In silico Antivirus Repurposing and its Modification to Organoselenium Compounds as SARS-CoV-2 Spike Inhibitors.

<b>Background and Objective:</b> The COVID-19, which has been circulating since late 2019, is caused by SARS-CoV-2. Because of its high infectivity, this virus has spread widely throughout the world. Spike glycoprotein is one of the proteins found in SARS-CoV-2. Spike glycoproteins directly affect infection by forming ACE-2 receptors on host cells. Inhibiting glycoprotein spikes could be one method of treating COVID-19. In this study, the antivirus marketed as a database will be repurposed into an antiviral SARS-CoV-2 and the selected compounds will be modified to become organoselenium compounds. <b>Materials and Methods:</b> The research was carried out using <i>in silico</i> methods, such as rigid docking and flexible docking. To obtain information about the interaction between spike glycoprotein and ligands, MOE 2014.09 was used to perform the molecular docking simulation. <b>Results:</b> The analysis of binding energy values was used to select the ten best ligands from the first stage of the molecular docking simulation, which was then modified according to the previous QSAR study to produce 96 new molecules. The second stage of molecular docking simulation was performed with modified molecules. The best-modified ligand was chosen by analyzing the ADME-Tox property, RMSD value and binding energy value. <b>Conclusion:</b> The best three unmodified ligands, Ombitasvir, Elbasvir and Ledipasvir, have a binding energy value of -15.8065, -15.3842 and -15.1255 kcal mol¹, respectively and the best three modified ligands ModL1, ModL2 and ModL3 has a binding value of -15.6716, -13.9489 and -13.2951 kcal mol¹, respectively with an RMSD value of 1.7109 Å, 2.3179 Å and 1.7836 Å.

Structural Design and Synthesis of Novel Cyclic Peptide Inhibitors Targeting Mycobacterium tuberculosis Transcription.

Tuberculosis (TB) remains one of the deadliest infectious diseases in the world. Although several established antitubercular drugs have been found, various factors obstruct efforts to combat this disease due to the existence of drug-resistance (DR) TB strains, the need for lengthy treatment, and the occurrence of side effects from drug-drug interactions. Rifampicin (RIF) is the first line of antitubercular drugs and targets RNA polymerase (RNAP) of Mycobacterium tuberculosis (MTB). Here, RIF blocks the synthesis of long RNA during transcription initiation. The efficacy of RIF is low in DR-TB strains, and the use of RIF leads to various side effects. In this study, novel cyclic peptides were computationally designed as inhibitors of MTB transcription initiation. The designed cyclic peptides were subjected to a virtual screening to generate compounds that can bind to the RIF binding site in MTB RNAP subunit ß (RpoB) for obtaining a new potential TB drug with a safe clinical profile. The molecular simulations showed that the cyclic peptides were capable of binding with RpoB mutants, suggesting that they can be possibility utilized for treating DR-TB. Structural modifications were carried out by acetylation and amidation of the N- and C-terminus, respectively, to improve their plasma stability and bioavailability. The modified linear and cyclic peptides were successfully synthesized with a solid-phase peptide synthesis method using Fmoc chemistry, and they were characterized by analytical HPLC, LC-ESI-MS+, and 1H NMR.

Epitope-Based Vaccine Design for Tuberculosis HIV Infection Through in silico Approach.

<b>Background and Objective:</b> Tuberculosis (TB) is one of the leading causes of HIV-related death among people living with it. TB occurs more often severe in a weakened immune system, particularly when a patient is infected with HIV. People infected with HIV are 15-22 times more likely to fall ill with TB. In this research, an epitope-based vaccine has been specially designed for people living with HIV, since the current tuberculosis vaccine Bacillus Calmette-Guerin (BCG) has been proven to cause more harm than good in treating patients suffering from poor immune systems. <b>Materials and Methods:</b> The epitopes were selected from polysaccharide-protein of Mycobacterium tuberculosis and protein envelope of the Human immunodeficiency virus. B cell epitopes have been predicted using BepiPred 2.0, while T cell epitopes predicted using SMM, both are provided by Immune Epitope Database (IEDB). <b>Results:</b> This research had designed vaccine combinations for each type of epitopes and types of the pathogen with world population coverage of >85% for MHC class I epitopes and >99% for MHC class II epitopes. <b>Conclusion:</b> With each epitope were selected based on how strong its bond with HLA and how many HLA can bind with it. As this research was done through <i>in silico</i> approach, <i>in vivo</i> test is still needed to guarantee the result of the designed vaccine.

Recent Progress and Challenges for Drug-Resistant Tuberculosis Treatment.

Control of Mycobacterium tuberculosis infection continues to be an issue, particularly in countries with a high tuberculosis (TB) burden in the tropical and sub-tropical regions. The effort to reduce the catastrophic cost of TB with the WHO's End TB Strategy in 2035 is still obstructed by the emergence of drug-resistant TB (DR-TB) cases as result of various mutations of the MTB strain. In the approach to combat DR-TB, several potential antitubercular agents were discovered as inhibitors for various existing and novel targets. Host-directed therapy and immunotherapy also gained attention as the drug-susceptibility level of the pathogen can be reduced due to the pathogen's evolutionary dynamics. This review is focused on the current progress and challenges in DR-TB treatment. We briefly summarized antitubercular compounds that are under development and trials for both DR-TB drug candidates and host-directed therapy. We also highlighted several problems in DR-TB diagnosis, the treatment regimen, and drug discovery that have an impact on treatment adherence and treatment failure.

Identification of DNA Methyltransferase-1 Inhibitor for Breast Cancer Therapy through Computational Fragment-Based Drug Design.

Epimutation by DNA Methyltransferase 1 (DNMT1), an epigenetic regulator enzyme, may lead to the proliferation of breast cancer. In this report, 168,686 natural products from the PubChem database were screened and modified by in silico method to acquire the potential inhibitor of DNMT1. The initial screening of PubChem natural products using Lipinski's and Veber's rules of three and toxic properties have resulted in 2601 fragment candidates. Four fragments from pharmacophore-based molecular docking simulation were modified by utilizing FragFP and the Lipinski's and Veber's rules of five, and resulted in 51,200 ligands. The toxicological screening collected 13,563 ligands for a series of pharmacophore-based molecular docking simulations to sort out the modified ligands, which had the better binding activity and interactions to DNMT1 compared to the standards, SAH, SAM, and SFG. This step resulted in five ligand candidates, namely C-7756, C-5769, C-1723, C-2129, and C-2140. The ADME-Tox properties prediction showed that the selected ligands are generally better than standards in terms of druglikeness, GI absorption, and oral bioavailability. C-7756 exhibited a stronger affinity to DNMT1 as well as better ADME-Tox properties compared to the other ligands.