Computational Services

Product

Princeton BioMolecular provides quality and innovative Computational Chemistry services founded on integration with medicinal and biological chemistry requirements. Our computational chemistry team experienced within broad range of Drug Development and AgroScience projects is highly flexible with use of different approaches and innovative techniques. Working closely with both chemists and biologists we are able to focus on the current needs of a project while anticipating future requirements. Generation of reliable screening models could be provided basing on analysis of all public available data as well as on customer in-house data sets with strong intellectual property (IP) position. Results obtained from the calculations can be then used to focus synthetic effort toward compounds with improved activity, ADMET profile, selectivity, and novelty perspectives.

Cheminformatics

Calculation of the different molecular properties and descriptors, creation of compound sets with certain PhysChem parameters
Diversity or Similarity-based compound sets
Property maps and prediction of the molecule features
Diagrams analyzes

Ligand-based virtual screening

2D & 3D Similarity searches
Topomer Search, Shape-based screening
Pharmacophore screening models basing on single or a set of reference actives
2D and 3D QSAR modeling

Receptor-based virtual screening

Analysis and refinement of protein structures
Protein-Ligand and Protein-Protein Docking
Homology modeling
Binding site prediction and in silico validation
Pharmacophore-based virtual screening (basing on protein structure or superposition of protein and bounded ligand’s features).

Scaffold hopping

Using de novo design techniques and pharmacophore matching tools we are able to perform re-scaffolding of series of active compounds in order to decries toxicity, improve ADME properties or to identify new patent-busting cores. During a client project, there is close collaboration between computational chemists and experienced synthetic chemists who were involved in numerous hit-to-lead optimization projects and design of patent-free analogues.