Amides pharmacophore points

Robust peptide-derived approaches aim to identify a small drug-like molecule to mimic the peptide interactions. The primary peptide molecule is considered in these approaches as a tool compound to demonstrate that small molecules can compete with a given interaction. A variety of chemical, 3D structural and molecular modeling approaches are used to validate the essential 3D pharmacophore model which in turn is the basis for the design of the mimics. The chemical approaches include in addition to N- and C-terminal truncations a variety of positional scanning methods. Using alanine scans one can identify the key pharmacophore points D-amino-acid or proline scans allow stabilization of (i-turn structures cyclic scans bias the peptide or portions of the peptide in a particular conformation (a-helix, (i-turn and so on) other scans, like N-methyl-amino-acid scans and amide-bond-replacement (depsi-peptides) scans aim to improve the ADME properties." ... 

The basic set of Pharmacophore Points includes amine, amide, alcohol, ketone, sulfone, sulfonamide, carboxylic acid, carbamate, guaifidine, amidine, urea, and ester. 

Apart from pharmacophore-based approaches, a variety of methods were applied to decipher important ligand features of PXR activation. VolSurf descriptor-based partial least squares (PLS) regression-based models pointed toward amide responsive regions that implicated good acceptor abilities as key variables [33]. 

The DIVSEL program was developed by Pickett et al. for combinatorial reagent selection using three-point pharmacophores as the descriptor for similarity calculations [2], The algorithm starts by selecting the compound most dissimilar to the others in the set and then iteratively selects compounds most dissimilar to those already selected. DIVSEL was used to select a set of carboxylic acids from a collection of 1100 monocarboxylic acids for an amide library, based on the pharmacophoric diversity of the products. Eleven diverse amines were selected based on pharmacophoric diversity. A virtual library of 12100 amides was constructed from the 11 amines and 1100 carboxylic acids. The DIVSEL program used the pharmacophore fingerprints for the product virtual library to select a diverse set of the carboxylic acids. The products of 90 acids with the 11 amines selected with DIVSEL covered 85% of the three-point pharmacophores represented by the entire 12100 compound virtual library. 

Several product-based approaches to library design that do not require full enumeration have been developed. Pickett et al. have described the design of a diverse amide library where diversity is measured in product space. The DIVSEL program is a DBCS method where dissimilarity is measured in three-point pharmacophore space [83]. Initially, 11 amines were selected based on maximum pharmacophore diversity. Then a total of 1100 carboxylic acids were identified following substructure searching. A set of 1100 pharmacophores keys was generated, where each key corresponds to one acid combined with the 11 amines. DIVSEL was used to select 100 acids based on the diversity of the products. The final library was found to cover 85% of the pharmacophores represented by the entire 12,100 virtual libraries. 

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