Albert Neil G. Dulay , John Christian C. de Guzman , Zyra Ysha D. Marquez , Elisha Sofia D. Santana , Jessamine Arce , Fredmoore L. Orosco
{"title":"通过虚拟筛选管道研究小球藻作为非洲猪瘟病毒抗病毒源的潜力","authors":"Albert Neil G. Dulay , John Christian C. de Guzman , Zyra Ysha D. Marquez , Elisha Sofia D. Santana , Jessamine Arce , Fredmoore L. Orosco","doi":"10.1016/j.jmgm.2024.108846","DOIUrl":null,"url":null,"abstract":"<div><p>African swine fever (ASF) causes high mortality in pigs and threatens global swine production. There is still a lack of therapeutics available, with two vaccines under scrutiny and no approved small-molecule drugs. Eleven (11) viral proteins were used to identify potential antivirals in <em>in silico</em> screening of secondary metabolites (127) from <em>Chlorella</em> spp. The metabolites were screened for affinity and binding selectivity. High-scoring compounds were assessed through <em>in silico</em> ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) predictions, compared to structurally similar drugs, and checked for off-target docking with prepared swine receptors. Molecular dynamics (MD) simulations determined binding stability while binding energy was measured in Molecular Mechanics - Generalized Born Surface Area (MMGBSA) or Poisson-Boltzmann Surface Area (MMPBSA). Only six (6) compounds passed until MD analyses, of which five (5) were stable after 100 ns of MD runs. Of these five compounds, only three had binding affinities that were comparable to or stronger than controls. Specifically, phytosterols 24,25-dihydrolanosterol and CID 4206521 that interact with the RNA capping enzyme (pNP868R), and ergosterol which bound to the Erv-like thioreductase (pB119L). The compounds identified in this study can be used as a theoretical basis for <em>in vitro</em> screening to develop potent antiviral drugs against ASFV.</p></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"132 ","pages":"Article 108846"},"PeriodicalIF":2.7000,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The potential of Chlorella spp. as antiviral source against African swine fever virus through a virtual screening pipeline\",\"authors\":\"Albert Neil G. Dulay , John Christian C. de Guzman , Zyra Ysha D. Marquez , Elisha Sofia D. Santana , Jessamine Arce , Fredmoore L. Orosco\",\"doi\":\"10.1016/j.jmgm.2024.108846\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>African swine fever (ASF) causes high mortality in pigs and threatens global swine production. There is still a lack of therapeutics available, with two vaccines under scrutiny and no approved small-molecule drugs. Eleven (11) viral proteins were used to identify potential antivirals in <em>in silico</em> screening of secondary metabolites (127) from <em>Chlorella</em> spp. The metabolites were screened for affinity and binding selectivity. High-scoring compounds were assessed through <em>in silico</em> ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) predictions, compared to structurally similar drugs, and checked for off-target docking with prepared swine receptors. Molecular dynamics (MD) simulations determined binding stability while binding energy was measured in Molecular Mechanics - Generalized Born Surface Area (MMGBSA) or Poisson-Boltzmann Surface Area (MMPBSA). Only six (6) compounds passed until MD analyses, of which five (5) were stable after 100 ns of MD runs. Of these five compounds, only three had binding affinities that were comparable to or stronger than controls. Specifically, phytosterols 24,25-dihydrolanosterol and CID 4206521 that interact with the RNA capping enzyme (pNP868R), and ergosterol which bound to the Erv-like thioreductase (pB119L). The compounds identified in this study can be used as a theoretical basis for <em>in vitro</em> screening to develop potent antiviral drugs against ASFV.</p></div>\",\"PeriodicalId\":16361,\"journal\":{\"name\":\"Journal of molecular graphics & modelling\",\"volume\":\"132 \",\"pages\":\"Article 108846\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of molecular graphics & modelling\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1093326324001463\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of molecular graphics & modelling","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1093326324001463","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
The potential of Chlorella spp. as antiviral source against African swine fever virus through a virtual screening pipeline
African swine fever (ASF) causes high mortality in pigs and threatens global swine production. There is still a lack of therapeutics available, with two vaccines under scrutiny and no approved small-molecule drugs. Eleven (11) viral proteins were used to identify potential antivirals in in silico screening of secondary metabolites (127) from Chlorella spp. The metabolites were screened for affinity and binding selectivity. High-scoring compounds were assessed through in silico ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) predictions, compared to structurally similar drugs, and checked for off-target docking with prepared swine receptors. Molecular dynamics (MD) simulations determined binding stability while binding energy was measured in Molecular Mechanics - Generalized Born Surface Area (MMGBSA) or Poisson-Boltzmann Surface Area (MMPBSA). Only six (6) compounds passed until MD analyses, of which five (5) were stable after 100 ns of MD runs. Of these five compounds, only three had binding affinities that were comparable to or stronger than controls. Specifically, phytosterols 24,25-dihydrolanosterol and CID 4206521 that interact with the RNA capping enzyme (pNP868R), and ergosterol which bound to the Erv-like thioreductase (pB119L). The compounds identified in this study can be used as a theoretical basis for in vitro screening to develop potent antiviral drugs against ASFV.
期刊介绍:
The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design.
As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.