Ligand-Based Virtual Screening

An overview of InhibOx's proprietary ligand-based search technologies and tools is given below. The idea of using molecular similarity  to search molecular databases has a long history [1]. Combining the best of the results from a wide variety of these approaches (superpositional, non-superpositional, electrostatic and chemical feature-based) gives a diverse set of potentially similar ligands for subsequent analysis or assay.

ElectroShape

ElectroShape is InhibOx’s ultrafast method for ligand searching based on combinations of shape, charge and various phyico-chemical properties.

InhibOx has developed a non-superpositional in-house method for ligand-based screening called Chiral Shape Recognition (CSR), incorporated in ElectroShape. A key enhancement over previously described non-superpositional methods is that CSR takes into account the chirality of the molecules being compared, while retaining the speed and efficiency of these methods. These differences are important because interactions between proteins and small molecules are often chiral in nature. Using CSR similarly shaped compounds can be quickly identified from within even the largest molecular databases. In addition, the problematic requirement of aligning molecules for comparison is circumvented, as the proposed distributions are independent of molecular orientation. CSR has been demonstrated [2] to provide superior enrichment to previously described methods.

This approach is implemented in ElectroShape[3] for ultra-fast comparison of molecules based on the electrostatic and other physico-chemical properties of the atoms, in addition to the molecular shape and stereochemistry. Combining these properties maximizes the discovery of relevant lead molecules within the top few percent of structures screened, nearly doubling the enrichment ratio at 1% over previously published shape-based methods.

 

FOx

FOx is our proprietary ultrafast method for shape-based screening of a library against a query molecule. It uses a variation of the MaP descriptor method introduced by Steifl and Baumann [4].

InhibOx’s in-house molecule shape comparison platform has been implemented in an efficient manner to enable the screening of many millions of molecules, represented in 3-D conformational databases, in an acceptable amount of time. Molecules with similar shapes are found by comparing volume overlaps having aligned them onto a common coordinate frame.

The software uses a customized simplex optimizer based method to align database molecules against the query molecule and then assigns scores for their similarity [5] using the Tanimoto and Carbo indices.

 

MOx

InhibOx has developed and validated in-house methods for identifying structural similarity based on recognition of structural features (fingerprint searching).

Fingerprint searching measures similarity using the Tanimoto index and feature detection based on chemical functional groups.

 

COver

COver is Inhibox’s proprietary superpositional search method, based on original research in Professor Graham Richards’ group in Oxford. It is used by the InhibOx team after a first pass with a fast search method, such as ElectroShape, in its superpositional mode to align top hits on the query molecule.  COver can also be used to assess quickly the steric overlap between molecules, which is particularly useful for filtering results from our de novo fragment-based ligand design software, LOx.

 

References

[1] A.C. Good, E.E. Hodgkin, and W.G. Richards (1992). "Similarity screening of molecular data sets." Journal of Computer-Aided Molecular Design, 6(5): 513-520.

[2] M.S. Armstrong, G.M. Morris, P.W. Finn, R. Sharma, and W.G. Richards (2009). "Molecular similarity including chirality", Journal of Molecular Graphics and Modelling, 28: 368-370.

[3]    M.S., Armstrong, G.M., Morris, P.W., Finn, R. Sharma, L. Moretti, R.I. Cooper, and W.G. Richards (2010). "ElectroShape: fast molecular similarity calculations incorporating shape, chirality and electrostatics." Journal of Computer-Aided Molecular Design 24(9): 789–801. Epub 2010 Jul 8.

[4]   N. Stiefl and K. Baumann (2003). "Mapping property distributions of molecular surfaces: Algorithm and evaluation of a novel 3D quantitative structure-activity relationship technique." Journal of Medicinal Chemistry, 46(8): 1390–1407.

[5]   P. Willett, J.M. Barnard, and G.M. Downs (1998). "Chemical similarity searching". Journal of Chemical Information and Computer Sciences, 38(6): 983–996.