cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21931371.v1
title: Network pharmacology- and molecular simulation-based exploration of therapeutic targets and mechanisms of heparin for the treatment of sepsis/COVID-19

description: Critically infected patients with COVID-19 (coronavirus disease 2019) are prone to develop sepsis-related coagulopathy as a result of a robust immune response. The mechanism underlying the relationship between sepsis and COVID-19 is largely unknown. LMWH (low molecular weight heparin) exhibits both anti-inflammatory and anti-coagulating properties that result in a better prognosis of severely ill patients with COVID-19 co-associated with sepsis-induced coagulopathy or with a higher D-dimer value. Heparin-associated molecular targets and their mechanism of action in sepsis/COVID-19 are not well understood. In this work, we characterize the pharmacological targets, biological functions and therapeutic actions of heparin in sepsis/COVID-19 from the perspective of network pharmacology. A total of 38 potential targets for heparin action against sepsis/COVID-19 and 8 core pharmacological targets were identified, including IL6, KNG1, CXCL8, ALB, VEGFA, F2, IL10 and TNF. Moreover, enrichment analysis showed that heparin could help in treating sepsis/COVID-19 through immunomodulation, inhibition of the inflammatory response, regulation of angiogenesis and antiviral activity. The pharmacological effects of heparin against these targets were further confirmed by molecular docking and simulation analysis, suggesting that heparin exerts effective binding capacity by targeting the essential residues in sepsis/COVID-19. Prospective clinical practice evaluations may consider the use of these key prognostic indicators for the treatment of sepsis/COVID-19. Communicated by Ramaswamy H. Sarma
DOI: 10.48597/mecm-kedw
title: Measurement of pH at Starina

description: Measurement of pH at Starina
DOI: 10.6084/m9.figshare.22047416
title: Quality assessment of V<sub>H</sub>H models

description: Heavy Chain Only Antibodies are specific to Camelid species. Despite the lack of the light chain variable domain, their heavy chain variable domain (VH) domain, named V<sub>H</sub>H or nanobody, has promising potential applications in research and therapeutic fields. The structural study of V<sub>H</sub>H is therefore of great interest. Unfortunately, considering the huge amount of sequences that might be produced, only about one thousand of V<sub>H</sub>H experimental structures are publicly available in the Protein Data Bank, implying that structural model <i>prediction</i> of V<sub>H</sub>H is a necessary alternative to obtaining 3D information besides its sequence. The present study aims to assess and compare the quality of predictions from different modelling methodologies. Established comparative & homology modelling approaches to recent Deep Learning-based modelling strategies were applied, i.e. Modeller using single or multiple structural templates, ModWeb, SwissModel (with two evaluation schema), RoseTTAfold, AlphaFold 2 and NanoNet. The prediction accuracy was evaluated using RMSD, TM-score, GDT-TS, GDT-HA and Protein Blocks distance metrics. Besides the global structure assessment, we performed specific analyses of Frameworks and CDRs structures. We observed that AlphaFold 2 and especially NanoNet performed better than the other evaluated softwares. Importantly, we performed molecular dynamics simulations of an experimental structure and a NanoNet predicted model of a V<sub>H</sub>H in order to compare the global structural flexibility and local conformations using Protein Blocks. Despite rather similar structures, substantial differences in dynamical properties were observed, which underlies the complexity of the task of model evaluation. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.22047416.v1
title: Quality assessment of V<sub>H</sub>H models

description: Heavy Chain Only Antibodies are specific to Camelid species. Despite the lack of the light chain variable domain, their heavy chain variable domain (VH) domain, named V<sub>H</sub>H or nanobody, has promising potential applications in research and therapeutic fields. The structural study of V<sub>H</sub>H is therefore of great interest. Unfortunately, considering the huge amount of sequences that might be produced, only about one thousand of V<sub>H</sub>H experimental structures are publicly available in the Protein Data Bank, implying that structural model <i>prediction</i> of V<sub>H</sub>H is a necessary alternative to obtaining 3D information besides its sequence. The present study aims to assess and compare the quality of predictions from different modelling methodologies. Established comparative & homology modelling approaches to recent Deep Learning-based modelling strategies were applied, i.e. Modeller using single or multiple structural templates, ModWeb, SwissModel (with two evaluation schema), RoseTTAfold, AlphaFold 2 and NanoNet. The prediction accuracy was evaluated using RMSD, TM-score, GDT-TS, GDT-HA and Protein Blocks distance metrics. Besides the global structure assessment, we performed specific analyses of Frameworks and CDRs structures. We observed that AlphaFold 2 and especially NanoNet performed better than the other evaluated softwares. Importantly, we performed molecular dynamics simulations of an experimental structure and a NanoNet predicted model of a V<sub>H</sub>H in order to compare the global structural flexibility and local conformations using Protein Blocks. Despite rather similar structures, substantial differences in dynamical properties were observed, which underlies the complexity of the task of model evaluation. Communicated by Ramaswamy H. Sarma
DOI: 10.48597/mud9-rtce
title: Measurement of Calcium at Starina

description: Measurement of Calcium at Starina
DOI: 10.6084/m9.figshare.22015230
title: High-affinity binding of celastrol to monomeric α-synuclein mitigates in vitro aggregation

description: α-Synuclein (αSyn) aggregation is associated with Parkinson’s disease (PD). The region αSyn<sub>36-42</sub> acts as the nucleation 'master controller’ and αSyn<sub>1-12</sub> as a ‘secondary nucleation site’. They drive monomeric αSyn to aggregation. Small molecules targeting these motifs are promising for disease-modifying therapy. Using computational techniques, we screened thirty phytochemicals for αSyn binding. The top three compounds were experimentally validated for their binding affinity. Amongst them, celastrol showed high binding affinity. NMR analysis confirmed stable αSyn-celastrol interactions involving several residues in the N-terminus and NAC regions but not in the C-terminal tail. Importantly, celastrol interacted extensively with the key motifs that drive αSyn aggregation. Thioflavin-T assay indicated that celastrol reduced αSyn aggregation. Thus, celastrol holds promise as a potent drug candidate for PD. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.22015230.v1
title: High-affinity binding of celastrol to monomeric α-synuclein mitigates in vitro aggregation

description: α-Synuclein (αSyn) aggregation is associated with Parkinson’s disease (PD). The region αSyn<sub>36-42</sub> acts as the nucleation 'master controller’ and αSyn<sub>1-12</sub> as a ‘secondary nucleation site’. They drive monomeric αSyn to aggregation. Small molecules targeting these motifs are promising for disease-modifying therapy. Using computational techniques, we screened thirty phytochemicals for αSyn binding. The top three compounds were experimentally validated for their binding affinity. Amongst them, celastrol showed high binding affinity. NMR analysis confirmed stable αSyn-celastrol interactions involving several residues in the N-terminus and NAC regions but not in the C-terminal tail. Importantly, celastrol interacted extensively with the key motifs that drive αSyn aggregation. Thioflavin-T assay indicated that celastrol reduced αSyn aggregation. Thus, celastrol holds promise as a potent drug candidate for PD. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.22060113
title: Identification of structural scaffold from interbioscreen (IBS) database to inhibit 3CLpro, PLpro, and RdRp of SARS-CoV-2 using molecular docking and dynamic simulation studies

description: A novel coronavirus SARS-CoV-2 has caused a worldwide pandemic and remained a severe threat to the entire human population. Researchers worldwide are struggling to find an effective drug treatment to combat this deadly disease. Many FDA-approved drugs from varying inhibitory classes and plant-derived compounds are screened to combat this virus. Still, due to the lack of structural information and several mutations of this virus, initial drug discovery efforts have limited success. A high-resolution crystal structure of important proteins like the main protease (3CLpro) that are required for SARS-CoV-2 viral replication and polymerase (RdRp) and papain-like protease (PLpro) as a vital target in other coronaviruses still presents important targets for the drug discovery. With this knowledge, scaffold library of Interbioscreen (IBS) database was explored through molecular docking, MD simulation and postdynamic binding free energy studies. The 3D docking structures and simulation data for the IBS compounds was studied and articulated. The compounds were further evaluated for ADMET studies using QikProp and SwissADME tools. The results revealed that the natural compounds STOCK2N-00385, STOCK2N-00244, and STOCK2N-00331 interacted strongly with 3CLpro, PLpro, and RdRp, respectively, and ADMET data was also observed in the range of limits for almost all the compounds with few exceptions. Thus, it suggests that these compounds may be potential inhibitors of selected target proteins, or their structural scaffolds can be further optimized to obtain effective drug candidates for SARS-CoV-2. The findings of <i>in-silico</i> data need to be supported by <i>in-vivo</i> studies which could shed light on understanding the exact mode of inhibitory action. Communicated by Ramaswamy H. Sarma
DOI: 10.48597/ndwh-9zuy
title: Measurement of Nitrate at Starina

description: Measurement of Nitrate at Starina
DOI: 10.6084/m9.figshare.22060113.v1
title: Identification of structural scaffold from interbioscreen (IBS) database to inhibit 3CLpro, PLpro, and RdRp of SARS-CoV-2 using molecular docking and dynamic simulation studies

description: A novel coronavirus SARS-CoV-2 has caused a worldwide pandemic and remained a severe threat to the entire human population. Researchers worldwide are struggling to find an effective drug treatment to combat this deadly disease. Many FDA-approved drugs from varying inhibitory classes and plant-derived compounds are screened to combat this virus. Still, due to the lack of structural information and several mutations of this virus, initial drug discovery efforts have limited success. A high-resolution crystal structure of important proteins like the main protease (3CLpro) that are required for SARS-CoV-2 viral replication and polymerase (RdRp) and papain-like protease (PLpro) as a vital target in other coronaviruses still presents important targets for the drug discovery. With this knowledge, scaffold library of Interbioscreen (IBS) database was explored through molecular docking, MD simulation and postdynamic binding free energy studies. The 3D docking structures and simulation data for the IBS compounds was studied and articulated. The compounds were further evaluated for ADMET studies using QikProp and SwissADME tools. The results revealed that the natural compounds STOCK2N-00385, STOCK2N-00244, and STOCK2N-00331 interacted strongly with 3CLpro, PLpro, and RdRp, respectively, and ADMET data was also observed in the range of limits for almost all the compounds with few exceptions. Thus, it suggests that these compounds may be potential inhibitors of selected target proteins, or their structural scaffolds can be further optimized to obtain effective drug candidates for SARS-CoV-2. The findings of <i>in-silico</i> data need to be supported by <i>in-vivo</i> studies which could shed light on understanding the exact mode of inhibitory action. Communicated by Ramaswamy H. Sarma
DOI: 10.48597/nqqd-6rm9
title: Measurement of Sodium at Starina

description: Measurement of Sodium at Starina
DOI: 10.6084/m9.figshare.21904027
title: Virtual screening of gut microbiome bacteriocins as potential inhibitors of stearoyl-CoA desaturase 1 to regulate adipocyte differentiation and thermogenesis to combat obesity

description: The gut bacterial strains and their metabolites have been shown to play a significant role in obesity, but the molecular mechanisms underlying this association are largely unresolved. Obesity is a multifactorial problem and is controlled by various mechanisms and pathways to produce and store fat cells. Bacteriocins are secondary metabolites produced by gut bacteria to defend themselves against their competitors. Recently, they have gained great attention due to their role in metabolic disorders, including obesity. Stearoyl-CoA desaturase 1 (SCD1) is a key enzyme involved in the differentiation of adipocytes. The aim of this study is to show the regulation of SCD1 by bacteriocins and thus their importance in obesity control. We screened the human gut bacteriome for the presence of bacteriocins, predicted their structures, and showed their inhibitory role by molecular docking with SCD1. Further, to confirm the docking results, MDS of six top scoring SCD1-bacteriocin complexes were carried out for 100 ns. These six bacteriocins namely, Plantaricin S-beta, Carnolysin, Lactococcin B, Bacteriocin Iic, Plantaricin N, and Thermophilin A, with strong binding affinities, are primarily produced by bacterial strains from the Lactobacillaeacea family. These findings can be the basis of further experiments for enhanced understanding of the underlying mechanisms for obesity control, specifically bacteriocins driven regulation of the SCD1 enzyme. In addition, a consortium of bacterial strains producing these bacteriocins can be developed and used as probiotics for the amelioration of obesity and other metabolic complications. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21904027.v1
title: Virtual screening of gut microbiome bacteriocins as potential inhibitors of stearoyl-CoA desaturase 1 to regulate adipocyte differentiation and thermogenesis to combat obesity

description: The gut bacterial strains and their metabolites have been shown to play a significant role in obesity, but the molecular mechanisms underlying this association are largely unresolved. Obesity is a multifactorial problem and is controlled by various mechanisms and pathways to produce and store fat cells. Bacteriocins are secondary metabolites produced by gut bacteria to defend themselves against their competitors. Recently, they have gained great attention due to their role in metabolic disorders, including obesity. Stearoyl-CoA desaturase 1 (SCD1) is a key enzyme involved in the differentiation of adipocytes. The aim of this study is to show the regulation of SCD1 by bacteriocins and thus their importance in obesity control. We screened the human gut bacteriome for the presence of bacteriocins, predicted their structures, and showed their inhibitory role by molecular docking with SCD1. Further, to confirm the docking results, MDS of six top scoring SCD1-bacteriocin complexes were carried out for 100 ns. These six bacteriocins namely, Plantaricin S-beta, Carnolysin, Lactococcin B, Bacteriocin Iic, Plantaricin N, and Thermophilin A, with strong binding affinities, are primarily produced by bacterial strains from the Lactobacillaeacea family. These findings can be the basis of further experiments for enhanced understanding of the underlying mechanisms for obesity control, specifically bacteriocins driven regulation of the SCD1 enzyme. In addition, a consortium of bacterial strains producing these bacteriocins can be developed and used as probiotics for the amelioration of obesity and other metabolic complications. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21909044
title: <i>Rhizophora mucronata</i> Lam., a halophyte from Mauritius Island, inhibits the entry of Zika virus in human cells (A549)- an <i>in vitro</i> and <i>in silico</i> analysis

description: The recent appearance of Zika virus (ZIKV) in Brazil should serve as a wake-up call to international authorities, as it poses a threat to global public health. In the present study, we investigated whether a mangrove plant, <i>Rhizophora mucronata</i> Lam. (<i>R. mucronata</i>) collected in Mauritius, possesses anti-ZIKV activity at the non-cytotoxic doses. ZIKVMC-MR766NIID (ZIKVGFP) was used for assessing anti ZIKV activity. In silico docking (Autodock 4) and molecular simulation were performed on collected data. Using a recombinant ZIKV expressing reporter green fluorescent protein(GFP) protein, we discovered that fruit and root methanolic, decocted fruit and root extracts were effective inhibitors of ZIKV infection in human epithelial A549 cells at negligible cytotoxicity. The mechanisms by which such extracts prevented ZIKV infection are linked to the inability of the virus to attach to the host cell surface. The outcomes of this study were supported by the docking calculations in which some of the dominant compounds have shown high binding affinity against ZIKV. The scientific data gathered in this study might pave the way for the future development of possible <i>R. mucronata</i> inhibitors to combat ZIKV.f Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21909044.v1
title: <i>Rhizophora mucronata</i> Lam., a halophyte from Mauritius Island, inhibits the entry of Zika virus in human cells (A549)- an <i>in vitro</i> and <i>in silico</i> analysis

description: The recent appearance of Zika virus (ZIKV) in Brazil should serve as a wake-up call to international authorities, as it poses a threat to global public health. In the present study, we investigated whether a mangrove plant, <i>Rhizophora mucronata</i> Lam. (<i>R. mucronata</i>) collected in Mauritius, possesses anti-ZIKV activity at the non-cytotoxic doses. ZIKVMC-MR766NIID (ZIKVGFP) was used for assessing anti ZIKV activity. In silico docking (Autodock 4) and molecular simulation were performed on collected data. Using a recombinant ZIKV expressing reporter green fluorescent protein(GFP) protein, we discovered that fruit and root methanolic, decocted fruit and root extracts were effective inhibitors of ZIKV infection in human epithelial A549 cells at negligible cytotoxicity. The mechanisms by which such extracts prevented ZIKV infection are linked to the inability of the virus to attach to the host cell surface. The outcomes of this study were supported by the docking calculations in which some of the dominant compounds have shown high binding affinity against ZIKV. The scientific data gathered in this study might pave the way for the future development of possible <i>R. mucronata</i> inhibitors to combat ZIKV.f Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21940069
title: Deciphering the interaction mechanism of natural actives against larval proteins of <i>Aedes aegypti</i> to identify potential larvicides: a computational biology analysis

description: <i>Aedes aegypti</i> is the target for repellents to curb incidences of vector-borne diseases. Stopping breeding of this mosquito species at its larval stages helps in controlling spread of insect-borne diseases. Therefore, the present study focused on deciphering the mechanism of interaction of selected natural actives against larval proteins of <i>A. aegypti</i> to identify potential natural alternative larvicides. 65 larval proteins were identified from literature, whose structures were modelled and validated using RaptorX and ProCheck. 11 natural actives were selected for predicting their ligand properties and toxicities via Toxicity Estimation Software Tool and ProTox-II. Molecular docking studies were carried out using POAP followed by 100 ns molecular dynamic simulation studies for top three best docked complexes to better understand the robustness of docking, complex stabilities and molecular mechanisms of interactions. Toxicity predictions revealed that 6 molecules belonged to toxicity class 4, and five to toxicity class 5, implying that they were all safe to use. Complexes goniothalamin-translation elongation factor (−10 kcal/mol), andrographolide-acetyl-CoA C-myristoyltransferase (−9.2 kcal/mol) and capillin-translation elongation factor (−8.4 kcal/mol) showed best binding energies. When simulated, capillin-translation elongation factor showed most stability, while the remaining two also evidenced robust docking. Evolutionary studies for top two larval proteins disclosed 100 other insect species in which these proteins can be targeted using various larvicides. Protein-protein interaction network analysis revealed several protein pathways that might be affected due to aforesaid naturals. Therefore, this study provides computational insights into the molecular interaction of naturals against larval proteins, acting as potential natural larvicides. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.22015055
title: Computational design of candidate multi-epitope vaccine against SARS-CoV-2 targeting structural (S and N) and non-structural (NSP3 and NSP12) proteins

description: The COVID-19 pandemic caused by SARS-CoV-2 virus has created a global damage and has exposed the vulnerable side of scientific research towards novel diseases. The intensity of the pandemic is huge, with mortality rates of more than 6 million people worldwide in a span of 2 years. Considering the gravity of the situation, scientists all across the world are continuously attempting to create successful therapeutic solutions to combat the virus. Various vaccination strategies are being devised to ensure effective immunization against SARS-CoV-2 infection. SARS-CoV-2 spreads very rapidly, and the infection rate is remarkably high than other respiratory tract viruses. The viral entry and recognition of the host cell is facilitated by S protein of the virus. N protein along with NSP3 is majorly responsible for viral genome assembly and NSP12 performs polymerase activity for RNA synthesis. In this study, we have designed a multi-epitope, chimeric vaccine considering the two structural (S and N protein) and two non-structural proteins (NSP3 and NSP12) of SARS-CoV-2 virus. The aim is to induce immune response by generating antibodies against these proteins to target the viral entry and viral replication in the host cell. In this study, computational tools were used, and the reliability of the vaccine was verified using molecular docking, molecular dynamics simulation and immune simulation studies <i>in silico</i>. These studies demonstrate that the vaccine designed shows steady interaction with Toll like receptors with good stability and will be effective in inducing a strong and specific immune response in the body. Communicated by Ramaswamy H. Sarma
DOI: 10.48597/qvtc-7r5c
title: Measurement of Precipitation_amount at Stará Lesná

description: Measurement of Precipitation_amount at Stará Lesná