Fragmental topology-activity landscapes (FRAGTAL), a new concept for encoding molecular descriptors for
fragonomics into the framework of the molecular database records is presented in this paper. Thus, a structural repository
containing biological activity data was searched in a substructure mode by a series of molecular fragments constructed in
an incremental or decremental manner. The resulted series of database hits annotated with their activities construct
FRAGTAL descriptors encoding a frequency of the certain fragments among active compounds and/or their activities.
Actually, this method might be interpreted as a simplified adaptation of the frequent subgraph mining (FSM) method. The
FRAGTAL method reconstructs the way in which medicinal chemists are used to designing a prospective drug structure
intuitively. A representative example of the practical application of FRAGTAL within the ChemDB Anti-HIV/OI/TB
database for disclosing new fragments for HIV-1 integrase inhibition is discussed. In particular, FRAGTAL method
identifies ethyl malonate amide (EMA) as the diketo acid (DKA) related arrangement. Since new molecular constructs
based on the EMA fragment are still a matter of future investigations we referred to this as anthe DKA offspring.
Keywords: Druglikeness, fragment-based design, HIV-1 integrase inhibitors, molecular scaffolds, virtual ligand screening, fragmental topology-activity landscape, IC50, caffeic fragment, DKA-based IN inhibitors, Diketo Acid Analogues, Anti-HIV Database.
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