cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0799722.10fu
title: SH0799722.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0799723.10fu
title: SH0799723.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0799724.10fu
title: SH0799724.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0799725.10fu
title: SH0799725.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0799726.10fu
title: SH0799726.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.9q8d4n
title: Occurrence Download

description: A dataset containing 1572 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is DEU.9_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Castor fiber Linnaeus, 1758"
 ]
}

 The dataset includes 1572 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0077172-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/4k4i7z
title: TrajAnim20191015_20200315.mp4

description: winter 2019 movements of catfish
DOI: 10.57745/eu1gbh
title: TrajAnim20171015_20180315.mp4

description: winter 2017 movements of catfish
DOI: 10.57745/uulp3z
title: TrajAnim20181015_20190315.mp4

description: winter 2018 movements of catfish
DOI: 10.57745/pr42ic
title: TrajAnim20201015_20210315.mp4

description: winter 2020 movements of catfish
DOI: 10.6084/m9.figshare.21778015
title: Identification of potent inhibitors against transmembrane serine protease 2 for developing therapeutics against SARS-CoV-2

description: In viral binding and entry, the Spike(S) protein of SARS-CoV-2 uses transmembrane serine protease 2 (TMPRSS2) for priming to cleavage themselves. In this study, we have screened ‘drug-like’ 7476 ligands and found that over thirty ligands can effectively inhibit the TMPRSS-2 better than the control ligand. Finally, the three best drug agents L1, L2, and L6 were selected according to their average binding affinities and fitting score. These ligands interact with Asp435, Cys437, Ser436, Trp461, and Cys465 amino acid residues. The three best candidates and a reported drug Nafamostat mesylate (NAM) were selected to run 250 ns molecular dynamics (MD) simulations. Various properties of ligand-protein interactions obtained from MD simulation such as bonds, angle, dihedral, planarity, coulomb, and van der Waals (VdW) were used for principal component analysis (PCA) calculation. PCA discloses the evidence of the structural similarities to the corresponding complexes of L1, L2, and L6 with the complex of TMPRSS2(TM) and Nafamostat mesylate (TM-NAM). Moreover, Quantitative structure-activity relationship (QSAR) pattern recognition was generated using PCA for the investigation of structural similarities among the selected ligands. Multiple Linear Regression (MLR) model was built to predict the binding energy compared to the binding energy obtained from molecular docking. The MLR regression model reveals an accuracy of 80% for the prediction of the binding energy of ligands. ADMET analysis demonstrates that these drug agents are appeared to be safer inhibitors. These three ligands can be used as potential inhibitors against the TMPRSS2. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21778015.v1
title: Identification of potent inhibitors against transmembrane serine protease 2 for developing therapeutics against SARS-CoV-2

description: In viral binding and entry, the Spike(S) protein of SARS-CoV-2 uses transmembrane serine protease 2 (TMPRSS2) for priming to cleavage themselves. In this study, we have screened ‘drug-like’ 7476 ligands and found that over thirty ligands can effectively inhibit the TMPRSS-2 better than the control ligand. Finally, the three best drug agents L1, L2, and L6 were selected according to their average binding affinities and fitting score. These ligands interact with Asp435, Cys437, Ser436, Trp461, and Cys465 amino acid residues. The three best candidates and a reported drug Nafamostat mesylate (NAM) were selected to run 250 ns molecular dynamics (MD) simulations. Various properties of ligand-protein interactions obtained from MD simulation such as bonds, angle, dihedral, planarity, coulomb, and van der Waals (VdW) were used for principal component analysis (PCA) calculation. PCA discloses the evidence of the structural similarities to the corresponding complexes of L1, L2, and L6 with the complex of TMPRSS2(TM) and Nafamostat mesylate (TM-NAM). Moreover, Quantitative structure-activity relationship (QSAR) pattern recognition was generated using PCA for the investigation of structural similarities among the selected ligands. Multiple Linear Regression (MLR) model was built to predict the binding energy compared to the binding energy obtained from molecular docking. The MLR regression model reveals an accuracy of 80% for the prediction of the binding energy of ligands. ADMET analysis demonstrates that these drug agents are appeared to be safer inhibitors. These three ligands can be used as potential inhibitors against the TMPRSS2. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.16822376
title: Computational studies reveal co-occurrence of two mutations in IL7R gene of high-grade serous carcinoma patients

description: Major cause of mortality in ovarian cancer can be attributed to a lack of specific and sensitive biomarkers for diagnosis and prognosis of the disease. Uncovering the mutations in genes involved in crucial oncogenic pathways is a key step in discovery and development of novel biomarkers. Whole exome sequencing (WES) is a powerful method for the detection of cancer driver mutations. The present work focuses on identifying functionally damaging mutations in patients with high-grade serous ovarian carcinoma (HGSC) through computational analysis of WES. In this study, WES data of HGSC patients was retrieved from the genomic literature available in sequence read archive, the variants were identified and comprehensive structural and functional analysis was performed. Interestingly, I66T and V138I mutations were found to be co-occurring in the IL7R gene in four out of five HGSC patient samples investigated in this study. The V138I mutation was located in the fibronectin type-3 domain and computationally assessed to be causing disruptive effects on the structure and dynamics of IL7R protein. This mutation was found to be co-occurring with the neutral I66T mutation in the same domain which compensated the disruptive effects of V138I variant. These comprehensive studies point to a hitherto unexplored significant role of the IL7R gene in ovarian carcinoma. It is envisaged that the work will lay the foundation for the development of a novel biomarker with potential application in molecular profiling and in estimation of the disease prognosis. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.16822376.v1
title: Computational studies reveal co-occurrence of two mutations in IL7R gene of high-grade serous carcinoma patients

description: Major cause of mortality in ovarian cancer can be attributed to a lack of specific and sensitive biomarkers for diagnosis and prognosis of the disease. Uncovering the mutations in genes involved in crucial oncogenic pathways is a key step in discovery and development of novel biomarkers. Whole exome sequencing (WES) is a powerful method for the detection of cancer driver mutations. The present work focuses on identifying functionally damaging mutations in patients with high-grade serous ovarian carcinoma (HGSC) through computational analysis of WES. In this study, WES data of HGSC patients was retrieved from the genomic literature available in sequence read archive, the variants were identified and comprehensive structural and functional analysis was performed. Interestingly, I66T and V138I mutations were found to be co-occurring in the IL7R gene in four out of five HGSC patient samples investigated in this study. The V138I mutation was located in the fibronectin type-3 domain and computationally assessed to be causing disruptive effects on the structure and dynamics of IL7R protein. This mutation was found to be co-occurring with the neutral I66T mutation in the same domain which compensated the disruptive effects of V138I variant. These comprehensive studies point to a hitherto unexplored significant role of the IL7R gene in ovarian carcinoma. It is envisaged that the work will lay the foundation for the development of a novel biomarker with potential application in molecular profiling and in estimation of the disease prognosis. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21778018
title: Screening of <i>Azadirachta indica</i> phytoconstituents as GSK-3β inhibitor and its implication in neuroblastoma: molecular docking, molecular dynamics, MM-PBSA binding energy, and in-vitro study

description: Glycogen synthase kinase-3 (GSK-3), a constitutively active serine/threonine kinase, primary regulator of various cellular activities varying from glycogen metabolism to cell proliferation and regulation. GSK-3β is associated with the pathogenesis of numerous human diseases, including cancer, metabolic disorder, and Alzheimer's disease. In this study, <i>Azadirachta indica</i> compounds were selected and further screened on the BOILED-Egg model. The compounds showing good GIT absorption were docked with the crystal structure of GSK-3β. The compounds with high docking score were submitted for the molecular dynamic simulation (MDS) and Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA). Based upon the MDS and MM-PBSA study, gedunin showed the highest binding energy throughout the MDS process. Gedunin was isolated from the <i>Azadirachta indica</i>, and its efficacy on GSK-3β inhibition was studied in the human neuroblastoma (SH-SY5Y) cells. Gedunin induced apoptosis and anti-proliferative activity by arresting G2/M phase, as evident by cell-cycle analysis. From immunoblot study, gedunin significantly enhanced the expression of an inhibitory form of GSK-3β (p-GSK-3β Ser9) in concentration-dependent manner. Our findings demonstrate that gedunin may act as an effective GSK-3β inhibitor suggesting that this compound may be used for the management of neuroblastoma. Further preclinical and clinical investigation is desirable. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21778018.v1
title: Screening of <i>Azadirachta indica</i> phytoconstituents as GSK-3β inhibitor and its implication in neuroblastoma: molecular docking, molecular dynamics, MM-PBSA binding energy, and in-vitro study

description: Glycogen synthase kinase-3 (GSK-3), a constitutively active serine/threonine kinase, primary regulator of various cellular activities varying from glycogen metabolism to cell proliferation and regulation. GSK-3β is associated with the pathogenesis of numerous human diseases, including cancer, metabolic disorder, and Alzheimer's disease. In this study, <i>Azadirachta indica</i> compounds were selected and further screened on the BOILED-Egg model. The compounds showing good GIT absorption were docked with the crystal structure of GSK-3β. The compounds with high docking score were submitted for the molecular dynamic simulation (MDS) and Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA). Based upon the MDS and MM-PBSA study, gedunin showed the highest binding energy throughout the MDS process. Gedunin was isolated from the <i>Azadirachta indica</i>, and its efficacy on GSK-3β inhibition was studied in the human neuroblastoma (SH-SY5Y) cells. Gedunin induced apoptosis and anti-proliferative activity by arresting G2/M phase, as evident by cell-cycle analysis. From immunoblot study, gedunin significantly enhanced the expression of an inhibitory form of GSK-3β (p-GSK-3β Ser9) in concentration-dependent manner. Our findings demonstrate that gedunin may act as an effective GSK-3β inhibitor suggesting that this compound may be used for the management of neuroblastoma. Further preclinical and clinical investigation is desirable. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21778021
title: Detection of differential selection pressure and functional-specific sites in subunits of vertebrate neuronal nicotinic acetylcholine receptors

description: The nicotinic acetylcholine receptors (nAChR) are made of subunits evolved from a common ancestor. Despite the similarity in their sequences and structures, the properties of these subunits vary significantly. Thus, identifying the evolution features and function-related sites specific to each subunit is essential for understanding the characteristics of the subunits and the receptors assembled by them. In this study, we examined the sequence features of the nine neuronal nAChRs subunits from representative vertebrate species. Analysis revealed that all the subunits were subject to strong purifying selection in evolution, and each was under a unique pattern of selection pressures. At the same time, the functional constraints were not uniform within each subunit, with different domains in the molecule being subject to different selection pressures. We also detected potential positive selection events in the subunits or subunit clusters, and identified the sites might be associated with the function specificity of each subunit. Furthermore, positive selection at some domains might contribute to the diversity of subunit function; for example, the β9 strand might be related to the agonist specificity of α subunit in heteromeric receptor and β4-β5 linker could be involved in Ca<sup>2+</sup> permeability. Subunits α7, α4 and β2 subunits possess a strong adaptability in vertebrates. Our results highlighted the importance of tracking functional differentiation in protein sequence underlying functional properties of nAChRs. In summary, our work may provide clues on understanding the diversity and the function specificity of the nAChR subunits, as well as the receptors co-assembled by them. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21778021.v1
title: Detection of differential selection pressure and functional-specific sites in subunits of vertebrate neuronal nicotinic acetylcholine receptors

description: The nicotinic acetylcholine receptors (nAChR) are made of subunits evolved from a common ancestor. Despite the similarity in their sequences and structures, the properties of these subunits vary significantly. Thus, identifying the evolution features and function-related sites specific to each subunit is essential for understanding the characteristics of the subunits and the receptors assembled by them. In this study, we examined the sequence features of the nine neuronal nAChRs subunits from representative vertebrate species. Analysis revealed that all the subunits were subject to strong purifying selection in evolution, and each was under a unique pattern of selection pressures. At the same time, the functional constraints were not uniform within each subunit, with different domains in the molecule being subject to different selection pressures. We also detected potential positive selection events in the subunits or subunit clusters, and identified the sites might be associated with the function specificity of each subunit. Furthermore, positive selection at some domains might contribute to the diversity of subunit function; for example, the β9 strand might be related to the agonist specificity of α subunit in heteromeric receptor and β4-β5 linker could be involved in Ca<sup>2+</sup> permeability. Subunits α7, α4 and β2 subunits possess a strong adaptability in vertebrates. Our results highlighted the importance of tracking functional differentiation in protein sequence underlying functional properties of nAChRs. In summary, our work may provide clues on understanding the diversity and the function specificity of the nAChR subunits, as well as the receptors co-assembled by them. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.19410321
title: Validation of crystal structure of 2‐acetamidophenyl acetate: an experimental and theoretical study

description: In this present study, we have determined the crystal structure of 2-acetamidophenyl acetate (2-AAPA) commonly used as influenza neuraminidase inhibitor, to analyze the polymorphism. Molecular docking and molecular dynamics have been performed for the 2-AAPA-neuraminidase complex as the ester-derived benzoic group shows several biological properties. The X-ray diffraction studies confirmed that the 2-AAPA crystals are stabilized by N–H···O type of intermolecular interactions. Possible conformers of 2-AAPA crystal structures were computationally predicted by <i>ab initio</i> methods and the stable crystal structure was identified. Hirshfeld surface analysis of both experimental and predicted crystal structure exhibits the intermolecular interactions associated with 2D fingerprint plots. The lowest docking score and intermolecular interactions of 2-AAPA molecule against influenza neuraminidase confirm the binding affinity of the 2-AAPA crystals. The quantum theory of atoms in molecules analysis of these intermolecular interactions was implemented to understand the charge density redistribution of the molecule in the active site of influenza neuraminidase to validate the strength of the interactions. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.19410321.v1
title: Validation of crystal structure of 2‐acetamidophenyl acetate: an experimental and theoretical study

description: In this present study, we have determined the crystal structure of 2-acetamidophenyl acetate (2-AAPA) commonly used as influenza neuraminidase inhibitor, to analyze the polymorphism. Molecular docking and molecular dynamics have been performed for the 2-AAPA-neuraminidase complex as the ester-derived benzoic group shows several biological properties. The X-ray diffraction studies confirmed that the 2-AAPA crystals are stabilized by N–H···O type of intermolecular interactions. Possible conformers of 2-AAPA crystal structures were computationally predicted by <i>ab initio</i> methods and the stable crystal structure was identified. Hirshfeld surface analysis of both experimental and predicted crystal structure exhibits the intermolecular interactions associated with 2D fingerprint plots. The lowest docking score and intermolecular interactions of 2-AAPA molecule against influenza neuraminidase confirm the binding affinity of the 2-AAPA crystals. The quantum theory of atoms in molecules analysis of these intermolecular interactions was implemented to understand the charge density redistribution of the molecule in the active site of influenza neuraminidase to validate the strength of the interactions. Communicated by Ramaswamy H. Sarma