Pub Date : 2021-11-15DOI: 10.3390/mol2net-07-11808
Rie Ohara, F. Dario, Gabriela Bueno, V. Rodrigues, Maycon A. Silva, Renata Assunção, Ana Fioretto, L. D. da Rocha, C. Hiruma-Lima
{"title":"Modulation of matrix metalloproteinases exerted by Citral in the healing of gastric ulcers in eutrophic and obese mice","authors":"Rie Ohara, F. Dario, Gabriela Bueno, V. Rodrigues, Maycon A. Silva, Renata Assunção, Ana Fioretto, L. D. da Rocha, C. Hiruma-Lima","doi":"10.3390/mol2net-07-11808","DOIUrl":"https://doi.org/10.3390/mol2net-07-11808","url":null,"abstract":"","PeriodicalId":136053,"journal":{"name":"Proceedings of MOL2NET'21, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 7th ed.","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121774719","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 : 2021-11-14DOI: 10.3390/mol2net-07-11803
Ana Fioretto, Rie Ohara, Maycon Tavares Emílio Silva, Vinícius Peixoto Rodrigues, Gabriela Bueno, Renata Assunção, Felipe Lima Dario, V. Gomes, Priscila Romano Raimundo, Lúcia Regina Machado da Rocha, Clélia Akiko Hiruma-Lima
{"title":"Evaluation of protective effect of citral on gastroesophageal reflux disease in eutrophic and obese mice","authors":"Ana Fioretto, Rie Ohara, Maycon Tavares Emílio Silva, Vinícius Peixoto Rodrigues, Gabriela Bueno, Renata Assunção, Felipe Lima Dario, V. Gomes, Priscila Romano Raimundo, Lúcia Regina Machado da Rocha, Clélia Akiko Hiruma-Lima","doi":"10.3390/mol2net-07-11803","DOIUrl":"https://doi.org/10.3390/mol2net-07-11803","url":null,"abstract":"","PeriodicalId":136053,"journal":{"name":"Proceedings of MOL2NET'21, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 7th ed.","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128771945","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 : 2021-11-14DOI: 10.3390/mol2net-07-11743
Renata Priscila Barros de Menezes, Chonny Herrera-Acevedo, L. Scotti, Marcus Tullius Scotti
Abstract. The Aedes aegypti mosquito belongs to the order Diptera and is one of the main vectors of transmission of etiological agents that cause several diseases. This mosquito can transmit diseases such as dengue, yellow fever, Zika, chikungunya, among others. The aim of this study was combining structure-based and ligand-based virtual screening (VS) techniques to select potentially larvicidal active molecules against Ae. aegypti from in-house secondary metabolite dataset (SistematX). From the ChEMBL database, we selected a set of 161 chemical structures with larvicidal activity against Ae. aegypti to create random forest models with an accuracy value higher than 82% for cross-validation and test sets. Afterward, the ligand-based virtual screen selected 38 secondary metabolites. In addition, a structure-based virtual screening was also performed for the 38 molecules selected. Finally, using consensus analyzes approach combining ligand-based and structure-based VS, five molecules were selected as potential larvicidal against Ae. aegypti .
{"title":"Ligand-Based and Structure-based virtual screening for the discovery of natural larvicidal against Aedes aegypti","authors":"Renata Priscila Barros de Menezes, Chonny Herrera-Acevedo, L. Scotti, Marcus Tullius Scotti","doi":"10.3390/mol2net-07-11743","DOIUrl":"https://doi.org/10.3390/mol2net-07-11743","url":null,"abstract":"Abstract. The Aedes aegypti mosquito belongs to the order Diptera and is one of the main vectors of transmission of etiological agents that cause several diseases. This mosquito can transmit diseases such as dengue, yellow fever, Zika, chikungunya, among others. The aim of this study was combining structure-based and ligand-based virtual screening (VS) techniques to select potentially larvicidal active molecules against Ae. aegypti from in-house secondary metabolite dataset (SistematX). From the ChEMBL database, we selected a set of 161 chemical structures with larvicidal activity against Ae. aegypti to create random forest models with an accuracy value higher than 82% for cross-validation and test sets. Afterward, the ligand-based virtual screen selected 38 secondary metabolites. In addition, a structure-based virtual screening was also performed for the 38 molecules selected. Finally, using consensus analyzes approach combining ligand-based and structure-based VS, five molecules were selected as potential larvicidal against Ae. aegypti .","PeriodicalId":136053,"journal":{"name":"Proceedings of MOL2NET'21, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 7th ed.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128512082","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 : 2021-11-14DOI: 10.3390/mol2net-07-11744
Luana Bitú, Prof. Dr. Luis Rodrigues, Ms. Fernando Ferreira
{"title":"Synthesis and structural elucidation of Isoliquiritigenin by Nuclear Magnetic Resonance","authors":"Luana Bitú, Prof. Dr. Luis Rodrigues, Ms. Fernando Ferreira","doi":"10.3390/mol2net-07-11744","DOIUrl":"https://doi.org/10.3390/mol2net-07-11744","url":null,"abstract":"","PeriodicalId":136053,"journal":{"name":"Proceedings of MOL2NET'21, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 7th ed.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129188310","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 : 2021-11-14DOI: 10.3390/mol2net-07-11791
G. Pereira, R. Araújo, A. Alves
{"title":"The use of natural products as an adjunct to the treatment of Osteonecrosis: a literature review","authors":"G. Pereira, R. Araújo, A. Alves","doi":"10.3390/mol2net-07-11791","DOIUrl":"https://doi.org/10.3390/mol2net-07-11791","url":null,"abstract":"","PeriodicalId":136053,"journal":{"name":"Proceedings of MOL2NET'21, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 7th ed.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122473330","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 : 2021-11-13DOI: 10.3390/mol2net-07-11654
Nayana Lé, F. Nunes, K. Freire
{"title":"Study of the larvicide activity and toxicity of Humulus lupulus extract and beer hop residue , part 1: larvicide activity in Aedes aegypti","authors":"Nayana Lé, F. Nunes, K. Freire","doi":"10.3390/mol2net-07-11654","DOIUrl":"https://doi.org/10.3390/mol2net-07-11654","url":null,"abstract":"","PeriodicalId":136053,"journal":{"name":"Proceedings of MOL2NET'21, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 7th ed.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116032251","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 : 2021-11-13DOI: 10.3390/mol2net-07-11647
Igor Nascimento, Lucas Costa, T. Aquino
Graphical Abstract: Abstract. This work aimed to perform a virtual screening using a covalent docking and MM-PBSA protocol in an FDA-approved drugs library dataset to search for new compounds useful against this cruzain. Initially, 1615 FDA-approved compounds were visually inspected for the presence of chemical groups reactive against cruzain reactive cysteine (Cys 25 ), followed by the choice of the most suitable 3D structure for the virtual protocols. Thus, 241 compounds were selected and the covalent docking assays and the drugs with a fit score covalent greater than 100, were selected to the MM-PBSA calculations. Finally, the drugs neratinib, sacubitril, alprostadil, trandolapril, and florbetapir showed a covalent fit score between 102.14 and 116.59; ΔG binding values between -72.851 and -148,811 Kcal/mol calculated by MM-PBSA; and interactions with the key residues of the cruzain (Cys 25 , His 159 , Gly 23 , and Gly 65 ), showing best values than other cruzain inhibitors experimentally assayed. Our findings suggest that these drugs may be possible cruzain inhibitors, and biological assays
{"title":"Virtual screening based on covalent docking and MM-PBSA calculations predict the drugs neratinib, sacubitril, alprostadil, trandolapril, and florbetapir as promising cruzain inhibitors useful against Chagas disease.","authors":"Igor Nascimento, Lucas Costa, T. Aquino","doi":"10.3390/mol2net-07-11647","DOIUrl":"https://doi.org/10.3390/mol2net-07-11647","url":null,"abstract":"Graphical Abstract: Abstract. This work aimed to perform a virtual screening using a covalent docking and MM-PBSA protocol in an FDA-approved drugs library dataset to search for new compounds useful against this cruzain. Initially, 1615 FDA-approved compounds were visually inspected for the presence of chemical groups reactive against cruzain reactive cysteine (Cys 25 ), followed by the choice of the most suitable 3D structure for the virtual protocols. Thus, 241 compounds were selected and the covalent docking assays and the drugs with a fit score covalent greater than 100, were selected to the MM-PBSA calculations. Finally, the drugs neratinib, sacubitril, alprostadil, trandolapril, and florbetapir showed a covalent fit score between 102.14 and 116.59; ΔG binding values between -72.851 and -148,811 Kcal/mol calculated by MM-PBSA; and interactions with the key residues of the cruzain (Cys 25 , His 159 , Gly 23 , and Gly 65 ), showing best values than other cruzain inhibitors experimentally assayed. Our findings suggest that these drugs may be possible cruzain inhibitors, and biological assays","PeriodicalId":136053,"journal":{"name":"Proceedings of MOL2NET'21, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 7th ed.","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122458249","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 : 2021-11-11DOI: 10.3390/mol2net-07-11622
J. Castillo-Garit, Y. Cañizares-Carmenate, H. Pham-The, F. Torrens, F. Pérez-Giménez
Abstract. The novel coronavirus SARS-CoV-2 responsible for COVID-19, for which there is no vaccine or any known effective treatment created a sense of urgency for novel drug discovery approaches. One of the most important COVID-19 protein targets is the 3C-like (main) protease for which the crystal structure is known. In this study, we used QSAR methodology to identify compounds with potential inhibition activity for 3C-like protease. First we collect a dataset of 204 compounds, with experimental report of inhibition against SARS-CoV main protease, to develop a predictive model, using Multiple Linear Regression and a Genetic Algorithm for the selection of variables, implemented in the QSARINS software. The model was assessed and validated using the OECDs principles. The best model showed good value for the determination coefficient (R 2 =0.61), and others parameters were appropriate for fitting ( s =0.47 and RMSE tr =0.45). The validation results confirmed that the model has good robustness (Q 2LOO =0.53) and stability (R 2 –Q 2LOO =0.08) with low correlation between the descriptors (K XX =0.41), an excellent predictive power (R 2ext =0.54) and was product of a non-random correlation (R 2Yscr =0.06). This model is employed for the virtual screening of the Drug Bank database and several compounds, which belong to the applicability domain of the models, were identified as potential 3C-like protease inhibitors and proposed to further experiments to corroborate the predicted activity.
{"title":"QSARINS Based Computational Identification of Sars-Cov-2 Main Protease Inhibitors","authors":"J. Castillo-Garit, Y. Cañizares-Carmenate, H. Pham-The, F. Torrens, F. Pérez-Giménez","doi":"10.3390/mol2net-07-11622","DOIUrl":"https://doi.org/10.3390/mol2net-07-11622","url":null,"abstract":"Abstract. The novel coronavirus SARS-CoV-2 responsible for COVID-19, for which there is no vaccine or any known effective treatment created a sense of urgency for novel drug discovery approaches. One of the most important COVID-19 protein targets is the 3C-like (main) protease for which the crystal structure is known. In this study, we used QSAR methodology to identify compounds with potential inhibition activity for 3C-like protease. First we collect a dataset of 204 compounds, with experimental report of inhibition against SARS-CoV main protease, to develop a predictive model, using Multiple Linear Regression and a Genetic Algorithm for the selection of variables, implemented in the QSARINS software. The model was assessed and validated using the OECDs principles. The best model showed good value for the determination coefficient (R 2 =0.61), and others parameters were appropriate for fitting ( s =0.47 and RMSE tr =0.45). The validation results confirmed that the model has good robustness (Q 2LOO =0.53) and stability (R 2 –Q 2LOO =0.08) with low correlation between the descriptors (K XX =0.41), an excellent predictive power (R 2ext =0.54) and was product of a non-random correlation (R 2Yscr =0.06). This model is employed for the virtual screening of the Drug Bank database and several compounds, which belong to the applicability domain of the models, were identified as potential 3C-like protease inhibitors and proposed to further experiments to corroborate the predicted activity.","PeriodicalId":136053,"journal":{"name":"Proceedings of MOL2NET'21, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 7th ed.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127732437","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 : 2021-11-11DOI: 10.3390/mol2net-07-11623
M. Pinto, Antonio F Bobey, V. Bolzani, E. Cilli
{"title":"Brazilian cyclotides from plants: An overview","authors":"M. Pinto, Antonio F Bobey, V. Bolzani, E. Cilli","doi":"10.3390/mol2net-07-11623","DOIUrl":"https://doi.org/10.3390/mol2net-07-11623","url":null,"abstract":"","PeriodicalId":136053,"journal":{"name":"Proceedings of MOL2NET'21, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 7th ed.","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124398102","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 : 2021-11-10DOI: 10.3390/mol2net-07-11616
Bairong Shen, Li Chen, J. Meana
, Abstract Background Newer antiepileptic drugs (AEDs), such as Levetiracetam (LEV), Lacosamide(LCM), Topiramate(TPM), Gabapentin(GBP), Oxcarbazepine(OXA), Lamotrigine(LTG) and Zonisamide(ZNS), are prescribed frequently for epilepsy by physicians. Simultaneously, they are known to be associated with a series of eye disorders. But very few studies have systemically compared eye disorders of newer AEDs in a large sample of patients diagnosed with epilepsy. Objective The aim of this study is to evaluate the association between eye disorders and several newer antiepileptic drugs (AEDs), including LEV, LTG, TPM, GBP, OXA, LCM, ZNS, as well as to look for differences in the frequency of AEs across individual AEDs, by data-mining a self-reporting database, the FDA Adverse Event Report System (FAERS). Methods The definition relied on system organ class (SOCs) and preferred terms (PTs) by the Medical Dictionary for Regulatory Activities (MedDRA). Disproportionality analysis was used to detect the risk signals from the data in the US Food and Drug Administration (FDA) adverse event reporting system database (FAERS). The reporting odds ratio (ROR), the proportional reporting ratio (PRR) and
{"title":"Eye Disorders Associated with newer Antiepileptic drugs: A real-world disproportionality analysis of FDA Adverse Reporting System events","authors":"Bairong Shen, Li Chen, J. Meana","doi":"10.3390/mol2net-07-11616","DOIUrl":"https://doi.org/10.3390/mol2net-07-11616","url":null,"abstract":", Abstract Background Newer antiepileptic drugs (AEDs), such as Levetiracetam (LEV), Lacosamide(LCM), Topiramate(TPM), Gabapentin(GBP), Oxcarbazepine(OXA), Lamotrigine(LTG) and Zonisamide(ZNS), are prescribed frequently for epilepsy by physicians. Simultaneously, they are known to be associated with a series of eye disorders. But very few studies have systemically compared eye disorders of newer AEDs in a large sample of patients diagnosed with epilepsy. Objective The aim of this study is to evaluate the association between eye disorders and several newer antiepileptic drugs (AEDs), including LEV, LTG, TPM, GBP, OXA, LCM, ZNS, as well as to look for differences in the frequency of AEs across individual AEDs, by data-mining a self-reporting database, the FDA Adverse Event Report System (FAERS). Methods The definition relied on system organ class (SOCs) and preferred terms (PTs) by the Medical Dictionary for Regulatory Activities (MedDRA). Disproportionality analysis was used to detect the risk signals from the data in the US Food and Drug Administration (FDA) adverse event reporting system database (FAERS). The reporting odds ratio (ROR), the proportional reporting ratio (PRR) and","PeriodicalId":136053,"journal":{"name":"Proceedings of MOL2NET'21, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 7th ed.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130649708","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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