Comparative Molecular Surface Analysis (CoMSA) for Virtual Combinatorial Library Screening of Styrylquinoline HIV-1 Blocking Agents

Halina      Niedbala; Jaroslaw      Polanski; Rafal      Gieleciak; Robert      Musiol; Dominik      Tabak; Barbara      Podeszwa; Andrzej      Bak; Anna      Palka; Jean-Francois      Mouscadet; Johann      Gasteiger; Marc Le Bret

Abstract

We used comparative molecular surface analysis to design molecules for the synthesis as part of the search for new HIV-1 integrase inhibitors. We analyzed the virtual combinatorial library (VCL) constituted from various moieties of styrylquinoline and styrylquinazoline inhibitors. Since imines can be applied in a strategy of dynamic combinatorial chemistry (DCC), we also tested similar compounds in which the -C=N- or -N=C- linker connected the heteroaromatic and aromatic moieties. We then used principal component analysis (PCA) or self-organizing maps (SOM), namely, the Kohonen neural networks to obtain a clustering plot analyzing the diversity of the VCL formed. Previously synthesized compounds of known activity, used as molecular probes, were projected onto this plot, which provided a set of promising virtual drugs. Moreover, we further modified the above mentioned VCL to include the single bond linker -C-N- or -N-C-. This allowed increasing compound stability but expanded also the diversity between the available molecular probes and virtual targets. The application of the CoMSA with SOM indicated important differences between such compounds and active molecular probes. We synthesized such compounds to verify the computational predictions.

Keywords: integrase (IN), Self-Organizing Neural Networks, docking, molecular electrostatic potential (MEP), Microwave-Assisted Condensation

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