COVID-19 and the Importance of Being Prepared: A Multidisciplinary Strategy for the Discovery of Antivirals to Combat Pandemics

During an emergency, such as a pandemic in which time and resources are extremely scarce, it is important to find effective and rapid solutions when searching for possible treatments. One possibility in this regard is the repurposing of available “on the market” drugs. This is a proof of the concept study showing the potential of a collaboration between two research groups, engaged in computer-aided drug design and control of viral infections, for the development of early strategies to combat future pandemics. We describe a QSAR (quantitative structure activity relationship) based repurposing study on molecular topology and molecular docking for identifying inhibitors of the main protease (Mpro) of SARS-CoV-2, the causative agent of COVID-19. The aim of this computational strategy was to create an agile, rapid, and efficient way to enable the selection of molecules capable of inhibiting SARS-CoV-2 protease. Molecules selected through in silico method were tested in vitro using human coronavirus 229E as a surrogate for SARS-CoV-2. Three strategies were used to screen the antiviral activity of these molecules against human coronavirus 229E in cell cultures, e.g., pre-treatment, co-treatment, and post-treatment. We found >99% of virus inhibition during pre-treatment and co-treatment and 90–99% inhibition when the molecules were applied post-treatment (after infection with the virus). From all tested compounds, Molport-046-067-769 and Molport-046-568-802 are here reported for the first time as potential anti-SARS-CoV-2 compounds

Selection of nutraceutical compounds as COX inhibitors by molecular topology

QSAR based on molecular topology (MT) has proven to be a very efficient method in drug design and discovery. In this study, some models based on MT have been obtained by linear discriminant analysis (LDA) and artificial neural networks (ANN). Later on, the models were applied to the search of new cyclooxygenase (COX) inhibitors showing anti-inflammatory activity. Moreover, an external validation test has been carried out, yielding 80 % of correct classification within the active compounds and 78.6 % within the inactive. The results from ANN showed a correct classification percentage above 85 % for the test set and of 90 % for the external validation set. The accuracy of the models was also checked using the literature data, upon the carrageenan-induced mice paw edema test. In this case, the models were capable to classify correctly four out of five active compounds as well as two out of the two inactive ones, which enabled the models\u2019 optimization. Finally, a virtual screening on a nutraceutical database was performed, from which ten compounds were selected for their potential COX inhibitory activity. The results shown here enhance MT\u2019s role as a very efficient tool for the discovery of new COX inhibitors with potential anti-inflammatory activity

Application of Molecular Topology to the Search of Novel NSAIDs: Experimental Validation of Activity

A topological-mathematical model obtained by linear discriminant analysis has been used to the search of new nonsteroidal antinflammatory drugs (NSAIDs). After carrying out an in silico screening based on such a model, on the Aldrich database, new structures potentially active were selected. Among these structures stand fourteen compounds, from which only one had been previously recorded as NSAID in the literature. The experimental tests performed on the remaining substances demonstrated that several compounds showed either in vitro or in vivo or both activity. Moreover, four compounds, namely 1,3-bis(benzyloxycarbonyl)-2-methyl-2-thiopseudourea, 4,6-dichloro-2-methylthio-5-phenylpyrimidine, 2-chloro-2',6'-acetoxylidide and trans-1,3-diphenyl-2-propen-1-ol, showed a significant in vivo antinflammatory activity as compared to the reference drug (indomethacin). These results reinforce the role of Molecular Topology as a useful tool for drug discovery

Molecular Topology Applied to the Discovery of 1-Benzyl-2-(3-fluorophenyl)-4-hydroxy-3-(3-phenylpropanoyl)-2 H

We report the discovery of 1-benzyl-2-(3-fluorophenyl)-4-hydroxy-3-(3-phenylpropanoyl)-2H-pyrrole-5-one as a novel non-ligand binding pocket (non-LBP) antagonist of the androgen receptor (AR) through the application of molecular topology techniques. This compound, validated through time-resolved fluorescence resonance energy transfer and fluorescence polarization biological assays, provides the basis for lead optimization and structure−activity relationship analysis of a new series of non-LBP AR antagonists. Induced-fit docking and molecular dynamics studies have been performed to establish a consistent hypothesis for the interaction of the new active molecule on the AR surface

Latest advances in molecular topology applications for drug discovery

Introduction: Molecular topology (MT) has emerged in recent years as a powerful approach for the in silico generation of new drugs. In the last decade, its application has become more and more popular among the leading research groups in the field of quantitative structure--activity relationships (QSAR) and drug design. This has, in turn, contributed to the rapid development of new techniques and applications of MT in QSAR studies, as well as the introduction of new topological indices. Areas covered: This review collates the main innovative techniques in the field of MT and provides a description of the novel topological indices recently introduced, through an exhaustive recompilation of the most significant works carried out by the leading research groups in the field of drug design and discovery. The objective is to show the importance of MT methods combined with the effectiveness of the descriptors. Expert opinion: Recent years have witnessed a remarkable rise in QSAR methods based on MTand its application to drug design. New methodologies have been introduced in the area such as QSAR multi-target, Markov networks or perturbation methods. Moreover, novel topological indices, such as Bourgas’ descriptors and other new concepts as the derivative of a graph or cliques capable to distinguish between conformers, have also been introduced. New drugs have also been discovered, including anticonvulsants, anineoplastics, antimalarials or antiallergics, just to name a few. In the authors’ opinion, MT and QSAR have moved from an attractive possibility to representing a foundation stone in the process of drug discovery

Modeling Drug-Induced Anorexia by Molecular Topology

Molecular topology (MT) has demonstrated to be a very good technique for describing molecular structures and to predict physical, chemical, and biological properties of compounds. In this paper, a topological−mathematical model based on MT has been developed for identifying drug compounds showing anorexia as a side effect. An external validation (test set) has been carried out, yielding over an 80% correct classification in the active and inactive compounds. These results reinforce the role of MT as a potential useful tool for predicting drug side effects