cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1029452.09fu
title: SH1029452.09FU

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/sh1029453.09fu
title: SH1029453.09FU

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/sh1029454.09fu
title: SH1029454.09FU

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/sh1029455.09fu
title: SH1029455.09FU

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/sh1029456.09fu
title: SH1029456.09FU

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: 10.6084/m9.figshare.19170063
title: High throughput virtual screening and molecular dynamics simulation analysis of phytomolecules against BfmR of <i>Acinetobacter baumannii</i>: anti-virulent drug development campaign

description: <i>Acinetobacter baumannii</i> is a notorious multidrug resistant bacterium responsible for several hospital acquired infections assisted by its capacity to develop biofilms. <i>A. baumannii</i> BfmR (RstA), a response regulator from the BfmR/S two-component signal transduction system, is the major controller of <i>A. baumannii</i> biofilm development and formation. As a result, BfmR represents a novel target for anti-biofilm treatment against <i>A. baumannii</i>. The discovery of the high-resolution crystal structure of BfmR provides a good chance for computational screening of its probable inhibitors. Therefore, in this study we aim to search new, less toxic, and natural BfmR inhibitors from 8450 phytomolecules available in the Indian Medicinal Plants, Phytochemistry and Therapeutic (IMPPAT) database by analyzing molecular docking against BfmR (PDB ID: 6BR7). Out of these 8450 phytomolecules 6742 molecules were successfully docked with BfmR with the docking score range −6.305 kcal/mol to +5.120 kcal/mol. Structure based-molecular docking (SB-MD) and ADMET (absorption, distribution, metabolism, excretion, & toxicity) profile examination revealed that Norepinephrine, Australine, Calystegine B3, 7,7 A-Diepialexine, and Alpha-Methylnoradrenaline phytocompounds strongly binds to the active site residues of BfmR. Furthermore, molecular dynamics simulation (MDS) studies for 100 ns and the binding free energy (MM/GBSA) analysis elucidated the binding mechanism of Calystegine B3, 7,7 A-Diepialexine, and Alpha-Methylnoradrenaline to BfmR. In summary, these phytocompounds seems to have the promising molecules against BfmR, and thus necessitates further verification by both <i>in vitro</i> and <i>in vivo</i> experiments. HighlightsBfmR plays a key role in biofilm development and exopolysaccharide (EPS) synthesis in <i>A. baumannii.</i>Computational approach to search for promising BfmR inhibitors from IMPAAT database.The lead phytomolecules such as Calystegine B3, 7,7 A-Diepialexine, and Alpha-Methylnoradrenaline displayed significant binding with BfmR active site.The outcome of BfmR binding phytomolecules has broadened the scope of hit molecules validation. BfmR plays a key role in biofilm development and exopolysaccharide (EPS) synthesis in <i>A. baumannii.</i> Computational approach to search for promising BfmR inhibitors from IMPAAT database. The lead phytomolecules such as Calystegine B3, 7,7 A-Diepialexine, and Alpha-Methylnoradrenaline displayed significant binding with BfmR active site. The outcome of BfmR binding phytomolecules has broadened the scope of hit molecules validation. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.19170063.v1
title: High throughput virtual screening and molecular dynamics simulation analysis of phytomolecules against BfmR of <i>Acinetobacter baumannii</i>: anti-virulent drug development campaign

description: <i>Acinetobacter baumannii</i> is a notorious multidrug resistant bacterium responsible for several hospital acquired infections assisted by its capacity to develop biofilms. <i>A. baumannii</i> BfmR (RstA), a response regulator from the BfmR/S two-component signal transduction system, is the major controller of <i>A. baumannii</i> biofilm development and formation. As a result, BfmR represents a novel target for anti-biofilm treatment against <i>A. baumannii</i>. The discovery of the high-resolution crystal structure of BfmR provides a good chance for computational screening of its probable inhibitors. Therefore, in this study we aim to search new, less toxic, and natural BfmR inhibitors from 8450 phytomolecules available in the Indian Medicinal Plants, Phytochemistry and Therapeutic (IMPPAT) database by analyzing molecular docking against BfmR (PDB ID: 6BR7). Out of these 8450 phytomolecules 6742 molecules were successfully docked with BfmR with the docking score range −6.305 kcal/mol to +5.120 kcal/mol. Structure based-molecular docking (SB-MD) and ADMET (absorption, distribution, metabolism, excretion, & toxicity) profile examination revealed that Norepinephrine, Australine, Calystegine B3, 7,7 A-Diepialexine, and Alpha-Methylnoradrenaline phytocompounds strongly binds to the active site residues of BfmR. Furthermore, molecular dynamics simulation (MDS) studies for 100 ns and the binding free energy (MM/GBSA) analysis elucidated the binding mechanism of Calystegine B3, 7,7 A-Diepialexine, and Alpha-Methylnoradrenaline to BfmR. In summary, these phytocompounds seems to have the promising molecules against BfmR, and thus necessitates further verification by both <i>in vitro</i> and <i>in vivo</i> experiments. HighlightsBfmR plays a key role in biofilm development and exopolysaccharide (EPS) synthesis in <i>A. baumannii.</i>Computational approach to search for promising BfmR inhibitors from IMPAAT database.The lead phytomolecules such as Calystegine B3, 7,7 A-Diepialexine, and Alpha-Methylnoradrenaline displayed significant binding with BfmR active site.The outcome of BfmR binding phytomolecules has broadened the scope of hit molecules validation. BfmR plays a key role in biofilm development and exopolysaccharide (EPS) synthesis in <i>A. baumannii.</i> Computational approach to search for promising BfmR inhibitors from IMPAAT database. The lead phytomolecules such as Calystegine B3, 7,7 A-Diepialexine, and Alpha-Methylnoradrenaline displayed significant binding with BfmR active site. The outcome of BfmR binding phytomolecules has broadened the scope of hit molecules validation. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.19227798
title: Structure-based pharmacophore mapping and virtual screening of natural products to identify polypharmacological inhibitor against c-MET/EGFR/VEGFR-2

description: Three receptor tyrosine kinases (RTKs), c-MET, EGFR, and VEGFR-2 have been identified as potential oncogenic targets involved in tumor development, metastasis, and invasion. Designing inhibitors that can simultaneously interact with multiple targets is a promising approach, therefore, inhibiting these three RTKs with a single chemical component might give an effective chemotherapeutic strategy for addressing the disease while limiting adverse effects. The <i>in-silico</i> methods have been developed to identify the polypharmacological inhibitors particularly for drug repurposing and multitarget drug design. Here, to find a viable inhibitor from natural source against these three RTKs, structure–based pharmacophore mapping and virtual screening of SN-II database were carried out. The filtered compound SN00020821, identified as Cedeodarin, from different computational approaches, demonstrated good interactions with all the three targets, c-MET/EGFR/VEGFR-2, with interaction energies of −42.35 kcal/mol, −49.32 kcal/mol and −44.83 kcal/mol, respectively. SN00020821displayed stable key interactions with critical amino acids of all the three receptors' kinase catalytic domains including “DFG motif” explored through the MD simulations. Furthermore, it also met the ADMET requirements and was determined to be drug-like as predicted from the Lipinski’s rule of five and Veber’s rule. Finally, SN00020821 provides a novel molecular scaffold that could be investigated further as a polypharmacological anticancer therapeutic candidate that targets the three RTKs. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.19227798.v1
title: Structure-based pharmacophore mapping and virtual screening of natural products to identify polypharmacological inhibitor against c-MET/EGFR/VEGFR-2

description: Three receptor tyrosine kinases (RTKs), c-MET, EGFR, and VEGFR-2 have been identified as potential oncogenic targets involved in tumor development, metastasis, and invasion. Designing inhibitors that can simultaneously interact with multiple targets is a promising approach, therefore, inhibiting these three RTKs with a single chemical component might give an effective chemotherapeutic strategy for addressing the disease while limiting adverse effects. The <i>in-silico</i> methods have been developed to identify the polypharmacological inhibitors particularly for drug repurposing and multitarget drug design. Here, to find a viable inhibitor from natural source against these three RTKs, structure–based pharmacophore mapping and virtual screening of SN-II database were carried out. The filtered compound SN00020821, identified as Cedeodarin, from different computational approaches, demonstrated good interactions with all the three targets, c-MET/EGFR/VEGFR-2, with interaction energies of −42.35 kcal/mol, −49.32 kcal/mol and −44.83 kcal/mol, respectively. SN00020821displayed stable key interactions with critical amino acids of all the three receptors' kinase catalytic domains including “DFG motif” explored through the MD simulations. Furthermore, it also met the ADMET requirements and was determined to be drug-like as predicted from the Lipinski’s rule of five and Veber’s rule. Finally, SN00020821 provides a novel molecular scaffold that could be investigated further as a polypharmacological anticancer therapeutic candidate that targets the three RTKs. Communicated by Ramaswamy H. Sarma
DOI: 10.15156/bio/sh1029457.09fu
title: SH1029457.09FU

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: 10.6084/m9.figshare.19247926
title: Molecular modelling studies and identification of novel phytochemical inhibitor of DLL3

description: Prostate cancer has been recently considered the most diagnosed cancer in male. DLL3 is overexpressed in CRPC-NE but not in localised prostate cancer or BPH. There are no effective treatments for neuroendocrine differentiated prostate cancer due to a lack of understanding of DLL3 structure and function. The structure of DLL3 is not yet determined using any experimental techniques. Hence, the structure-based drug discovery approach against prostate cancer has not shown great success. In present study, molecular modelling techniques were employed to generate three-dimensional structure of DLL3 and performed its thorough structural analysis. Further, all-atom molecular dynamics simulation was performed to obtain energetically favourable conformation. Further, we used a virtual screening using a library of &gt;13800 phytochemicals from the IMPPAT database and other literature to select the best possible phytochemical inhibitor for DLL3 and identified the top five compounds. Relative binding affinity was calculated using the MM-PBSA approach. ADMET properties of the screened compounds reveal the toxic effect of Gnemonol C. We believe these studied physicochemical properties, functional domain identification, and binding site identification would be very useful to gain more structural and functional insights of DLL3; also, it can be used to infer their pharmacodynamics properties of DLL3 which was recently reported as an important prostate cancer target. The current study also proposes that Ergosterol Peroxide, Dioslupecin A, Mulberrofuran K, and Caracurine V have strong affinities and could serve as plausible inhibitors against DLL3. We believe this study would further help develop better drug candidates against neuroendocrine prostate cancer. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.19247926.v1
title: Molecular modelling studies and identification of novel phytochemical inhibitor of DLL3

description: Prostate cancer has been recently considered the most diagnosed cancer in male. DLL3 is overexpressed in CRPC-NE but not in localised prostate cancer or BPH. There are no effective treatments for neuroendocrine differentiated prostate cancer due to a lack of understanding of DLL3 structure and function. The structure of DLL3 is not yet determined using any experimental techniques. Hence, the structure-based drug discovery approach against prostate cancer has not shown great success. In present study, molecular modelling techniques were employed to generate three-dimensional structure of DLL3 and performed its thorough structural analysis. Further, all-atom molecular dynamics simulation was performed to obtain energetically favourable conformation. Further, we used a virtual screening using a library of &gt;13800 phytochemicals from the IMPPAT database and other literature to select the best possible phytochemical inhibitor for DLL3 and identified the top five compounds. Relative binding affinity was calculated using the MM-PBSA approach. ADMET properties of the screened compounds reveal the toxic effect of Gnemonol C. We believe these studied physicochemical properties, functional domain identification, and binding site identification would be very useful to gain more structural and functional insights of DLL3; also, it can be used to infer their pharmacodynamics properties of DLL3 which was recently reported as an important prostate cancer target. The current study also proposes that Ergosterol Peroxide, Dioslupecin A, Mulberrofuran K, and Caracurine V have strong affinities and could serve as plausible inhibitors against DLL3. We believe this study would further help develop better drug candidates against neuroendocrine prostate cancer. Communicated by Ramaswamy H. Sarma
DOI: 10.15156/bio/sh1029458.09fu
title: SH1029458.09FU

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: 10.6084/m9.figshare.19137537
title: Natural phytocompounds physalin D, withaferin a and withanone target L-asparaginase of <i>Mycobacterium tuberculosis</i>: a molecular dynamics study

description: Tuberculosis is a major infectious disease that is responsible for high mortality in humans. The reason for the global burden is the emergence of new antibiotic resistant strains of Mycobacteria that showed resistance against the currently given therapy. It is identified that the pathogen utilizes the L-asparaginase enzyme as a virulence factor for survival benefits inside the host. Therefore, L-asparaginase of <i>Mycobacterium tuberculosis</i> is a promising therapeutic drug target. In view of the light, the present study explores thirty phytocompounds from medicinal plants to determine the binding affinity in the catalytic site of L-asparaginase. The studies initiated with the construction of the 3 D structure of L-asparaginase using homology modeling. Using the robustness of molecular docking with binding energy cut-off value &lt; −9.0 kcal/mol and 100 ns molecular dynamics simulations, three phytocompounds viz., Physalin D (−9.11 kcal/mol), Withanone (−9.45 kcal/mol) and Withaferin A (−9. 67 kcal/mol) showed strong binding potential compared to the product, L-aspartate (−5.87 kcal/mol). The active site residues identified are Thr 12, Asp 51, Ser 53, Thr 84, Asp 85, and Lys 157. Upon MD simulations, the phytocompounds and the product L-aspartate remain present in the same catalytic pocket of the enzyme. The RMSD, RMSF, radius of gyration and H-bond analysis of enzyme ligand complexes efficiently showed the stability of ligands at the docked site. Further, ADME studies distinctly demonstrate the potential of selected phytoconstituents as therapeutics. Thus, serve as safe and low-cost alternatives to chemical compounds to be used in combination therapy for treatment of tuberculosis. Communicated by Ramaswamy H. Sarma