title: Ligand-based virtual screening procedure for the prediction and the identification of novel β-amyloid aggregation inhibitors using Kohonen maps and Counterpropagation Artificial Neural Networks.
abstract: In this work we have developed an in silico model to predict the inhibition of β-amyloid aggregation by small organic molecules. In particular we have explored the inhibitory activity of a series of 62 N-phenylanthranilic acids using Kohonen maps and Counterpropagation Artificial Neural Networks. The effects of various structural modifications on biological activity are investigated and novel structures are designed using the developed in silico model. More specifically a search for optimized pharmacophore patterns by insertions, substitutions, and ring fusions of pharmacophoric substituents of the main building block scaffolds is described. The detection of the domain of applicability defines compounds whose estimations can be accepted with confidence.
authors.affiliation: Department of ChemoInformatics, NovaMechanics Ltd, John Kennedy Ave 62-64, Nicosia 1046, Cyprus. afantitis@novamechanics.com
authors.forename: Antreas
authors.initials: A
authors.lastname: Afantitis
authors.forename: Georgia
authors.initials: G
authors.lastname: Melagraki
authors.forename: Panayiotis A
authors.initials: PA
authors.lastname: Koutentis
authors.forename: Haralambos
authors.initials: H
authors.lastname: Sarimveis
authors.forename: George
authors.initials: G
authors.lastname: Kollias
mesh_terms: D016229:Amyloid beta-Peptides / Q000037:antagonists & inhibitors*; D016000:Cluster Analysis; D054361:Fenamates / Q000737:chemistry / Q000494:pharmacology*; D057166:High-Throughput Screening Assays; D008024:Ligands; D008958:Models, Molecular; D015394:Molecular Structure; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D013237:Stereoisomerism; D013329:Structure-Activity Relationship
chemical_list: D016229:Amyloid beta-Peptides; D054361:Fenamates; D008024:Ligands