BackgroundThe cervical cancer is the second most prevalent cancer for the woman in the world. It is caused by the oncogenic human papilloma virus (HPV). The inhibition activity of histone deacetylase (HDAC) is a potential strategy for cancer therapy. Suberoylanilide hydroxamic acid (SAHA) is widely known as a low toxicity HDAC inhibitor. This research presents in silico SAHA modification by utilizing triazole, in order to obtain a better inhibitor. We conducted docking of the SAHA inhibitor and 12 modified versions to six class II HDAC enzymes, and then proceeded with drug scanning of each one of them.ResultsThe docking results show that the 12 modified inhibitors have much better binding affinity and inhibition potential than SAHA. Based on drug scan analysis, six of the modified inhibitors have robust pharmacological attributes, as revealed by drug likeness, drug score, oral bioavailability, and toxicity levels.ConclusionsThe binding affinity, free energy and drug scan screening of the best inhibitors have shown that 1c and 2c modified inhibitors are the best ones to inhibit class II HDAC.

Meningitis infection is one of the major threats during Hajj season in Mecca. Meningitis vaccines are available, but their uses are limited in some countries due to religious reasons. Furthermore, they only give protection to certain serogroups, not to all types of meningitis-inducing bacteria. Recently, research on epitope-based vaccines has been developed intensively. Such vaccines have potential advantages over conventional vaccines in that they are safer to use and well responded to the antibody. In this study, we developed epitope-based vaccine candidates against various meningitis-inducing bacteria, including Streptococcus pneumoniae, Neisseria meningitidis, and Haemophilus influenzae type b. The epitopes were selected from their protein of polysaccharide capsule. B-cell epitopes were predicted by using BCPred, while T-cell epitope for major histocompatibility complex (MHC) class I was predicted using PAProC, TAPPred, and Immune Epitope Database. Immune Epitope Database was also used to predict T-cell epitope for MHC class II. Population coverage and molecular docking simulation were predicted against previously generated epitope vaccine candidates. The best candidates for MHC class I- and class II-restricted T-cell epitopes were MQYGDKTTF, MKEQNTLEI, ECTEGEPDY, DLSIVVPIY, YPMAMMWRNASNRAI, TLQMTLLGIVPNLNK, ETSLHHIPGISNYFI, and SLLYILEKNAEMEFD, which showed 80% population coverage. The complexes of class I T-cell epitopes–HLA-C*03:03 and class II T-cell epitopes–HLA-DRB1*11:01 showed better affinity than standards as evaluated from their ΔGbinding value and the binding interaction between epitopes and HLA molecules. These peptide constructs may further be undergone in vitro and in vivo testings for the development of targeted vaccine against meningitis infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes COVID-19 which is responsible for respiratory illness infection in humans. The virus was first identified in China in 2019 and later spread to other countries worldwide. This study aims to identify the bioactive compounds from mangosteen (Garcinia mangostana L.) as an antiviral agent via dual inhibitor mechanisms against two SARS-CoV-2 proteases through the in silico approach. The three-dimensional structure of various bioactive compounds of mangosteen from the database was examined. Furthermore, all the target compounds were analyzed for drug, antiviral activity prediction, virtual screening, molecular interactions, and threedimensional structure visualization. It aimed to determine the potential of the bioactive compounds from mangosteen that can serve as antiviral agents to fight SARS-CoV-2. Results showed that the bioactive compounds from mangosteen have the prospective to provide antiviral agents that contradict the virus via dual inhibitory mechanisms. In summary, the binding of the various bioactive compounds from mangosteen results in low binding energy and is expected to have the ability to induce any activity of the target protein binding reaction. Therefore, it allows various bioactive compounds from mangosteen to act as dual inhibitory mechanisms for COVID-19 infection.

Histone deacetylase (HDAC) has a critical function in regulating gene expression. The inhibition of HDAC has developed as an interesting anticancer research area that targets biological processes such as cell cycle, apoptosis, and cell differentiation. In this study, an HDAC inhibitor that is available commercially, suberoyl anilide hydroxamic acid (SAHA), has been modified to improve its efficacy and reduce the side effects of the compound. Hydrophobic cap and zinc-binding group of these compounds were substituted with boron-based compounds, whereas the linker region was substituted with p-aminobenzoic acid. The molecular docking analysis resulted in 8 ligands with ΔG binding value more negative than the standards, SAHA and trichostatin A (TSA). That ligands were analyzed based on the nature of QSAR, pharmacological properties, and ADME-Tox. It is conducted to obtain a potent inhibitor of HDAC class II Homo sapiens. The screening process result gave one best ligand, Nova2 (513246-99-6), which was then further studied by molecular dynamics simulations.

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Pharmacokinetics and druglikeness propertiesSwiss ADME is a tool based on the website (http:// www.swissadme.ch) that is used to estimate the ADME, pharmacokinetics and drug-likeness

COVID-19 is a syndrome affecting pulmonary function but rather in serious conditions leads to death. Kencur (Kaempferia galanga L.) is a type of rhizome plant in Indonesia that is used as an herbal medicine called Jamu because it is believed to be able to cure various types of diseases. One of which is for anti-virus. The goal of this study was to see how effective the compounds in kencur are against COVID-19 with a molecular docking strategy. Kencur biological activities were obtained from the library and the design of the Acute Respiratory Syndrome Main protease (Mpro) has been gained from the protein data bank website. In addition, the biological activities in kencur were examined utilizing Lipinski's five-point concept was used to evaluate their substance molecular characteristics. Molecular docking analysis was performed with the PyRx Virtual Screening Tool software. The PyRx program was used for molecular docking simulation. While, the Discovery Studio Visualizer program was used to visualize the interaction between SARS-CoV-2 (Mpro) and the pharmacologically active metabolites in kencur. The docking evaluation on three antiviral substances revealed that Quercetin had the lowest binding energy when bound with Mpro and thus had the greatest potential as a viral inhibitor.

The SARS-CoV-2 or COVID-19 pandemic has reached a new height with an unprecedented infection rate and mortality post-world war II history. However, there is no particular designed drug for COVID-19 up to this point. Thus, there exist three strategies for COVID-19 drug design; drug repurposing option, herbal medicine development, and transcriptomics-based drug lead. As the most underutilized option, transcriptomics-based drug lead could be leveraged to deal with SARS-CoV-2 infection. One of the main methods to block the SARS-CoV-2 infection is to inhibit the RNA polymerase enzyme that is responsible to the viral replication. In this regard, the objective of the strategy is to design the anti-sense siRNA drug and lead to inhibit the mRNA of the RNA Polymerase Enzyme (RdRp) gene that encodes the viral RNA Polymerase of the SARS-CoV-2. The Computer-Aided Drug Design (CADD)-based method was leveraged with sequence retrieval of 24 RdRp gene sequences, multiple sequence alignment, phylogenetic tree reconstruction, 2D/3D RNA structure predictions, and RNA-RNA docking. Both the RNAalifold conserved structure from the RdRp genes and the RNAfold structure of the siRNA for blocking the conserved structure are negative or less than 0 kcal/mol. The predicted RNA docking occurred with the best RMSD score of 22.53 Å, which is beyond the accepted threshold of 10-20 Å. Based on the findings, the 2D/3D structures of both the siRNA and mRNA could be elucidated, and the docking between them is feasible. However, this finding should be elucidated in the wet laboratory setting for the final lead validation.