Field-Based QSAR: Discover and optimize new lead compounds using quantitative predictions of binding-site chemistry

Field-Based QSAR opens up new possibilities in ligand-based drug discovery projects. Supplied with an aligned training set of active and inactive compounds, Field-Based QSAR predicts drug activity on the basis of either force fields or Gaussian fields that describe ligand chemistry.

The Advantages of Field-Based QSAR

Quantitative structure-activity relationships (QSAR) have long been a favorite way for researchers to optimize lead compounds. However, traditional QSAR models typically incorporate only crude approximations of 3D structure.

Field-Based QSAR disposes of this limitation. Beginning with a set of aligned ligands that have known activities, Field-Based QSAR is capable of inferring how the ligand’s electrostatic, hydrophobic, and steric fields result in biological activity or inactivity.

Like all ligand-based approaches, Field-Based QSAR requires no knowledge of receptor structure. Ideal for both lead discovery and lead optimization, Field-Based QSAR is capable of quickly turning existing data sets into useful QSAR models, helping researchers to leapfrog around patent space, synthetic roadblocks, and ADME restrictions.