cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18419/darus-2996/16
title: invlbox_gamma.dat

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DOI: 10.18419/darus-2996/17
title: predict_ST.py

description: :unav
DOI: 10.18419/darus-2996/18
title: raw.tgz

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DOI: 10.18419/darus-2996/19
title: storage.py

description: :unav
DOI: 10.18419/darus-2996/20
title: shukla_enthalpies.dat

description: :unav
DOI: 10.18419/darus-2996/21
title: input_data_for_thermo_models_energies.dat

description: :unav
DOI: 10.18419/darus-2996/22
title: inter_temp_molfrac_soret_temp_1_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/23
title: tdamp_vs_selfdiff_temp_paramset2_temp1_press1.8.dat

description: :unav
DOI: 10.18419/darus-2996/24
title: ST_8000part.dat

description: :unav
DOI: 10.18419/darus-2996/25
title: invlbox_L11_LE1.dat

description: :unav
DOI: 10.18419/darus-2996/26
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/27
title: slurm.py

description: :unav
DOI: 10.18419/darus-2996/28
title: gen_lj_systems.py

description: :unav
DOI: 10.18419/darus-2996/29
title: inter_temp_molfrac_soret_temp_0.85_rho_0.266.dat

description: :unav
DOI: 10.18419/darus-2996/30
title: README.txt

description: :unav
DOI: 10.18419/darus-2996/31
title: inter_temp_molfrac_soret_temp_1_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/32
title: raw.tgz

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DOI: 10.18419/darus-2996/33
title: README.txt

description: :unav
DOI: 10.18419/darus-2996/34
title: settings_vtk.json

description: :unav
DOI: 10.18419/darus-2996/35
title: math.py

description: :unav
DOI: 10.18419/darus-2996/36
title: inter_temp_molfrac_soret_temp_1_press_1.8.dat

description: :unav
DOI: 10.18419/darus-2996/37
title: tdamp_vs_selfdiff_temp_paramset1_temp0.75_press0.09.dat

description: :unav
DOI: 10.18419/darus-2996/38
title: inter_temp_molfrac_soret_temp_1_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/39
title: README.txt

description: :unav
DOI: 10.18419/darus-2996/40
title: units.py

description: :unav
DOI: 10.18419/darus-2996/41
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/42
title: inter_temp_molfrac_soret_temp_1_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/43
title: inter_temp_molfrac_soret_temp_0.75_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/44
title: README.txt

description: :unav
DOI: 10.18419/darus-2996/45
title: files.py

description: :unav
DOI: 10.18419/darus-2996/46
title: README.txt

description: :unav
DOI: 10.18419/darus-2996/47
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/48
title: inter_temp_molfrac_soret_temp_1_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/49
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/50
title: calculate_soret_data_one_simulation.py

description: :unav
DOI: 10.18419/darus-2996/51
title: readme.txt

description: :unav
DOI: 10.18419/darus-2996/52
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/53
title: ST_DT_q_DFick_Gamma.dat

description: :unav
DOI: 10.18419/darus-2996/54
title: tdamp_vs_selfdiff_temp_paramset2_temp0.75_press0.09.dat

description: :unav
DOI: 10.18419/darus-2996/55
title: reith.dat

description: :unav
DOI: 10.18419/darus-2996/56
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/57
title: vtk.py

description: :unav
DOI: 10.18419/darus-2996/58
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/59
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/60
title: inter_temp_molfrac_soret_temp_1_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/61
title: analyze_lj_nemd.py

description: :unav
DOI: 10.18419/darus-2996/62
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/63
title: tdamp_vs_selfdiff_temp_paramset3_temp1_press1.8.dat

description: :unav
DOI: 10.18419/darus-2996/64
title: inter_temp_molfrac_soret_temp_0.75_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/65
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/66
title: tdamp_vs_selfdiff_temp_paramset3_temp0.75_press0.09.dat

description: :unav
DOI: 10.18419/darus-2996/67
title: extra_temp_molfrac_soret_temp_1_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/68
title: README.txt

description: :unav
DOI: 10.18419/darus-2996/69
title: analyze_lj_emd_equil.py

description: :unav
DOI: 10.18419/darus-2996/70
title: inter_temp_molfrac_soret_temp_1_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/71
title: prep_emd_equil.py

description: :unav
DOI: 10.18419/darus-2996/72
title: tdamp_vs_selfdiff_temp_paramset1_temp1_press0.09.dat

description: :unav
DOI: 10.18419/darus-2996/73
title: shukla_energies.dat

description: :unav
DOI: 10.18419/darus-2996/74
title: lammps.py

description: :unav
DOI: 10.18419/darus-2996/75
title: inter_temp_molfrac_soret_temp_1_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/76
title: input_data_for_thermo_models_enthalpies.dat

description: :unav
DOI: 10.18419/darus-2996/77
title: ST_1200part.dat

description: :unav
DOI: 10.18419/darus-2996/78
title: inter_temp_molfrac_soret_temp_0.85_rho_0.81.dat

description: :unav
DOI: 10.18419/darus-2996/79
title: gen_temp_conc_prof.py

description: :unav
DOI: 10.18419/darus-2996/80
title: inter_temp_molfrac_soret_temp_1_press_1.8.dat

description: :unav
DOI: 10.18419/darus-2996/81
title: average_soret_data.py

description: :unav
DOI: 10.18419/darus-2996/82
title: inter_temp_molfrac_soret_temp_1_press_0.09.dat

description: :unav
DOI: 10.18419/darus-2996/83
title: README.md

description: :unav
DOI: 10.18419/darus-2996/84
title: color.py

description: :unav
DOI: 10.18419/darus-2996/85
title: inter_temp_molfrac_soret_temp_1_rho_0.8.dat

description: :unav
DOI: 10.18419/darus-2996/86
title: extra_temp_molfrac_soret_temp_0.85_rho_0.81.dat

description: :unav
DOI: 10.18419/darus-2996/87
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/88
title: prep_nemd.py

description: :unav
DOI: 10.18419/darus-2996/89
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/90
title: tdamp_vs_selfdiff_temp_paramset3_temp1_press0.09.dat

description: :unav
DOI: 10.18419/darus-2996/91
title: inter_temp_molfrac_soret_temp_0.931_rho_0.81.dat

description: :unav
DOI: 10.18419/darus-2996/92
title: ST_10percent_change_enthalpy_L11.dat

description: :unav
DOI: 10.18419/darus-2996/93
title: inter_temp_molfrac_soret_temp_0.85_rho_0.609.dat

description: :unav
DOI: 10.18419/darus-2996/94
title: analyze_lj_nemd_campaign.py

description: :unav
DOI: 10.18419/darus-2996/95
title: raw.tgz

description: :unav
DOI: 10.18419/darus-2996/96
title: create_configs.bash

description: :unav
DOI: 10.18419/darus-2996/97
title: README.txt

description: :unav
DOI: 10.18419/darus-2996/98
title: README.txt

description: :unav
DOI: 10.18419/darus-2996/100
title: nemd_german.mp4

description: :unav
DOI: 10.18419/darus-2996/99
title: nemd_english.mp4

description: :unav
DOI: 10.5281/zenodo.7024864
title: Underground trees are under threat in the Afrotropics

description: GBIF records of geoxyles listed by Maurin et al. (2014) in the Zambezi region
DOI: 10.5281/zenodo.7024863
title: Underground trees are under threat in the Afrotropics

description: GBIF records of geoxyles listed by Maurin et al. (2014) in the Zambezi region
DOI: 10.6084/m9.figshare.20654136
title: Data set used in "Full-waveform inversion based on generalized Renyi entropy using patched Greens function techniques"

description: Data set used in "Full-waveform inversion based on generalized Renyi entropy using patched Greens function techniques"
DOI: 10.6084/m9.figshare.20654136.v1
title: Data set used in "Full-waveform inversion based on generalized Renyi entropy using patched Greens function techniques"

description: Data set used in "Full-waveform inversion based on generalized Renyi entropy using patched Greens function techniques"
DOI: 10.6084/m9.figshare.14179003
title: Identification of novel allosteric binding sites and multi-targeted allosteric inhibitors of receptor and non-receptor tyrosine kinases using a computational approach

description: EGFR1, VEGFR2, Bcr-Abl and Src kinases are key drug targets in non-small cell lung cancer (NSCLC), bladder cancer, pancreatic cancer, CML, ALL, colorectal cancer, etc. The available drugs targeting these kinases have limited therapeutic efficacy due to novel mutations resulting in drug resistance and toxicity, as they target ATP binding site. Allosteric drugs have shown promising results in overcoming drug resistance, but the discovery of allosteric drugs is challenging. The allosteric binding pockets are difficult to predict, as they are generally associated with high energy conformations and regulate protein function in yet unknown mechanisms. In addition, the discovery of drugs using conventional methods takes long time and goes through several challenges, putting the lives of many cancer patients at risk. Therefore, the aim of the present work was to apply the most successful, drug repurposing approach in combination with computational methods to identify kinase inhibitors targeting novel allosteric sites on protein structure and assess their potential multi-kinase binding affinity. Multiple crystal structures belonging to EGFR1, VEGFR2, Bcr-Abl and Src tyrosine kinases were selected, including mutated, inhibitor bound and allosteric conformations to identify potential leads, close to physiological conditions. Interestingly the potential inhibitors identified were peptides. The drugs identified in this study could be used in therapy as a single multi-kinase inhibitor or in a combination of single kinase inhibitors after experimental validation. In addition, we have also identified new hot spots that are likely to be druggable allosteric sites for drug discovery of kinase-specific drugs in the future. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.14179003.v1
title: Identification of novel allosteric binding sites and multi-targeted allosteric inhibitors of receptor and non-receptor tyrosine kinases using a computational approach

description: EGFR1, VEGFR2, Bcr-Abl and Src kinases are key drug targets in non-small cell lung cancer (NSCLC), bladder cancer, pancreatic cancer, CML, ALL, colorectal cancer, etc. The available drugs targeting these kinases have limited therapeutic efficacy due to novel mutations resulting in drug resistance and toxicity, as they target ATP binding site. Allosteric drugs have shown promising results in overcoming drug resistance, but the discovery of allosteric drugs is challenging. The allosteric binding pockets are difficult to predict, as they are generally associated with high energy conformations and regulate protein function in yet unknown mechanisms. In addition, the discovery of drugs using conventional methods takes long time and goes through several challenges, putting the lives of many cancer patients at risk. Therefore, the aim of the present work was to apply the most successful, drug repurposing approach in combination with computational methods to identify kinase inhibitors targeting novel allosteric sites on protein structure and assess their potential multi-kinase binding affinity. Multiple crystal structures belonging to EGFR1, VEGFR2, Bcr-Abl and Src tyrosine kinases were selected, including mutated, inhibitor bound and allosteric conformations to identify potential leads, close to physiological conditions. Interestingly the potential inhibitors identified were peptides. The drugs identified in this study could be used in therapy as a single multi-kinase inhibitor or in a combination of single kinase inhibitors after experimental validation. In addition, we have also identified new hot spots that are likely to be druggable allosteric sites for drug discovery of kinase-specific drugs in the future. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.14095676
title: Investigation of the inhibitory activity of some dietary bioactive flavonoids against SARS-CoV-2 using molecular dynamics simulations and MM-PBSA calculations

description: Eventhough the development of vaccine against COVID-19 pandemic is progressing in different part of the world a well-defined treatment plan is not yet developed. Therefore, we investigate the inhibitory activity of a group of dietary bioactive flavonoids against SARS-CoV-2 main protease (M<sup>pro</sup>), which are identified as one of the potential targets in the drug discovery process of COVID-19. After the initial virtual screening of a number of bioactive flavonoids, the binding affinity of three compounds - Naringin, Naringenin and Amentoflavone - at the active site of M<sup>pro</sup> was investigated through MD Simulations, MM-PBSA and DFT Binding Energy calculations. From the MD trajectory analysis, Amentoflavone and Naringin showed consistent protein-ligand interactions with the aminoacid residues of the active site domains of M<sup>pro</sup>. The excellent inhibitory activity of Amentoflavone and Naringin was established from its MM-PBSA binding energy values of −190.50 and −129.87 kJ/mol respectively. The MET165 residue of M<sup>pro</sup> is identified as one of the key residue which contributed significantly to MM-PBSA binding energy through hydrophobic interactions. Furthermore, the DFT binding energy values of Amentoflavone (-182.92 kJ/mol) and Naringin (-160.67 kJ/mol) in active site molecular clusters with hydrogen bonds confirmed their potential inhibitory activity. These compounds are of high interest because of their wide availability, low cost, no side effects, and long history of use. We can prevent the severity of this disease for home care patients using these effective dietary supplements. We are hopeful that our results have implications for the development of prophylaxis of COVID-19. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.14095676.v1
title: Investigation of the inhibitory activity of some dietary bioactive flavonoids against SARS-CoV-2 using molecular dynamics simulations and MM-PBSA calculations

description: Eventhough the development of vaccine against COVID-19 pandemic is progressing in different part of the world a well-defined treatment plan is not yet developed. Therefore, we investigate the inhibitory activity of a group of dietary bioactive flavonoids against SARS-CoV-2 main protease (M<sup>pro</sup>), which are identified as one of the potential targets in the drug discovery process of COVID-19. After the initial virtual screening of a number of bioactive flavonoids, the binding affinity of three compounds - Naringin, Naringenin and Amentoflavone - at the active site of M<sup>pro</sup> was investigated through MD Simulations, MM-PBSA and DFT Binding Energy calculations. From the MD trajectory analysis, Amentoflavone and Naringin showed consistent protein-ligand interactions with the aminoacid residues of the active site domains of M<sup>pro</sup>. The excellent inhibitory activity of Amentoflavone and Naringin was established from its MM-PBSA binding energy values of −190.50 and −129.87 kJ/mol respectively. The MET165 residue of M<sup>pro</sup> is identified as one of the key residue which contributed significantly to MM-PBSA binding energy through hydrophobic interactions. Furthermore, the DFT binding energy values of Amentoflavone (-182.92 kJ/mol) and Naringin (-160.67 kJ/mol) in active site molecular clusters with hydrogen bonds confirmed their potential inhibitory activity. These compounds are of high interest because of their wide availability, low cost, no side effects, and long history of use. We can prevent the severity of this disease for home care patients using these effective dietary supplements. We are hopeful that our results have implications for the development of prophylaxis of COVID-19. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.14406322
title: Inhibition of SARS-CoV-2 main protease: a repurposing study that targets the dimer interface of the protein

description: Coronavirus disease-2019 (COVID-19) was firstly reported in Wuhan, China, towards the end of 2019, and emerged as a pandemic. The spread and lethality rates of the COVID-19 have ignited studies that focus on the development of therapeutics for either treatment or prophylaxis purposes. In parallel, drug repurposing studies have also come into prominence. Herein, we aimed at having a holistic understanding of conformational and dynamical changes induced by an experimentally characterized inhibitor on main protease (M<sup>pro</sup>) which would enable the discovery of novel inhibitors. To this end, we performed molecular dynamics simulations using crystal structures of <i>apo</i> and <i>α</i>-ketoamide 13b-bound M<sup>pro</sup> homodimer. Analysis of trajectories pertaining to <i>apo</i> M<sup>pro</sup> revealed a new target site, which is located at the homodimer interface, next to the catalytic dyad. Thereafter, we performed ensemble-based virtual screening by exploiting the ZINC and DrugBank databases and identified three candidate molecules, namely eluxadoline, diosmin, and ZINC02948810 that could invoke local and global conformational rearrangements which were also elicited by <i>α</i>-ketoamide 13b on the catalytic dyad of M<sup>pro.</sup> Furthermore, ZINC23881687 stably interacted with catalytically important residues Glu166 and Ser1 and the target site throughout the simulation. However, it gave positive binding energy, presumably, due to displaying higher flexibility that might dominate the entropic term, which is not included in the MM-PBSA method. Finally, ZINC20425029, whose mode of action was different, modulated dynamical properties of catalytically important residue, Ala285. As such, this study presents valuable findings that might be used in the development of novel therapeutics against M<sup>pro.</sup> Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.14406322.v1
title: Inhibition of SARS-CoV-2 main protease: a repurposing study that targets the dimer interface of the protein

description: Coronavirus disease-2019 (COVID-19) was firstly reported in Wuhan, China, towards the end of 2019, and emerged as a pandemic. The spread and lethality rates of the COVID-19 have ignited studies that focus on the development of therapeutics for either treatment or prophylaxis purposes. In parallel, drug repurposing studies have also come into prominence. Herein, we aimed at having a holistic understanding of conformational and dynamical changes induced by an experimentally characterized inhibitor on main protease (M<sup>pro</sup>) which would enable the discovery of novel inhibitors. To this end, we performed molecular dynamics simulations using crystal structures of <i>apo</i> and <i>α</i>-ketoamide 13b-bound M<sup>pro</sup> homodimer. Analysis of trajectories pertaining to <i>apo</i> M<sup>pro</sup> revealed a new target site, which is located at the homodimer interface, next to the catalytic dyad. Thereafter, we performed ensemble-based virtual screening by exploiting the ZINC and DrugBank databases and identified three candidate molecules, namely eluxadoline, diosmin, and ZINC02948810 that could invoke local and global conformational rearrangements which were also elicited by <i>α</i>-ketoamide 13b on the catalytic dyad of M<sup>pro.</sup> Furthermore, ZINC23881687 stably interacted with catalytically important residues Glu166 and Ser1 and the target site throughout the simulation. However, it gave positive binding energy, presumably, due to displaying higher flexibility that might dominate the entropic term, which is not included in the MM-PBSA method. Finally, ZINC20425029, whose mode of action was different, modulated dynamical properties of catalytically important residue, Ala285. As such, this study presents valuable findings that might be used in the development of novel therapeutics against M<sup>pro.</sup> Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.14710027
title: Molecular modeling of potent novel sulfonamide derivatives as non-peptide small molecule anti-COVID 19 agents

description: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent for the COVID-19. The Sulfonamides groups have been widely introduced in several drugs, especially for their antibacterial activities and generally prescribed for respiratory infections. On the other hand, imidazole groups have the multipotency to act as drugs, including antiviral activity. We have used a structure-based drug design approach to design some imidazole derivatives of sulfonamide, which can efficiently bind to the active site of SARS-CoV-2 main protease and thus may have the potential to inhibit its proteases activity. We conducted molecular docking and molecular dynamics simulation to observe the stability and flexibility of inhibitor complexes. We have checked ADMET (absorption, distribution, metabolism, excretion and toxicity) and drug-likeness rules to scrutinize toxicity and then designed the most potent compound based on computational chemistry. Our small predicted molecule non-peptide protease inhibitors could provide a useful model in the further search for novel compounds since it has many advantages over peptidic drugs, like lower side effects, toxicity and less chance of drug resistance. Further, we confirmed the stability of our inhibitor-complex and interaction profile through the Molecular dynamics simulation study. Our small predicted molecule Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.14710027.v1
title: Molecular modeling of potent novel sulfonamide derivatives as non-peptide small molecule anti-COVID 19 agents

description: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent for the COVID-19. The Sulfonamides groups have been widely introduced in several drugs, especially for their antibacterial activities and generally prescribed for respiratory infections. On the other hand, imidazole groups have the multipotency to act as drugs, including antiviral activity. We have used a structure-based drug design approach to design some imidazole derivatives of sulfonamide, which can efficiently bind to the active site of SARS-CoV-2 main protease and thus may have the potential to inhibit its proteases activity. We conducted molecular docking and molecular dynamics simulation to observe the stability and flexibility of inhibitor complexes. We have checked ADMET (absorption, distribution, metabolism, excretion and toxicity) and drug-likeness rules to scrutinize toxicity and then designed the most potent compound based on computational chemistry. Our small predicted molecule non-peptide protease inhibitors could provide a useful model in the further search for novel compounds since it has many advantages over peptidic drugs, like lower side effects, toxicity and less chance of drug resistance. Further, we confirmed the stability of our inhibitor-complex and interaction profile through the Molecular dynamics simulation study. Our small predicted molecule Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.14135004
title: Spectroscopic investigations, concentration dependent SERS, and molecular docking studies of a hydroxybenzylidene derivative

description: Spectroscopic analysis, density functional theory (DFT) studies and surface enhanced Raman scattering (SERS) of (<i>E</i>)-<i>N</i>’-(5-chloro-2-hydroxybenzylidene)-4-trifluoromethyl) benzohydrazide (CHTB) have been studied on different silver colloids in order to know the particular chemical species responsible for the spectra. Very significant shifts are observed for Raman and SERS wavenumbers. Observed changes in the υ-ring modes may be due to surface interaction of the π-electrons and the presence of this suggested that RingII is more tilted in both cases than RingI and the molecule assumes a tilted orientation for the concentration 10<sup>−3</sup> M. Orientation changes are seen in concentration dependent SERS spectra. The molecular electrostatic potential has also been constructed to determine the electron rich and poor site of CHTB. The molecular docking studies indicate that the binding affinity and hydrogen bond interactions with the receptors may be supporting evidence for further studies in designing other pharmaceutical applications of CHTB. Communicated by Ramaswamy H. Sarma