Abstract

C-type natriuretic peptide (CNP), secreted by vascular endothelial cells, belongs to a family of peptides that includes atrial and brain natriuretic peptides. CNP exhibits many vasoprotective effects against pulmonary hypertension and pulmonary fibrosis.. In lungs of CNP-treated mice, expression of the monocyte chemoattractant protein-1, S100A8, and E-selectin genes was significantly lower than that in vehicle-treated mice. CNP had a protective effect on ALI induced by LPS by reducing inflammatory cell infiltration. CNP may hold promise in therapeutic strategies for ALI after pulmonary resection surgery. The continuous molecular fields (CMF) approach is based on the application of continuous functions for the description of molecular fields instead of finite sets of molecular descriptors (such as interaction energies computed at grid nodes) commonly used for this purpose. These functions can be encapsulated into kernels and combined with kernel-based machine learning algorithms to provide a variety of novel methods for building classification and regression structure-activity models, visualizing chemical datasets and conducting virtual screening. In this Research and Scientific Project, the CMF approach is applied to building 3D-QSAR models for 8 datasets through the use of five types of molecular fields (the electrostatic, steric, hydrophobic, hydrogen-bond acceptor and donor ones), the linear convolution molecular kernel with the contribution of each atom approximated with a single isotropic Gaussian function, and the kernel ridge regression data analysis technique. Here, in Biogenea Pharmaceuticals Ltd we discovered for the first time the GENEA-Natriolipontin-0073. An In silico designed of a C-type natriuretic mimetic peptide pharmacophore for the attenuation of lipopolysaccharide-induced acute lung injury using continuous molecular fields approaches to building 3D-QSAR models.