cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.7vqky8
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006581-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wcv99m
title: Occurrence Download

description: A dataset containing 705008469 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is EOD – eBird Observation Dataset"
 ]
}

 The dataset includes 705008469 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0137358-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qjiuqh
title: Occurrence Download

description: A dataset containing 386834668 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is EOD – eBird Observation Dataset"
 ]
}

 The dataset includes 386834668 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005366-171113114016250/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c4zyon
title: Occurrence Download

description: A dataset containing 1514342407 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 1514342407 records from 18028 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003061-171025204727650/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.24543657.v1
title: Inter-BRCT linker is probably the most intolerant region of the BRCA1 BRCT domain

description: Pathogenic mutations in <i>BRCA1</i> are associated with an increased risk of hereditary breast, ovarian, and some other cancers; however, the clinical significance of many mutations in this gene remains unknown (Variants of Unknown Significance/VUS). Since mutations in intolerant regions of a protein lead to dysfunction and pathogenicity, identifying these regions helps to predict the clinical importance of VUSs. This study aimed to identify intolerant regions of BRCA1 and understand the possible root of this susceptibility. Intolerant regions appear to carry more pathogenic mutations than expected due to their lower tolerance to missense variations. Therefore, we hypothesized that among the BRCA1 regions, the higher the mutation density, the greater the intolerance. Thus, pathogenic mutation density and regional intolerance scores were calculated to identify BRCA1-intolerant regions. To investigate the pathogenic mechanisms of missense-intolerant regions in <i>BRCA1</i>, transcription activation (TA) experiments and molecular dynamics (MD) simulations were also performed. The results showed that the RING domain, followed by the BRCT domain, has the highest density of pathogenic mutations. In the BRCT domain, a higher density of pathogenic mutations was observed in the inter-BRCT linker. Additionally, scores generated by Missense Tolerance Ratio-3D (MTR3D) and the Missense Tolerance Ratio consensus (MTRX) showed that the inter-BRCT linker is more intolerant than other regions of the BRCT domain. The MD results showed that mutations in the inter-BRCT linker led to cancer susceptibility, likely due to disruption of the interaction between BRCA1 and phosphopeptides. TA laboratory assays further supported the importance of the inter-BRCT linker. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24543657
title: Inter-BRCT linker is probably the most intolerant region of the BRCA1 BRCT domain

description: Pathogenic mutations in <i>BRCA1</i> are associated with an increased risk of hereditary breast, ovarian, and some other cancers; however, the clinical significance of many mutations in this gene remains unknown (Variants of Unknown Significance/VUS). Since mutations in intolerant regions of a protein lead to dysfunction and pathogenicity, identifying these regions helps to predict the clinical importance of VUSs. This study aimed to identify intolerant regions of BRCA1 and understand the possible root of this susceptibility. Intolerant regions appear to carry more pathogenic mutations than expected due to their lower tolerance to missense variations. Therefore, we hypothesized that among the BRCA1 regions, the higher the mutation density, the greater the intolerance. Thus, pathogenic mutation density and regional intolerance scores were calculated to identify BRCA1-intolerant regions. To investigate the pathogenic mechanisms of missense-intolerant regions in <i>BRCA1</i>, transcription activation (TA) experiments and molecular dynamics (MD) simulations were also performed. The results showed that the RING domain, followed by the BRCT domain, has the highest density of pathogenic mutations. In the BRCT domain, a higher density of pathogenic mutations was observed in the inter-BRCT linker. Additionally, scores generated by Missense Tolerance Ratio-3D (MTR3D) and the Missense Tolerance Ratio consensus (MTRX) showed that the inter-BRCT linker is more intolerant than other regions of the BRCT domain. The MD results showed that mutations in the inter-BRCT linker led to cancer susceptibility, likely due to disruption of the interaction between BRCA1 and phosphopeptides. TA laboratory assays further supported the importance of the inter-BRCT linker. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.23599759.v1
title: Comprehensive bioinformatics analysis of structural and functional consequences of deleterious missense mutations in the human QDPR gene

description: Quinonoid dihydropteridine reductase (QDPR) is an enzyme that regulates tetrahydrobiopterin (BH4), a cofactor for enzymes involved in neurotransmitter synthesis and blood pressure regulation. Reduced QDPR activity can cause dihydrobiopterin (BH2) accumulation and BH4 depletion, leading to impaired neurotransmitter synthesis, oxidative stress, and increased risk of Parkinson’s disease. A total of 10,236 SNPs were identified in the QDPR gene, with 217 being missense SNPs. Over 18 different sequence-based and structure-based tools were employed to assess the protein’s biological activity, with several computational tools identifying deleterious SNPs. Additionally, the article provides detailed information about the QDPR gene and protein structure and conservation analysis. The results showed that 10 mutations were harmful and linked to brain and central nervous system disorders, and were predicted to be oncogenic by Dr. Cancer and CScape. Following conservation analysis, the HOPE server was used to analyse the effect of six selected mutations (L14P, V15G, G23S, V54G, M107K, G151S) on the protein structure. Overall, the study provides insights into the biological and functional impact of nsSNPs on QDPR activity and the potential induced pathogenicity and oncogenicity. In the future, research can be conducted to systematically evaluate QDPR gene variation through clinical studies, investigate mutation prevalence across different geographical regions, and validate computational results with conclusive experiments. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.23599759
title: Comprehensive bioinformatics analysis of structural and functional consequences of deleterious missense mutations in the human QDPR gene

description: Quinonoid dihydropteridine reductase (QDPR) is an enzyme that regulates tetrahydrobiopterin (BH4), a cofactor for enzymes involved in neurotransmitter synthesis and blood pressure regulation. Reduced QDPR activity can cause dihydrobiopterin (BH2) accumulation and BH4 depletion, leading to impaired neurotransmitter synthesis, oxidative stress, and increased risk of Parkinson’s disease. A total of 10,236 SNPs were identified in the QDPR gene, with 217 being missense SNPs. Over 18 different sequence-based and structure-based tools were employed to assess the protein’s biological activity, with several computational tools identifying deleterious SNPs. Additionally, the article provides detailed information about the QDPR gene and protein structure and conservation analysis. The results showed that 10 mutations were harmful and linked to brain and central nervous system disorders, and were predicted to be oncogenic by Dr. Cancer and CScape. Following conservation analysis, the HOPE server was used to analyse the effect of six selected mutations (L14P, V15G, G23S, V54G, M107K, G151S) on the protein structure. Overall, the study provides insights into the biological and functional impact of nsSNPs on QDPR activity and the potential induced pathogenicity and oncogenicity. In the future, research can be conducted to systematically evaluate QDPR gene variation through clinical studies, investigate mutation prevalence across different geographical regions, and validate computational results with conclusive experiments. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.23578183
title: Isolation, identification, and characterization of α- asarone, from hydromethanolic leaf extract of <i>Acorus calamus</i> L. and its apoptosis-inducing mechanism in A549 cells

description: Due to the presence of several active secondary metabolites, the traditional Indian and Chinese medicinal herb <i>Acorus calamus</i> L. has been utilized for both medical and culinary purposes since ancient times. A recent report has underscored the promising cytotoxic effect of <i>A. calamus</i> leaves extract against non-small cell lung cancer A549 cells. Thus, we want to separate the bioactive substance from the hydromethanolic extract of <i>A. calamus</i> leaves in the current investigation. Thin-layer chromatography was used to separate the compounds and different spectroscopic methods (UV, FTIR, NMR, and LCMS/MS) were used for the structure prediction. <i>α-</i>asarone was found to be the main bioactive compound present and it was isolated from <i>A. calamus</i> leaves extract. It exerted a good cytotoxic effect with an IC<sub>50</sub> value of 21.43 ± 1.27 μM against A549 cells and IC<sub>50</sub> value of 324.12 ± 1.32 μM against WI-38 cells. The induction of apoptosis in A549 cells by α<i>-</i>asarone was reaffirmed by the diverse differential staining methods including DAPI, Acridine Orange/Ethidium Bromide, and Giemsa staining. Additionally, α-asarone induced mitochondrial membrane potential (ΔΨ<sub>m</sub>) dissipation with a concomitant increase in the production of ROS. Furthermore, it also increased expressions of caspase-3, caspase-9, caspase-8, DR4, and DR5 genes in A549 cells. In conclusion, α-asarone-induced apoptotic cell death in non-small lung cancer cells (A549) as a result of loss of mitochondrial function, increased ROS production, subsequent activation of an internal and extrinsic caspase pathway, and altered expression of genes controlling apoptosis. As a whole, α<i>-</i>asarone is a plausible therapeutic agent for managing lung cancer. HIGHLIGHTSIsolation of bioactive compound from hydromethanolic leaves extract of <i>Acorus calamus</i> L. by thin layer chromatography.Structural elucidation of the bioactive compound was carried out using different methods like UV analysis, FTIR, NMR, and LC-MS/MS analysis.A plausible mode of action revealed that α-asarone can induce apoptosis in lung cancer cells (A549). Isolation of bioactive compound from hydromethanolic leaves extract of <i>Acorus calamus</i> L. by thin layer chromatography. Structural elucidation of the bioactive compound was carried out using different methods like UV analysis, FTIR, NMR, and LC-MS/MS analysis. A plausible mode of action revealed that α-asarone can induce apoptosis in lung cancer cells (A549). Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.23578183.v1
title: Isolation, identification, and characterization of α- asarone, from hydromethanolic leaf extract of <i>Acorus calamus</i> L. and its apoptosis-inducing mechanism in A549 cells

description: Due to the presence of several active secondary metabolites, the traditional Indian and Chinese medicinal herb <i>Acorus calamus</i> L. has been utilized for both medical and culinary purposes since ancient times. A recent report has underscored the promising cytotoxic effect of <i>A. calamus</i> leaves extract against non-small cell lung cancer A549 cells. Thus, we want to separate the bioactive substance from the hydromethanolic extract of <i>A. calamus</i> leaves in the current investigation. Thin-layer chromatography was used to separate the compounds and different spectroscopic methods (UV, FTIR, NMR, and LCMS/MS) were used for the structure prediction. <i>α-</i>asarone was found to be the main bioactive compound present and it was isolated from <i>A. calamus</i> leaves extract. It exerted a good cytotoxic effect with an IC<sub>50</sub> value of 21.43 ± 1.27 μM against A549 cells and IC<sub>50</sub> value of 324.12 ± 1.32 μM against WI-38 cells. The induction of apoptosis in A549 cells by α<i>-</i>asarone was reaffirmed by the diverse differential staining methods including DAPI, Acridine Orange/Ethidium Bromide, and Giemsa staining. Additionally, α-asarone induced mitochondrial membrane potential (ΔΨ<sub>m</sub>) dissipation with a concomitant increase in the production of ROS. Furthermore, it also increased expressions of caspase-3, caspase-9, caspase-8, DR4, and DR5 genes in A549 cells. In conclusion, α-asarone-induced apoptotic cell death in non-small lung cancer cells (A549) as a result of loss of mitochondrial function, increased ROS production, subsequent activation of an internal and extrinsic caspase pathway, and altered expression of genes controlling apoptosis. As a whole, α<i>-</i>asarone is a plausible therapeutic agent for managing lung cancer. HIGHLIGHTSIsolation of bioactive compound from hydromethanolic leaves extract of <i>Acorus calamus</i> L. by thin layer chromatography.Structural elucidation of the bioactive compound was carried out using different methods like UV analysis, FTIR, NMR, and LC-MS/MS analysis.A plausible mode of action revealed that α-asarone can induce apoptosis in lung cancer cells (A549). Isolation of bioactive compound from hydromethanolic leaves extract of <i>Acorus calamus</i> L. by thin layer chromatography. Structural elucidation of the bioactive compound was carried out using different methods like UV analysis, FTIR, NMR, and LC-MS/MS analysis. A plausible mode of action revealed that α-asarone can induce apoptosis in lung cancer cells (A549). Communicated by Ramaswamy H. Sarma
DOI: 10.15468/dl.ixsd62
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004561-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.23592980.v1
title: Host-guest interaction of tryptophane with acid-functionalized calix[4]pyrrole: a fluorescence-based study

description: Functionalized calix[4]pyrroles are at forefront of host-guest aided molecular sensors. They offer unique platform for flexible functionalization to develop receptors suitable for different applications. In this context, calix[4]pyrrole derivative (TACP) was functionalized with an acidic group to investigate its binding behavior with different amino acids. The acid functionalization facilitated host-guest interactions through hydrogen bonding and increase the solubility of ligand in 90% aqueous media. The results indicated that TACP exhibited significant fluorescence enhancement in the presence of tryptophan while no considerable changes were observed with other amino acids. The other complexation properties such as LOD and LOQ were determined to be 25 µM and 22 µM respectively with 1:1 stoichiometry. In addition, the proposed binding phenomena were further confirmed through computational docking studies and NMR complexation study. Overall, this work highlights the potential of acid functionalization in developing molecular sensors for amino acid detection using calix[4]pyrrole derivatives. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.23559868
title: Exploring binding modes of the selected inhibitors to SND1 by all-atom molecular dynamics simulations

description: Breast cancer is the leading cause of cancer-related deaths in women. Previous studies have indicated that disrupting the interaction between Metadherin (MTDH) and Staphylococcal nuclease domain containing 1 (SND1) can inhibit breast cancer development. Understanding the binding mode of small molecule inhibitors with SND1 is of great significance for designing drugs targeting the MTDH-SND1 complex. In this study, we conducted all-atom molecular dynamics (MD) simulations in solution and performed binding energy calculations to gain insights into the binding mechanism of small molecules to SND1. The binding site of SND1 for small molecules is relatively rigid, and the binding of the small molecule and the mutation of key residues have little effect on the conformation of the binding site. SND1 binds more tightly to C26-A6 than to C26-A2, as C26-A2 undergoes a 180° directional change during the simulation process. The key residue mutations have a direct effect on the position and orientation of small molecule in the binding site. The key residues make primary contributions to the binding energy through van der Waals interaction and nonpolar solvation energy, although the contribution from nonpolar solvation is relatively minor. The key residue mutations also affect the formation of hydrogen bonds and ultimately the stability of the small molecule-SND1 complex. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.23592980
title: Host-guest interaction of tryptophane with acid-functionalized calix[4]pyrrole: a fluorescence-based study

description: Functionalized calix[4]pyrroles are at forefront of host-guest aided molecular sensors. They offer unique platform for flexible functionalization to develop receptors suitable for different applications. In this context, calix[4]pyrrole derivative (TACP) was functionalized with an acidic group to investigate its binding behavior with different amino acids. The acid functionalization facilitated host-guest interactions through hydrogen bonding and increase the solubility of ligand in 90% aqueous media. The results indicated that TACP exhibited significant fluorescence enhancement in the presence of tryptophan while no considerable changes were observed with other amino acids. The other complexation properties such as LOD and LOQ were determined to be 25 µM and 22 µM respectively with 1:1 stoichiometry. In addition, the proposed binding phenomena were further confirmed through computational docking studies and NMR complexation study. Overall, this work highlights the potential of acid functionalization in developing molecular sensors for amino acid detection using calix[4]pyrrole derivatives. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24303242
title: Epigenetic target identification strategy based on multi-feature learning

description: The identification of potential epigenetic targets for a known bioactive compound is essential and promising as more and more epigenetic drugs are used in cancer clinical treatment and the availability of chemogenomic data related to epigenetics increases. In this study, we introduce a novel epigenetic target identification strategy (ETI-Strategy) that integrates a multi-task graph convolutional neural network prior model and a protein-ligand interaction classification discriminating model using large-scale bioactivity data for a panel of 55 epigenetic targets. Our approach utilizes machine learning techniques to achieve an AUC value of 0.934 for the prior model and 0.830 for the discriminating model, outperforming inverse docking in predicting protein-ligand interactions. When comparing with other open-source target identification tools, it was found that only our tool was able to accurately predict all the targets corresponding to each compound. This further demonstrates the ability of our strategy to take full advantage of molecular-level information as well as protein-level information in molecular activity prediction. Our work highlights the contribution of machine learning in the identification of potential epigenetic targets and offers a novel approach for epigenetic drug discovery and development. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24303242.v1
title: Epigenetic target identification strategy based on multi-feature learning

description: The identification of potential epigenetic targets for a known bioactive compound is essential and promising as more and more epigenetic drugs are used in cancer clinical treatment and the availability of chemogenomic data related to epigenetics increases. In this study, we introduce a novel epigenetic target identification strategy (ETI-Strategy) that integrates a multi-task graph convolutional neural network prior model and a protein-ligand interaction classification discriminating model using large-scale bioactivity data for a panel of 55 epigenetic targets. Our approach utilizes machine learning techniques to achieve an AUC value of 0.934 for the prior model and 0.830 for the discriminating model, outperforming inverse docking in predicting protein-ligand interactions. When comparing with other open-source target identification tools, it was found that only our tool was able to accurately predict all the targets corresponding to each compound. This further demonstrates the ability of our strategy to take full advantage of molecular-level information as well as protein-level information in molecular activity prediction. Our work highlights the contribution of machine learning in the identification of potential epigenetic targets and offers a novel approach for epigenetic drug discovery and development. Communicated by Ramaswamy H. Sarma