Dipeptidyl peptidase IV inhibition of phytocompounds from Artocarpus champeden (Lour.) Stokes: In silico molecular docking study and ADME-Tox prediction approach.

The present study examines the potential activity prediction based on free binding energy (ΔG) and interaction confirmation of phytocompounds from Artocarpus champeden (Lour.) Stokes with macromolecule protein receptor of dipeptidyl peptidase IV (DPP-IV) using in silico molecular docking studies and physicochemical and pharmacokinetic properties (ADME-Tox) prediction approaches. The active subsites of the DPP-IV receptor macromolecule protein Protein Data Bank (ID: 1 × 70) were docked using Autodock v4.2.6 (100 docking runs). A grid box of 52 × 28 × 26 Å points spaced by 0.37 Å was centered on the active site of x = 40.926 Å; y = 50.522 Å; z = 35.031 Å. For ADME-Tox prediction, Swiss ADME online-based application programs were used. The results show that 12 pythocompounds from A. champeden have the potential as DPP-IV inhibitors based on ΔG value and interaction conformation. There are five pythocompounds with lower ΔG values and inhibition constants than the native ligand and seven pythocompounds with ΔG values and inhibition constants close to the native ligand. The 12 compounds form an interaction conformation at the active subsites of the DPP-IV receptor. At the same time, the results of the ADME-Tox prediction analysis showed that the 12 compounds had different physicochemical and pharmacokinetic properties.

Prediction of human-Streptococcus pneumoniae protein-protein interactions using logistic regression.

Streptococcus pneumoniae is a major cause of mortality in children under five years old. In recent years, the emergence of antibiotic-resistant strains of S. pneumoniae increases the threat level of this pathogen. For that reason, the exploration of S. pneumoniae protein virulence factors should be considered in developing new drugs or vaccines, for instance by the analysis of host-pathogen protein-protein interactions (HP-PPIs). In this research, prediction of protein-protein interactions was performed with a logistic regression model with the number of protein domain occurrences as features. By utilizing HP-PPIs of three different pathogens as training data, the model achieved 57-77 % precision, 64-75 % recall, and 96-98 % specificity. Prediction of human-S. pneumoniae protein-protein interactions using the model yielded 5823 interactions involving thirty S. pneumoniae proteins and 324 human proteins. Pathway enrichment analysis showed that most of the pathways involved in the predicted interactions are immune system pathways. Network topology analysis revealed ß-galactosidase (BgaA) as the most central among the S. pneumoniae proteins in the predicted HP-PPI networks, with a degree centrality of 1.0 and a betweenness centrality of 0.451853. Further experimental studies are required to validate the predicted interactions and examine their roles in S. pneumoniae infection.

Peptide-Based Subunit Vaccine Design of T- and B-Cells Multi-Epitopes against Zika Virus Using Immunoinformatics Approaches.

The Zika virus disease, also known as Zika fever is an arboviral disease that became epidemic in the Pacific Islands and had spread to 18 territories of the Americas in 2016. Zika virus disease has been linked to several health problems such as microcephaly and the Guillain-Barré syndrome, but to date, there has been no vaccine available for Zika. Problems related to the development of a vaccine include the vaccination target, which covers pregnant women and children, and the antibody dependent enhancement (ADE), which can be caused by non-neutralizing antibodies. The peptide vaccine was chosen as a focus of this study as a safer platform to develop the Zika vaccine. In this study, a collection of Zika proteomes was used to find the best candidates for T- and B-cell epitopes using the immunoinformatics approach. The most promising T-cell epitopes were mapped using the selected human leukocyte antigen (HLA) alleles, and further molecular docking and dynamics studies showed a good peptide-HLA interaction for the best major histocompatibility complex-II (MHC-II) epitope. The most promising B-cell epitopes include four linear peptides predicted to be cross-reactive with T-cells, and conformational epitopes from two proteins accessible by antibodies in their native biological assembly. It is believed that the use of immunoinformatics methods is a promising strategy against the Zika viral infection in designing an efficacious multiepitope vaccine.

The Antiviral Effect of Indonesian Medicinal Plant Extracts Against Dengue Virus In Vitro and In Silico.

Dengue infections are still a worldwide burden, especially in Indonesia. There is no specific medication against the dengue virus. Recently, many types of research have been conducted to discover a new drug for dengue virus using natural resource extracts. Indonesia, as a tropical country, has a wide biodiversity. There are several medicinal plants in Indonesia that are believed to possess anti-dengue activity, such as Myristica fatua, Cymbopogon citratus, and Acorus calamus plants. We conducted an in vitro laboratory experiment of several extracts from Indonesian herbs combined with in silico analysis. The extracts were evaluated for safety and antiviral activity in Huh7it-1 cell lines, using a single dose of 20 µg/mL and dose-dependent (5, 10, 20, 40, 80 and 160 µg/mL) of plant extracts against dengue virus serotype 2 (DENV-2) NGC strain. The DMSO 0.1% was used as a negative control. The cytotoxic aspect was assessed by counting the cell viability, while the antiviral activity was calculated by counting the average inhibition. The selectivity index (SI) of plant extracts were performed from a ratio of CC50/EC50 value. In silico analysis was conducted to determine the free energy of binding between NS5 of dengue virus with bioactive compounds contained in Myristica fatua, Cymbopogon citratus and Acorus calamus extract plants. We determined that all extracts were not toxic against Huh7it-1 cell lines. The methanolic extracts of A. calamus, C. citratus, and M. fatua showed inhibition of DENV-2 at a dose of 20 µg/mL to 96.5%, 98.9%, and 122.7%, respectively. The dose-dependent effects showed that M. fatua has the best inhibition activity towards DENV-2. Molecular docking result showed that artesunic acid within M. fatua has the best free energy of binding (-7.2 kcal/mol), followed by homoegonol (-7.1 kcal/mol) which was slightly different from artesunic acid among others. The methanolic extracts of A. calamus, C. citratus, and M. fatua showed prospective anti-dengue activities both in vitro and in silico. Future research should be conducted to find the pure extracts of all useful herbs as a new candidate of antiviral drug.