Local intersection volume (LIV) descriptors: 3D-QSAR models for PGI2 receptor ligands

Abstract

Prostaciclina I 2 inibe a agregação plaquetária pela interação com um receptor específico de membrana. Neste trabalho, desenvolvemos modelos de QSAR-3D para uma série de compostos heterocíclicos aromáticos usando como descritor o volume de interseção local. Os modelos obtidos podem ser aplicados no desenvolvimento de novos ligantes de receptor da PGI 2 com potencial atividade anti-agregante plaquetária.Prostacyclin I 2 inhibits platelet aggregation through specific binding to its membrane receptor. In this work, we developed 3D-QSAR models for a series of aromatic heterocyclic compounds from literature using the local intersection volume descriptor. The models obtained can be applied to design new PGI 2 receptor ligands with potential platelet anti-aggregating activity. Keywords: 3D-QSAR, local intersection volume (LIV), prostacyclin receptor, platelet aggregation IntroductionProstacyclin I 2 (PGI 2 ) (Figure 1) is an endogenous chemical mediator acting as a potent inhibitor of platelet aggregation, interacting with its specific receptor (IP) located on cellular membranes. [1][2][3] Under physiological conditions, prostacyclin is a labile compound of limited clinical usage, 3 which has a half-life of approximately 3 minutes. In order to develop antithrombotic agents with better pharmacokinetic profile, Meanwell and co-workers [4][5][6][7][8] synthesized and evaluated a series of aromatic heterocyclic compounds (see compound 2 in Figure 1). [4][5][6][7][8] Based on data from their research, we developed, in this work, 3D-QSAR models for ligands of IP receptor using the local intersection volume (LIV) descriptor, 9 i.e., the intersection volume between the volumes of the compound atoms and the volumes of a set of spheres of defined atom size. It composes a three-dimensional box, in analogy to the Grid method.10 The LIV-3D-QSAR models were obtained and evaluated by genetic algorithms (GA) and partial least squares (PLS) methods. [11][12][13] They can be applied to design new PGI 2 receptor ligands that could be potential inhibitors of blood platelet aggregation. Methods Steps on the LIV-3D-QSAR models developmentStep 1. Selection of 42 aromatic heterocyclic compounds 4-8 (see Table 1, Supplementary Material) divided in a training data set (30 compounds) and a test data set (12 compounds). The corresponding values of the biological activity 4-8 according to the pharmacological protocol established by Seiler and co-workers 14 are shown on Table 1.Step 2. Construction of a grid matrix composed by cubic unitary cells, where the vertices of the cells 4-8 and pharmacophoric sites (S1, S2, S3, and S4) definition according SAR studies. 5,20 817 Local Intersection Volume (LIV) Descriptors: 3D-QSAR Models Vol. 13, No. 6, 2002 correspond to the Cartesian coordinates of the eight carbon atoms. The vertices arrest lengths are 1.50Å (that is, almost equal to the carbon van der Waals radii of 1.54Å). The grid matrix is composed by a total of 2197 (13x13x13) carbon atoms, constructed on an Excel ® program, and imported into the...

Pharmacophore mapping of arylbenzothiophene derivatives for MCF cell inhibition using classical and 3D space modeling approaches

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Residue-Ligand Interaction Energy (ReLIE) on a Receptor-Dependent 3D-QSAR Analysis of S- and NH-DABOs as Non-Nucleoside Reverse Transcriptase Inhibitors

“…GFA applies the same procedures described above for GAs, and coupled with PLS, the GFA-PLS technique has as its most important feature the generation of multiple good models rather than the optimization of only a single model [ 53 ]. Several authors have reported the use of combined GA and PLS analyses [ 28 , 55 , 56 , 57 , 58 , 59 , 60 , 61 ].…”