Context: The COVID-19 outbreak is caused by the transmission and infection of SARS-CoV-2 at the end of 2019. It has led many countries to implement lockdown policies to prevent the viral spreading. Problems arise in a COVID-19 patient because of viral infection that leads to a systemic response in the immune system, specifically due to cytokine storm. Moreover, the antiviral drugs that have not been found. Indonesia had a variety of traditional medicines, such as is ‘jamu’. It consists of a mixture of natural ingredients such as Moringa oleifera Lam. and Curcuma longa L. Aims: To identify the activity of dual inhibitors as antiviral and anti-inflammatory agents from herbal combination compounds. Methods: Sample was collected from PubChem (NCBI, USA) and Protein Data Bank (PDB), then drug-likeness analysis using Lipinski rule of five in SCFBIO web server and bioactive probability analysis of bioactive compounds were conducted by PASS web server. Furthermore, the blind docking method was performed using PyRx 0.8 software to determine the binding activity and molecular interaction by PoseView web server and PyMol software v2.4.1 (Schrödinger, Inc, USA). Results: Cryptochlorogenic acid and curcumin have been computationally proven as dual inhibitors for antivirals by inhibiting Mpro SARS-CoV-2 and as anti-inflammatory through inhibition of NFKB1 activity. However, the results are merely computational so that it must be validated through a wet lab research. Conclusions: The combination of Moringa oleifera Lam. and Curcuma longa L. is predicted to have antiviral and anti-inflammatory activity through dual inhibitor mechanism played by cryptochlorogenic acid and curcumin.

https://jppres.com/jppres/pdf/vol10/jppres21.1174_10.1.138.pdf

Herbal combination from Moringa oleifera Lam. and Curcuma longa L. as SARS-CoV-2 antiviral via dual inhibitor pathway: A viroinformatics approach

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In Silico Screening of Bioactive Compounds from Syzygium cumini L. and Moringa oleifera L. Against SARS-CoV-2 via Tetra Inhibitors

/pdf/bioactive-compounds-from-purslane-portulaca-oleracea-l-and-2ako7rb8.pdf

Bioactive Compounds from Purslane (Portulaca oleracea L.) and Star Anise (Illicium verum Hook) as SARS-CoV-2 Antiviral Agent via Dual Inhibitor Mechanism: In Silico Approach

SARS-CoV-2 infection in humans also causes cytokine storm and can lead to patient death, this condition occurs due to the excessive release of pro-inflammatory cytokines by immune cells. SARS-CoV-2 infects cells in the human respiratory tract. Spike glycoprotein aims to bind to ACE2 in the viral entry process. Several studies have suggested that the SARS-CoV-2 spike is an ideal target for drug design. Camellia sinensis or black tea is a member of the Theaceae family and the genus Camellia. Camellia is a vast genus to East India, the Malay Peninsula, and Southeast Asia, together with Indonesia. In truth, Camellia sinensis is a tropical fruit that has been used as a traditional medicine for hundreds of years globally. This study is to identify the bioactive compounds from Camellia sinensis as an antiviral agent via spike glycoprotein inhibitor mechanisms against the SARS-CoV-2 infection through the in silico approach

/pdf/molecular-mechanism-of-black-tea-camellia-sinensis-as-sars-3n213lui.pdf

Molecular Mechanism of Black Tea (Camellia sinensis) as SARS-CoV-2 Spike Glycoprotein Inhibitor through Computational Approach

Human papillomavirus (HPV) is one of the causes of cervical cancer in women. These viruses have DNA-type genetic material, are not enveloped, and are divided into two types based on their ability to trigger cancer. High-risk HPV is the type of HPV that often causes cervical cancer cases, this is due to the high expression of oncoprotein E6. E6 works through the inhibition and degradation of p53 to trigger cancer. HPV drugs tend to be expensive and must use alternative solutions such as the herbal Curcuma longa L. Curcuma longa L. is an herbal plant that is widely used by the public for their daily needs, for example as an antiviral, antioxidant, and anti-inflammatory. This study aims to predict the molecular mechanism and screening of drug candidate compounds in Curcuma longa L. to inhibit the activity of the HPV E6 protein through a bioinformatics approach. This study used in silico methods such as docking simulations and molecular interaction analysis to identify potential antiviral candidate compounds. Curcuma longa L. can act as an antiviral through the binding activity of Curcumin compounds in preventing the E6-p53 complex through the specific domains and stable because it have a many number of hydrogen bonds. We recommend the E6-binding domain for further research as a target for HPV drug design and the results of this study are yet to be verified through wet lab testing

https://sainstek.ppj.unp.ac.id/index.php/sainstek/article/download/2/1

Computational Drug Design Study of Curcuma longa L. Compound as HPV-16 Antiviral Candidate Against Cervical Cancer

Sudden emergence and a rapid outbreak of SARS-CoV-2 accompanied by a devastating impact on the economy and public health has driven extensive scientific mobilization to study and elucidate the various associated concerns about SARS-CoV-2. Bioinformatics plays a crucial role in addressing and providing solutions to questions about SARS-CoV-2. It helps shorten the duration for the vaccine development process and the discovery of potential clinical interventions through the simulation and information retrieval, and the development of well-ordered information hubs and resources, which are essential to derive data and meaningful findings from the current massive information about SARS-CoV-2. Advanced algorithms in this field also provide approaches that are essential to elucidate the relationship, origin, and evolutionary process of SARS-CoV-2. Here, we report essential bioinformatics entities, such as database and platform development, molecular evolution and phylogenetic analyses, and vaccine designs, that are useful to solve the SARS-CoV-2 conundrum.

Retrieval and Investigation of Data on SARS-CoV-2 and COVID-19 Using Bioinformatics Approach.

Rett syndrome (RTT) is mainly caused by mutations in methyl CpG-binding protein 2, cyclin-dependent kinase-like 5, or forkhead box protein G1. These RTT-causing proteins harbor an intrinsically disordered region (IDR) whose conformation exhibits spatiotemporal heterogeneity, which not only confer versatility to the protein, but also implicates them in diseases. The IDR generally evolves more rapidly than an ordered structure. In this study, we examined the relationship between pathogenic RTT-associated point mutations in RTT-causing proteins and the evolutionary dynamics of sequence features including structural order–disorder, phosphorylation sites, and evolutionary rates. We also analyzed the molecular properties and evolution of proteins that interact with RTT-causing proteins in terms of phylogenetic profiles, tissue specificity, subcellular localization, expression level, and functions. The results indicate that constrained IDRs may function by forming contacts with other regions in the protein sequence causing pathogenic missense mutations likely to arise in the rapidly evolving IDR and affect molecular networks, leading to disease. The results also provide novel insights into the genetic basis for RTT and the evolution of the neocortex in higher vertebrates.

/pdf/evolutionary-analysis-of-rett-syndrome-causing-proteins-and-22mp5s244p.pdf

Evolutionary Analysis of Rett Syndrome-Causing Proteins and Their Pathogenic Missense Point Mutations: Structural Order–Disorder, Post-Translational Modifications, Evolutionary Rates, and Interacting Proteins

Muhamad Fahmi

Papers

Retrieval and Investigation of Data on SARS-CoV-2 and COVID-19 Using Bioinformatics Approach.

Evolutionary Analysis of Rett Syndrome-Causing Proteins and Their Pathogenic Missense Point Mutations: Structural Order–Disorder, Post-Translational Modifications, Evolutionary Rates, and Interacting Proteins