Abstract:At several stages of drug discovery, bioisosteric replacement is a common and efficient practice to find new bioactive chemotypes or to optimize series of molecules toward drug candidates. The critical steps consisting in selecting which molecular moiety should be replaced by which other chemical fragment is often relying on the expertise of specialists. Nowadays, valuable support can be obtained through the wealth of dedicated structural and knowledge data. The present article details the update of SwissBiois… Show more
“…These differences are computed using four standard activity types (IC 50 , EC 50 , K i , and K d ), , which are experimental measures extracted from the ChEMBL database. The potential bioisosteric replacements reported in the SwissBioisostere database are primarily, although not solely, based on two types of experimental assays, the binding assays and the functional assays. , Binding assays are meant to measure the binding affinity and interactions between two molecules including ligand–receptor interactions . On the other hand, functional assays are designed to assess the functional activity of molecular entries as part of biological processes …”
Using the Quantum Theory of Atoms in Molecules, the average electron density (AED) tool was developed and employed to quantitatively evaluate the similarities between bioisosteric moieties in drug design. Bioisosteric replacements are valuable in drug molecules to fine-tune their pharmacokinetic and pharmacodynamic properties while maintaining their biological activity. This study was performed on non-classical bioisosteres of carboxylic acid. It was found that the AED of a given bioisostere is generally transferable, within less than 5% difference, irrespective of its environment. It was shown that the AED tool succeeds at depicting not only the similarities of bioisosteric groups but also at highlighting, as counter examples, the differences in non-bioisosteric groups. For the first time, the AED was used to evaluate bioisosterism in an FDA-approved drug molecule, furosemide, and in five analogues of this medicine. In one of the analogues, non-bioisosteric moieties were exchanged, and in four of the analogues, carboxylic acid was replaced with either furan or sulfonamide, and vice versa. It was also found that irrespective of the pH, the AED tool consistently reproduced experimental predictions. The distinct power of the AED tool in quantitatively and precisely measuring the similarity among bioisosteric groups is contrasted with the relatively ambiguous bioisosteric evaluations through the classical qualitative electrostatic potential (ESP) maps. The ESP maps were demonstrated to fail, even qualitatively, in depicting the similarities, in some cases.
“…These differences are computed using four standard activity types (IC 50 , EC 50 , K i , and K d ), , which are experimental measures extracted from the ChEMBL database. The potential bioisosteric replacements reported in the SwissBioisostere database are primarily, although not solely, based on two types of experimental assays, the binding assays and the functional assays. , Binding assays are meant to measure the binding affinity and interactions between two molecules including ligand–receptor interactions . On the other hand, functional assays are designed to assess the functional activity of molecular entries as part of biological processes …”
Using the Quantum Theory of Atoms in Molecules, the average electron density (AED) tool was developed and employed to quantitatively evaluate the similarities between bioisosteric moieties in drug design. Bioisosteric replacements are valuable in drug molecules to fine-tune their pharmacokinetic and pharmacodynamic properties while maintaining their biological activity. This study was performed on non-classical bioisosteres of carboxylic acid. It was found that the AED of a given bioisostere is generally transferable, within less than 5% difference, irrespective of its environment. It was shown that the AED tool succeeds at depicting not only the similarities of bioisosteric groups but also at highlighting, as counter examples, the differences in non-bioisosteric groups. For the first time, the AED was used to evaluate bioisosterism in an FDA-approved drug molecule, furosemide, and in five analogues of this medicine. In one of the analogues, non-bioisosteric moieties were exchanged, and in four of the analogues, carboxylic acid was replaced with either furan or sulfonamide, and vice versa. It was also found that irrespective of the pH, the AED tool consistently reproduced experimental predictions. The distinct power of the AED tool in quantitatively and precisely measuring the similarity among bioisosteric groups is contrasted with the relatively ambiguous bioisosteric evaluations through the classical qualitative electrostatic potential (ESP) maps. The ESP maps were demonstrated to fail, even qualitatively, in depicting the similarities, in some cases.
“…This led to the design of six different novel compounds. 8 , 30 Figure 2 Plot of predicted activities against observed activities. Figure 3 Plot of standardized residuals against observed activities.…”
“…Among the most popular AI platforms used in drug design is the SwissDrugDesign system developed by the Swiss Institute of Bioinformatics [ 43 ]. The platform is freely accessible via the Expasy portal ( , accessed on 20 February 2022) and consists of several modules: molecular docking (SwissDock) [ 44 ], pharmacokinetics and drug likeness prediction (SwissADME) [ 45 ], virtual screening (SwissSimilarity) [ 46 ], lead optimisation (SwissBioisostere) [ 47 ] and target prediction of small molecules (SwissTargetPrediction) [ 48 ].…”
Section: Current Methods For Drug Designmentioning
Drug design is a complex pharmaceutical science with a long history. Many achievements have been made in the field of drug design since the end of 19th century, when Emil Fisher suggested that the drug–receptor interaction resembles the key and lock interplay. Gradually, drug design has been transformed into a coherent and well-organized science with a solid theoretical background and practical applications. Now, drug design is the most advanced approach for drug discovery. It utilizes the innovations in science and technology and includes them in its wide-ranging arsenal of methods and tools in order to achieve the main goal: discovery of effective, specific, non-toxic, safe and well-tolerated drugs. Drug design is one of the most intensively developing modern sciences and its progress is accelerated by the implication of artificial intelligence. The present review aims to capture some of the most important milestones in the development of drug design, to outline some of the most used current methods and to sketch the future perspective according to the author’s point of view. Without pretending to cover fully the wide range of drug design topics, the review introduces the reader to the content of Molecules’ Special Issue “Drug Design—Science and Practice”.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
