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The complex structures of SARS-CoV and ACE2 were downloaded from the Protein Data Bank [PDB ID 6ACG (Dolinsky et al., 2004)]. Several SARS-CoV-2 S protein RBD/ACE2 complex structures were determined (Arkhipov et al., 2006; Roos et al., 2010). In this work, we used 6VW1 (Luan et al., 2020b) as our complex structure to study the electrostatic binding interactions between SARS-CoV-2 S protein RBD and ACE2. However, the 6VW1 only contains the binding domains of SARS-CoV-2 S protein and ACE2. To study the electrostatic features for the overall structure of SARS-CoV-2 S protein, SWISS model (Sievers and Higgins, 2014) was used to model the whole structure of the SARS-CoV-2 S protein trimmer binding with ACE2 based on the template of 6ACG. The sequence of SARS-CoV-2 was obtained from Genebank (Maiorov and Crippen, 1994), which was from the early patients in December 2019. The modeled RBD structure has <1 Å RMSD compared to the experimental determined RBD structures, which demonstrates that the modeled RBD structure is very reliable (as shown in Supplementary Figure 1). When studying the electrostatic interactions, we mainly focused on the receptor binding domain (RBD) of S protein and the binding domain of ACE2. To understand the mechanisms of S protein binding to ACE2, S protein RBD was separated from the ACE2 binding domain by a distance from 5 to 40 Å with a step of 1 Å, when analyzing the electrostatic binding forces.

In order to study the electrostatic features, DelPhi is utilized to calculate the electrostatic potential for the S protein RBD and ACE2 binding domain. In the framework of continuum electrostatics, DelPhi calculates the electrostatic potential ϕ (in systems comprised of biological macromolecules and water in the presence of mobile ions) by solving the Poisson-Boltzmann equation (PBE):

where ϕ(r) is the electrostatic potential, ϵ (r) is the dielectric distribution, ρ (r) is the charge density based on the atomic structures, κ is the Debye-Huckel parameter, k_B is the Boltzmann constant, and T is the temperature. Due to the irregular shape of macromolecules, DelPhi uses a finite difference (FD) method to solve the PBE.

The electrostatic potential of RBDs of SARS-CoV and SARS-CoV-2 with ACE2 were calculated by Delphi. The calculated electrostatic potential on the surface was visualized with Chimera (Figure 3). In order to visualize electric field lines between SARS-CoV and ACE2 and between SARS-CoV-2 and ACE2, Visual Molecular Dynamics (VMD) (Peng et al., 2019) (Figure 4) was implemented based on the electrostatic potential map from DelPhi calculations. The color scale range was set from −1.0 to 1.0 kT/Å. In order to clearly show the difference between the surface of SARS-CoV-2 and of SARS, the difference (Figure 3C) has been calculated and visualized by subtracting the electrostatic potential values of SARS-CoV-2 by that of SARS-CoV. Since the surface structures are not completely the same, the surface of SARS-CoV-2 was used as the model to visualize the difference of charge distribution (Figure 3C).

In the process of DelPhi calculations, the PQR file of each capsomer was generated by PDB2PQR (World Health Organization, 2020). During DelPhi calculations, the resolution was set as 1 grids/Å. The dielectric constants were set as 2.0 for protein and 80.0 for the water environment, respectively. The protein filling percentage of Delphi calculation box (perfil) was set to be 70.0. The probe radius for generating the molecular surface was 1.4 Å. Salt concentration was set as 0.15 M. The boundary condition for the Poisson Boltzmann equation was set as a dipolar boundary condition. The calculated electrostatic potential on the surface was visualized with Chimera (Figure 3). VMD was used to illustrate electric field lines between S protein and ACE2 (Figure 4). Finally, the color scale range was set to be from −1.0 to 1.0 kT/Å.

To compare the strengths and directions of electrostatic forces between RBDs of SARS-CoV-2 and SARS-CoV with ACE2, DelphiForce (Li et al., 2016a, 2017) was implemented to perform the force calculations. As mentioned above, the structures at each distance of S protein and ACE2 protein were used to calculate binding forces. The electrostatic binding forces calculated by DelphiForce were visualized with VMD and represented by arrows. Forces are shown with different S protein RBD-ACE2 distances from 5 to 40 Å with a step of 2 Å. The S protein RBD and ACE2 are separated in the direction of their mass centers connection line. For better visualization of force directions in VMD (Li et al., 2013), arrows were normalized to be of the same size at variable distances, which shows only the direction of each force without considering its strength by sizes. The magnitudes of the electrostatic binding forces were illustrated in Figure 5 and the trends of forces change of the total binding forces are shown in Figure 6.

To simulate the dynamic interactions between S proteins and ACE2 protein, MD simulations were carried out on GPUs using Lonestar5 clusters at the Texas Advanced Computing Center (TACC https://www.tacc.utexas.edu/). A 2,000-step minimization was performed for each simulation, followed by a 100 million steps, during which 20,000 frames were saved from two 100 ns simulations of both SARS-CoV and SARS-CoV-2 separately (1.0 fs per step, 1 frame at each 5000 steps, 100 million steps in total). The RMSDs of the SARS-CoV and SARS-CoV-2 trajectories are about 3.4 and 1.1 Å, respectively (Supplementary Figure 4). During the MD simulations, the temperature was set to be 300 K, and the pressure was set to be standard using the Langevin dynamics. For PME, which is set for full-system periodic electrostatics, with the grid size (86, 88, 132) as (x, y, z) value, respectively. In those two simulations, atoms that are not located in binding domains were constrained within a margin of 10.0 Å of their natural movement maximum length values. In order to get a more accurate result of the simulation, data of the last 50 ns of simulations were selected and used for later data analysis, since the structure of the first 50 ns is not as stable as the last 50 ns of simulations. The simulation processes are visualized in Supplementary Movies 1, 2, generated by VMD.

To analyze the interaction between S proteins and ACE2, the salt bridges that formed within the distance of 4 Å were extracted from the last 10,000 frames of simulations, and for hydrogen bonds the cutoff was 4 Å. The several top-strongest salt bridges in each binding domain were determined by calculating their formation frequency (the occupancy in Supplementary Figure 6) during MD simulation.

To analyze the overall sequence and structural differences between SARS-CoV and SARS-CoV-2, the sequences of SARS-CoV and SARS-CoV-2 studied in this work are aligned using clustal omega (Yan et al., 2020). The result is shown in the Supplementary Figure 2. The positions of those mutations are mapped to SARS-CoV-2 structure as labeled in in four colors (Figure 1) on a single chain of S protein: Red represents residues which are mutated to be more negative; Blue represents residues which are mutated to be more positive; yellow represents residues which are mutated from polar to hydrophobic; cyan represents residues which are mutated from hydrophobic to polar. It is found that most of the mutations distribute on the surface of the S protein. We observed that the mutations in the RBD region (red circle of the Figure 1B) locate close to the interface by facing to the ACE2. This observation indicates that the mechanisms of S protein binding to ACE2 between SARS-CoV and SARS-CoV-2 may be quite different. Therefore, we performed comprehensive analysis of the binding interfaces to investigate their different binding mechanisms. Furthermore, it is obvious that some mutations are located on the hinge, which links the RBD and other regions of the S protein, as shown in the green circle of Figure 1B. It suggests that the flexibility of the RBD may also be different between those two viruses, which might open an avenue for our future research on coronaviruses.

We compared the structure of the S protein RBDs of SARS-CoV with the same part of SARS-CoV-2. As shown in Figure 2A, SARS-CoV S protein RBD (purple) and SARS-CoV-2 S protein RBD (yellow) are aligned based on their structures, while human ACE2 binding domain (gray) are bound with S protein RBDs. The overall RBDs structures of SARS-CoV and SARS-CoV-2 S proteins are very similar, with the RMSD (Wang, Q. et al., 2020) of 0.965 Å, but some differences can still be noticed in several loops of the RBDs (Figure 2B), which is due to two factors: (1) The high flexibility of the loops; (2) The amino acid differences between SARS-CoV and SARS-CoV-2. The variation of binding mechanisms between the two viruses could be caused by the differential residues rather than the whole structures.

To study the electrostatic features, DelPhi is utilized to calculate the electrostatic surfaces of the S protein RBDs and ACE2. The charge distribution on SARS-CoV S protein RBD is showed in Figure 3A and Supplementary Movie 3 rendered by Chimera, with a color scale from −1.0 to 1.0 kT/Å. The charge distribution on SARS-CoV-2 S protein RBD is shown in Figure 3B and Supplementary Movie 4 rendered by Chimera, with a color scale from −1.0 to 1.0 kT/Å. Negatively and positively charged areas are colored in red and blue, respectively. The electrostatic surfaces shown that the binding interface of ACE2 is dominantly negative, while the binding interfaces of S protein RBDs are all dominantly positive (Figure 3D and Supplementary Movie 5).

The difference of the electrostatic potential (which are generated from DelPhi) between SARS-CoV and SARS-CoV-2 S protein RBDs was calculated and mapped on the surface of SARS-CoV-2, as shown in Figure 3C. From the presentation in Figure 3C, an area of positive charge is observed, which also shows that SARS-CoV-2 S protein RBD is more attractive than the SARS-CoV to ACE2, since ACE2 has an overall negative charged surface, as shown in Figure 3D. Therefore, we expect the SARS-CoV-2 S protein RBD may form more non-covalent bonds with ACE2, such as hydrogen bonds and salt bridges. In the later sections we demonstrate that besides salt bridge residue pairs, the SARS-CoV-2 utilizes a cluster of residues to interact with ACE2, which is more robust than individual salt bridges.

Electric field lines that surround the binding interfaces are calculated using Delphi. To better visualize the field lines between interfaces and show its interaction area with a clear representation, S protein RBDs were separated from ACE2 by 20 Å (Figure 4). In Figure 4, densities of field lines represent the strengths of interactions. Higher density indicates stronger interaction in the region.

Shown in Figures 4A,B, we see the similarity in field lines of SARS-CoV and SARS-CoV-2 complex structures. In those two panels, the field lines that connect S proteins and ACE2 are clearly shown with high densities all around the surfaces. This fact shows that both SARS-CoV and SARS-CoV-2 S protein RBDs have strong attractive binding forces to ACE2 protein, and the further discussions on binding forces are in the later section of electrostatic forces (Figure 5).

However, there are still several remarkable differences if we take a closer look at the interface areas, as shown in Figures 4C–H. The first difference is the distribution dissimilarity of electric field line related residues. The residues forming salt bridges are distributed differently in SARS-CoV (Figures 4C,E) compared to SARS-CoV-2 (Figures 4D,F). The salt bridge residues of SARS-CoV are clearly shown in the front view of the complex (Figure 4C). In contrast, the salt bridge residues of SARS-CoV-2 are mainly observed in the back view of the complex (Figure 4F). This indicates that the salt bridge residues are distributed on the opposite sides of the S protein RBDs for SARS-CoV and SARS-CoV-2. Besides the front and back views, we also rendered the bottom views of SARS-CoV (Figure 4G) and SARS-CoV (Figure 4H) with colorful patches, where green patches represent salt bridge residues, purple patches represent hydrogen bonds, and yellow patches represent special regions that form high-density field lines but do not belong to salt bridges nor hydrogen bonds. By comparing those patches, SARS-CoV-2 (Figure 4H) has a bigger and more joint hydrogen bond distribution (purple patches) than SARS-CoV (Figure 4G); salt bridges(green patches) in SARS-CoV-2 (Figure 4H) are more concentrated in the distribution, while salt bridges(green patches) in SARS-CoV-2 (Figure 4G) are distributed more separately; and SARS-CoV-2 (Figure 4H) has 5 major special regions (yellow patches), while SARS-CoV (Figure 4G) has only 2 major special regions (yellow patches). The second difference is about density. Figures 4G,H have the same representation setting of field lines with the gradient values of 2.39 kT/(eÅ), it is obvious that SARS-CoV-2 (Figure 4H) has several higher-density field line regions than SARS-CoV (Figure 4G). Since the higher density indicates the stronger interactions, SARS-CoV-2 definitely has stronger attractive interaction than SARS-CoV.

Electrostatic forces of SARS-CoV and SARS-CoV-2 S protein RBDs at different distances with human ACE2 binding domain are calculated by DelPhiForce to model the binding forces when S proteins bind to ACE2 (Figure 5). Arrows in Figures 5A,B are shown to visualize the net forces between proteins by shifting the S proteins away from ACE2 by a distance ranging from 5 to 40 with a step of 2 Å. The directions of arrows represent the force directions at different distances. To better visualize the directions of the net forces, the magnitudes of net forces are normalized to be of the same size at different distances, which means that the size of arrows do not represent the force strength. Comparing Figures 5A,B, as we expected, the overall binding forces are all shown to be attractive for both viruses. As for the force directions, only slight differences were found at different distances. From Figures 5C,D that represent the force on every residue in the RBDs at a distance of 5 Å, with the arrow sizes representing the force magnitudes, a conclusion can be drawn that SARS-CoV-2 has quite a different force distribution on individual residues with SARS-CoV. A closeup view of the difference is noticed by comparing Figures 5E,F. The salt bridge involved residues are labeled in the Figures 5E,F, which confirms that the salt bridge residues do provide significant attractive forces in the interaction process.

The directions of the net forces are shown in Figures 5A,B, while the magnitudes of the net forces are shown in Figure 6. The magnitudes of the net forces on the directions of mass center lines, x, y, z directions are shown in Supplementary Figure 3. For both SARS-CoV-2 and SARS-CoV, the net forces are enhanced when the distance is decreased from 40 to 5 Å, which is expected to see because the main force is a type of electrostatic force. Based on the Coulomb's law, when the charges on the RBD interfaces get closer to the charged residues on the interface of ACE2, the force increases significantly. Besides, by comparing Figures 6A,B, the net force of SARS-CoV S protein RBD is actually stronger than that of SARS-CoV-2, which might be due to the charge distribution differences between those two binding domains. Even though the attractive force is weaker, the SARS-CoV-2 may still be easier to bind with ACE2. Because there are sequence differences at the hinge which connects the RBD and other parts of the S protein (Figure 1). Such sequence differences may make the RBD more flexible and easier to open and bind with ACE2. We will study the flexibilities of the RBDs from SARS-CoV and SARS-CoV-2 in future work.

Salt-bridge-involved residues on SARS-CoV RBD are marked with different colors in Figure 5C and labeled with their residue types and sequence numbers in Figure 5E. As shown in Figure 5E, for SARS-CoV RBD, four salt bridge residues, ARG426 (orange), ASP468 (cyan), LYS390 (green), and LYS465 (yellow), are labeled. Among them, ARG426 provides a strong attractive force to ACE2 while LYS465 results in a repulsive force to ACE2, due to the fact that the LYS465 faces a positively charged region at the ACE2 interface. However, a negatively charged residue, ASP463 (yellow), is located in a neighborhood which results in attractive force that overcome the repulsive force from LYS465. Also, as shown in Supplementary Figure 6C, the h-bond formed by LYS465 has a 52.32% appearance occupancy and ASP463 has 48.50%. These results indicate that even though LYS465 has repulsive force to ACE2, still the nearby region has attractive force to ACE2. Note that this calculation is based on the structure of S protein separated from ACE2 by 5 Å. When S protein binds to ACE2, the sidechain of LYS465 on S protein changes the configuration to form a salt bridge with GLU23 on ACE2, which is demonstrated in the later section of salt bridges.

Salt bridge residues of SARS-CoV-2 RBD are marked with different colors in Figure 5D and labeled with their residue types and sequence numbers in Figure 5F. For SARS-CoV-2 RBD, two strong salt bridge residues ARG121(brown) and LYS134(green) are observed. As the red arrows shown in Figure 5F all have the direction pointing to ACE2, we can conclude that those two residues are all attractive to ACE2, among which LYS134 has a stronger attractive force strength based on the comparison of arrow sizes.

In terms of the total electrostatic forces between S protein RBDs and human ACE2 RBD, it should be noticed that SARS-CoV-2 has relatively lower values than SARS-CoV, especially when the distance has a smaller value. Note here that in this comparison, we only take the force strength into consideration rather than the directions of forces, and directions can also play an essential role in the comparison.

Salt bridges at the interfaces of S protein RBDs and ACE2 are analyzed based on the MD simulation results and shown in Supplementary Figure 6. Four pairs of salt bridges have been observed between SARS-CoV RBD and ACE2 RBD, comparing to two pairs between SARS-CoV-2 RBD and ACE2 RBD. Among the four pairs of SARS-CoV salt bridges, as shown in Supplementary Figures 6A–D, three of them (ASP463–LYS26, GLU23–LYS465, GLU329–ARG426) are strong salt bridge pairs during 50–100 ns time duration, as the distance is all below 4 Å, which is the selected cut-off value for salt bridge calculations; while the fourth salt bridge (GLU37–LYS390) performs interestingly: at the beginning, GLU37 and LYS390 keep a distance of about 6 Å, from 73 ns, it suddenly becomes the strongest pair with the shortest distance (about 2.75 Å) among those four observations. This change is due to the side chain flexibilities.

Speaking of the two observations of SARS-CoV-2 salt bridges, as shown in Supplementary Figures 6E,F, they are all strong pairs (ASP20–LYS134 and GLU311–ARG121) during the whole 50 ns. While there is a special pair (GLU166–LYS13) which has been observed that is included in Supplementary Figure 5. This special pair has a strong salt bridge feature during the first 30 ns of the whole 100 ns simulation, while those two residues apart from each other to a distance over 7.5 Å after 30 ns. Since we only took the last 50 ns for our data analysis, this special pair is not considered as a salt bridge pair in this work. However, we can still draw a conclusion that some residues involved in the binding process between SARS-CoV-2 and ACE2 are flexible.

Hydrogen bonds at the interfaces of S protein RBDs and ACE2 are also calculated based on the MD simulations as shown in Figure 7. By comparing Figures 7A,B, the average numbers of hydrogen bonds at the same time between SARS-CoV and SARS-CoV-2 S protein RBDs and ACE2 are very similar, with the mean values of 25.90 and 21.85, respectively (marked as the red lines). While by comparing Figures 7C,D, the details of hydrogen bonds with the occupancies above 30% are quite different. The first difference to notice is the highest occupancy of each complex structure, where we find that SARS-CoV-2 has the highest occupancy of 98.98%, compared to 90.91% for SARS-CoV. Besides, if you pick the 90% as a cutoff value, SARS-CoV-2 has 3 pairs, compared to only 1 pair in SARS-CoV analysis, which means SARS-CoV-2 has more extremely high occupancy hydrogen bonds than SARS-CoV. This fact is also an evidence to show the more robust binding strategy of SARS-CoV-2. And it might be another reason why the COVID-19 is spreading easier and faster than SARS in 2003.

The residues involved in salt bridges and hydrogen bonds are identified as the key residues which may significantly contribute to the binding affinity. Figure 8 illustrates the key residues involved in salt bridges observed. As shown in Figures 8A,B, key residues are mostly around the edges of the binding interfaces rather than the center of the interfaces, and most of the key residues are positive in S protein RBD and negative in ACE2, except for the pair ASP463–LYS26 in SARS-CoV S protein RBD and the special pair GLU166–LYS13 (Supplementary Figure 5) in SARS-CoV-2 S protein RBD. Such salt bridges also play significant roles in binding forces (Figure 5) and electric field line distributions (Figure 4).