Performance: Probability density imaging (PDI) analysis is our proprietary process, allowing computation of a series of images superimposed on a protein surface. The relative intensity of these images highly correlates with distribution of short- and long-range physicochemical forces surrounding the analyzed region of a protein. PdiCAD™ technology uses these images as representations of protein structures in a computer simulation of the behavior of proteins in interactions with other molecular entities. Docking procedures based on these concepts afford an unprecedented combination of speed and accuracy in prediction of the affinity of small organic molecules toward therapeutic targets.

Validation: During performance evaluation, pdiCAD™ reproduced structures of 300 known protein-ligand complexes, on average, with an RMSD of 0.36 Å (range 0.16-0.72 Å), without prior fitting of algorithms to reproduce the experimental data. A similar performance has been achieved where only fragments of the native ligands were used in the docking procedures. These results surpass by a wide margin any other method used in the pharmaceutical industry or academia. The ability of pdiCAD™ to reproduce experimental data illustrates its excellent complementarity with the forces driving the interactions of proteins with other molecular entities.

 
Application: We apply PDI technology in combination with virtual screening and fragment evolution (VSFE) techniques. Initially, we screen libraries of small molecules or fragments, selected on the basis of their atomic compositions and associated safety data.  Within the framework of PDI representations, docked fragments are linked through covalent bonds, or are structurally modified to derive molecules with a high affinity toward therapeutic targets. Through appropriate fragment selection, we simultaneously optimize the affinity of molecules and their physicochemical properties. A combination of these factors provides an opportunity to design molecules with high structural efficiency, possessing good physicochemical properties and toxicity profiles, positioned for expedient progress through the R&D process. In the broader context of our research efforts, we carry out parallel screening of fragments against a variety of therapeutic targets, seeking structural similarities that create a basis for our proprietary synchronized fragment evolution matrix (SFEM), designed to maximize the efficiency of our drug discovery efforts.
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