COVID-19 latest papers

1. “COVID - 19 latest papers Review”
Subash Chandra Pakhrin
PhD Student
Wichita State University
Wichita, Kansas
1

2. Introduction
• alpha, beta, delta and gamma
• alpha and beta coronaviruses are known to infect humans
• Coronaviruses are spherical in shape with an average diameter of 80 –
120 nm
• Under the electron microscope, the virus are characterized by surface
projections (Spike Glycoprotein / S protein)

3. Introduction
Source: https://commons.wikimedia.org/wiki/File:3D_medical_animation_corona_virus.jpg
Figure 1: 3D medical animation of corona virus

4. Objective
• Understand underlining mechanism of COVID-19 virus
• Understand different protein structure prediction of COVID-19 virus
• Role of Glycosylation Post Translation Modification at Spike Protein
• Understand how AI / ML is used to identify drug of COVID-19 virus
• Understand how Next Generation Sequencing is used to identify
intermediate host.

5. Angiotensin converting enzyme 2 (ACE2)
• Angiotensin converting enzyme 2
(ACE2) is an essential regulator
expressed in the heart, lung etc.
• Coronaviruses enter into human
lung cell through ACE2 [35].
• Molecules that can block S protein
binding to ACE2 may potentially
prevent the virus from entering
human cells and serve as an
effective antiviral drug.
Figure 2: ACE2 receptors interaction with the Spike protein

6. ACE2 receptors interaction with the Spike protein
• ACE2 receptors interacts with
the spike protein (S) of SARS-
COV-2 as confirmed by
structural analysis of SARS-COV-
2 [36] [37]
Figure 3: structural analysis of SARS-COV-2

7. Protein structure prediction
• Zhang lab developed three dimensional structural models and
function for all proteins of SARS-CoV-2
• The structure models are generated by the C-I-TASSER pipeline, which
utilizes deep convolutional neural-network based contact-map
predictions
• Based on this idea, authors designed a series of peptides that can
strongly bind to SARS-CoV-2 receptor binding domain (RBD) in
computational experiments [41]

8. Protein structure prediction

9. Protein structure prediction
Figure 4: 3-chymotrypsin-like cysteine protease (3CLpro)

10. Protein structure prediction
• The receptor binding domain (RBD)
located on the head of Spike protein,
bind with the cellular receptor
angiotensin-converting enzyme 2
(ACE2), initiating the membrane
fusion of the virus and host cell.
Figure 5: Spike glycoprotein (S)

11. Protein structure prediction
• Senior et al. [40] developed a model called AlphaFold
• AlphaFold is based on a deep learning architecture and it predicts
protein structure accurately when structures of similar proteins are
not available.
• AlphaFold predicted the structures of six proteins related to SARS-
CoV-2 (the membrane protein, protein 3a, nsp2, nsp4, nsp6, and
papain-like protease)

12. Protein structure prediction
Figure 6: SARS-COV-2 MEMBRANE PROTEIN

13. Spike Glycoprotein prediction
• B. Robson [14] worked to find a short section of viral protein
sequence suitable for preliminary design proposal for a peptide
synthetic vaccine, and to explore some design possibilities.
• Author used Q-UEL systems to access relevant and emerging
literature
• KRSFIEDLLFNKV motif was found to be well conserved and
corresponds to the region around one sites of the SARS virus that are
believed to be required for virus activation for cell entry.
• This motif and surrounding variations formed the basis for proposing
a specific synthetic vaccine epitope.

14. Virus Structure prediction
• Yan Gao, et al. [43] found Non Structural Protein (nsp) 12 or RdRp is
the central component of corona virus replication and appears to be a
primary target for the antiviral drug, remdesivir.
• Authors reported Cryogenic Electron Microscopy structure of nsp12 in
complex with cofactors nsp7 and nsp8 at 2.9-Å resolution.
• nsp12 possesses a newly identified β-hairpin domain at its N
terminus.
• The structure provides a basis for the design of new antiviral
therapeutics targeting viral protein nsp12.

15. Virus Structure prediction
• Ibrahim, et al. [23], found spike protein of coronavirus is the main
driving force for host cell recognition
• COVID-19 spike binding site to the cell-surface receptor (GRP78) is
predicted using combined molecular modeling docking and structural
bioinformatics.
• Authors, found that the binding is more favorable between regions III
(C391-C525) and IV (C480-C488) of the spike protein model and
GRP78.
• Region IV is the main driving force for GRP78 binding with the
predicted binding affinity of -9.8 kcal/mol.

16. Figure 7: (A) Part of the multiple sequence alignment for the spike protein of all of the currently reported human coronaviruses
strains (COVID-19, SARS, MERS, NL63, 229E, OC43, and HKU1). The red highlighted residues are identical, while yellow
highlighted residues are conserved among the seven HCoVs. Secondary structures are represented at the top of the MSA for
the COVID-19 spike, while the surface accessibility is shown at the bottom (blue, surface accessible, cyan, partially accessible,
and white for buried residues). The four regions of the spike protein are shaded with green, blue, magenta, and red for regions
I, II, III, and IV, respectively.
Virus Structure prediction

17. Figure 8: (B) Structural superposition of SARS spike structure (green cartoon) and
COVID-19 spike model (cyan cartoon).
Virus Structure prediction

18. Figure 9: (A) The structure of the spike protein model of COVID-19 in its homo - trimer state (colored
cartoon). Two chains, A (green) and B (cyan) are in the closed conformation, while chain C (magenta)
is the open configuration that makes it able to recognize the host cell receptor. Region IV of the spike
(C480-C488), which we suggest is the recognition site for cell-surface GRP78, is shown in the black
cartoon in the enlarged panel.
Virus Structure prediction

19. Figure 10: (B) Region III of spike (black cartoon)
Virus Structure prediction

20. Figure 11: The structure of the docking complexes of GRP78 (green cartoon) and COVID-19 spike (yellow
cartoon) regions I and II (A)
Virus Structure prediction

21. Figure 12: The structure of the docking complexes of GRP78 (green cartoon) and COVID-19 spike (yellow
cartoon) and regions III and IV (B)
Virus Structure prediction

22. Figure 13: (A) The proposed binding mode of the host cell GRP78 (cyan surface) and the COVID-19 spike model
(green surface) through region IV (C480-C488) (red surface). The amino acids from the GRP78 SBDβ that interact
with the spike protein region IV (red cartoon) are labeled and represented in yellow sticks in the enlarged panel.
Virus Structure prediction

23. Figure 14: (B) The proposed recognition mode of the COVID-19 spike (red surface) and cell-surface GRP78 (green
surface) through the spike protein region C480-C488.
Virus Structure prediction

24. Post Translation Modification
• Naveen Vankadari, et al. [32] predicted N - linked and O - linked
glycosylation occur at spike protein
• Many COVID - 19 proteins are modified by PTMs
• Palmitoylation occurs at envelope protein
• N - linked and O - linked glycosylation occurs at membrane protein
• Phosphorylation and ADP - ribosylation occurs at nucleo capsid
protein

25. Figure 15: Overall homo - trimer model structure of the COVID-19 spike glycoprotein (A) ligand unbound
conformation (B) ligand-bound conformation. The three protomers are colored pink, green and cyan. S1- and S2-
domains labelled. Receptor-binding induced hinge motion of S1 is distinguishable.
Post Translation Modification

26. Figure 16: (A and B) Ribbon and a surface diagram showing the docking interface of modelled COVID-19 (grey)
and human CD26 (orange)(PDB: 4QZV) complex. Predicted key residues involved in the interaction are shown in
sticks (CD26 residues are underlined) (C) Overall docking results showing the surface model of CD26 with COVID-
19 predicted homo - trimer structure (ligand-bound conformation).
Post Translation Modification

27. Figure 17: Predicted N-linked glycosylation sites for COVID-19(D) and SARS-CoV (E). Unique glycosylation sites
are colored in Blue, and shared sites are shaded in Red.
Post Translation Modification

28. Post Translation Modification, Glycosylation
• Oligosaccharides attaches via nitrogen atom on the side chain of
asparagine ( N-Linked)
• Oligosaccharides attaches via oxygen atom on the side chain of threonine
or serine (O-Linked)
Figure 18: N-linked glycosylation and O-linked glycosylation.

29. Post Translation Modification, Glycosylation
• Celia Henry Arnaud [46] reported that “Viruses use glycosylation to hide
their viral proteins”
• Glycosylation can act as camouflage because the sugars on viral proteins
come from the animal or person that has been infected.
• Viruses commandeer the enzymatic machinery that host cells use to add
sugars to their own proteins and get those enzymes to attach glycan's to
viral proteins.
• SARS-CoV-2 spike protein’s is covered in carbohydrates, but it’s slightly
lower than in HIV
• SARS-CoV-2’s sparser glycosylation means that the sugars are more
naturally processed than the ones in HIV
Note: Glycosylation helps to identify different types of blood groups

30. Camouflaging nature of SARS-CoV 2
• Author suggests that the coronavirus’s glycan shield may not be as effective as
that of HIV
• When a virus infects a human cell, the cell’s ribosome picks up viral RNA and
translates it into proteins inside a part of the cell called the endoplasmic
reticulum.
• Cellular enzymes start adding sugars to newly synthesized proteins as they exit
the ribosome.
• Once synthesized, the proteins travel through the Golgi apparatus to be secreted
into the cell.
• Along the way, those added glycan’s go through a maturation process in which
other enzymes iteratively trim sugar structures and decorate them with other
types of sugars to yield complex, branched structures.
• The more processed the sugars are, the more they look like the host’s own
sugars.

31. Next Generation sequencing application
• Lam et al. found several putative pangolin CoV sequences with 85.5%
to 92.4% similarity to 2019-nCoV, hence pangolins serves as a
potential intermediate host.
• Jeong-Min Kim, et al. [5] Sequence homology of SARS-CoV-2 with
SARS-CoV, and MERS-CoV was 77.5% and 50%, respectively.

32. Next Generation sequencing application
Figure 19:Intermediate host of COVID 2019.

33. AI / ML based approaches for Drug discover
• Zhang et al. [26] used dense fully connected neural network
architecture, trained to predict binding affinities on the PDBbind
database, in order to identify potential inhibitors of the 3C-like
protease.
• Ren Kong et al. [15] introduce COVID-19 Docking Server, that predicts
the binding modes between COVID-19 targets and the ligands
including small molecules, peptide and antibody.
• Anh-Tien Ton, et al. [18] a novel deep learning platform was used to
identify potential inhibitors of the SARS-CoV-2 main protease (Mpro)
by screening 1.3 billion compounds

34. AI / ML based approaches for Drug discover
• Muhammad, et al. [13] Authors analyzed the 3CLpro sequence,
constructed its 3D homology model, and screened it against a
medicinal plant library containing 32,297 potential anti-viral
phytochemicals / traditional Chinese medicinal compounds.
• Authors revealed top nine hits which might serve as potential anti-
SARS-CoV-2 lead molecules for drug development process to combat
COVID-19.
• Wang, et al. [16] screened some of the FDA approved anti-virus and
found that remdesivir and chloroquine could effectively inhibit the
virus

35. References
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36. References
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37. References
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molecules, peptides and antibodies against potential targets of COVID-19
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38. References
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39. References
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40. References
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41. References
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42. List of Abbreviations
• receptor-binding motif (RBM)
• angiotensin-converting enzyme 2 (ACE2)
• N terminal domain (NTD) and a C terminal domain (CTD)
• Real-time reverse transcription polymerase chain reaction (RT-PCR)
• 3-chymotrypsin-like cysteine protease (3CLpro)
• Antagonist: a substance that interferes with or inhibits the physiological action of another.
• Lesion: a region in an organ or tissue which has suffered damage through injury or disease, such
as a wound, ulcer, abscess, or tumor.
• A least absolute shrinkage and selection operator (LASSO)
• Non Structural Protein (NSP)
• Glucose Regulated Protein 78 (GRP78)
• Substrate Binding Domain (SBD)
• RdRp: RNA-dependent RNA polymerase (RdRp also called nsp12)
• This scenario could occur in stressed cells when GRP78 us overexpressed and translocate from the
Endoplasmic Reticulum (ER) to the cell membrane (M).
• cluster of differentiation 26 (CD26)
• Solvent Accessible Surface Area (SASA)