Predicting targets of compounds against neurological diseases using cheminformatic methodology

Abstract

Recently developed multi-targeted ligands are novel drug candidates able to interact with monoamine oxidase A and B; acetylcholinesterase and butyrylcholinesterase; or with histamine N-methyltransferase and histamine H<inf>3</inf>-receptor (H<inf>3</inf>R). These proteins are drug targets in the treatment of depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease. A probabilistic method, the Parzen-Rosenblatt window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Molecular structures were represented based on the circular fingerprint methodology. The same approach was used to build a "predictor" model from the DrugBank dataset to determine the main pharmacological groups of the compound. The study of off-target interactions is now recognised as crucial to the understanding of both drug action and toxicology. Primary pharmaceutical targets and off-targets for the novel multi-target ligands were examined by use of the developed cheminformatic method. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. The cheminformatic targets identifications were in agreement with four 3D-QSAR (H<inf>3</inf>R/D<inf>1</inf>R/D<inf>2</inf>R/5-HT<inf>2a</inf>R) models and by in vitro assays for serotonin 5-HT<inf>1a</inf> and 5-HT<inf>2a</inf> receptor binding of the most promising ligand (71/MBA-VEG8)

Rational Drug Design of Antineoplastic Agents Using 3D-QSAR, Cheminformatic, and Virtual Screening Approaches

“…In recent years, such off-target drug interactions with unexpected proteins have led to a significant number of serious adverse drug reactions (ADRs). This has affected both compounds in development, many of which fail to reach the market due to these unforeseen side-effects, and also marketed drugs whose safety and viability can be seriously compromised in this way [150], and may have to be withdrawn [147,[152][153][154][155], its essence is to use descriptor-based molecular similarity to estimate the probability that a query compound belongs to the set of binders for the given target.…”

Molecular Aspects of the Activity and Inhibition of the FAD-Containing Monoamine Oxidases

“…With a clinically and biologically validated target identified, crystallized proteins and proven ligands enable the development of the descriptors for key interactions with the target binding site. The phamacophore derived from effective, selective molecules allows chemi-informatics to identify similarity-based compounds and, with advanced data-mining, to exclude binding to undesirable off-targets (Nikolic et al , 2015). The dual resource of ligand and target information provides the basis for virtual screening that is now routine in drug discovery.…”

The Forty-Sixth Euro Congress on Drug Synthesis and Analysis: Snapshot †

“…The pharmacophore analysis was performed to define the molecular determinant of these donepezil hybrids, to propose structural modifications that would increase inhibition of the enzymes, and to evaluate activities of the designed hybrids [ 152 , 153 ]. The main chemical diversities, pharmacophores and pharmacological profiles of the agents acting as a histamine H 3 R antagonist/inverse agonist and dual H 3 R antagonist/inverse agonist with an inhibiting effect on acetylcholine esterase, histamine N -methyltransferase, and the serotonin transporters were successfully developed in a few recent studies [ 155 , 156 ].…”