Archive 21/1/22

In the new coronavirus (SARS-CoV-2), heparan sulfate is involved in the capture of viruses, and sialic acid modification of ACE2 weakens viral binding

A group from The University of Hong Kong etc. has reported on the effects of heparan sulfate and glycan modification of ACE2 in the infection of the new coronavirus (SARS-CoV-2).

Calu3 (lung epithelial cells) and Caco2 (intestine epithelial cells) are used in SARS-CoV-2 infection experiments. Heparinase was used to investigate the effects of heparan sulfate, and Neuraminidase (NA) was used for the effects of ACE2 glycan modification, with a particular focus on sialic acid.

As shown in the figure below, heparinase suppresses viral infection and shows that heparan sulfate is involved in the capture of the virus as a co-receptor for ACE2. For the sialic acid modification of ACE2, it is shown that the infection of the virus is rather stronger by cleaving the sialic acid with NA.

Evaluation of glycan structure of reference mAb (humanized IgG Type 1) in NIST, U.S.A.

NIST in the U.S. offers humanized IgG Type 1 mAb as a reference mAb. NS0 cells are used to manufacture this mAb. NS0 cell is a model cell line derived from non-secretory mouse myeloma, which is commercially used in biomedical research and the production of therapeutic proteins.

The status of glycan addition is reported by comprehensively following the results of 103 evaluations conducted at 73 institutions around the world. It is likely to be useful as glycan modification information of reference mAb of IgG Type 1.

Priority of vaccine administration for the new coronavirus (COVID-19): Should over-60s still be prioritized?

A group from The University of Colorado Boulder etc.  has simulated on the priority of vaccine administration for the new coronavirus (COVID-19).

Five age groups of vaccination were assumed, and simulated changing the combination of the following parameters: vaccine rollout speeds to the population (0.05% to 1%/day), infection rates (1.15, 1.5), vaccine efficacy (90%), and also the case that the effectiveness of the vaccine decreases with age (60 years old = 90% – > 80 years old = 50%).
The results vary depending on the conditions, and the best choice replaced between the case that prioritizes the over-60s and the one that prioritizes 20 ~ 59 year-olds. However, since the prerequisites are always changing in reality, overall, it would be a better choice to prioritize the over-60s .

The most dynamic unifying predictor of the disease pathology of the new coronavirus (COVID-19) is the saliva viral load.

A group from Yale University School of Medicine etc. has reported that the most dynamic unifying indicator of the pathophysiology of the new coronavirus (COVID-19) is the saliva viral load.

Existing markers for COVID-19 include inflammatory cytokines and chemokines (CXCL10, IL-6, IL-10), inflammasome (IL-18, IL-1β), interferon (IFNα, IFNγ, IFNλ), etc.), however, they have found that the saliva virus load was very well correlated with the disease pathology. The nasopharyngeal viral load was also evaluated as a comparison. The amount of virus in saliva and nasopharyngeal (RNA copies/mL) was calculated from Ct values of RT-PCR extracting RNA from saliva. For the discrimination accuracy among non-hospitalization, moderate, severe, and deceased, strong predictive ability was obtained as follows, moderate disease (AUC = 0.96), severe disease (AUC = 0.89), and fatal (AUC = 0.91).

The upper figure of the below shows the correlation between the saliva viral load and the disease pathology, and the lower figure shows the nasopharyngeal viral load and the disease pathology.

Demonstration of ultra-high recognition method of cells combining Deep Learning and lectin microarray

A group from the National Institute of Child Health and Development demonstrated that deep learning can be combined with glycan profiling data from lectin microarrays to recognize cell differences with ultra-high accuracy.

The lectin microarray used was LecChip Ver1.0 of GlycoTechnica. The lectin microarray has 45 kinds of carefully selected natural lectins and has been widely used worldwide as a de facto standard for lectin arrays since its launch in 2007.
Deep Learning, as you know, is now used in various fields as one of methods of AI, and in this research, Google’s TensorFlow was used as the backend, and Keras was used as wrapper software. The layer configuration of this deep Leaning had an input layer of 45 (the same number of lectins) and an output layer of 5 (to discriminate five cells), and hidden layer from 1 to 5. There were five types of cells evaluated (Pluripotent stem cell, Mesenchymal stromal cell, Endometrial and ovarian cancer cell, Cervical cancer cell, Endometrial cell), and a total of 1,577 samples were used for the evaluation.
The results were astonishing as follows, and showed a high recognition accuracy of 97.4% overall.



Deep Learning software used in this paper is sold under the soft name “SA/DL Easy” from Mx. “SA/DL Easy” does not require any knowledge of programming such as Python, you can build neural networks and run deep learning just by clicking a mouse using a one-dimensional array dataset (such as glycan profiling data of lectin microarrays used in the above paper) as an input. “SA/DL Easy” is a quite user-friendly software to use Deep Learning. If you are interested in this software, please contact Mx.

U.S. Department of State releases a FACT Sheet on origin of the new coronavirus (SARS-CoV-2)

On December 15, 2020, Blog Admin uploaded an article saying that the new coronavirus (SARS-CoV-2) is likely an artificial product, citing “The 2nd Yan Report”.

On January 15, 2021, the U.S. Department of State released a FACT Sheet titled Activity at the Wuhan Institute of Virology (WIV).

In this article, the U.S. Department of State avoids saying that SARS-CoV-2 originated in WIV, but it does show three FACTs in WIV as follows.

  1. In the fall of 2019, there were several researchers who showed similar pathology to COVID-19 were in WIV.
  2. Since 2016, WIV has been studying bat coronaviruses including “RatG13” (96.2% similar to SARS-CoV-2).
  3. Secret Chinese biological weapons researches were being conducted on WIV

Specificity of antibody responses in asymptomatic to mild new coronavirus (COVID-19) patients in Japan

A group from School of Medicine, Keio Univ. has reported a cohort study on antibody responses in asymptomatic to mild new coronavirus (COVID-19) patients who were positive for PCR testing in Japan.

Many overseas cohort studies have targeted patients with more symptomatic and severe cases, and antibody responses have appeared in 80% to 100% of patients three weeks after infection. Numerous studies have also shown that these antibodies correlate with age, severity, lymphopenia, and serum CRP levels.

This cohort study was conducted in asymptomatic to milder patients than in known cohort studies, and 87.5% of asymptomatic patients and 23.5% of mild patients did not have antibody responses.

Metyrene blue blocks all excess cytokines and inflammatory mediators from the new coronavirus (COVID-19)

A group of Fondazione IRCCS Estituto Neurologico Carlo Besta, Via Padova, Milan, Italy etc. believes that the low efficacy of antiviral drugs such as cytokine inhibitors is (1) probably due to delays in administration in which the virus causes an inflammatory response and is no longer the main protagonist, (2) the relatively low efficacy of cytokine inhibitors is explained because they only act on one or a few of the dozens of cytokines, and (3) other inflammatory mediators (reactive oxygen and nitrogen species) are not targeted.

When inflammatory mediators are over-generated, reactive species cause extensive cell and tissue damages. The only drug known to inhibit the over production of active species and cytokines is methylene blue, a low-cost dye with antiseptic properties that is effectively used in the treatment of malaria, urinary tract infections, septic shock, and methaemoglobinaemia. They suggest testing methylene blue to treat COVID-19 acute respiratory distress syndrome.

M Protein Comparison: SARS-CoV-2, SARS-CoV, MERS-CoV

The virus envelope of the new coronavirus (SARS-CoV-2) contains S proteins, E proteins, and M proteins. Because S proteins are so deeply involved in the infection, so much research has been done targeting S proteins. However, very little information is available on the structure and function of M proteins. In general, the function of the M protein is understood as the protection of the viral particle structure, and it is thought that the RNA-N protein complex and the S-protein bind to the M protein, bud out as infectious particles in the small cavity, and are released out of the cell by exocytosis.

A group of King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia focused on M proteins and its differences between SARS-CoV-2, SARS-CoV, and MERS-CoV.

The following points are pointed out:

The M protein is a transmembrane protein, and there are N-terminal domain and C-terminal domain on either side of the three transmembrane domains.
From the viewpoint of the amino acid sequence, SARS-CoV-2 has an S4 residue (221-224) inserted, and it would be an unique feature of SARS-CoV-2.
As intrinsically disordered regions, there are two regions (1-7, 205-222) in SRAS-CoV-2, three regions (1-6, 207-210, 216-221) in SARS-CoV, and two regions (1-6, 216-219) in MERS-CoV, and these differences would reflect viral particles protection capability in different environments of the virus and might be related to viral transmission mode.
Domains that could be potential B-cell epitopes would be:

Evaluation of saponins and tannins targeting SARS-CoV-2 precursor protein main protease (Mpro) as an inhibitor of the new coronavirus (SARS-CoV-2)

Similar to the last blog, a group of Ladake Akintola Unyv. of Technology, Ogbomoso, Oyo State Nigeria has evaluated the inhibitory effects of saponins and tannins by molecular docking and molecular dynamics simulations, targeting SARS-CoV-2 precursor protein main protease (Mpro).

Saponins are found in plant roots, leaves, stems, etc., but are especially found in beans and are known to have antioxidant properties. On the other hand, tannins are astringent components contained in many seeds, and astringency of persimmons is a good example of tannin. Tannins strongly bind to proteins and have the effect of causing denaturation, and the effect of tannins on their properties is called “Astringent.”

The results are as follows, but may show potential antiviral effects that are no less so than remdesivir. Evaluation in vivo is expected.

Ligands Binding affinity (ΔG) kcal/mol Inhibition constant (Ki), µM
Priverogenin A − 8.3 0.83
Arjunic acid − 8.1 1.16
Theasapogenol B − 8.1 1.16
Euscaphic Acid − 8.0 1.37
Punicalagin − 9.0 0.25
Punicalin − 8.6 0.5
Ellagic acid − 8.4 0.7
Corilagin  − 8.2  0.98
Gallagic acid − 8.1 1.16
Remdesivir − 7.6 2.7


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