6533b861fe1ef96bd12c4e3d

RESEARCH PRODUCT

Advances in the molecular modeling and quantitative structure–activity relationship-based design for antihistamines

Jorge GalvezRiccardo ZanniRamón García-domenechMaria Galvez-llompart

subject

Models MolecularQuantitative structure–activity relationshipVirtual screeningMolecular modelDrug discoveryComputer scienceIn silicoHistamine AntagonistsQuantitative Structure-Activity RelationshipNanotechnologyComputational biologyDocking (molecular)Drug DesignExpert opinionDrug DiscoveryAnimalsComputer-Aided DesignHumansMolecular topology

description

Nowadays the use of antihistamines (AH) is increasing steadily. These drugs are able to act on a variety of pathological conditions of the organism. A number of computer-aided (in silico) approaches have been developed to discover and develop novel AH drugs. Among these methods stand the ones based on drug-receptor docking, thermodynamics, as well as the quantitative structure-activity relationships (QSAR).This review collates the most recent advances in the use of computer approaches for the search and characterization of novel AH drugs. Within the QSAR methods, particular attention will be paid to those based on molecular topology (MT) because of their demonstrated efficacy in discovering new drugs. Collateral topics will also be dealt with including: docking studies, thermodynamic aspects, molecular modeling and so on. These issues will be treated to the extent that they have interest as complementary to QSAR-MT.Given the importance of the use of AHs, the search for new drugs in this field has become imperative today. In this regard, the use of QSAR methods based on MT, namely QSAR-MT, has proven to be a powerful tool when the goal is discovering new hit or lead structures. It has been shown that antihistaminic activity is complex and different for the four known types of receptors (H1 to H4) and that electronic, steric and physicochemical issues determine drug activity. These factors, along with the purely structural ones, can be deduced from topological and topochemical information.

https://doi.org/10.1517/17460441.2013.748745