BACKGROUND Coronavirus disease 2019(COVID-19)has demonstrated several clinical manifestations which include not only respiratory system issues but also liver,kidney,and other organ injuries.One of these abnormalities ...BACKGROUND Coronavirus disease 2019(COVID-19)has demonstrated several clinical manifestations which include not only respiratory system issues but also liver,kidney,and other organ injuries.One of these abnormalities is coagulopathies,including thrombosis and disseminated intravascular coagulation.Because of this,the administration of low molecular weight heparin is required for patients that need to be hospitalized.In addition,Remdesivir is an antiviral that was used against Middle East Acute Respiratory Syndrome,Ebola,Acute Respiratory Syndrome,and other diseases,showing satisfactory results on recovery.Besides,there is evidence suggesting that this medication can provide a better prognosis for patients with COVID-19.AIM To investigate in silico the interaction between Remdesivir and clotting factors,pursuing a possibility of using it as medicine.METHODS In this in silico study,the 3D structures of angiotensin-converting enzyme 2(ACE2),Factor I(fibrinogen),Factor II(prothrombin),Factor III(thromboplastin),Factor V(proaccelerin),Factor VII(proconvertin),Factor VIII(antihemophilic factor A),Factor IX(antihemophilic factor B),Factor X(Stuart-Prower factor),and Factor XI(precursor of thromboplastin(these structures are technically called receptors)were selected from the Protein Data Bank.The structures of the antivirals Remdesivir and Osetalmivir(these structures are called ligands)were selected from the PubChem database,while the structure of Atazanavir was selected from the ZINC database.The software AutoDock Tools(ADT)was used to prepare the receptors for molecular docking.Ions,peptides,water molecules,and other ones were removed from each ligand,and then,hydrogen atoms were added to the structures.The grid box was delimited and calculated using the same software ADT.A physiological environment with pH 7.4 is needed to make the ligands interact with the receptors,and still the software Marvin sketch®(ChemAxon®)was used to forecast the protonation state.To perform molecular docking,ADT and Vina software was connected.Using PyMol®software and Discovery studio®software from BIOVIA,it was possible to analyze the amino acid residues from receptors that were involved in the interactions with the ligands.Ligand tortions,atoms that participated in the interactions,and the type,strength,and duration of the interactions were also analyzed using those software.RESULTS Molecular docking analysis showed that Remdesivir and ACE2 had an affinity energy of-8.8 kcal/moL,forming a complex with eight hydrogen bonds involving seven atoms of Remdesivir and five amino acid residues of ACE2.Remdesivir and prothrombin had an interaction with six hydrogen bonds involving atoms of the drug and five amino acid residues of the clotting factor.Similar to that,Remdesivir and thromboplastin presented interactions via seven hydrogen bonds involving five atoms of the drug and four residues of the clotting factor.While Remdesivir and Factor V established a complex with seven hydrogen bonds between six antiviral atoms and six amino acid residues from the factor,and Factor VII connected with the drug by four hydrogen bonds,which involved three atoms of the drug and three residues of amino acids of the factor.The complex between Remdesivir and Factor IX formed an interaction via 11 hydrophilic bonds with seven atoms of the drug and seven residues of the clotting factor,plus one electrostatic bond and three hydrophobic interactions.Factor X and Remdesivir had an affinity energy of-9.6 kcal/moL,and the complex presented 10 hydrogen bonds and 14 different hydrophobic interactions which involved nine atoms of the drug and 16 amino acid residues of the clotting factor.The interaction between Remdesivir and Factor XI formed five hydrogen bonds involving five amino acid residues of the clotting factor and five of the antiviral atoms.CONCLUSION Because of the in silico significant affinity,Remdesivir possibly could act in the severe acute respiratory syndrome coronavirus 2 infection blockade by interacting with ACE2 and concomitantly act in the modulation of the coagulation cascade preventing the hypercoagulable state.展开更多
BACKGROUND Colonization with Helicobacter pylori(H.pylori)has a strong correlation with gastric cancer,and the virulence factor CagA is implicated in carcinogenesis.Studies have been conducted using medicinal plants w...BACKGROUND Colonization with Helicobacter pylori(H.pylori)has a strong correlation with gastric cancer,and the virulence factor CagA is implicated in carcinogenesis.Studies have been conducted using medicinal plants with the aim of eliminating the pathogen;however,the possibility of blocking H.pylori-induced cell differentiation to prevent the onset and/or progression of tumors has not been addressed.This type of study is expensive and time-consuming,requiring in vitro and/or in vivo tests,which can be solved using bioinformatics.Therefore,prospective computational analyses were conducted to assess the feasibility of interaction between phenolic compounds from medicinal plants and the CagA oncoprotein.AIM To perform a computational prospecting of the interactions between phenolic compounds from medicinal plants and the CagA oncoprotein of H.pylori.METHODS In this in silico study,the structures of the phenolic compounds(ligands)kaempferol,myricetin,quercetin,ponciretin(flavonoids),and chlorogenic acid(phenolic acid)were selected from the PubChem database.These phenolic compounds were chosen based on previous studies that suggested medicinal plants as non-drug treatments to eliminate H.pylori infection.The three-dimensional structure model of the CagA oncoprotein of H.pylori(receptor)was obtained through molecular modeling using computational tools from the I-Tasser platform,employing the threading methodology.The primary sequence of CagA was sourced from GenBank(BAK52797.1).A screening was conducted to identify binding sites in the structure of the CagA oncoprotein that could potentially interact with the ligands,utilizing the GRaSP online platform.Both the ligands and receptor were prepared for molecular docking using AutoDock Tools 4(ADT)software,and the simulations were carried out using a combination of ADT and AutoDock Vina v.1.2.0 software.Two sets of simulations were performed:One involving the central region of CagA with phenolic compounds,and another involving the carboxy-terminus region of CagA with phenolic compounds.The receptor-ligand complexes were then analyzed using PyMol and BIOVIA Discovery Studio software.RESULTS The structure model obtained for the CagA oncoprotein exhibited high quality(C-score=0.09)and was validated using parameters from the MolProbity platform.The GRaSP online platform identified 24 residues(phenylalanine and leucine)as potential binding sites on the CagA oncoprotein.Molecular docking simulations were conducted with the three-dimensional model of the CagA oncoprotein.No complexes were observed in the simulations between the carboxy-terminus region of CagA and the phenolic compounds;however,all phenolic compounds interacted with the central region of the oncoprotein.Phenolic compounds and CagA exhibited significant affinity energy(-7.9 to-9.1 kcal/mol):CagA/kaempferol formed 28 chemical bonds,CagA/myricetin formed 18 chemical bonds,CagA/quercetin formed 16 chemical bonds,CagA/ponciretin formed 13 chemical bonds,and CagA/chlorogenic acid formed 17 chemical bonds.Although none of the phenolic compounds directly bound to the amino acid residues of the K-Xn-R-X-R membrane binding motif,all of them bound to residues,mostly positively or negatively charged,located near this region.CONCLUSION In silico,the tested phenolic compounds formed stable complexes with CagA.Therefore,they could be tested in vitro and/or in vivo to validate the findings,and to assess interference in CagA/cellular target interactions and in the oncogenic differentiation of gastric cells.展开更多
文摘BACKGROUND Coronavirus disease 2019(COVID-19)has demonstrated several clinical manifestations which include not only respiratory system issues but also liver,kidney,and other organ injuries.One of these abnormalities is coagulopathies,including thrombosis and disseminated intravascular coagulation.Because of this,the administration of low molecular weight heparin is required for patients that need to be hospitalized.In addition,Remdesivir is an antiviral that was used against Middle East Acute Respiratory Syndrome,Ebola,Acute Respiratory Syndrome,and other diseases,showing satisfactory results on recovery.Besides,there is evidence suggesting that this medication can provide a better prognosis for patients with COVID-19.AIM To investigate in silico the interaction between Remdesivir and clotting factors,pursuing a possibility of using it as medicine.METHODS In this in silico study,the 3D structures of angiotensin-converting enzyme 2(ACE2),Factor I(fibrinogen),Factor II(prothrombin),Factor III(thromboplastin),Factor V(proaccelerin),Factor VII(proconvertin),Factor VIII(antihemophilic factor A),Factor IX(antihemophilic factor B),Factor X(Stuart-Prower factor),and Factor XI(precursor of thromboplastin(these structures are technically called receptors)were selected from the Protein Data Bank.The structures of the antivirals Remdesivir and Osetalmivir(these structures are called ligands)were selected from the PubChem database,while the structure of Atazanavir was selected from the ZINC database.The software AutoDock Tools(ADT)was used to prepare the receptors for molecular docking.Ions,peptides,water molecules,and other ones were removed from each ligand,and then,hydrogen atoms were added to the structures.The grid box was delimited and calculated using the same software ADT.A physiological environment with pH 7.4 is needed to make the ligands interact with the receptors,and still the software Marvin sketch®(ChemAxon®)was used to forecast the protonation state.To perform molecular docking,ADT and Vina software was connected.Using PyMol®software and Discovery studio®software from BIOVIA,it was possible to analyze the amino acid residues from receptors that were involved in the interactions with the ligands.Ligand tortions,atoms that participated in the interactions,and the type,strength,and duration of the interactions were also analyzed using those software.RESULTS Molecular docking analysis showed that Remdesivir and ACE2 had an affinity energy of-8.8 kcal/moL,forming a complex with eight hydrogen bonds involving seven atoms of Remdesivir and five amino acid residues of ACE2.Remdesivir and prothrombin had an interaction with six hydrogen bonds involving atoms of the drug and five amino acid residues of the clotting factor.Similar to that,Remdesivir and thromboplastin presented interactions via seven hydrogen bonds involving five atoms of the drug and four residues of the clotting factor.While Remdesivir and Factor V established a complex with seven hydrogen bonds between six antiviral atoms and six amino acid residues from the factor,and Factor VII connected with the drug by four hydrogen bonds,which involved three atoms of the drug and three residues of amino acids of the factor.The complex between Remdesivir and Factor IX formed an interaction via 11 hydrophilic bonds with seven atoms of the drug and seven residues of the clotting factor,plus one electrostatic bond and three hydrophobic interactions.Factor X and Remdesivir had an affinity energy of-9.6 kcal/moL,and the complex presented 10 hydrogen bonds and 14 different hydrophobic interactions which involved nine atoms of the drug and 16 amino acid residues of the clotting factor.The interaction between Remdesivir and Factor XI formed five hydrogen bonds involving five amino acid residues of the clotting factor and five of the antiviral atoms.CONCLUSION Because of the in silico significant affinity,Remdesivir possibly could act in the severe acute respiratory syndrome coronavirus 2 infection blockade by interacting with ACE2 and concomitantly act in the modulation of the coagulation cascade preventing the hypercoagulable state.
文摘BACKGROUND Colonization with Helicobacter pylori(H.pylori)has a strong correlation with gastric cancer,and the virulence factor CagA is implicated in carcinogenesis.Studies have been conducted using medicinal plants with the aim of eliminating the pathogen;however,the possibility of blocking H.pylori-induced cell differentiation to prevent the onset and/or progression of tumors has not been addressed.This type of study is expensive and time-consuming,requiring in vitro and/or in vivo tests,which can be solved using bioinformatics.Therefore,prospective computational analyses were conducted to assess the feasibility of interaction between phenolic compounds from medicinal plants and the CagA oncoprotein.AIM To perform a computational prospecting of the interactions between phenolic compounds from medicinal plants and the CagA oncoprotein of H.pylori.METHODS In this in silico study,the structures of the phenolic compounds(ligands)kaempferol,myricetin,quercetin,ponciretin(flavonoids),and chlorogenic acid(phenolic acid)were selected from the PubChem database.These phenolic compounds were chosen based on previous studies that suggested medicinal plants as non-drug treatments to eliminate H.pylori infection.The three-dimensional structure model of the CagA oncoprotein of H.pylori(receptor)was obtained through molecular modeling using computational tools from the I-Tasser platform,employing the threading methodology.The primary sequence of CagA was sourced from GenBank(BAK52797.1).A screening was conducted to identify binding sites in the structure of the CagA oncoprotein that could potentially interact with the ligands,utilizing the GRaSP online platform.Both the ligands and receptor were prepared for molecular docking using AutoDock Tools 4(ADT)software,and the simulations were carried out using a combination of ADT and AutoDock Vina v.1.2.0 software.Two sets of simulations were performed:One involving the central region of CagA with phenolic compounds,and another involving the carboxy-terminus region of CagA with phenolic compounds.The receptor-ligand complexes were then analyzed using PyMol and BIOVIA Discovery Studio software.RESULTS The structure model obtained for the CagA oncoprotein exhibited high quality(C-score=0.09)and was validated using parameters from the MolProbity platform.The GRaSP online platform identified 24 residues(phenylalanine and leucine)as potential binding sites on the CagA oncoprotein.Molecular docking simulations were conducted with the three-dimensional model of the CagA oncoprotein.No complexes were observed in the simulations between the carboxy-terminus region of CagA and the phenolic compounds;however,all phenolic compounds interacted with the central region of the oncoprotein.Phenolic compounds and CagA exhibited significant affinity energy(-7.9 to-9.1 kcal/mol):CagA/kaempferol formed 28 chemical bonds,CagA/myricetin formed 18 chemical bonds,CagA/quercetin formed 16 chemical bonds,CagA/ponciretin formed 13 chemical bonds,and CagA/chlorogenic acid formed 17 chemical bonds.Although none of the phenolic compounds directly bound to the amino acid residues of the K-Xn-R-X-R membrane binding motif,all of them bound to residues,mostly positively or negatively charged,located near this region.CONCLUSION In silico,the tested phenolic compounds formed stable complexes with CagA.Therefore,they could be tested in vitro and/or in vivo to validate the findings,and to assess interference in CagA/cellular target interactions and in the oncogenic differentiation of gastric cells.
