Pea eggplant (Solanum torvum Swartz) is a source of plant food polyphenols with SARS-CoV inhibiting potential.

Background: Pea eggplant (Solanum torvum Swartz) commonly known as turkey berry or 'terung pipit' in Malay is a vegetable plant widely consumed by the local community in Malaysia. The shrub bears pea-like turkey berry fruits (TBFs), rich in phytochemicals of medicinal interest. The TBF phytochemicals hold a wide spectrum of pharmacological properties. In this study, the TBF phytochemicals' potential inhibitory properties were evaluated against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) of the Coronavirus disease 2019 (COVID-19). The TBF polyphenols were screened against SARS-CoV receptors via molecular docking and the best receptor-ligand complex was validated further by molecular dynamics (MD) simulation. Method: The SARS-CoV receptor structure files (viral structural components) were retrieved from the Protein Data Bank (PDB) database: membrane protein (PDB ID: 3I6G), main protease (PDB ID: 5RE4), and spike glycoproteins (PDB ID: 6VXX and 6VYB). The receptor binding pocket regions were identified by Discovery Studio (BIOVIA) for targeted docking with TBF polyphenols (genistin, kaempferol, mellein, rhoifolin and scutellarein). The ligand and SARS-CoV family receptor structure files were pre-processed using the AutoDock tools. Molecular docking was performed with the Lamarckian genetic algorithm using AutoDock Vina 4.2 software. The best pose (ligand-receptor complex) from the molecular docking analysis was selected based on the minimum binding energy (MBE) and extent of structural interactions, as indicated by BIOVIA visualization tool. The selected complex was validated by a 100 ns MD simulation run using the GROMACS software. The dynamic behaviour and stability of the receptor-ligand complex were evaluated by the root mean square displacement (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), solvent accessible surface volume (SASV) and number of hydrogen bonds. Results: At RMSD = 0, the TBF polyphenols showed fairly strong physical interactions with SARS-CoV receptors under all possible combinations. The MBE of TBF polyphenol-bound SARS CoV complexes ranged from -4.6 to -8.3 kcal/mol. Analysis of the structural interactions showed the presence of hydrogen bonds, electrostatic and hydrophobic interactions between the receptor residues (RR) and ligands atoms. Based on the MBE values, the 3I6G-rhoifolin (MBE = -8.3 kcal/mol) and 5RE4-genistin (MBE = -7.6 kcal/mol) complexes were ranked with the least value. However, the latter showed a greater extent of interactions between the RRs and the ligand atoms and thus was further validated by MD simulation. The MD simulation parameters of the 5RE4-genistin complex over a 100 ns run indicated good structural stability with minimal flexibility within genistin binding pocket region. The findings suggest that S. torvum polyphenols hold good therapeutics potential in COVID-19 management.

Bioassay Analysis and Molecular Docking Study Revealed the Potential Medicinal Activities of Active Compounds Polygonumins B, C and D from Polygonum minus (Persicaria minor).

Polygonumins B, C and D, derivative compounds of polygonumins A, were isolated from the stem of Polygonum minus. Based on NMR results, the structure of polygonumins derivatives is comprised of four phenylpropanoid units and a sucrose unit, with a similar structure to polygonumins A. However, the structural differences between polygonumins B (1), C (2) and D (3) can be distinguished based on the existence of methoxy, ethanoyl and hydroxyl groups and protons which bind to C-4, C-4' and C-3″. Interestingly, these bioactive compounds showed various medicinal properties based on our investigation on antioxidant, anticholinesterase and anti-HIV-1 protease activities. The IC50 value of DPPH and ABTS (antioxidant activities) was in the following descending order: polygonumins B > polygonumins C > polygonumins A > polygonumins D. In addition, almost similar pattern of antioxidant activity was observed for anti-acetylcholinesterase activity based on its IC50 value in descending order: polygonumins B > polygonumins C > polygonumins D > polygonumins A. On the other hand, polygonumins C and D showed inhibition of HIV-1 protease activity more than the positive control, pepstatin A. Finally, molecular docking studies on AChE and BChE proteins were carried out in order to gain insight into the mode of interactions between these compounds and the active residues for both enzymes. These remarkable findings indicate that these compounds have potential to be developed as targeted drugs for Alzheimer's disease or as anti-HIV drugs.

Side chain similarity comparisons for integrated drug repositioning and potential toxicity assessments in epidemic response scenarios: The case for COVID-19.

Structures of protein-drug-complexes provide an atomic level profile of drug-target interactions. In this work, the three-dimensional arrangements of amino acid side chains in known drug binding sites (substructures) were used to search for similarly arranged sites in SARS-CoV-2 protein structures in the Protein Data Bank for the potential repositioning of approved compounds. We were able to identify 22 target sites for the repositioning of 16 approved drug compounds as potential therapeutics for COVID-19. Using the same approach, we were also able to investigate the potentially promiscuous binding of the 16 compounds to off-target sites that could be implicated in toxicity and side effects that had not been provided by any previous studies. The investigations of binding properties in disease-related proteins derived from the comparison of amino acid substructure arrangements allows for effective mechanism driven decision making to rank and select only the compounds with the highest potential for success and safety to be prioritized for clinical trials or treatments. The intention of this work is not to explicitly identify candidate compounds but to present how an integrated drug repositioning and potential toxicity pipeline using side chain similarity searching algorithms are of great utility in epidemic scenarios involving novel pathogens. In the case of the COVID-19 pandemic caused by the SARS-CoV-2 virus, we demonstrate that the pipeline can identify candidate compounds quickly and sustainably in combination with associated risk factors derived from the analysis of potential off-target site binding by the compounds to be repurposed.

Transcriptomic and Proteomic Analyses of Nepenthes ampullaria and Nepenthes rafflesiana Reveal Parental Molecular Expression in the Pitchers of Their Hybrid, Nepenthes × hookeriana.

Nepenthes is a genus comprising carnivorous tropical pitcher plants that have evolved trapping organs at the tip of their leaves for nutrient acquisition from insect trapping. Recent studies have applied proteomics approaches to identify proteins in the pitcher fluids for better understanding the carnivory mechanism, but protein identification is hindered by limited species-specific transcriptomes for Nepenthes. In this study, the proteomics informed by transcriptomics (PIT) approach was utilized to identify and compare proteins in the pitcher fluids of Nepenthes ampullaria, Nepenthes rafflesiana, and their hybrid Nepenthes × hookeriana through PacBio isoform sequencing (Iso-Seq) and liquid chromatography-mass spectrometry (LC-MS) proteomic profiling. We generated full-length transcriptomes from all three species of 80,791 consensus isoforms with an average length of 1,692 bp as a reference for protein identification. The comparative analysis found that transcripts and proteins identified in the hybrid N. × hookeriana were more resembling N. rafflesiana, both of which are insectivorous compared with omnivorous N. ampullaria that can derive nutrients from leaf litters. Previously reported hydrolytic proteins were detected, including proteases, glucanases, chitinases, phosphatases, nucleases, peroxidases, lipid transfer protein, thaumatin-like protein, pathogenesis-related protein, and disease resistance proteins. Many new proteins with diverse predicted functions were also identified, such as amylase, invertase, catalase, kinases, ligases, synthases, esterases, transferases, transporters, and transcription factors. Despite the discovery of a few unique enzymes in N. ampullaria, we found no strong evidence of adaptive evolution to produce endogenous enzymes for the breakdown of leaf litter. A more complete picture of digestive fluid protein composition in this study provides important insights on the molecular physiology of pitchers and carnivory mechanism of Nepenthes species with distinct dietary habits.

Drug ReposER: a web server for predicting similar amino acid arrangements to known drug binding interfaces for potential drug repositioning.

A common drug repositioning strategy is the re-application of an existing drug to address alternative targets. A crucial aspect to enable such repurposing is that the drug's binding site on the original target is similar to that on the alternative target. Based on the assumption that proteins with similar binding sites may bind to similar drugs, the 3D substructure similarity data can be used to identify similar sites in other proteins that are not known targets. The Drug ReposER (DRug REPOSitioning Exploration Resource) web server is designed to identify potential targets for drug repurposing based on sub-structural similarity to the binding interfaces of known drug binding sites. The application has pre-computed amino acid arrangements from protein structures in the Protein Data Bank that are similar to the 3D arrangements of known drug binding sites thus allowing users to explore them as alternative targets. Users can annotate new structures for sites that are similarly arranged to the residues found in known drug binding interfaces. The search results are presented as mappings of matched sidechain superpositions. The results of the searches can be visualized using an integrated NGL viewer. The Drug ReposER server has no access restrictions and is available at http://mfrlab.org/drugreposer/.