Role of Chemical Reactivity and Transition State Modeling for Virtual Screening
Sanjeev S. Tambe,
Bhaskar D. Kulkarni.
Every drug discovery research program involves synthesis of a novel and potential drug molecule utilizing
atom efficient, economical and environment friendly synthetic strategies. The current work focuses on the role of the
reactivity based fingerprints of compounds as filters for virtual screening using a tool ChemScore. A reactant-like (RLS)
and a product- like (PLS) score can be predicted for a given compound using the binary fingerprints derived from the
numerous known organic reactions which capture the molecule-molecule interactions in the form of addition, substitution,
rearrangement, elimination and isomerization reactions. The reaction fingerprints were applied to large databases in
biology and chemistry, namely ChEMBL, KEGG, HMDB, DSSTox, and the Drug Bank database. A large network of
1113 synthetic reactions was constructed to visualize and ascertain the reactant product mappings in the chemical reaction
space. The cumulative reaction fingerprints were computed for 4000 molecules belonging to 29 therapeutic classes of
compounds, and these were found capable of discriminating between the cognition disorder related and anti-allergy
compounds with reasonable accuracy of 75% and AUC 0.8. In this study, the transition state based fingerprints were also
developed and used effectively for virtual screening in drug related databases. The methodology presented here provides
an efficient handle for the rapid scoring of molecular libraries for virtual screening.
Keywords: Fingerprints, intermediates, metabolic pathways, product-like score, reactant-like score, reaction, screening,
synthesis, virtual screening.
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