BackgroundCoronavirus disease 2019 (COVID-19) and Influenza A are common disease caused by viral infection. The clinical symptoms and transmission routes of the two diseases are similar. This study established a model of laboratory findings to distinguish COVID-19 from influenza A perfectly. MethodsIn this study, 56 COVID-19 patients and 54 influenza A patients were included. Laboratory findings, epidemiological characteristics and demographic data were obtained from electronic medical record databases. Elastic network models, followed by a stepwise logistic regression model were implemented to identify indicators capable of discriminating COVID-19 and influenza A. ResultsA monogram is diagramed to show the resulting discriminative model. The majority of hematological and biochemical parameters in COVID-19 patients were significantly different from those in influenza A patients. In the final model, albumin/globulin, total bilirubin and erythrocyte specific volume were selected as predictors. This model has been demonstrated to have a satisfactory predictive performance to discriminate between COVID-19 and influenza A (AUC=0.844) using an external validation set. ConclusionThe establishment of a diagnostic model on laboratory findings is of great significance for the identification of COVID-19 and influenza A.
{"title":"Establishment of a Diagnostic Model to Distinguish Coronavirus Disease 2019 From Influenza a Based on Laboratory Findings","authors":"Dongyang Xing, S. Tian, Yukun Chen, Jinmei Wang, Xuejuan Sun, Shanji Li, Jiancheng Xu","doi":"10.21203/RS.3.RS-500524/V1","DOIUrl":"https://doi.org/10.21203/RS.3.RS-500524/V1","url":null,"abstract":"\u0000 BackgroundCoronavirus disease 2019 (COVID-19) and Influenza A are common disease caused by viral infection. The clinical symptoms and transmission routes of the two diseases are similar. This study established a model of laboratory findings to distinguish COVID-19 from influenza A perfectly. MethodsIn this study, 56 COVID-19 patients and 54 influenza A patients were included. Laboratory findings, epidemiological characteristics and demographic data were obtained from electronic medical record databases. Elastic network models, followed by a stepwise logistic regression model were implemented to identify indicators capable of discriminating COVID-19 and influenza A. ResultsA monogram is diagramed to show the resulting discriminative model. The majority of hematological and biochemical parameters in COVID-19 patients were significantly different from those in influenza A patients. In the final model, albumin/globulin, total bilirubin and erythrocyte specific volume were selected as predictors. This model has been demonstrated to have a satisfactory predictive performance to discriminate between COVID-19 and influenza A (AUC=0.844) using an external validation set. ConclusionThe establishment of a diagnostic model on laboratory findings is of great significance for the identification of COVID-19 and influenza A.","PeriodicalId":8447,"journal":{"name":"arXiv: Biomolecules","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88249552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It has been known that the uptake mechanisms of cell-penetrating peptides(CPPs) depend on the experimental conditions such as concentration of peptides, lipid composition, temperature, etc. In this study we investigate the temperature dependence of the penetration of Arg9s into a DOPC/DOPG(4:1) membrane using molecular dynamics(MD) simulations at two different temperatures, T = 310 K and T = 288 K. Although it is difficult to identify the temperature dependence because of having only one single simulation at each temperature and no evidence of translocation of Arg9s across the membrane at both temperatures, our simulations suggest that followings are strongly correlated with the penetration of Arg9s: a number of water molecules coordinated by Arg9s, electrostatic energy between Arg9s and the lipids molecules. We also present how Arg9s change a bending rigidity of the membrane and how a collective behavior between Arg9s enhances the penetration and the membrane bending. Our analyses can be applicable to any cell-penetrating peptides(CPPs) to investigate their interactions with various membranes using MD simulations.
{"title":"Molecular dynamics studies of interactions between Arg9(nona-arginine) and a DOPC/DOPG(4:1) membrane","authors":"S. Choe","doi":"10.1063/5.0015665","DOIUrl":"https://doi.org/10.1063/5.0015665","url":null,"abstract":"It has been known that the uptake mechanisms of cell-penetrating peptides(CPPs) depend on the experimental conditions such as concentration of peptides, lipid composition, temperature, etc. In this study we investigate the temperature dependence of the penetration of Arg9s into a DOPC/DOPG(4:1) membrane using molecular dynamics(MD) simulations at two different temperatures, T = 310 K and T = 288 K. Although it is difficult to identify the temperature dependence because of having only one single simulation at each temperature and no evidence of translocation of Arg9s across the membrane at both temperatures, our simulations suggest that followings are strongly correlated with the penetration of Arg9s: a number of water molecules coordinated by Arg9s, electrostatic energy between Arg9s and the lipids molecules. We also present how Arg9s change a bending rigidity of the membrane and how a collective behavior between Arg9s enhances the penetration and the membrane bending. Our analyses can be applicable to any cell-penetrating peptides(CPPs) to investigate their interactions with various membranes using MD simulations.","PeriodicalId":8447,"journal":{"name":"arXiv: Biomolecules","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75915681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-13DOI: 10.1038/s41598-021-92388-5.
Sakshi Piplani, P. Singh, D. Winkler, N. Petrovsky
{"title":"In silico comparison of spike protein-ACE2 binding affinities across species; significance for the possible origin of the SARS-CoV-2 virus","authors":"Sakshi Piplani, P. Singh, D. Winkler, N. Petrovsky","doi":"10.1038/s41598-021-92388-5.","DOIUrl":"https://doi.org/10.1038/s41598-021-92388-5.","url":null,"abstract":"","PeriodicalId":8447,"journal":{"name":"arXiv: Biomolecules","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76041248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
COVID-19, a member of corona virus family is spreading its tentacles across the world due to lack of drugs at present. However, the main viral proteinase (Mpro/3CLpro) has recently been regarded as a suitable target for drug design against SARS infection due to its vital role in polyproteins processing necessary for coronavirus reproduction. The present in silico study was designed to evaluate the effect of Jensenone, a essential oil component from eucalyptus oil, on Mpro by docking study. In the present study, molecular docking studies were conducted by using 1-click dock and swiss dock tools. Protein interaction mode was calculated by Protein Interactions Calculator.The calculated parameters such as binding energy, and binding site similarity indicated effective binding of Jensenone to COVID-19 proteinase. Active site prediction further validated the role of active site residues in ligand binding. PIC results indicated that, Mpro/ Jensenone complexes forms hydrophobic interactions, hydrogen bond interactions and strong ionic interactions. Therefore, Jensenone may represent potential treatment potential to act as COVID-19 Mpro inhibitor. However, further research is necessary to investigate their potential medicinal use.
{"title":"Molecular docking studies on Jensenone from eucalyptus essential oil as a potential inhibitor of COVID 19 corona virus infection","authors":"A. Sharma, Inderjeet Kaur","doi":"10.5281/ZENODO.3748477","DOIUrl":"https://doi.org/10.5281/ZENODO.3748477","url":null,"abstract":"COVID-19, a member of corona virus family is spreading its tentacles across the world due to lack of drugs at present. However, the main viral proteinase (Mpro/3CLpro) has recently been regarded as a suitable target for drug design against SARS infection due to its vital role in polyproteins processing necessary for coronavirus reproduction. The present in silico study was designed to evaluate the effect of Jensenone, a essential oil component from eucalyptus oil, on Mpro by docking study. In the present study, molecular docking studies were conducted by using 1-click dock and swiss dock tools. Protein interaction mode was calculated by Protein Interactions Calculator.The calculated parameters such as binding energy, and binding site similarity indicated effective binding of Jensenone to COVID-19 proteinase. Active site prediction further validated the role of active site residues in ligand binding. PIC results indicated that, Mpro/ Jensenone complexes forms hydrophobic interactions, hydrogen bond interactions and strong ionic interactions. Therefore, Jensenone may represent potential treatment potential to act as COVID-19 Mpro inhibitor. However, further research is necessary to investigate their potential medicinal use.","PeriodicalId":8447,"journal":{"name":"arXiv: Biomolecules","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90832962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Coronaviruses are a class of virus responsible of the recent outbreak of Human Severe Acute Respiratory Syndrome. The molecular machinery behind the viral entry and thus infectivity is based on the formation of the complex of virus spike protein with the angiotensin-converting enzyme 2 (ACE2). The detection of putative allosteric sites on the viral spike protein can trace the path to develop allosteric drugs to weaken the strength of the spike-ACE2 interface and, thus, reduce the viral infectivity. In this work we present results of the application of the Protein Contact Network (PCN) paradigm to the complex SARS-CoV spike - ACE2 relative to both 2003 SARS and the recent 2019 - CoV. Results point to a specific region, present in both structures, that is predicted to act as allosteric site modulating the binding of the spike protein with ACE2.
{"title":"Mapping active allosteric loci SARS-CoV Spike Proteins by means of Protein Contact Networks","authors":"L. Paola, A. Giuliani","doi":"10.5281/ZENODO.3776150","DOIUrl":"https://doi.org/10.5281/ZENODO.3776150","url":null,"abstract":"Coronaviruses are a class of virus responsible of the recent outbreak of Human Severe Acute Respiratory Syndrome. The molecular machinery behind the viral entry and thus infectivity is based on the formation of the complex of virus spike protein with the angiotensin-converting enzyme 2 (ACE2). The detection of putative allosteric sites on the viral spike protein can trace the path to develop allosteric drugs to weaken the strength of the spike-ACE2 interface and, thus, reduce the viral infectivity. In this work we present results of the application of the Protein Contact Network (PCN) paradigm to the complex SARS-CoV spike - ACE2 relative to both 2003 SARS and the recent 2019 - CoV. Results point to a specific region, present in both structures, that is predicted to act as allosteric site modulating the binding of the spike protein with ACE2.","PeriodicalId":8447,"journal":{"name":"arXiv: Biomolecules","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90938206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-10DOI: 10.22036/ORG.CHEM.2021.240124.1250
M. Dayer
Coronavirus (COVID-19) outbreak in late 2019 and 2020 comprises a serious and more likely a pandemic threat worldwide. Given that the disease has not approved vaccines or drugs up to now, any efforts for drug design and or clinical trails of old drugs based on their mechanism of action are worthy and creditable in such circumstances. Experienced docking experiments using the newly released coordinate structure for COVID-19 protease as a receptor and thoughtfully selected chemicals among antiviral and antibiotics drugs as ligands may be leading in this context. We selected nine drugs from HIV-1 protease inhibitors and twenty-one candidates from anti bronchitis drugs based on their chemical structures and enrolled them in blind and active site-directed dockings in different modes and in native-like conditions of interactions. Our findings suggest the binding capacity and the inhibitory potency of candidates are as follows Tipranavir>Indinavir>Atazanavir>Darunavir>Ritonavir>Amprenavir for HIV-1 protease inhibitors and Cefditoren>Cefixime>Erythromycin>Clarithromycin for anti bronchitis medicines. The drugs bioavailability, their hydrophobicity and the hydrophobic properties of their binding sites and also the rates of their metabolisms and deactivations in the human body are the next determinants for their overall effects on viral infections, the net results that should survey by clinical trials to assess their therapeutic usefulness for coronavirus infections.
{"title":"Old Drugs for Newly Emerging Viral Disease, COVID-19: Bioinformatic Prospective","authors":"M. Dayer","doi":"10.22036/ORG.CHEM.2021.240124.1250","DOIUrl":"https://doi.org/10.22036/ORG.CHEM.2021.240124.1250","url":null,"abstract":"Coronavirus (COVID-19) outbreak in late 2019 and 2020 comprises a serious and more likely a pandemic threat worldwide. Given that the disease has not approved vaccines or drugs up to now, any efforts for drug design and or clinical trails of old drugs based on their mechanism of action are worthy and creditable in such circumstances. Experienced docking experiments using the newly released coordinate structure for COVID-19 protease as a receptor and thoughtfully selected chemicals among antiviral and antibiotics drugs as ligands may be leading in this context. We selected nine drugs from HIV-1 protease inhibitors and twenty-one candidates from anti bronchitis drugs based on their chemical structures and enrolled them in blind and active site-directed dockings in different modes and in native-like conditions of interactions. Our findings suggest the binding capacity and the inhibitory potency of candidates are as follows Tipranavir>Indinavir>Atazanavir>Darunavir>Ritonavir>Amprenavir for HIV-1 protease inhibitors and Cefditoren>Cefixime>Erythromycin>Clarithromycin for anti bronchitis medicines. The drugs bioavailability, their hydrophobicity and the hydrophobic properties of their binding sites and also the rates of their metabolisms and deactivations in the human body are the next determinants for their overall effects on viral infections, the net results that should survey by clinical trials to assess their therapeutic usefulness for coronavirus infections.","PeriodicalId":8447,"journal":{"name":"arXiv: Biomolecules","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76947886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-19DOI: 10.13140/RG.2.2.35286.96322
R. Cataldo, L. Giotta, M. Guascito, E. Alfinito
Computational procedures to foresee the 3D structure of aptamers are in continuous progress. They constitute a crucial input to research, mainly when the crystallographic counterpart of the structures in silico produced is not present. At now, many codes are able to perform structure and binding prediction, although their ability in scoring the results remains rather weak. In this paper, we propose a novel procedure to complement the ranking outcomes of free docking code, by applying it to a set of anti-angiopoietin aptamers, whose performances are known. We rank the in silico produced configurations, adopting a maximum likelihood estimate, based on their topological and electrical properties. From the analysis, two principal kinds of conformers are identified, whose ability to mimick the binding features of the natural receptor is discussed. The procedure is easily generalizable to many biological biomolecules, useful for increasing chances of success in designing high-specificity biosensors (aptasensors).
{"title":"New indicators for assessing the quality of in silico produced biomolecules: the case study of the aptamer-Angiopoietin-2 complex","authors":"R. Cataldo, L. Giotta, M. Guascito, E. Alfinito","doi":"10.13140/RG.2.2.35286.96322","DOIUrl":"https://doi.org/10.13140/RG.2.2.35286.96322","url":null,"abstract":"Computational procedures to foresee the 3D structure of aptamers are in continuous progress. They constitute a crucial input to research, mainly when the crystallographic counterpart of the structures in silico produced is not present. At now, many codes are able to perform structure and binding prediction, although their ability in scoring the results remains rather weak. In this paper, we propose a novel procedure to complement the ranking outcomes of free docking code, by applying it to a set of anti-angiopoietin aptamers, whose performances are known. We rank the in silico produced configurations, adopting a maximum likelihood estimate, based on their topological and electrical properties. From the analysis, two principal kinds of conformers are identified, whose ability to mimick the binding features of the natural receptor is discussed. The procedure is easily generalizable to many biological biomolecules, useful for increasing chances of success in designing high-specificity biosensors (aptasensors).","PeriodicalId":8447,"journal":{"name":"arXiv: Biomolecules","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74316637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Efficient syntheses of some new substituted pyrazoline derivatives linked to substituted benzimidazole scaffold were performed by multistep reaction sequences. All the synthesized compounds were characterized using elemental analysis and spectral studies (IR, 1D/2D NMR techniques and mass spectrometry). The synthesized compounds were screened for their antimicrobial activity against selected Gram-positive and Gram-negative bacteria, and fungi strain. The compounds with halo substituted phenyl group at C5 of the 1-phenyl pyrazoline ring (15, 16 and 17) showed significant antibacterial activity. Among the screened compounds, 17 showed most potent inhibitory activity (MIC = 64 {mu}g mL-1) against a bacterial strain. The tested compounds werefound to be almost inactive against the fungal strain C. albicans, apart from pyrazoline-1-carbothiomide 21, which was moderately active.
{"title":"Synthesis and characterization of novel benzimidazole embedded 1,3,5-trisubstituted pyrazolines as antimicrobial agents","authors":"Gopal Krishna Padhy, J. Panda, A. Behera","doi":"10.2298/JSC160604089P","DOIUrl":"https://doi.org/10.2298/JSC160604089P","url":null,"abstract":"Efficient syntheses of some new substituted pyrazoline derivatives linked to substituted benzimidazole scaffold were performed by multistep reaction sequences. All the synthesized compounds were characterized using elemental analysis and spectral studies (IR, 1D/2D NMR techniques and mass spectrometry). The synthesized compounds were screened for their antimicrobial activity against selected Gram-positive and Gram-negative bacteria, and fungi strain. The compounds with halo substituted phenyl group at C5 of the 1-phenyl pyrazoline ring (15, 16 and 17) showed significant antibacterial activity. Among the screened compounds, 17 showed most potent inhibitory activity (MIC = 64 {mu}g mL-1) against a bacterial strain. The tested compounds werefound to be almost inactive against the fungal strain C. albicans, apart from pyrazoline-1-carbothiomide 21, which was moderately active.","PeriodicalId":8447,"journal":{"name":"arXiv: Biomolecules","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87862292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-06DOI: 10.1007/978-3-030-00630-3_3
R. Phillips
{"title":"Membranes by the Numbers","authors":"R. Phillips","doi":"10.1007/978-3-030-00630-3_3","DOIUrl":"https://doi.org/10.1007/978-3-030-00630-3_3","url":null,"abstract":"","PeriodicalId":8447,"journal":{"name":"arXiv: Biomolecules","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80783075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-13DOI: 10.1142/9789813227880_0002
R. Mondaini, S. C. D. A. Neto
A pattern Recognition of a probability distribution of amino acids is obtained for selected families of proteins. The mathematical model is derived from a theory of protein families formation which is derived from application of a Pauli's master equation method.
{"title":"The Pattern Recognition of Probability Distributions of Amino acids in protein families","authors":"R. Mondaini, S. C. D. A. Neto","doi":"10.1142/9789813227880_0002","DOIUrl":"https://doi.org/10.1142/9789813227880_0002","url":null,"abstract":"A pattern Recognition of a probability distribution of amino acids is obtained for selected families of proteins. The mathematical model is derived from a theory of protein families formation which is derived from application of a Pauli's master equation method.","PeriodicalId":8447,"journal":{"name":"arXiv: Biomolecules","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82743132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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