Editorial: In silico Methods for Drug Design and Discovery
Simone Brogi, Teodorico C. Ramalho, Kamil Kuča, José L. Medina‐Franco, Marián Valko · Frontiers in Chemistry · 2020
In silico Methods for Drug Design and DiscoveryComputer-aided drug design (CADD) methodologies are playing an ever-increasing role in drug discovery that are critical in the cost-effective identification of promising drug candidates.These computational methods are relevant in limiting the use of animal models in pharmacological research, for aiding the rational design of novel and safe drug candidates, and for repositioning marketed drugs, supporting medicinal chemists and pharmacologists during the drug discovery trajectory.Within this field of research, we launched a Research Topic in Frontiers in Chemistry in March 2019 entitled "In silico Methods for Drug Design and Discovery," which involved two sections of the journal: Medicinal and Pharmaceutical Chemistry and Theoretical and Computational Chemistry.For the reasons mentioned, this Research Topic attracted the attention of scientists and received a large number of submitted manuscripts.Among them 27 Original Research articles, five Review articles, and two Perspective articles have been published within the Research Topic.The Original Research articles cover most of the topics in CADD, reporting advanced in silico methods in drug discovery, while the Review articles offer a point of view of some computer-driven techniques applied to drug research.Finally, the Perspective articles provide a vision of specific computational approaches with an outlook in the modern era of CADD.Regarding the Original Research articles, two of them are related to innovative approaches concerning ADMET properties of the molecules.In particular, de Bruyn Kops et al. reported the development and validation of GLORY, an innovative tool for predicting the metabolism of molecules, identifying chemical structures of metabolites formed by cytochrome P450 enzyme family (CYPs). The mentioned software combines two main ideas: a literature-based pool of CYP- mediated reaction rules and the site of metabolism (SoM) prediction. This approach is relevant since a tool for the in silico prediction of the metabolism of xenobiotic compounds can offer key information for developing novel chemical entities with improved metabolic stability (i.e., cosmetics, drugs, agrochemicals). The GLORY web-server version is accessible at https://acm. zbh.uni-hamburg.de/glory/ (de Bruyn Kops et al.).Montanari et al. described a computational approach for predicting potential toxicity of molecules taking into account transporter proteins.These latter proteins, expressed in the liver, are crucial in drug pharmacokinetics and are important constituents of the physiological bile flow and their inhibition could be relevant to the druginduced liver toxicity.Using a comprehensive analysis of the publicly available data, a set of classification models was developed for predicting the inhibition of the transport for a set of liver transporters deemed relevant by different regulatory agencies.The models were computationally