Epitope Mapping Daerah Conserved Pada Kapsid L1 Human Papillomavirus Sebagai Pengembangan Vaksin Pencegahan Kanker Serviks

Human papillomavirus (HPV) merupakan virus yang memainkan peran penting dalam terjadinya kanker serviks, HPV adalah anggota famili papoviridae, genus papillomavirus. Gen HPV terdiri atas 2 bagian yaitu early dan late gene. Protein early pada HPV meliputi E1, E2, E4, E5, E6, dan E7 Late gene yang terekspresi dari late promoter berperan sebagai pengkode protein kapsid L1 dan L2. Protein L1 memiliki region conserved yang tersusun oleh residu cystein dan lysine, kedua residu tersebut memiliki keterlibatan dalam proses pengikatan antara virion dengan reseptor host. Penelitian sebelumnya menunjukkan bahwa vaksin dapat dikembangkan berdasarkan epitop yang memiliki daerah conserved. Penelitian ini penting dilakukan untuk mengidentifikasi sekuens protein conserved pada L1 kapsid HPV, memprediksi epitope mapping sel B serta antigenisitas pada daerah conserved kapsid L1 HPV, serta kesamaan residu asam amino penyusun epitop dengan reseptor permukaan sel tubuh manusia. Daerah conserved teridentifikasi pada L1 HPV yang berpotensi sebagai epitop sel B berdasarkan analisis epitope mapping yaitu posisi 23- 46 dan 97-119 dengan peptida EGRGQPLGGSGHPNDDEDRDKQ dan RHNGGPGPSGSSQFNKPYWAQGN serta masing-masing memiliki panjang peptida sebesar 22-mer dan 23-mer. Epitop dengan posisi 97-119 memiliki skor antigenisitas tinggi dan kesamaan urutan residu asam amino yang rendah, terhadap reseptor permukaan sel tubuh manusia. Jadi peptida RHNGGPGPSGSSQFNKPYWAQGN dengan panjang 23-mer dapat digunakan sebagai rujukan pengembangan vaksin pencegahan kanker serviks

Edible Bird’s Nest as Potential Food with Anti-Viral and Anti-Inflammatory Properties Against Covid-19: an in Silico Study

The Chinese believe consuming edible bird’s nests (EBN) can increase immunity to various diseases, including Covid-19. This study attempts to identify SARS COV-2-specific anti-viral and anti-inflammatory agents of EBN. We gathered samples from PubChem and Protein Data Bank (PDB). Afterwards, drug likeness was examined using the Lipinski model from the SCFBIO online service. The PASS web server analyzed the bioactive likelihood of chemicals found in EBN. Using PyRx 0.8 software with the blind docking technique. The PoseView web server and PyMol v2.4.1 software were utilized to ascertain molecular interactions. The in silico results show the potential of EBN as food therapy for Covid-19 sufferers, which is indicated by the presence of bioactive compounds from edible bird’s nest consisting of 9-O-acetylated GD3, glycopeptide, N-acetyl neuraminic acid, N-glycolyl-neuraminic acid, sialic acid, and tetra acetyl-thymol-beta-D-glucoside. These bio compounds are predicted to work as anti-viral and anti-inflammatory candidates against SARS-COV-2

New Perspectives on Reverse Translation: Brief History and Updates

Since the 1950s, reverse translation has been an enigmatic part of Crick’s central dogma of molecular biology. It might be described as the possibility to back-translate information from proteins to nucleic acids (or codons). A few studies have attempted to theorize and/or conduct in vitro experiments to test the likelihood of reverse translation, with ideas often involving the creation of peptide recognition sites that bridge the peptide and the codon. However, due to many constraints including an asymmetrical informational transfer, the stability of protein-peptide bonds, the structural non-uniformity of protein R-groups, and the informational loss in post-translational protein modifications, this concept requires follow-up studies. On the other hand, current bioinformatic tools that rely on computational programs and biological databases represent a growing branch of biology. Bioinformatics-based reverse translation can utilize codon usage tables to predict codons from their peptide counterparts. In addition, the development of machine learning tools may allow for the exploration of biological reverse translation in vitro. Thus, while in vivo reverse translation appears to be nearly impossible (due to biological complexity), related biological and bioinformatics studies might be useful to understand better the central dogma’s informational transfer and to develop more complex biological machinery

Immunobioinformatics analysis and phylogenetic tree construction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Indonesia: spike glycoprotein gene

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has spread worldwide and as a result, the World Health Organization (WHO) declared it a pandemic. At present, there are no approved vaccines against SARS-CoV-2. Therefore, the aim of this study was to predict epitope-based vaccines using bioinformatics approaches and phylogenetic tree construction of SARS-CoV-2 against the backdrop of the COVID-19 pandemic. In this study, we employed 27 isolates of SARS-CoV-2 spike glycoprotein genes retrieved from GenBank® (National Center for Biotechnology Information, USA) and the GISAID EpiCoV™ Database (Germany). We analyzed the candidate epitopes using the Immune Epitope Database and Analysis Resource. Furthermore, we performed a protective antigen prediction with VaxiJen 2.0. Data for B-cell epitope prediction, protective antigen prediction, and the underlying phylogenetic tree of SARS-CoV-2 were obtained in this research. Therefore, these data could be used to design an epitope-based vaccine against SARS-CoV-2. However, the advanced study is recommended for confirmation (in vitro and in vivo)

In Silico Analysis and Identification of Possible Inhibitor of H5N1 Virus

Fingerroot (Boesenbergia pandurata (Roxb.) belongs to the family Zingiberaceae (Ginger). B. pandurata has pharmacological benefits such as neuroprotective, chemoprotective, anti-inflammatory, anti-angiogenic, antioxidant, an inhibitor of protease enzyme NS2B/NS3 dengue virus, Japanese encephalitis virus and swine flu virus (H1N1). This study aims to determine the most effective compounds from B. pandurata as neuraminidase inhibitors of H5N1 virus. The amino acid sequence for neuraminidase of avian influenza A virus subtype H5N1 of A/China/GD02/2006 (ABX57872.1) was retrieved from protein sequence database at NCBI. Then, modeled by Swiss Model. Analyse of molecular docking was performed using PyRx and the interactions between neuraminidase inhibitors of H5N1 and B. pandurata active compound was analyzed by PyMol software and LigPlot+ software. From the 30 active compounds which have been docked, 4-hydroxypanduratin A, rubranine, boesenbergin B, boesenbergin A, 5,7-dimethoxyflavone, and tectochrysin had an equal or smaller free binding energy than control compound. 4-hydroxypanduratin A proved to be the most potent active compound as a neuraminidase inhibitor (NA 1) because it has the most negative binding energy and the same amino acid binding residue with the control compound. Therefore, 4-hydroxypanduratin A is predicted to be used as inhibitors of neuraminidase in the H5N1 virus

Alpha-Mangostin as an Antiviral Candidate: A Mini Review

This mini review aims to explore the potential of alpha-mangostin as an antiviral candidate. Alpha-mangostin is a natural compound found in the fruit of the Garcinia mangostana tree. Over the years, it has attracted considerable attention due to its diverse pharmacological properties, including antiviral activity. This review provides an overview of the current literature on the antiviral effects of alpha-mangostin, focusing on its mechanisms of action and its efficacy against various viral infections. The potential application of alpha-mangostin as a therapeutic agent against viral diseases is discussed, along with future research directions and challenges in the development of alpha-mangostin-based antiviral therapies

A mini review of Curcuma longa: Antimicrobial properties

This review discusses the antimicrobial potential of Curcuma longa, a plant traditionally recognized for its medicinal properties. The emerging concern over antimicrobial resistance, coupled with the adverse effects of synthetic drugs, necessitates an exploration of plant-based natural antimicrobials. Curcuma longa, commonly known as turmeric, provides a compelling case with its broad spectrum of antimicrobial activity. The review first delves into the phytochemical composition of Curcuma longa, focusing on its primary bioactive compounds, the curcuminoids, with curcumin being the most prominent. These compounds, along with essential oils and polysaccharides, contribute significantly to the antimicrobial properties of the plant

Genetic Variant of SARS-CoV-2 Isolates in Indonesia: Spike Glycoprotein Gene

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a novel coronavirus and the primary causative agent of coronavirus disease 2019 (COVID-19), first occurred in China and rapidly spread worldwide. The government of the Republic of Indonesia confirmed its first two cases of COVID-19 in March 2020. COVID-19 is a serious illness with no efficacious antiviral medication or approved vaccine currently available. Therefore, there is a need to investigate the genome of SARS-CoV-2. In this study, we characterized SARS-CoV-2 spike glycoprotein genes from Indonesia to investigate their genetic composition and variability. Overall, ten SARS-CoV-2 spike glycoprotein gene sequences retrieved from GenBank (National Center for Biotechnology Information, USA) and the GISAID EpiCoV database (Germany) were compared. We analyzed nucleotide variants and amino acid changes using Molecular Evolutionary Genetics Analysis (MEGA) X and analyzed gene similarity using the LALIGN web server. Interestingly, we revealed several specific mutation sites, however, there were no significant changes in the genetic composition of SARS-CoV-2 spike glycoprotein genes, when compared to the WuhanHu-1 isolate from China. However, this is a preliminary study and we recommend that molecular epidemiology and surveillance programs against COVID-19 in Indonesia be improve

Concept of SARS-CoV-2 Vaccine Design to Fight COVID-19 Pandemic: A Review Insight

Cluster of pneumonia infection emerged in Wuhan, China due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Additionally, more than 190 countries have confirmed 82 million cases of SARS-CoV-2 infection. Currently, there is a SARS-CoV-2 epidemic, and no effective prophylactic methods are available. A vaccine is considered as an effective method to restrict an epidemic. Several vaccine designing techniques have been established, which is enabling researchers from various institutes for developing vaccine towards SARS-CoV-2 infections. In this review, we condense the development of vaccine research against SARS-CoV-

Computational study of Cu2+, Fe2+, Mn2+, Mn3+, Fe3+, CrO42-, Si4+, and Hg+ binding sites identification on cytokines to predict dental metal allergy: An in silico study.

Context: Metal allergy is a general term to describe allergic diseases due to the release of metal ion reactions in the body which are mediated by T cells and involve inflammatory cytokines that can cause morbidity and mortality. Molecular docking is an analysis that can be used to assess the interaction of ligand bonds with target proteins that are used to predict metal allergies caused by metal ions that stimulate cytokines. Aims: To analyze the binding sites of Cu2+, Fe2+, Mn2+, Mn3+, Fe3+, CrO42-, Si4+, and Hg+ ions on cytokines to predict dental metal allergy through a bioinformatics approach, in silico. Methods: Metal ion particles consisting of Cu2+, Fe2+, Mn2+, Mn3+, Fe3+, CrO42-, Si4+, and Hg+ were predicted to bind tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), interleukin (IL) IL-1b, IL-2, IL-4, IL-10, IL-13, IL-17, IL-23, and IL-33 act as target proteins were examined. Results: The blind docking simulation succeeded in identifying the comparison of the binding activity of metal ion particles on cytokines target proteins. The docking simulation results show that the metal ion with the most negative binding affinity value binds to the IL-17 protein. Conclusions: Metal ion particles consisting of Cu2+, Fe2+, Mn2+, Mn3+, Fe3+, CrO42-, Si4+, and Hg+ have the most negative binding affinity values for binding to IL-17 protein, which can cause allergic reactions predicted by molecular docking, in silico