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. 2020 Aug 26;12(9):942.
doi: 10.3390/v12090942.

Optimization Rules for SARS-CoV-2 Mpro Antivirals: Ensemble Docking and Exploration of the Coronavirus Protease Active Site

Shana V Stoddard  1 , Serena D Stoddard  1   2 , Benjamin K Oelkers  1 , Kennedi Fitts  1 , Kellen Whalum  1 , Kaylah Whalum  1 , Alexander D Hemphill  1 , Jithin Manikonda  1 , Linda Michelle Martinez  1 , Elizabeth G Riley  1 , Caroline M Roof  1 , Nowreen Sarwar  1 , Doni M Thomas  1 , Emily Ulmer  1 , Felissa E Wallace  1   3 , Pankaj Pandey  4 , Sudeshna Roy  5
Affiliations

Optimization Rules for SARS-CoV-2 Mpro Antivirals: Ensemble Docking and Exploration of the Coronavirus Protease Active Site

Shana V Stoddard et al. Viruses. .

Abstract

Coronaviruses are viral infections that have a significant ability to impact human health. Coronaviruses have produced two pandemics and one epidemic in the last two decades. The current pandemic has created a worldwide catastrophe threatening the lives of over 15 million as of July 2020. Current research efforts have been focused on producing a vaccine or repurposing current drug compounds to develop a therapeutic. There is, however, a need to study the active site preferences of relevant targets, such as the SARS-CoV-2 main protease (SARS-CoV-2 Mpro), to determine ways to optimize these drug compounds. The ensemble docking and characterization work described in this article demonstrates the multifaceted features of the SARS-CoV-2 Mpro active site, molecular guidelines to improving binding affinity, and ultimately the optimization of drug candidates. A total of 220 compounds were docked into both the 5R7Z and 6LU7 SARS-CoV-2 Mpro crystal structures. Several key preferences for strong binding to the four subsites (S1, S1', S2, and S4) were identified, such as accessing hydrogen binding hotspots, hydrophobic patches, and utilization of primarily aliphatic instead of aromatic substituents. After optimization efforts using the design guidelines developed from the molecular docking studies, the average docking score of the parent compounds was improved by 6.59 -log10(Kd) in binding affinity which represents an increase of greater than six orders of magnitude. Using the optimization guidelines, the SARS-CoV-2 Mpro inhibitor cinanserin was optimized resulting in an increase in binding affinity of 4.59 -log10(Kd) and increased protease inhibitor bioactivity. The results of molecular dynamic (MD) simulation of cinanserin-optimized compounds CM02, CM06, and CM07 revealed that CM02 and CM06 fit well into the active site of SARS-CoV-2 Mpro [Protein Data Bank (PDB) accession number 6LU7] and formed strong and stable interactions with the key residues, Ser-144, His-163, and Glu-166. The enhanced binding affinity produced demonstrates the utility of the design guidelines described. The work described herein will assist scientists in developing potent COVID-19 antivirals.

Keywords: COVID-19; SARS-CoV-2 Mpro; SARS-CoV-2 main protease; coronaviruses; inhibitor design; molecular docking; molecular dynamics; molecular interactions.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Overview of SARS-CoV-2 Active site using PDB 6LU7 and 5R7Z: (A) Surface of SARS-CoV-2 Mpro active site in PDB 6LU7, regions colored represent the binding subsites S1, S1′, S2, S4, and the cleft S6, which is accessible in the 6LU7 receptor; (B) Surface of SARS-CoV-2 Mpro active site in PDB 5R7Z, regions colored represent the binding subsites S1, S1′, S2, S4. (C) Residues comprise the key active site regions in SARS-CoV-2 Mpro (PDB 6LU7); (D) Residues which make of the key active site regions in SARS-CoV-2 Mpro (PDB 5R7Z); (E) The ribbon structure of the 6LU7 crystal structure of SARS-CoV-2 Mpro showing residues contributing to the S1, S2, S4 subsites. The N3 inhibitor is shown to assist in visualizing the subsite binding pockets. (F) Overlay of the 6LU7 (cyan) and the 5R7Z (pink) active sites. The highlighted residues are the residues shown to have different side-chain orientations.
Figure 2
Figure 2
Impact of Met-49 in the length of S2 subsite. The orientation of the residue Met-49 in the 5R7Z receptor decreases the length of the S2 subsite.
Figure 3
Figure 3
Analysis of binding subsites of SARS-CoV-2 active site using PDB 6LU7: The larger image is the overall active site. The S2 subsite is shown in the smaller image in each panel. This orientation shows the characteristics of inside of the S2 subsite that cannot be seen in the larger image. (A) Subsites S1, S1′, S2, and S4. N3 inhibitor is shown for orientation; (B) Conservation of subsites. Pink and magenta represent regions that are more conserved, dark cyan and light cyan represent regions that are less conserved. White represents regions without a high or low degree of conservation. (C) Electrostatic potential map of subsites. Red represents areas of negative charge density, while blue represents regions of positive charge density. White represents neutral regions. The darker the red or the blue, the greater the degree of negative or positive charge density. (D) Hydrophobicity plot of each subsite. The sienna-colored areas represent regions of hydrophobic character. The blue regions represent areas of hydrophilic character. The darker shades of sienna or blue represent greater hydrophobic or hydrophilic character.
Figure 4
Figure 4
Structures of the five zinc database inhibitors selected as parent structures for further docking analysis.
Figure 5
Figure 5
Structures of T47and T1J compound derivatives designed for the halogen dataset.
Figure 6
Figure 6
Structures of T47 and SFY compound derivatives designed for aliphatic substituent dataset.
Figure 7
Figure 7
Modes of binding for (A) HS04 (sandy); (B) SD11 (tan); (C) SD12 (salmon); (D) SD15 (plum); (E) SD23 (deep pink); (F) and SD27 (blue) compounds designed for aliphatic substituent dataset in PDB 6LU7. Hydrogen bonding is indicated by solid yellow lines.
Figure 8
Figure 8
SD26 (purple) and SD27 (green) penetration into the S2 subsite (blue surface) SARS-CoV-2 Mpro active site. Depth of penetration by SD27 is 3.22Å deeper than SD26.
Figure 9
Figure 9
Structures of T47 and SFY compound derivatives designed for nitrogen heterocycle dataset.
Figure 10
Figure 10
Modes of binding of nitrogen-containing heterocycles. (A) DB04 (coral); (B) DB02 (olive); (C) SD29 (green) and SD25 (pink); (D) SD19 (hot pink) and SD20 (sea green). Hydrogen bonds are indicated by solid yellow or orange lines, π-π stacking interactions are shown in purple dash lines.
Figure 11
Figure 11
Structures of K3S and SFY compound derivatives designed for aliphatic dataset.
Figure 12
Figure 12
Modes of binding of SFY derivatives. (A) SD34 (tan); (B) LEA4 (tan); (C) SD34 (purple); (D) LEA4 (pink); (E) SD35 (light green); (F) SD36 (brown). In panels (A) and (B) it can be seen that the aliphatic tails bind in the S2 and the S4 subsites. In panels (C) through (F) of the surface of the subsites, each of the bound aliphatic substituents is shown. The S2 subsite is colored blue, and the S4 subsite is green. Grey regions are portions of the S1′ subsite. Hydrogen bonds are indicated by solid yellow lines.
Figure 13
Figure 13
Structures of T7D and T1J compound derivatives designed for hydrogen bonding dataset.
Figure 14
Figure 14
Modes of binding for compounds demonstrating key hydrogen bonding hotspots in the active site of SARS-CoV-2 Mpro (A) JN16 (green) interacting in the S4 hydrogen bonding hotspot; (B) KF08 (pink) hydrogen bonding in hotspots located in the S2 subsite and the active site core; (C) KF03 (salmon) hydrogen bonding in hotspots located in the S1′ subsite and the active site core; (D) KF04 (olive) hydrogen bonding S1 subsite hotspots; (E) EW14 (tan) hydrogen bonding in the hotspots located in the S2 subsite and the S1; (F) HS06 (purple) hydrogen bonding hotspots located in the S1 subsite and the active site core; (G) AMM2 (lime) shown hydrogen bonding in S2 subsite hotspot and the active site core; and (H) AMM4 compounds designed for aliphatic substituent dataset in SARS-CoV-2 Mpro receptor. Hydrogen bonds are indicated by solid yellow lines.
Figure 15
Figure 15
Structures of optimized compounds designed using the guidelines garnered from the molecular docking study.
Figure 16
Figure 16
Mode of binding of the top two optimized compounds (A) FL30 (green); and (B) FL20 (green) designed using molecular guidelines discovered to maximize binding to the SARS-CoV-2 Mpro active site.
Figure 17
Figure 17
Cinanserin and optimized cinanserin inhibitor compounds.
Figure 18
Figure 18
Mode of binding of the optimized cinanserin compounds (A) CM06 (pink); and (B) CM07 (green).
Figure 19
Figure 19
Root mean square deviation (RMSD) analysis of molecular dynamic (MD) simulation trajectory. The RMSD plot obtained for (A) C-α atoms of the protein SARS-CoV-2 Mpro (PDB ID 6LU7) with CM02, CM06 and CM07 complex; and (B) ligand-heavy atoms for CM02, CM06 and CM07-SARS-CoV-2 Mpro complex (PDB ID: 6LU7), with respect to the reference frame at time 0 ns.
Figure 20
Figure 20
Analysis of (A) molecular interactions; and (B) type of contacts (2D interaction contour map with the key protein residues) for CM06 with SARS-CoV-2 Mpro (PDB ID: 6LU7) after MD simulation. Interactions that lasted more than 10% of the simulation time were considered.
Figure 21
Figure 21
Analysis of (A) molecular interactions; and (B) type of contacts (2D interaction contour map with the key protein residues) for CM02 with SARS-CoV-2 Mpro (PDB ID: 6LU7) after MD simulation.
Figure 22
Figure 22
Visual summary of key molecular interactions facilitating strong binding affinity to SARS-CoV-2 Mpro. Hydrogen bond hotspots are shown as green spheres, with hydrogen bonds shown as yellow lines. The hydrophobic core in S2 pocket is indicated by pink sphere. Blue sphere indicates π-π stacking region.
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