cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24278140
title: Structure-guided computational insecticide discovery targeting <i>β</i>-N-acetyl-D-hexosaminidase of <i>Ostrinia furnacalis</i>

description: <i>Ostrinia furnacalis</i> is a species of moth in the Crambidae family that is harmful to maize and other corn crops in Southeast Asia and the Western Pacific regions. <i>Ostrinia furnacalis</i> causes devastating losses to economically important corn fields. The β-N-acetyl-D-hexosaminidase is an essential enzyme in <i>O. furnacalis</i> and its substrate binding +1 active site is different from that of the plants and humans β-N-acetyl-D-hexosaminidases. To develop environment-friendly insecticides against OfHex1, we conducted structure-guided computational insecticide discovery to identify potential inhibitors that can bind the active site and inhibit the substrate binding and activity of the enzyme. We adopted a three-pronged strategy to conduct virtual screening using Glide and virtual screening workflow (VSW) in Schrödinger Suite-2022-3, against crystal structures of OfHex1 (PDB Id:3NSN), its homologue in humans (PDB Id: 1NP0) and Alphafold model of β-N-acetyl-D-hexosaminidase from <i>Trichogramma pretiosum</i>, an egg parasitoid that protects the crops from <i>O. furnacalis.</i> A library of 20,313 commercially available and “insecticide-like” compounds was extracted from published literature. LigPrep enabled 44,943 ready-to-dock conformers generation. Glide docking revealed 18 OfHex1-specific hits that were absent in human and <i>T. pretiosum</i> screens. Reference docking was conducted using inhibitors/natural ligands in the crystal structures and hits with better docking scores than the reference were selected for MD simulations using Desmond to understand the stability of hit-target interactions. We noted five compounds that bound to OfHex1 TMX active-site based on their docking scores, consistent binding as noted by MD simulations and their insecticide/pesticide likeliness as noted by the Comprehensive Pesticide Likeness Analysis. Communicated by Ramaswamy H. Sarma
DOI: 10.15468/dl.xv6dby
title: Occurrence Download

description: A dataset containing 165 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pterygopleurum neurophyllum (Maxim.) Kitag."
 ]
}

 The dataset includes 165 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014300-241107131044228/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.24278140.v2
title: Structure-guided computational insecticide discovery targeting <i>β</i>-N-acetyl-D-hexosaminidase of <i>Ostrinia furnacalis</i>

description: <i>Ostrinia furnacalis</i> is a species of moth in the Crambidae family that is harmful to maize and other corn crops in Southeast Asia and the Western Pacific regions. <i>Ostrinia furnacalis</i> causes devastating losses to economically important corn fields. The β-N-acetyl-D-hexosaminidase is an essential enzyme in <i>O. furnacalis</i> and its substrate binding +1 active site is different from that of the plants and humans β-N-acetyl-D-hexosaminidases. To develop environment-friendly insecticides against OfHex1, we conducted structure-guided computational insecticide discovery to identify potential inhibitors that can bind the active site and inhibit the substrate binding and activity of the enzyme. We adopted a three-pronged strategy to conduct virtual screening using Glide and virtual screening workflow (VSW) in Schrödinger Suite-2022-3, against crystal structures of OfHex1 (PDB Id:3NSN), its homologue in humans (PDB Id: 1NP0) and Alphafold model of β-N-acetyl-D-hexosaminidase from <i>Trichogramma pretiosum</i>, an egg parasitoid that protects the crops from <i>O. furnacalis.</i> A library of 20,313 commercially available and “insecticide-like” compounds was extracted from published literature. LigPrep enabled 44,943 ready-to-dock conformers generation. Glide docking revealed 18 OfHex1-specific hits that were absent in human and <i>T. pretiosum</i> screens. Reference docking was conducted using inhibitors/natural ligands in the crystal structures and hits with better docking scores than the reference were selected for MD simulations using Desmond to understand the stability of hit-target interactions. We noted five compounds that bound to OfHex1 TMX active-site based on their docking scores, consistent binding as noted by MD simulations and their insecticide/pesticide likeliness as noted by the Comprehensive Pesticide Likeness Analysis. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24278140.v1
title: Structure-guided computational insecticide discovery targeting <i>β</i>-N-acetyl-D-hexosaminidase of <i>Ostrinia furnacalis</i>

description: <i>Ostrinia furnacalis</i> is a species of moth in the Crambidae family that is harmful to maize and other corn crops in Southeast Asia and the Western Pacific regions. <i>Ostrinia furnacalis</i> causes devastating losses to economically important corn fields. The β-N-acetyl-D-hexosaminidase is an essential enzyme in <i>O. furnacalis</i> and its substrate binding +1 active site is different from that of the plants and humans β-N-acetyl-D-hexosaminidases. To develop environment-friendly insecticides against OfHex1, we conducted structure-guided computational insecticide discovery to identify potential inhibitors that can bind the active site and inhibit the substrate binding and activity of the enzyme. We adopted a three-pronged strategy to conduct virtual screening using Glide and virtual screening workflow (VSW) in Schrödinger Suite-2022-3, against crystal structures of OfHex1 (PDB Id:3NSN), its homologue in humans (PDB Id: 1NP0) and Alphafold model of β-N-acetyl-D-hexosaminidase from <i>Trichogramma pretiosum</i>, an egg parasitoid that protects the crops from <i>O. furnacalis.</i> A library of 20,313 commercially available and “insecticide-like” compounds was extracted from published literature. LigPrep enabled 44,943 ready-to-dock conformers generation. Glide docking revealed 18 OfHex1-specific hits that were absent in human and <i>T. pretiosum</i> screens. Reference docking was conducted using inhibitors/natural ligands in the crystal structures and hits with better docking scores than the reference were selected for MD simulations using Desmond to understand the stability of hit-target interactions. We noted five compounds that bound to OfHex1 TMX active-site based on their docking scores, consistent binding as noted by MD simulations and their insecticide/pesticide likeliness as noted by the Comprehensive Pesticide Likeness Analysis. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24224064
title: Structure-based virtual screening of natural compounds as inhibitors of HCV using molecular docking and molecular dynamics simulation studies

description: The hepatitis C virus (HCV), which causes hepatitis C, is a viral infection that damages the liver and causes inflammation in the liver. New potentially effective antiviral drugs are required for its treatment owing to various issues associated with the existing medications, including moderate to severe adverse effects, higher costs, and the emergence of drug-resistant strains. The objective of the current study was to utilize computational techniques to assess the anti-HCV efficacy of certain phytochemicals against tetraspanin (CD81) and claudin 1 (CLDN1) entry proteins. A 200-nanosecond molecular dynamics (MD) simulation was employed to examine the stability of the lead-protein complexes. Free binding energy and molecular docking calculations were conducted utilizing MM/GBSA method, and the selectivity of hit compounds for CD81 and CLDN1 was determined. Five significant CD81 and CLDN1 inhibitors were identified: Petasiphenone, Silibinin, Tanshinone IIA, Taxifolin, and Topaquinone. The MM/GBSA analysis of the compounds revealed high free binding energies. All the identified compounds were stable within the CD81 and CLDN1 binding pockets. This study indicated the promising inhibitory potential of the identified compounds against CD81 and CLDN1 receptors and might develop into potential viral entry inhibitors. However, to validate the chemotherapeutic capabilities of the discovered leads extensive preclinical research is required. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24224064.v1
title: Structure-based virtual screening of natural compounds as inhibitors of HCV using molecular docking and molecular dynamics simulation studies

description: The hepatitis C virus (HCV), which causes hepatitis C, is a viral infection that damages the liver and causes inflammation in the liver. New potentially effective antiviral drugs are required for its treatment owing to various issues associated with the existing medications, including moderate to severe adverse effects, higher costs, and the emergence of drug-resistant strains. The objective of the current study was to utilize computational techniques to assess the anti-HCV efficacy of certain phytochemicals against tetraspanin (CD81) and claudin 1 (CLDN1) entry proteins. A 200-nanosecond molecular dynamics (MD) simulation was employed to examine the stability of the lead-protein complexes. Free binding energy and molecular docking calculations were conducted utilizing MM/GBSA method, and the selectivity of hit compounds for CD81 and CLDN1 was determined. Five significant CD81 and CLDN1 inhibitors were identified: Petasiphenone, Silibinin, Tanshinone IIA, Taxifolin, and Topaquinone. The MM/GBSA analysis of the compounds revealed high free binding energies. All the identified compounds were stable within the CD81 and CLDN1 binding pockets. This study indicated the promising inhibitory potential of the identified compounds against CD81 and CLDN1 receptors and might develop into potential viral entry inhibitors. However, to validate the chemotherapeutic capabilities of the discovered leads extensive preclinical research is required. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24270916
title: Structural insights into modeling of hepatitis B virus reverse transcriptase and identification of its inhibitors from potential medicinal plants of Western Ghats: an <i>in silic</i>o and <i>in vitro</i> study

description: The present study was proposed to model full-length HBV-RT and investigate the intermolecular interactions of known inhibitor and libraries of phytocompounds to probe the potential natural leads by <i>in silico</i> and <i>in vitro</i> studies. Homology modeling of RT was performed by Phyre2 and Modeller and virtual screening of ligands implemented through POAP pipeline. Molecular dynamics (MD) simulation (100 ns) and MM-GBSA calculations were performed using Schrodinger Desmond and Prime, respectively. Phytocompounds probable host protein targets gene set pathway enrichment and network analysis were executed by KEGG database and Cytoscape software. Prioritized plant extracts/enriched fraction LC-MS analysis was performed and along with pure compound, RT inhibitory activity, time-dependent HBsAg and HBeAg secretion, and intracellular HBV DNA, and pgRNA by qRT-PCR was performed in HepG2.2.15 cell line. Among the screened chemical library of 268 phytocompounds from 18 medicinal plants, 15 molecules from <i>Terminalia chebula</i> (6), <i>Bidens pilosa</i> (5), and <i>Centella asiatica</i> (4)) were identified as potential inhibitors of YMDD and RT1 motif of HBV-RT. MD simulation demonstrated stable interactions of 15 phytocompounds with HBV-RT, of which 1,2,3,4,6-Pentagalloyl Glucose (PGG) was identified as lead molecule. Out of 15 compounds, 11 were predicted to modulate 39 proteins and 15 molecular pathways associated with HBV infection. TCN and TCW (500 µg/mL) showed potent RT inhibition, decreased intracellular HBV DNA, and pgRNA, and time-dependent inhibition of HBsAg and HBeAg levels compared to PGG and Tenofovir Disoproxil Fumarate. We propose that the identified lead molecules from <i>T. chebula</i> as promising and cost-effective moieties for the management of HBV infection. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24270916.v1
title: Structural insights into modeling of hepatitis B virus reverse transcriptase and identification of its inhibitors from potential medicinal plants of Western Ghats: an <i>in silic</i>o and <i>in vitro</i> study

description: The present study was proposed to model full-length HBV-RT and investigate the intermolecular interactions of known inhibitor and libraries of phytocompounds to probe the potential natural leads by <i>in silico</i> and <i>in vitro</i> studies. Homology modeling of RT was performed by Phyre2 and Modeller and virtual screening of ligands implemented through POAP pipeline. Molecular dynamics (MD) simulation (100 ns) and MM-GBSA calculations were performed using Schrodinger Desmond and Prime, respectively. Phytocompounds probable host protein targets gene set pathway enrichment and network analysis were executed by KEGG database and Cytoscape software. Prioritized plant extracts/enriched fraction LC-MS analysis was performed and along with pure compound, RT inhibitory activity, time-dependent HBsAg and HBeAg secretion, and intracellular HBV DNA, and pgRNA by qRT-PCR was performed in HepG2.2.15 cell line. Among the screened chemical library of 268 phytocompounds from 18 medicinal plants, 15 molecules from <i>Terminalia chebula</i> (6), <i>Bidens pilosa</i> (5), and <i>Centella asiatica</i> (4)) were identified as potential inhibitors of YMDD and RT1 motif of HBV-RT. MD simulation demonstrated stable interactions of 15 phytocompounds with HBV-RT, of which 1,2,3,4,6-Pentagalloyl Glucose (PGG) was identified as lead molecule. Out of 15 compounds, 11 were predicted to modulate 39 proteins and 15 molecular pathways associated with HBV infection. TCN and TCW (500 µg/mL) showed potent RT inhibition, decreased intracellular HBV DNA, and pgRNA, and time-dependent inhibition of HBsAg and HBeAg levels compared to PGG and Tenofovir Disoproxil Fumarate. We propose that the identified lead molecules from <i>T. chebula</i> as promising and cost-effective moieties for the management of HBV infection. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24278634.v1
title: CORAL: probing the structural requirements for α-amylase inhibition activity of 5-(3-arylallylidene)-2-(arylimino)thiazolidin-4-one derivatives based on QSAR with correlation intensity index, molecular docking, molecular dynamics, and ADMET studies

description: The present study aims to examine the structural requirements governing α-amylase inhibitory activity of 5-(3-arylallylidene)-2-(arylimino)thiazolidin-4-one derivatives and their precursors by employing a multifaceted approach combining <i>in vitro</i> and <i>in silico</i> studies. The <i>in vitro</i> assay findings revealed strong inhibitory effect of this class of compounds against α-amylase and compound <b>20</b> exhibited maximum percentage inhibition of 88.54 ± 0.69, 84.98 ± 0.40, 77.26 ± 0.75, 67.80 ± 0.54, and 62.93 ± 1.17 at 200, 100, 50, 25, and 12.5 µg mL<sup>−1</sup>, respectively. Multiple CORAL QSAR models were developed from the randomly distributed eight splits by employing two target functions (TF<sub>1</sub>, TF<sub>2</sub> with W<sub>CII</sub> = 0.0 and = 0.3, respectively), and the quality of predictions by the produced models was validated with the help of various statistical parameters. The model M-4 (<b>R<sup>2</sup><sub>Val</sub> = 0.8799</b>) and model M-11 (<b>R<sup>2</sup><sub>Val</sub> = 0.9064</b>) were the leading models developed by using TF<sub>1</sub> and TF<sub>2</sub>. We designed five new congeneric inhibitors (D-1 to D-5) by incorporating SMILES features positively correlating with the activity. Molecular docking experiments were carried out to confirm the binding of these new inhibitors with the biological receptor α-amylase (<b>PDB ID: 7TAA</b>). Furthermore, molecular dynamic simulations provided a thorough knowledge of the binding process by shedding insight into the dynamic behavior and stability of the ligand-receptor complex over time. The results of this study highlight the key structural characteristics needed for improved α-amylase inhibitory efficacy and provide a rational basis for the development of more effective inhibitors. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24297109
title: <i>In silico</i> identification of colchicine derivatives as novel and potential inhibitors based on molecular docking and dynamic simulations targeting multifactorial drug targets involved in Alzheimer’s disease

description: Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder, characterized by a gradual and steady deterioration in cognitive function over time. At least 50 million people worldwide are considered to have AD or another form of dementia. AD is marked by a gradual decline in cognitive abilities, memory deterioration and neurodegenerative transformations within the brain. The intricate and multifaceted nature of polygenic AD presents significant challenges within the landscape of drug development. The pathophysiology of AD unfolds in a non-linear and dynamic pattern, encompassing various systems and giving rise to a multitude of factors and hypotheses that contribute to the disease’s onset. These encompass theories such as the beta-amyloid hypothesis, cholinergic hypothesis, tau hypothesis, oxidative stress and more. In the realm of drug development, polypharmacological drug profiles have emerged as a strategy that can yield combined or synergistic effects, effectively mitigating undesirable side effects and significantly enhancing the therapeutic efficacy of essential medications. With this concept in mind, our <i>in-silico</i> study sought to delve into the binding interactions of a diverse array of colchicine derivative compounds. These derivatives are chosen for their potential anti-inflammatory, antioxidant, anti-neurodegenerative and neuroprotective properties against Alzheimer’s and other neurodegenerative diseases. We investigated compound interactions with AD-related targets, utilizing comprehensive molecular docking and dynamic simulations. COM111X showed impressive docking with acetylcholinesterase, indicating potential as an anti-Alzheimer’s drug. COM112Y displayed strong docking scores with PDE4D and butyrylcholinesterase, suggesting dual inhibition for Alzheimer’s treatment. Further <i>in vitro</i> and <i>in vivo</i> studies are warranted to explore these findings. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24297109.v1
title: <i>In silico</i> identification of colchicine derivatives as novel and potential inhibitors based on molecular docking and dynamic simulations targeting multifactorial drug targets involved in Alzheimer’s disease

description: Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder, characterized by a gradual and steady deterioration in cognitive function over time. At least 50 million people worldwide are considered to have AD or another form of dementia. AD is marked by a gradual decline in cognitive abilities, memory deterioration and neurodegenerative transformations within the brain. The intricate and multifaceted nature of polygenic AD presents significant challenges within the landscape of drug development. The pathophysiology of AD unfolds in a non-linear and dynamic pattern, encompassing various systems and giving rise to a multitude of factors and hypotheses that contribute to the disease’s onset. These encompass theories such as the beta-amyloid hypothesis, cholinergic hypothesis, tau hypothesis, oxidative stress and more. In the realm of drug development, polypharmacological drug profiles have emerged as a strategy that can yield combined or synergistic effects, effectively mitigating undesirable side effects and significantly enhancing the therapeutic efficacy of essential medications. With this concept in mind, our <i>in-silico</i> study sought to delve into the binding interactions of a diverse array of colchicine derivative compounds. These derivatives are chosen for their potential anti-inflammatory, antioxidant, anti-neurodegenerative and neuroprotective properties against Alzheimer’s and other neurodegenerative diseases. We investigated compound interactions with AD-related targets, utilizing comprehensive molecular docking and dynamic simulations. COM111X showed impressive docking with acetylcholinesterase, indicating potential as an anti-Alzheimer’s drug. COM112Y displayed strong docking scores with PDE4D and butyrylcholinesterase, suggesting dual inhibition for Alzheimer’s treatment. Further <i>in vitro</i> and <i>in vivo</i> studies are warranted to explore these findings. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24278634
title: CORAL: probing the structural requirements for α-amylase inhibition activity of 5-(3-arylallylidene)-2-(arylimino)thiazolidin-4-one derivatives based on QSAR with correlation intensity index, molecular docking, molecular dynamics, and ADMET studies

description: The present study aims to examine the structural requirements governing α-amylase inhibitory activity of 5-(3-arylallylidene)-2-(arylimino)thiazolidin-4-one derivatives and their precursors by employing a multifaceted approach combining <i>in vitro</i> and <i>in silico</i> studies. The <i>in vitro</i> assay findings revealed strong inhibitory effect of this class of compounds against α-amylase and compound <b>20</b> exhibited maximum percentage inhibition of 88.54 ± 0.69, 84.98 ± 0.40, 77.26 ± 0.75, 67.80 ± 0.54, and 62.93 ± 1.17 at 200, 100, 50, 25, and 12.5 µg mL<sup>−1</sup>, respectively. Multiple CORAL QSAR models were developed from the randomly distributed eight splits by employing two target functions (TF<sub>1</sub>, TF<sub>2</sub> with W<sub>CII</sub> = 0.0 and = 0.3, respectively), and the quality of predictions by the produced models was validated with the help of various statistical parameters. The model M-4 (<b>R<sup>2</sup><sub>Val</sub> = 0.8799</b>) and model M-11 (<b>R<sup>2</sup><sub>Val</sub> = 0.9064</b>) were the leading models developed by using TF<sub>1</sub> and TF<sub>2</sub>. We designed five new congeneric inhibitors (D-1 to D-5) by incorporating SMILES features positively correlating with the activity. Molecular docking experiments were carried out to confirm the binding of these new inhibitors with the biological receptor α-amylase (<b>PDB ID: 7TAA</b>). Furthermore, molecular dynamic simulations provided a thorough knowledge of the binding process by shedding insight into the dynamic behavior and stability of the ligand-receptor complex over time. The results of this study highlight the key structural characteristics needed for improved α-amylase inhibitory efficacy and provide a rational basis for the development of more effective inhibitors. Communicated by Ramaswamy H. Sarma