Francesca Scantamburlo, Ionica Masgras, Francesco Ciscato, Claudio Laquatra, Francesco Frigerio, Fabrizio Cinquini, Silvia Pavoni, Alice Triveri, Elena Frasnetti, Stefano A. Serapian, Giorgio Colombo*, Andrea Rasola* and Elisabetta Moroni*,
{"title":"Design and Test of Molecules that Interfere with the Recognition Mechanisms between the SARS-CoV-2 Spike Protein and Its Host Cell Receptors","authors":"Francesca Scantamburlo, Ionica Masgras, Francesco Ciscato, Claudio Laquatra, Francesco Frigerio, Fabrizio Cinquini, Silvia Pavoni, Alice Triveri, Elena Frasnetti, Stefano A. Serapian, Giorgio Colombo*, Andrea Rasola* and Elisabetta Moroni*, ","doi":"10.1021/acs.jcim.4c0151110.1021/acs.jcim.4c01511","DOIUrl":null,"url":null,"abstract":"<p >The disruptive impact of the COVID-19 pandemic has led the scientific community to undertake an unprecedented effort to characterize viral infection mechanisms. Among these, interactions between the viral glycosylated Spike and the human receptors ACE2 and TMPRSS2 are key to allowing virus invasion. Here, we report and test a fully rational methodology to design molecules that are capable of perturbing the interactions between these critical players in SARS-CoV-2 pathogenicity. To this end, we computationally identify substructures on the fully glycosylated Spike protein that are not intramolecularly optimized and are thus prone to being stabilized by forming complexes with ACE2 and TMPRSS2. With the aim of competing with the Spike-mediated cell entry mechanisms, we have engineered the predicted putative interaction regions in the form of peptide mimics that could compete with Spike for interaction with ACE2 and/or TMPRSS2. Experimental models of viral entry demonstrate that the designed molecules are able to interfere with viral entry into ACE2/TMPRSS2 expressing cells, while they have no effects on the entry of control viral particles that do not harbor the Spike protein or on the entry of Spike-presenting viral particles into cells that do not display its receptors on their surface.</p>","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":"64 21","pages":"8274–8282 8274–8282"},"PeriodicalIF":5.6000,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Information and Modeling ","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jcim.4c01511","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0
Abstract
The disruptive impact of the COVID-19 pandemic has led the scientific community to undertake an unprecedented effort to characterize viral infection mechanisms. Among these, interactions between the viral glycosylated Spike and the human receptors ACE2 and TMPRSS2 are key to allowing virus invasion. Here, we report and test a fully rational methodology to design molecules that are capable of perturbing the interactions between these critical players in SARS-CoV-2 pathogenicity. To this end, we computationally identify substructures on the fully glycosylated Spike protein that are not intramolecularly optimized and are thus prone to being stabilized by forming complexes with ACE2 and TMPRSS2. With the aim of competing with the Spike-mediated cell entry mechanisms, we have engineered the predicted putative interaction regions in the form of peptide mimics that could compete with Spike for interaction with ACE2 and/or TMPRSS2. Experimental models of viral entry demonstrate that the designed molecules are able to interfere with viral entry into ACE2/TMPRSS2 expressing cells, while they have no effects on the entry of control viral particles that do not harbor the Spike protein or on the entry of Spike-presenting viral particles into cells that do not display its receptors on their surface.
期刊介绍:
The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery.
Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field.
As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.