, starting from aligned target sequences and template chains with sequence identity as low as 30%.

Ligand-based design in Flare

Efficiently and effectively design and prioritize new ligands for your target, with or without protein crystal structure information

Building on and including methods previously available in Forge™, ligand-based design is reimagined in Flare. Powered by Cresset’s patented ligand comparison method to align and score molecules based on electrostatic and shape properties, medicinal and computational chemists use Flare LigandPro to create 3D binding hypotheses, and build qualitative and quantitative 3D models of activity, for key insights on how compounds interact with protein targets using activity cliff analysis.

 

Structure-based design in Flare

Enhance your designs using advanced approaches for protein ligand analysis in an accessible and flexible interface

Flare StructurePro combines the best of Cresset’s internal research with open-source and proprietary methods, including a modern Python API. Computational chemists will get new insights into protein-ligand binding, enabling them to prioritize of new ligand designs, as well as the ability to make less compounds by predicting activities of new molecules using Flare FEP, before they are synthesized.

 

Ligand-based components of Flare

Compare congeneric and diverse active ligands to understand SAR and build models and pharmacophores

 

QSAR models

Decipher complex SAR and choose the best molecules to make

 

Activity Miner™

Find and understand activity and selectivity cliffs in your SAR

 

Activity Atlas™

Qualitative SAR insights from novel methods

 

FieldTemplater™

Generate realistic pharmacophores