cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10090638
title: Fuentes para la evaluación y resultados de experimentos con los software de indización automática SISA, KEA y MAUI

description: Para la evaluación de los tres software de indización automática se utilizó un corpus de 230 artículos científicos publicados en la Revista Española de Documentación Científica, de los cuales 30 se utilizaron para tareas formativas y no formaban parte del conjunto de pruebas de evaluación. Los artículos fueron escritos en español e indizados por indicadores humanos utilizando un vocabulario controlado en la base de datos InDICES, también perteneciente al CSIC. La indización humana de estos constituye la referencia (contra la cual se evalúa el resultado de los sistemas de indización automáticos, comparando conjuntos de términos usando métricas de evaluación de precisión, recuperación, medida F y consistencia.
DOI: 10.5281/zenodo.10090537
title: Projekt938_scRNAseq_FGK45_Heart_blood_spleen_NextSeq_demultiplex_150_AAC55NMHV_3
DOI: 10.5281/zenodo.10090590
title: Projekt966_scRNAseq_PBMC_Causa_Myocarditis_3
DOI: 10.5281/zenodo.10090536
title: Projekt938_scRNAseq_FGK45_Heart_blood_spleen_NextSeq_demultiplex_150_AAC55NMHV_3
DOI: 10.5281/zenodo.10090497
title: Projekt938_scRNAseq_TSd5_d7_d14_NextSeq_demultiplex_143_AAC2JFMHV_3
DOI: 10.5281/zenodo.10090496
title: Projekt938_scRNAseq_TSd5_d7_d14_NextSeq_demultiplex_143_AAC2JFMHV_3
DOI: 10.5281/zenodo.10090591
title: Projekt966_scRNAseq_PBMC_Causa_Myocarditis_3
DOI: 10.6084/m9.figshare.21716213
title: In vitro and computational studies of the β-lactamase inhibition and β-lactam potentiating properties of plant secondary metabolites

description: β-lactam resistance in bacteria is primarily mediated through the production of β-lactamases. Among the several strategies explored to mitigate the issue of β-lactam resistance, the use of plant secondary metabolites in combination with existing β-lactams seem promising. The present study aims to identify possible β-lactam potentiating plant secondary metabolites following <i>in vitro</i> and <i>in silico</i> approaches. Among 180 extracts from selected 30 medicinal plants, acetone extract of <i>Ficus religiosa</i> (FRAE) bark recorded the least IC<sub>50</sub> value of 3.9 mg/ml. Under <i>in vitro</i> conditions, FRAE potentiated the activity of ampicillin, which was evidenced by the significant reduction in IC<sub>50</sub> values of ampicillin against multidrug resistant bacteria. Metabolic profiling following HR-LCMS analysis revealed the presence of diverse metabolites viz. flavonoids, alkaloids, terpenoids, etc. in FRAE. Further, ensemble docking of the FRAE metabolites against four Class A β-lactamase (SHV1, TEM1, KPC2 and CTX-M-27) showed quercetin, taxifolin, myricetin, luteolin, and miquelianin as potential inhibitors with the least average binding energy. In molecular dynamic simulation studies, myricetin formed the most stable complex with SHV1 and KPC-2 while miquelianin with TEM1 and CTX-M-27. Further, all five metabolites interacted with amino acid residue Glu166 in Ω loop of β-lactamase, interfering with the deacylation step, thereby disrupting the enzyme activity. The pharmacokinetics and ADMET profile indicate their drug-likeness and non-toxic nature, making them ideal β-lactam potentiators. This study highlights the ability of metabolites present in FRAE to act as β-lactamase inhibitors. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21716213.v1
title: In vitro and computational studies of the β-lactamase inhibition and β-lactam potentiating properties of plant secondary metabolites

description: β-lactam resistance in bacteria is primarily mediated through the production of β-lactamases. Among the several strategies explored to mitigate the issue of β-lactam resistance, the use of plant secondary metabolites in combination with existing β-lactams seem promising. The present study aims to identify possible β-lactam potentiating plant secondary metabolites following <i>in vitro</i> and <i>in silico</i> approaches. Among 180 extracts from selected 30 medicinal plants, acetone extract of <i>Ficus religiosa</i> (FRAE) bark recorded the least IC<sub>50</sub> value of 3.9 mg/ml. Under <i>in vitro</i> conditions, FRAE potentiated the activity of ampicillin, which was evidenced by the significant reduction in IC<sub>50</sub> values of ampicillin against multidrug resistant bacteria. Metabolic profiling following HR-LCMS analysis revealed the presence of diverse metabolites viz. flavonoids, alkaloids, terpenoids, etc. in FRAE. Further, ensemble docking of the FRAE metabolites against four Class A β-lactamase (SHV1, TEM1, KPC2 and CTX-M-27) showed quercetin, taxifolin, myricetin, luteolin, and miquelianin as potential inhibitors with the least average binding energy. In molecular dynamic simulation studies, myricetin formed the most stable complex with SHV1 and KPC-2 while miquelianin with TEM1 and CTX-M-27. Further, all five metabolites interacted with amino acid residue Glu166 in Ω loop of β-lactamase, interfering with the deacylation step, thereby disrupting the enzyme activity. The pharmacokinetics and ADMET profile indicate their drug-likeness and non-toxic nature, making them ideal β-lactam potentiators. This study highlights the ability of metabolites present in FRAE to act as β-lactamase inhibitors. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21781386
title: SARS-CoV-2 variants infectivity prediction and therapeutic peptide design using computational approaches

description: The outbreak of severe acute respiratory coronavirus 2 (SARS-CoV-2) has created a public health emergency globally. SARS-CoV-2 enters the human cell through the binding of the spike protein to human angiotensin converting enzyme 2 (ACE2) receptor. Significant changes have been reported in the mutational landscape of SARS-CoV-2 in the receptor binding domain (RBD) of S protein, subsequent to evolution of the pandemic. The present study examines the correlation between the binding affinity of mutated S-proteins and the rate of viral infectivity. For this, the binding affinity of SARS-CoV and variants of SARS-CoV-2 towards ACE2 was computationally determined. Subsequently, the RBD mutations were classified on the basis of the number of strains identified with respect to each mutation and the resulting variation in the binding affinity was computationally examined. The molecular docking studies indicated a significant correlation between the Z-Rank score of mutated S proteins and the rate of infectivity, suitable for predicting SARS-CoV-2 infectivity. Accordingly, a 30-mer peptide was designed and the inhibitory properties were computationally analyzed. Single amino acid-wise mutation was performed subsequently to identify the peptide with the highest binding affinity. Molecular dynamics and free energy calculations were then performed to examine the stability of the peptide-protein complexes. Additionally, selected peptides were synthesized and screened using a colorimetric assay. Together, this study developed a model to predict the rate of infectivity of SARS-CoV-2 variants and propose a potential peptide that can be used as an inhibitor for the viral entry to human. Communicated by Ramaswamy H. Sarma.
DOI: 10.6084/m9.figshare.21781386.v1
title: SARS-CoV-2 variants infectivity prediction and therapeutic peptide design using computational approaches

description: The outbreak of severe acute respiratory coronavirus 2 (SARS-CoV-2) has created a public health emergency globally. SARS-CoV-2 enters the human cell through the binding of the spike protein to human angiotensin converting enzyme 2 (ACE2) receptor. Significant changes have been reported in the mutational landscape of SARS-CoV-2 in the receptor binding domain (RBD) of S protein, subsequent to evolution of the pandemic. The present study examines the correlation between the binding affinity of mutated S-proteins and the rate of viral infectivity. For this, the binding affinity of SARS-CoV and variants of SARS-CoV-2 towards ACE2 was computationally determined. Subsequently, the RBD mutations were classified on the basis of the number of strains identified with respect to each mutation and the resulting variation in the binding affinity was computationally examined. The molecular docking studies indicated a significant correlation between the Z-Rank score of mutated S proteins and the rate of infectivity, suitable for predicting SARS-CoV-2 infectivity. Accordingly, a 30-mer peptide was designed and the inhibitory properties were computationally analyzed. Single amino acid-wise mutation was performed subsequently to identify the peptide with the highest binding affinity. Molecular dynamics and free energy calculations were then performed to examine the stability of the peptide-protein complexes. Additionally, selected peptides were synthesized and screened using a colorimetric assay. Together, this study developed a model to predict the rate of infectivity of SARS-CoV-2 variants and propose a potential peptide that can be used as an inhibitor for the viral entry to human. Communicated by Ramaswamy H. Sarma.
DOI: 10.6084/m9.figshare.21789149
title: Design, synthesis, characterizing and DFT calculations of a binary CT complex co-crystal of bioactive moieties in different polar solvents to investigate its pharmacological activity

description: Imidazole (IM) and salicylic acid (SA) have a significant class among the medical compound. These are widely used as topical drugs like antifungal, antibacterial, anticancer, immunosuppressive agent, etc. These two bioactive organic moieties are combined by a weak hydrogen bond formed by hydrogen transfer. The charge transfer (CT) complex of acceptor (SA) and donor (IM), has been synthesized at room temperature in methanol and confirmed by signal-crystal XRD, conductance and UV–visible spectroscopy. The X-ray crystallography provides the original structural information of CT complex and displays the existence of N<sup>+</sup>—H––O<sup>–</sup> bond between IM and SA. The physical properties such as (<i>E<sub>CT</sub></i>), (<i>R<sub>N</sub></i>), (<i>I<sub>D</sub></i>), (<i>f</i>), (<i>D</i>) and (Δ G<sup>0</sup>) along with molar extinction coefficient (<i>ε<sub>CT</sub></i>) and formation constant (<i>K<sub>CT</sub></i>) were estimated through UV–visible spectroscopy. Job’s method and Benesi-Hildebrand equation suggested 1:1 stoichiometry of ([IM]<sup>+</sup>[SA]<sup>−</sup>). The results indicate a complete transfer of hydrogen atom and CT complex formation with 1:1 molar ratio of IM and SA. Antimicrobial activity was veiled against different bacteria like <i>Escherichia coli, Bacillus subtilis</i> and <i>Staphylococcus aureus</i>; and different fungi as <i>Fusarium oxysporum, Candida albicans</i> and <i>Aspergillus niger</i> by disc diffusion method. CT complex was also tested for cytotoxic activity against lung cancer cell lines in comparison to breast cancer cell lines. Molecular docking provides the information of binding of [(IM)<sup>+</sup>(SA)<sup>−</sup>] with the cancer marker (1M17), which has substantial application for drug designing. The investigational studies were supplemented through time-dependent density functional theory (TD-DFT) using basis set B3LYP/6-311G**. Through DFT calculations, HOMO→LUMO electronic energy gap (ΔE) was obtained. A new organic charge transfer complex co-crystal has been prepared, characterized and explored for, Antioxident, Anticancer, antibacterial and antifungal activities. The experimental results are supported by theoretical analysis. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21789149.v1
title: Design, synthesis, characterizing and DFT calculations of a binary CT complex co-crystal of bioactive moieties in different polar solvents to investigate its pharmacological activity

description: Imidazole (IM) and salicylic acid (SA) have a significant class among the medical compound. These are widely used as topical drugs like antifungal, antibacterial, anticancer, immunosuppressive agent, etc. These two bioactive organic moieties are combined by a weak hydrogen bond formed by hydrogen transfer. The charge transfer (CT) complex of acceptor (SA) and donor (IM), has been synthesized at room temperature in methanol and confirmed by signal-crystal XRD, conductance and UV–visible spectroscopy. The X-ray crystallography provides the original structural information of CT complex and displays the existence of N<sup>+</sup>—H––O<sup>–</sup> bond between IM and SA. The physical properties such as (<i>E<sub>CT</sub></i>), (<i>R<sub>N</sub></i>), (<i>I<sub>D</sub></i>), (<i>f</i>), (<i>D</i>) and (Δ G<sup>0</sup>) along with molar extinction coefficient (<i>ε<sub>CT</sub></i>) and formation constant (<i>K<sub>CT</sub></i>) were estimated through UV–visible spectroscopy. Job’s method and Benesi-Hildebrand equation suggested 1:1 stoichiometry of ([IM]<sup>+</sup>[SA]<sup>−</sup>). The results indicate a complete transfer of hydrogen atom and CT complex formation with 1:1 molar ratio of IM and SA. Antimicrobial activity was veiled against different bacteria like <i>Escherichia coli, Bacillus subtilis</i> and <i>Staphylococcus aureus</i>; and different fungi as <i>Fusarium oxysporum, Candida albicans</i> and <i>Aspergillus niger</i> by disc diffusion method. CT complex was also tested for cytotoxic activity against lung cancer cell lines in comparison to breast cancer cell lines. Molecular docking provides the information of binding of [(IM)<sup>+</sup>(SA)<sup>−</sup>] with the cancer marker (1M17), which has substantial application for drug designing. The investigational studies were supplemented through time-dependent density functional theory (TD-DFT) using basis set B3LYP/6-311G**. Through DFT calculations, HOMO→LUMO electronic energy gap (ΔE) was obtained. A new organic charge transfer complex co-crystal has been prepared, characterized and explored for, Antioxident, Anticancer, antibacterial and antifungal activities. The experimental results are supported by theoretical analysis. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21716212
title: <i>In silico</i> identification and characterization of potential druggable targets among hypothetical proteins of <i>Leptospira interrogans</i> serovar Copenhageni: a comprehensive bioinformatics approach

description: Leptospirosis is one of the neglected zoonosis, affecting human and animal populations worldwide. Reliable effective therapeutics and concerns to look for more research into the molecular analysis of its genome is therefore needed. In the genomic pool of the <i>Leptospira interrogans</i> many hypothetical proteins are still uncharacterized. In the current research, we performed extensive <i>in silico</i> analysis to prioritize the potential hypothetical proteins of <i>L. interrogans</i> serovar Copenhageni via stepwise reducing the available hypothetical proteins (Total 3606) of the assembly to only 15, based on non-homologous to homosapien, essential, functional, virulent, cellular localization. Out of them, only two proteins WP_000898918.1 (Hypothetical Protein 1) & WP_001014594.1 (Hypothetical Protein 2) were found druggable and involved in protein-protein interaction network. The 3 D structures of these two target proteins were predicted via ab initio homology modeling followed by structures refinement and validation, as no structures were available till date. The analysis also revealed that the functional domains, families and protein-protein interacting partners identified in both proteins are crucial for the survival of the bacteria. The binding cavities were predicted for both the proteins through blind and specific protein-ligand docking with their respective ligands and inhibitors and were found to be in accordance with the druggable sites predicted by DoGSiteScorer. The docking interactions were found within the active functional domains for both the proteins while for Hypothetical Protein 2, the same residues were involved in interactions with Cytidine-5'-triphosphate in blind and specific docking. Furthermore, the simulations of molecular dynamics and free binding energy revealed the stable substrate binding and efficient binding energies, and were in accordance to our docking results. The work predicted two unique hypothetical proteins of <i>L. interrogans</i> as a potential druggable targets for designing of inhibitors for them. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.22883859
title: Computational identification of a multi-peptide vaccine candidate in E2 glycoprotein against diverse Hepatitis C virus genotypes

description: Hepatitis C Virus (HCV) is estimated to affect nearly 180 million people worldwide, culminating in ∼0.7 million yearly casualties. However, a safe vaccine against HCV is not yet available. This study endeavored to identify a multi-genotypic, multi-epitopic, safe, and globally competent HCV vaccine candidate. We employed a consensus epitope prediction strategy to identify multi-epitopic peptides in all known envelope glycoprotein (E2) sequences, belonging to diverse HCV genotypes. The obtained peptides were screened for toxicity, allergenicity, autoimmunity and antigenicity, resulting in two favorable peptides viz., P2 (VYCFTPSPVVVG) and P3 (YRLWHYPCTV). Evolutionary conservation analysis indicated that P2 and P3 are highly conserved, supporting their use as part of a designed multi-genotypic vaccine. Population coverage analysis revealed that P2 and P3 are likely to be presented by &gt;89% Human Leukocyte Antigen (HLA) molecules from six geographical regions. Indeed, molecular docking predicted the physical binding of P2 and P3 to various representative HLAs. We designed a vaccine construct using these peptides and assessed its binding to toll-like receptor 4 (TLR-4) by molecular docking and simulation. Subsequent analysis by energy-based and machine learning tools predicted high binding affinity and pinpointed the key binding residues (i.e. hotspots) in P2 and P3. Also, a favorable immunogenic profile of the construct was predicted by immune simulations. We encourage the scientific community to validate our vaccine construct <i>in vitro</i> and <i>in vivo</i>. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.22883859.v1
title: Computational identification of a multi-peptide vaccine candidate in E2 glycoprotein against diverse Hepatitis C virus genotypes

description: Hepatitis C Virus (HCV) is estimated to affect nearly 180 million people worldwide, culminating in ∼0.7 million yearly casualties. However, a safe vaccine against HCV is not yet available. This study endeavored to identify a multi-genotypic, multi-epitopic, safe, and globally competent HCV vaccine candidate. We employed a consensus epitope prediction strategy to identify multi-epitopic peptides in all known envelope glycoprotein (E2) sequences, belonging to diverse HCV genotypes. The obtained peptides were screened for toxicity, allergenicity, autoimmunity and antigenicity, resulting in two favorable peptides viz., P2 (VYCFTPSPVVVG) and P3 (YRLWHYPCTV). Evolutionary conservation analysis indicated that P2 and P3 are highly conserved, supporting their use as part of a designed multi-genotypic vaccine. Population coverage analysis revealed that P2 and P3 are likely to be presented by &gt;89% Human Leukocyte Antigen (HLA) molecules from six geographical regions. Indeed, molecular docking predicted the physical binding of P2 and P3 to various representative HLAs. We designed a vaccine construct using these peptides and assessed its binding to toll-like receptor 4 (TLR-4) by molecular docking and simulation. Subsequent analysis by energy-based and machine learning tools predicted high binding affinity and pinpointed the key binding residues (i.e. hotspots) in P2 and P3. Also, a favorable immunogenic profile of the construct was predicted by immune simulations. We encourage the scientific community to validate our vaccine construct <i>in vitro</i> and <i>in vivo</i>. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.21716212.v1
title: <i>In silico</i> identification and characterization of potential druggable targets among hypothetical proteins of <i>Leptospira interrogans</i> serovar Copenhageni: a comprehensive bioinformatics approach

description: Leptospirosis is one of the neglected zoonosis, affecting human and animal populations worldwide. Reliable effective therapeutics and concerns to look for more research into the molecular analysis of its genome is therefore needed. In the genomic pool of the <i>Leptospira interrogans</i> many hypothetical proteins are still uncharacterized. In the current research, we performed extensive <i>in silico</i> analysis to prioritize the potential hypothetical proteins of <i>L. interrogans</i> serovar Copenhageni via stepwise reducing the available hypothetical proteins (Total 3606) of the assembly to only 15, based on non-homologous to homosapien, essential, functional, virulent, cellular localization. Out of them, only two proteins WP_000898918.1 (Hypothetical Protein 1) & WP_001014594.1 (Hypothetical Protein 2) were found druggable and involved in protein-protein interaction network. The 3 D structures of these two target proteins were predicted via ab initio homology modeling followed by structures refinement and validation, as no structures were available till date. The analysis also revealed that the functional domains, families and protein-protein interacting partners identified in both proteins are crucial for the survival of the bacteria. The binding cavities were predicted for both the proteins through blind and specific protein-ligand docking with their respective ligands and inhibitors and were found to be in accordance with the druggable sites predicted by DoGSiteScorer. The docking interactions were found within the active functional domains for both the proteins while for Hypothetical Protein 2, the same residues were involved in interactions with Cytidine-5'-triphosphate in blind and specific docking. Furthermore, the simulations of molecular dynamics and free binding energy revealed the stable substrate binding and efficient binding energies, and were in accordance to our docking results. The work predicted two unique hypothetical proteins of <i>L. interrogans</i> as a potential druggable targets for designing of inhibitors for them. Communicated by Ramaswamy H. Sarma