Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2023 May 23.
Published in final edited form as: J Chem Inf Model. 2022 Apr 18;62(10):2456–2465. doi: 10.1021/acs.jcim.2c00201

Impact of Remdesivir Incorporation Along the Primer Strand on SARS-CoV-2 RNA-dependent RNA polymerase

Sehr Naseem-Khan †, Madison B Berger †,‡, Emmett M Leddin †, Yazdan Maghsoud †,‡, G Andrés Cisneros †,¶,‡,*
PMCID: PMC9133223  NIHMSID: NIHMS1796627  PMID: 35435671

Abstract

Remdesivir was the first antiviral drug that received emergency use authorization from the United States Food and Drug Administration and is now formally approved to treat COVID-19. Remdesivir is a nucleotide analogue that targets the RNA-dependent RNA polymerase (RdRp) of coronaviruses, including SARS-CoV-2. The solution of multiple RdRp structures has been one of the main axes of research in the race against the SARS-CoV-2 virus. Several hypotheses of the mechanism of inhibition of RdRp by remdesivir have been proposed, although open questions remain. This work uses molecular dynamics (MD) simulations to explore the impact of remdesivir and two analogues as incoming nucleotides, and of up to four incorporations of remdesivir along the primer strand on RdRp. The simulation results suggest that the overall structure and dynamical behavior of RdRp is destabilized by remdesivir and the two analogues in the incoming position. The incorporation of remdesivir along the primer strand impacts specific non-bonded interactions between the nascent RNA and the polymerase subunit, as well as overall dynamical networks on RdRp. The strongest impact on the structure and dynamics are observed after three incorporations, when remdesivir is located at position -A3, in agreement with previously reported experimental and computational results. Our results provide atomic-level detail on the role played by remdesivir on the disruption of RNA synthesis by RdRp, and the main drivers of these disruptions.

Graphical Abstract

graphic file with name nihms-1796627-f0001.jpg

1. Introduction

The COVID-19 pandemic has garnered significant attention from the global scientific community. This has led to a world-wide effort to understand and develop effective therapeutics to treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus infection. Multiple approaches are being explored and have led to the development of various vaccines and small-molecule drugs. At the time of writing this paper, several vaccines have been developed and are currently being administrated to the global population.1–8 This is a major milestone and the first line of defense against SARS-CoV-2. The development of antivirals is also important due to multiple factors including (but not limited to) lack of vaccines for segments of the population, allergic reactions to vaccines, potential resistance of vaccine due to variants of the virus, or to reduce the severity of COVID-19 cases.

The SARS-CoV-2 virus is part of the betacoronavirus family. Its genome encodes 29 proteins, three of which have received the most attention as therapeutic targets:9 the spike glycoprotein,10–13 main protease (Mpro),14–18 and RNA-dependent RNA polymerase (RdRp).19–21 The glycoprotein, which drives the entry into human cells, has been a vaccine target, whereas Mpro and RdRp have been prominent drug targets due to their roles in replication and transcription of the virus (although they are not the only protein targets).

RdRp is composed of three main domains (nsp12, nsp7, nsp8) and the RNA template-product duplex. The polymerase region, which can be subdivided into the finger, palm and thumb subdomains, is localized in the nsp12 domain, as well as the NiRAN (nidovirus RdRp-associated nucleotidyltransferase) and Interface regions. Several cryo-electron microscopy (cryo-EM) structures of RdRp have been resolved including PDB 6M71 and PDB 7BTF from Gao et al.,19 and PDB 6YYT from Hillen et al.20 The latter is represented in Figure 1A showing the replicating form of the RdRp structure with elongated nsp8 and RNA template-product duplex. This structure includes the RNA strand position compared to the structures from Gao et al., where only the protein is present. Yin et al. have also determined cryo-EM structures with remdesivir incorporated on the primer RNA strand (PDB 7BV2),21 although the length of the RNA strand is shorter than in the structure from Hillen et al. (PDB 6YYT). However, none of these structures explicitly include a complex with a nucleotide triphosphate in the active site.

Figure 1:

Figure 1:

Open in a new tab

(A) Representation of the replicating SARS-CoV-2 polymerase structure (PDB: 6YYT). (B) Model of the RdRp active site with ATP as the incoming nucleotide triphosphate.

Remdesivir was the first drug approved by the United States FDA (Food and Drug Administration)22 to treat COVID-19 patients in the USA.23–26 Remdesivir has shown efficiency against the Ebola virus, and it started the clinical trial process before the 2019 COVID-19 outbreak.27,28 Because of this, the drug remdesivir has been the focus of many experimental and computational research studies in order to establish its possible mechanism of action and efficacy against the SARS-CoV-2 virus.21,29–34

When entering human cells, the remdesivir prodrug is reduced to an active triphosphate form through metabolic reactions.35,36 This active form of remdesivir (REM) is very similar to its natural analogue, ATP. One of its main differences from ATP is the presence of a cyano group at the C1′ position. REM’s overall similarity to ATP allows remdesivir to be incorporated into the primer strand during RNA synthesis. Remdesivir has been proposed to act as a chain terminator by blocking synthesis as it binds in the incoming nucleotide position,14,21 or as an RNA translocation blocker at the -A4 position, after the incorporation of four nucleotides with the first being remdesivir. This stalling (delayed) mechanism is proposed to occur due to a potential steric clash between remdesivir at -A4 and SER861.30,32 On the other hand, QM/MM studies have suggested that remdesivir at -A4 and SER861 could form a covalent bond.29

Here, we have used computational simulations based on all-atom classical molecular dynamics (MD) to investigate the impact of remdesivir incorporation at multiple positions along the primer strand. REM and two of its analogues (termed CID and CYD) were compared with ATP in the incoming nucleotide position to investigate the possibility of any of these drugs acting as chain terminators (Figure 2). Here, REM is in its trisphosphate form of the prodrug remdesivir, and CID is formed from the prodrug CID (PubChemID: 44468491). The remainder of this article is as follows: in the next section we describe the development of force field parameters for all non-standard nucleotides and simulation details. Next, we discuss the results for the investigation of effects of different inhibitors in the incoming nucleotide position compared with ATP, followed by the results of the impact of remdesivir on the primer strand and concluding remarks.

Figure 2:

Figure 2:

Open in a new tab

Graphical representations of the nine systems of interest studied in this work. The +A1 position indicates the added incoming nucleotide, whereas the -A1 to -A4 notations indicate the position of the nucleobases on the primer strand of the RNA. The ATP, REM, CID and CYD systems are respectively at the +A1 position.

2. Computational Details

2.1. Structure and MD simulations set-up

We constructed our model using the replicating SARS-CoV-2 RdRp structure obtained from cryo-EM by Hillen et al. (PDB 6YYT).20,37 The missing residues A4–V30, T51–T76, and K98–Q117 were incorporated after overlaying the cryo-EM RdRp structure by Gao et al. (PDB 7BTF).19,38 We have modelled the active site using the positions of the incoming nucleotide and the two Mg2+ cations from the Norovirus Polymerase structure by Zamyatkin et al. (PDB 3H5Y) (Figure 1B, and see also Figure S1).39,40 The RdRp structure was then solvated in TIP3P water using a 10 Å cutoff from the center mass of RdRp, and 61 K+ counterions were added to neutralize the water box with the LEaP program.41,42 The force fields used to describe the protein and RNA are Amber-ff14SB and RNA-χOL3, respectively.41,43–45 We have also used the ZAFF force field to describe the two Zn2+ cations and first coordination sphere ligands.46 Finally, the parameters of the incoming nucleotide studied here (CID, CYD, and REM) were obtained through pyRED calculations on the R.E.D server.47–50 The ATP parameters were obtained from Meagher et al.51 AMBER20 was used for MD simulations of all systems.

Each system was run in triplicate. Initially, each system was heated from 0 K to 100 K for 100 ps, followed by a 500 ps simulation to reach the production temperature of 300 K with a 2 fs time step, and a collision frequency of 5 ps−1. During these stages the protein/substrate/cofactor atoms were restrained with a force constant of 10 kcal mol−1 Å−2. After equilibration, restraints were removed except for the zinc cations and their coordinating ligands, which were restrained at 10 kcal mol−1 Å−2 during the whole MD simulation. Production simulations for all systems were performed using the NPT ensemble with a 2 fs time step at 300 K for 350 ns, using the Langevin thermostat52 with a collision frequency of 1 ps−1, and the Berendsen barostat53 using the default weak-coupling scheme. A 9 Å cutoff was employed for non-bonded interactions, and the smooth particle mesh Ewald (PME) approach was used to describe long-range electrostatic effects.54

2.2. Trajectory Analysis

Cpptraj55 was used to compute root mean squared deviation and fluctuation (RMSD/RMSF), matrix correlations, and distance analyses. Normal mode analysis was performed using the ProDy code.56 NCI (Non-Covalent Interactions) analysis was computed with the NCIPLOT program57,58 using its default color code (RGB) for plotting isosurfaces, where red, green and blue represent repulsive, attractive and weak attractive forces respectively. Network analysis was carried out using the dynamic network analysis (DyNetAn) python package via a Jupyter Notebook from Melo et al.59 Gephi60 was used to compose the node plots. The UCSF Chimera61 and VMD62 software programs were used to render the images.

2.3. Energy Decomposition Analysis

Energy Decomposition Analysis (EDA) was performed to understand the nature of the intermolecular interactions between two fragments using an open-source Fortran90 program.63 This approach is based on the calculation of the average non-bonded inter-molecular interaction energy, < Eij >, between every pair of fragments i and j. Subsequently, the alterations (if any) in inter-molecular interactions as a function of changes between different systems can be obtained:

ΔEijAB=<EijB>−EijA>, (1)

where A denotes the reference system, B denotes the target system, and <EijA> denotes the average non-bonded inter-molecular interaction energy of fragment i in system A with all other fragments j in A (and likewise for B). Based on this data, it is possible to investigate the non-bonded inter-molecular interactions as a function of a particular reference residue i. Here, all EDA results correspond to the difference of non-bonded intermolecular interactions, ΔEijAB (henceforth ΔEnb), with the ATP system obtained after averaging over the three replicates of each system; that is, the ATP system has been used as reference for all ΔEnb calculations.

2.4. Dynamic Network Analysis

Dynamic network analysis59 was carried out exclusively on the protein and RNA atoms. Due to the large number of atoms in all of these systems, cpptraj was used to strip the water and counterions. In addition, the combined trajectory for each system was trimmed by saving every 25th frame. Amino acids were represented by one node placed on the alpha carbon. Ribonucleotides were represented with two nodes; the first node was placed on the phosphorus (Pα) and the second on the nitrogen (N1) of the nitrogenous base (see Figure 2). 4.5 Å was used for the cutoff distance and 0.75 for contact persistence. Once the network was calculated, the Floyd–Warshall algorithm, as implemented in DyNetAn,59 was used to calculate the optimal path between two selected nodes: SER861 and the incoming nucleotide in the active site (either ATP, CID, CYD or REM). The optimal path can provide information as to how the allosteric communication between nodes throughout the protein may change. The node plots that will be further discussed in the Results and Discussion section were generated from the network data. The size of the circles reflect the number of node–node interactions within the designated subunit. The size of the edge that connects the circles refers to the number of interactions between nodes in those respective subunits.

2.5. MM/PBSA Analysis

The end-point molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA)64–66 approach was employed to calculate the binding enthalpies between RdRp and each incoming nucleotide (ATP, REM, CID, and CYD) at the +A1 position. The “single-trajectory” protocol,67 i.e., one trajectory of the system, was selected for the computations, using the last 10 ns from the selected representative replicate. The MM/PBSA calculations were performed with the MMPBSA.py internal module of AmberTools19.68 The ionic strength for the PB equation was set to 0.150 mM, the raddii and offest were set to the default values.68 The entropic contributions were not included in our calculations, although in the case where conformational entropy is neglected, MM/PBSA has been shown to achieve satisfactory accuracy of ranking relative ligand affinities.69–73

3. Results and Discussion

3.1. Effects of the incoming nucleotide

As described above, remdesivir has shown a strong potential to stop the RNA synthesis at the incoming nucleotide position (chain terminator). Byléhn et al. have recently computed the binding energies of remdesivir, favilavir, and ribavirin in their monophosphate form.33 They have found that the binding energy of remdesivir is more favorable, thus showing its ability to be incorporated into the RNA primer strand. Here, we compare remdesivir and its two analogues (CID & CYD), with respect to ATP (i.e the natural nucleotide).

All systems were observed to be stable throughout the simulation time, without major deviations in individual subunits or significant active site changes (Figure S2). Figures 3A,B and C show the difference residue-wise correlation with respect to the ATP system computed as a function of the incoming nucleotide, namely ATP, CID, CYD, and REM, as a heatmap projected on the protein structure (see also Figure S4). We observed that the finger and palm domains are anti-correlated with respect to ATP for the three systems. EDA results also show that two residues close to the incoming nucleotide, K551 and R555, have positive ΔEnb values across the three systems. This suggests that all three inhibitors show a destabilizing interaction within the active site compared with ATP. Interestingly, NCIPLOT analysis indicates multiple van der Waals and attractive forces around the active site that aid in the stability of the incoming nucleotide in the active site.

Figure 3:

Figure 3:

Open in a new tab

Comparison of the heatmap correlation matrix difference with the ATP system computed as a function of the incoming nucleotide for REM, CID and CYD systems. The black arrow indicates the motion of the first normal mode (A-C). The isosurfaces represent NCIPLOT results near the active site (isovalue=0.4, cutoff=5 Å). The values of the difference of EDA results with respect to ATP, computed as a function of the incoming nucleotide, are indicated in purple (D-F).

Overall, the CYD system differs the most compared to CID and REM. For CYD, we observe mostly non-correlated movements, with respect to ATP, for the whole structure. REM and CID systems behave similarly having correlated movements with respect to ATP such as the nsp7, nsp8, and thumb regions. Additionally, the directionality of the first normal mode of CYD is in the opposite direction compared to both REM and CID. Thus, the CYD system seems to have a stronger destabilizing effect on the RdRp structure.

The total binding enthalpies between each of the incoming nucleotides and the RdRp system were calculated via the MM/PBSA approach. The calculated values of each component of the MM/PBSA calculations are listed in Table S4. The relative values of ΔHbind with respect to ATP are −51.4, −39.3, and −49.0 kcal mol−1 for REM, CID, and CYD, respectively. These results are in agreement with related calculations of binding energies for remdesivir monophosphate by Byléhn et al..33

3.2. Role of remdesivir within the RNA primer strand

We next assessed the effect of REM incorporated at different positions from -A1 to -A4 in the RNA primer strand. We denote by REM-A[n] all the RdRp systems studied in this work: REM-A[4], REM-A[1,4], REM-A[1,2,4], REM-A[1,3,4] and REM-A[1,2,3,4] (Figure 2). As previously stated, the steric effect between SER861 and REM at position -A4, due to the cyano group of REM on the sugar ring, has been proposed to be the main cause for the disruption of RNA translocation from -A3 to -A4. For that reason, we aim here to shed a light on the delayed mechanism hypothesis.

To do so, we first measured the distance (dCβ−N) between the beta carbon (Cβ) of SER861 and the nitrogen atom of the cyano-group of REM located at the -A4 position (Figure 4F). For all of the REM-A[n] systems, dCβ−N stays near 3.5 Å during the entire MD simulation. Conversely, for the ATP, CID, CYD and REM systems, a guanine base is originally located at the -A4 position, and the distance between Cβ of SER861 and the oxygen atom (O2′) of the guanine fluctuates between 3 and 5 Å during the MD simulation (Figure S3). Additionally, most of the REM-A[n] systems have smaller RMSF values for the REM located at the -A4 position and SER861 residues.

Figure 4:

Figure 4:

Open in a new tab

Intermolecular interaction and structural analysis at the -A3 and -A4 positions of the RNA strand. (A-E): NCIPLOT analysis indicates mainly van der Waals intermolecular interaction between SER861 and its nearby residues (green isosurfaces, isovalue=0.4, cutoff=5 Å). EDA results are displayed for relevant residues using SER861 (values in purple) and REM at the -A3 position (values in red) respectively as the reference residue. EDA shows that the nature of the intermolecular interaction between SER861 and REM at -A4 position is mainly repulsive for most of the REM-A[n] systems, and that the salt bridge formed between K593 and D865 is stronger in the case of REM-A[1,3,4] and REM-A[1,2,3,4]. RMSF values are displayed in blue for SER861 and the residue at the -A4 position. The heatmap correlation matrix difference with the ATP system as a function of SER861 is also plotted. (F): Analysis of the distance between the beta carbon of SER861 and the nitrogen atom of the cyano-group of REM at the -A4 position.

Mainly vdW interactions, as displayed by the green isosurfaces from the NCIPLOT analysis, are observed for all systems. They are more spread out when the number of REM positioned in the RNA primer strand increases (Figures 4A–E, and Figure S5). This suggests an increase in the number of interactions between REM and SER861 at the -A4 position. The increase in interactions is consistent with the EDA results, which suggests that intermolecular interactions between SER861 and ATP are mainly repulsive (Figures 4A–E). ΔEnb varies between 1.4 kcal mol−1 to 3.3 kcal mol−1 for all the REM-A[n] systems except REM-A[1,2,4]. In this case, ΔEnb is −1.1 kcal mol−1, which slightly favors an attractive interaction between REM and SER861. Overall, these results are consistent with the steric repulsion hypothesis caused by the cyano group on REM when it is located at the -A4 position, albeit only weakly repulsive.

On the other hand, it has been shown that the formation of a salt bridge between K593 and D865 could stabilize REM positioned at the -A3 position.33,74 Here, we also observe a strong attractive interaction between K593 and D865 in the case of the REM-A[1,3,4] and REM-A[1,2,3,4] systems (Figures 4D–E), as opposed to REM-A[n] systems having a uracil nucleobase at the -A3 position (Figures 4A–C). Indeed, EDA results computed as a function of the nucleotide at the -A3 position show a significant increase of ΔEnb, ~20 kcal mol−1 for K593, and ~10 kcal mol−1 for D865 (in magnitude). The favorable intermolecular force induced by the salt bridge helps stabilize REM at the -A3 position. Finally, it is interesting to note that the movements of residues from the REM-A[n] system are anti-correlated with respect to ATP, except for the REM-A[1,2,3,4] system. In the latter, REM residues at -A3 and -A4 positions are correlated with ATP.

3.3. Dynamic effects of remdesivir throughout the RdRp structure

Furthermore, dynamic network analysis was carried out to gain insights into how incorporation of REM at different positions along the RNA primer strand may have effects throughout the entire structure. Specifically, we investigated how the number of node-to-node interactions within subunits and between subunits changed for the different systems. While much of this data is qualitative due to the need to sample small windows throughout the trajectory, some key trends were seen. A greater number of interactions within subunits was found for most of the REM-A[n] and CID/CYD systems. More specifically, we see an increase in intra-subunit interactions within the polymerase, interface, nsp8a subunits, as well as the RNA, with a few exceptions. This can be seen in Figure 5 by the purple circles representing subunits. The opposite is true for inter-subunit interactions. We see a large decrease in inter-subunit interactions, specifically interface-nsp8a, polymerase-nsp8a, polymerase-nsp8b, nsp8a-RNA and nsp8a-nsp7 for most of the REM-A[n] systems. This loss of inter-subunit interaction is represented by the green lines connecting subunits in Figure 5 (see also Figure S6 and Tables S1 and S2). From this, it can be inferred that there is an overall loss of allosteric communication between the different subunits and RNA of RdRp but a gain of communication within subunits when compared with the ATP system. The only outlier system found from these trends was the REM-A[4] which exhibited similar interactions to the ATP system.

Figure 5:

Figure 5:

Open in a new tab

Representation of the difference edge–node plots, with respect to the ATP system from the dynamic network analysis. (A-F): The size of the circles is proportional to the number of communications between the residues within the considered subunit. The thickness of the edges is proportional to the number of communication between the subunits. Communications favored in the ATP system are colored green, and those favored in the studied system are colored purple.

To gather further insight into how the allosteric communication changed between the different REM-A[n] and CID/CYD systems, we looked at the optimal pathways between SER861 and the incoming nucleotide. Figure 6 represents the two main optimal paths found across all the studied systems. We observed that one optimal path follows the RNA primer strand (A), while the other path (B) goes through the protein. The optimal path was calculated for each window of the trajectory for all replicates. The ATP, REM-A[4] and REM-A[1,2,4] almost equally favored both paths. All other systems exclusively favored a pathway through the RNA primer strand. This result corroborates the node–node interactions previously discussed in this section. Most of the REM-A[n] systems, except for REM-A[4], have lost communication between subunits but have maintained or increased the number of interactions within each isolated subunit. That is, when remdesivir or an analogue of it is introduced into the RNA primer strand, the protein experiences a major loss in allosteric communication between its residues.

Figure 6:

Figure 6:

Open in a new tab

The two dominating optimal pathways found between SER861 and the incoming nucleotide throughout all RdRp systems are shown. Path (A) follows the RNA, whereas path (B) favors a path through the protein. As an example, we show here (C) the optimal paths connecting SER861 and REM.

4. Conclusions

We have investigated the structural, intermolecular, and dynamical effects of several RdRp systems. Our results suggest that remdesivir and two analogues induce differences in structural and dynamic effects on RdRp compared with ATP. Calculated binding affinities suggest that REM and the two analogues have larger binding enthalpies compared with the natural substrate, consistent with previous studies.14,21,30,32 Non-covalent interaction and energy decomposition analyses indicate repulsive non–bonded interactions between SER861 and REM at the -A4 position of the RNA primer strand. This suggests that the translocation of RNA with REM in the primer strand from -A3 to -A4 could be impaired due to steric repulsion, albeit the steric effect induced by SER861 with REM is only weakly repulsive. However, our dynamical network analysis suggests strong destabilization of the whole RdRp structure. Particularly, we have found a loss of communication between the nsp domains with both the RNA and polymerase for most systems, with respect to the ATP system. As previously mentioned, Aranda and Orozco29 have discussed the probability of the formation of a covalent bond between the SER861 and remdesivir at the -A4 position. In this way, the full stop of the translocation of RNA would be ensured. Certainly, the cyano-group of remdesivir could be revisited or modified to increase its antiviral reactivity.

Supplementary Material

SI

Acknowledgement

This work was funded by NIH Grant No. R01GM108583. Computational time was provided by the University of North Texas CASCaM CRUNTCh3 high-performance cluster partially supported by NSF Grant No. CHE-1531468 and by XSEDE Project No. TG-CHE160044. Additional computational time from the COVID-19 HPC Consortium is gratefully acknowledged. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under contract No. DE-AC05-00OR22725. MBB thanks MolSSI for support provided via a software development fellowship.

Footnotes

Supporting Information Available

Additional RMSD, distance analysis, heatmap correlation matrix plots, active site, and edge–node data are provided in the SI.

Data and Software Availability

The initial structures and parameters for the non-standard incoming nucleotides used for this study, and the initial coordinates and parameter sets for all systems, are provided as part of the Supporting Information. All simulations and analysis third-party software employed are described and referenced in the methods section. The EDA software is available at: https://github.com/CisnerosResearch/AMBER-EDA

References

  • (1).Baden LR; El Sahly HM; Essink B; Kotloff K; Frey S; Novak R; Diemert D; Spector SA; Rouphael N; Creech CB; McGettigan J; Khetan S; Segall N; Solis J; Brosz A; Fierro C; Schwartz H; Neuzil K; Corey L; Gilbert P; Janes H; Follmann D; Marovich M; Mascola J; Polakowski L; Ledgerwood J; Graham BS; Bennett H; Pajon R; Knightly C; Leav B; Deng W; Zhou H; Han S; Ivarsson M; Miller J; Zaks T Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine. N. Engl. J. Med 2021, 384, 403–416, DOI: 10.1056/NEJ-Moa2035389. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (2).Polack FP; Thomas SJ; Kitchin N; Absalon J; Gurtman A; Lockhart S; Perez JL; Pérez Marc G; Moreira ED; Zerbini C; Bailey R; Swanson KA; Roychoudhury S; Koury K; Li P; Kalina WV; Cooper D; Frenck RW; Hammitt LL; Türeci O; Nell H; Schaefer A; Ünal S; Tresnan DB; Mather S; Dormitzer PR; Şahin U; Jansen KU; Gruber WC Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine. N. Engl. J. Med 2020, 383, 2603–2615, DOI: 10.1056/NEJMoa2034577. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (3).Sadoff J; Gray G; Vandebosch A; Cárdenas V; Shukarev G; Grinsztejn B; Goepfert PA; Truyers C; Fennema H; Spiessens B; Offergeld K; Scheper G; Taylor KL; Robb ML; Treanor J; Barouch DH; Stoddard J; Ryser MF; Marovich MA; Neuzil KM; Corey L; Cauwenberghs N; Tanner T; Hardt K; Ruiz-Guiñazú J; Le Gars M; Schuitemaker H; Van Hoof J; Struyf F; Douoguih M Safety and Efficacy of Single-Dose Ad26.COV2.S Vaccine Against Covid-19. N. Engl. J. Med 2021, 384, 2187–2201, DOI: 10.1056/NEJMoa2101544. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (4).Falsey AR; Sobieszczyk ME; Hirsch I; Sproule S; Robb ML; Corey L; Neuzil KM; Hahn W; Hunt J; Mulligan MJ; McEvoy C; DeJesus E; Hassman M; Little SJ; Pahud BA; Durbin A; Pickrell P; Daar ES; Bush L; Solis J; Carr QO; Oyedele T; Buchbinder S; Cowden J; Vargas SL; Guerreros Benavides A; Call R; Keefer MC; Kirkpatrick BD; Pullman J; Tong T; Brewinski Isaacs M; Benkeser D; Janes HE; Nason MC; Green JA; Kelly EJ; Maaske J; Mueller N; Shoemaker K; Takas T; Marshall RP; Pangalos MN; Villafana T; Gonzalez-Lopez A Phase 3 Safety and Efficacy of AZD1222 (ChAdOx1 nCoV-19) Covid-19 Vaccine. N. Engl. J. Med 2021, 385, 2348–2360, DOI: 10.1056/NEJMoa2105290. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (5).Xia S; Zhang Y; Wang Y; Wang H; Yang Y; Gao GF; Tan W; Wu G; Xu M; Lou Z; Huang W; Xu W; Huang B; Wang H; Wang W; Zhang W; Li N; Xie Z; Ding L; You W; Zhao Y; Yang X; Liu Y; Wang Q; Huang L; Yang Y; Xu G; Luo B; Wang W; Liu P; Guo W; Yang X Safety and Immunogenicity of an Inactivated SARS-CoV-2 Vaccine, BBIBP-CorV: A Randomised, Double-Blind, Placebo-Controlled, Phase 1/2 Trial. Lancet Infect. Dis 2021, 21, 39–51, DOI: 10.1016/S1473-3099(20)30831-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (6).Zhang Y; Zeng G; Pan H; Li C; Hu Y; Chu K; Han W; Chen Z; Tang R; Yin W; Chen X; Hu Y; Liu X; Jiang C; Li J; Yang M; Song Y; Wang X; Gao Q; Zhu F Safety, Tolerability, and Immunogenicity of an Inactivated SARS-CoV-2 Vaccine in Healthy Adults Aged 18–59 Years: A Randomised, Double-Blind, Placebo-Controlled, Phase 1/2 Clinical Trial. Lancet Infect. Dis 2021, 21, 181–192, DOI: 10.1016/S1473-3099(20)30843-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (7).Ella R; Reddy S; Blackwelder W; Potdar V; Yadav P; Sarangi V; Aileni VK; Kanungo S; Rai S; Reddy P; Verma S; Singh C; Redkar S; Mohapatra S; Pandey A; Ranganadin P; Gumashta R; Multani M; Mohammad S; Bhatt P; Kumari L; Sapkal G; Gupta N; Abraham P; Panda S; Prasad S; Bhargava B; Ella K; Vadrevu KM; Aggarwal P; Aglawe V; Ali A; Anand N; Awad N; Bafna V; Balasubramaniyam G; Bandkar A; Basha P; Bharge V; Bhate A; Bhate S; Bhavani V; Bhosale R; Chalapathy D; Chaubal C; Chaudhary D; Chavan A; Desai P; Dhodi D; Dutta S; Garg R; Garg K; George M; Goyal P; Guleria R; Gupta S; Jain M; Jain M; Jindal S; Kalra M; Kant S; Khosla P; Kulkarni P; Kumar P; Kumar Y; Majumdar A; Meshram P; Mishra V; Mohanty S; Nair J; Pandey S; Panigrahi S; Patil B; Patil V; Rahate P; Raj V; Ramanand S; Rami K; Ramraj B; Rane S; Rao E; Rao N; Raphael R; Reddy G; Redkar V; Redkar S; Sachdeva A; Saha J; Sahoo J; Sampath P; Savith A; Shah M; Shanmugam L; Sharma R; Sharma P; Sharma D; Singh A; Singh J; Singh P; Sivaprakasam S; Subramaniam S; Sudheer D; Tandon S; Tariq M; Tripathi V; Vable M; Verma R; Waghmare S Efficacy, Safety, and Lot-to-Lot Immunogenicity of an Inactivated SARS-CoV-2 Vaccine (BBV152): Interim Results of a Randomised, Double-Blind, Controlled, Phase 3 Trial. Lancet 2021, 398, 2173–2184, DOI: 10.1016/S0140-6736(21)02000-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (8).Dunkle LM; Kotloff KL; Gay CL; Áñez G; Adelglass JM; Barrat Hernández AQ; Harper WL; Duncanson DM; McArthur MA; Florescu DF; Mc-Clelland RS; Garcia-Fragoso V; Riesenberg RA; Musante DB; Fried DL; Safirstein BE; McKenzie M; Jeanfreau RJ; Kingsley JK; Henderson JA; Lane DC; Ruíz-Palacios GM; Corey L; Neuzil KM; Coombs RW; Greninger AL; Hutter J; Ake JA; Smith K; Woo W; Cho I; Glenn GM; Dubovsky F Efficacy and Safety of NVX-CoV2373 in Adults in the United States and Mexico. N. Engl. J. Med 2022, 386, 531–543, DOI: 10.1056/NEJMoa2116185. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (9).Wang MY; Zhao R; Gao LJ; Gao XF; Wang DP; Cao JM SARS-CoV-2: Structure, Biology, and Structure-Based Therapeutics Development. Front. Cell. Infect. Microbiol 2020, 10, 1–17, DOI: 10.3389/fcimb.2020.587269. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (10).Watanabe Y; Allen JD; Wrapp D; McLellan JS; Crispin M Site-Specific Glycan Analysis of the SARS-CoV-2 Spike. Science 2020, 369, 330–333, DOI: 10.1126/science.abb9983. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (11).Wrapp D; Wang N; Corbett KS; Goldsmith JA; Hsieh C-L; Abiona O; Graham BS; McLellan JS Cryo-EM Structure of the 2019-nCoV Spike in the Prefusion Conformation. Science 2020, 367, 1260–1263, DOI: 10.1126/science.abb2507. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (12).Walls AC; Park YJ; Tortorici MA; Wall A; McGuire AT; Veesler D Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein. Cell 2020, 181, 281–292.e6, DOI: 10.1016/j.cell.2020.02.058. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (13).Sztain T; Ahn SH; Bogetti AT; Casalino L; Goldsmith JA; Seitz E; Mc-Cool RS; Kearns FL; Acosta-Reyes F; Maji S; Mashayekhi G; McCammon JA; Ourmazd A; Frank J; McLellan JS; Chong LT; Amaro RE A Glycan Gate Controls Opening of the SARS-CoV-2 Spike Protein. Nat. Chem 2021, 13, 963–968, DOI: 10.1038/s41557-021-00758-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (14).Zhang L; Zhou R Structural Basis of the Potential Binding Mechanism of Remdesivir to SARS-CoV-2 RNA-Dependent RNA Polymerase. J. Phys. Chem. B 2020, 124, 6955–6962, DOI: 10.1021/acs.jpcb.0c04198. [DOI] [PubMed] [Google Scholar]
  • (15).Jin Z; Du X; Xu Y; Deng Y; Liu M; Zhao Y; Zhang B; Li X; Zhang L; Peng C; Duan Y; Yu J; Wang L; Yang K; Liu F; Jiang R; Yang X; You T; Liu X; Yang X; Bai F; Liu H; Liu X; Guddat LW; Xu W; Xiao G; Qin C; Shi Z; Jiang H; Rao Z; Yang H Structure of Mpro From SARS-CoV-2 and Discovery of Its Inhibitors. Nature 2020, 582, 289–293, DOI: 10.1038/s41586-020-2223-y. [DOI] [PubMed] [Google Scholar]
  • (16).Świderek K; Moliner V Revealing the Molecular Mechanisms of Proteolysis of SARS-CoV-2 Mpro by QM/MM Computational Methods. Chem. Sci 2020, 11, 10626–10630, DOI: 10.1039/d0sc02823a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (17).Citarella A; Scala A; Piperno A; Micale N SARS-CoV-2 Mpro: A Potential Target for Peptidomimetics and Small-Molecule Inhibitors. Biomolecules 2021, 11, 607, DOI: 10.3390/biom11040607. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (18).Mengist HM; Dilnessa T; Jin T Structural Basis of Potential Inhibitors Targeting SARS-CoV-2 Main Protease. Front. Chem 2021, 9, 7, DOI: 10.3389/fchem.2021.622898. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (19).Gao Y; Yan L; Huang Y; Liu F; Zhao Y; Cao L; Wang T; Sun Q; Ming Z; Zhang L; Ge J; Zheng L; Zhang Y; Wang H; Zhu Y; Zhu C; Hu T; Hua T; Zhang B; Yang X; Li J; Yang H; Liu Z; Xu W; Guddat LW; Wang Q; Lou Z; Rao Z Structure of the RNA-dependent RNA Polymerase From COVID-19 Virus. Science 2020, 368, 779–782, DOI: 10.1126/science.abb7498. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (20).Hillen HS; Kokic G; Farnung L; Dienemann C; Tegunov D; Cramer P Structure of Replicating SARS-CoV-2 Polymerase. Nature 2020, 584, 154–156, DOI: 10.1038/s41586-020-2368-8. [DOI] [PubMed] [Google Scholar]
  • (21).Yin W; Mao C; Luan X; Shen DD; Shen Q; Su H; Wang X; Zhou F; Zhao W; Gao M; Chang S; Xie YC; Tian G; Jiang HW; Tao SC; Shen J; Jiang Y; Jiang H; Xu Y; Zhang S; Zhang Y; Xu HE Structural Basis for Inhibition of the RNA-dependent RNA Polymerase From SARS-CoV-2 by Remdesivir. Science 2020, 368, 1499–1504, DOI: 10.1126/science.abc1560. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (22).ClinicalTrials.gov. Expanded Access Remdesivir (RDV; GS- 5734). https://clinicaltrials.gov/ct2/show/NCT04323761, Accessed: 2022-01-12.
  • (23).Beigel JH; Tomashek KM; Dodd LE; Mehta AK; Zingman BS; Kalil AC; Hohmann E; Chu HY; Luetkemeyer A; Kline S; Lopez de Castilla D; Finberg RW; Dierberg K; Tapson V; Hsieh L; Patterson TF; Paredes R; Sweeney DA; Short WR; Touloumi G; Lye DC; Ohmagari N; Oh M.-d.; Ruiz-Palacios GM; Benfield T; Fätkenheuer G; Kortepeter MG; Atmar RL; Creech CB; Lundgren J; Babiker AG; Pett S; Neaton JD; Burgess TH; Bonnett T; Green M; Makowski M; Osinusi A; Nayak S; Lane HC Remdesivir for the Treatment of Covid-19. N. Engl. J. Med 2020, 383, 1813–1826, DOI: 10.1056/NEJMoa2007764. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (24).Grein J; Ohmagari N; Shin D; Diaz G; Asperges E; Castagna A; Feldt T; Green G; Green ML; Lescure F-X; Nicastri E; Oda R; Yo K; Quiros-Roldan E; Studemeister A; Redinski J; Ahmed S; Bernett J; Chelliah D; Chen D; Chihara S; Cohen SH; Cunningham J; D’Arminio Monforte A; Ismail S; Kato H; Lapadula G; L’Her E; Maeno T; Majumder S; Massari M; Mora-Rillo M; Mutoh Y; Nguyen D; Verweij E; Zoufaly A; Osinusi AO; DeZure A; Zhao Y; Zhong L; Chokkalingam A; Elboudwarej E; Telep L; Timbs L; Henne I; Sellers S; Cao H; Tan SK; Winterbourne L; Desai P; Mera R; Gaggar A; Myers RP; Brainard DM; Childs R; Flanigan T Compassionate Use of Remdesivir for Patients with Severe Covid-19. N. Engl. J. Med 2020, 382, 2327–2336, DOI: 10.1056/NEJMoa2007016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (25).Teoh SL; Lim YH; Lai NM; Lee SW Directly Acting Antivirals for COVID-19: Where Do We Stand? Front. Microbiol 2020, 11, 1857, DOI: 10.3389/fmicb.2020.01857. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (26).Consortium WST Repurposed Antiviral Drugs for COVID-19—Interim WHO SOLIDARITY Trial Results. N. Engl. J. Med 2021, 384, 497–511, DOI: 10.1056/NEJMoa2023184. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (27).Warren T; Jordan R; Lo M; Soloveva V; Ray A; Bannister R; Mackman R; Perron M; Stray K; Feng J; Xu Y; Wells J; Stuthman K; Welch L; Doerffler E; Zhang L; Chun K; Hui H; Neville S; Lew W; Park Y; Babusis D; Strickley R; Wong P; Swaminathan S; Lee W; Mayers D; Cihlar T; Bavari S Nucleotide Prodrug GS-5734 is a Broad-Spectrum Filovirus Inhibitor That Provides Complete Therapeutic Protection Against the Development of Ebola Virus Disease (EVD) in Infected Non-Human Primates. Open Forum Infectious Diseases. 2015; pp LB–2, DOI: 10.1093/ofid/ofv130.02. [DOI] [Google Scholar]
  • (28).Eastman RT; Roth JS; Brimacombe KR; Simeonov A; Shen M; Patnaik S; Hall MD Remdesivir: A Review of Its Discovery and Development Leading to Emergency Use Authorization for Treatment of COVID-19. ACS Cent. Sci 2020, 6, 672–683, DOI: 10.1021/acscentsci.0c00489. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (29).Aranda J; Orozco M RNA-dependent RNA Polymerase From SARS-CoV-2. Mechanism of Reaction and Inhibition by Remdesivir. bioRxiv 2020, 1–18, DOI: 10.1101/2020.06.21.163592. [DOI] [Google Scholar]
  • (30).Gordon CJ; Tchesnokov EP; Woolner E; Perry JK; Feng JY; Porter DP; Götte M Remdesivir Is a Direct-Acting Antiviral That Inhibits RNA-dependent RNA Polymerase From Severe Acute Respiratory Syndrome Coronavirus 2 With High Potency. J. Biol. Chem 2020, 295, 6785–6797, DOI: 10.1074/jbc.RA120.013679. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (31).Zhang L; Lin D; Sun X; Curth U; Drosten C; Sauerhering L; Becker S; Rox K; Hilgenfeld R Crystal Structure of SARS-CoV-2 Main Protease Provides a Basis for Design of Improved α-Ketoamide Inhibitors. Science 2020, 368, 409–412, DOI: 10.1126/science.abb3405. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (32).Kokic G; Hillen HS; Tegunov D; Dienemann C; Seitz F; Schmitzova J; Farnung L; Siewert A; Höbartner C; Cramer P Mechanism of SARS-CoV-2 Polymerase Stalling by Remdesivir. Nat. Commun 2021, 12, 1–7, DOI: 10.1038/s41467-020-20542-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (33).Byléhn F; Menéndez CA; Perez-Lemus GR; Alvarado W; De Pablo JJ Modeling the Binding Mechanism of Remdesivir, Favilavir, and Ribavirin to SARS-CoV-2 RNA-Dependent RNA Polymerase. ACS Cent. Sci 2021, 7, 164–174, DOI: 10.1021/acscentsci.0c01242. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (34).Srivastava M; Mittal L; Kumari A; Asthana S Molecular Dynamics Simulations Reveal the Interaction Fingerprint of Remdesivir Triphosphate Pivotal in Allosteric Regulation of SARS-CoV-2 RdRp. Front. Mol. Biosci 2021, 8, 655, DOI: 10.3389/fmolb.2021.639614. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (35).Warren TK; Jordan R; Lo MK; Ray AS; Mackman RL; Soloveva V; Siegel D; Perron M; Bannister R; Hui HC; Larson N; Strickley R; Wells J; Stuthman KS; Van Tongeren SA; Garza NL; Donnelly G; Shurtleff AC; Retterer CJ; Gharaibeh D; Zamani R; Kenny T; Eaton BP; Grimes E; Welch LS; Gomba L; Wilhelmsen CL; Nichols DK; Nuss JE; Nagle ER; Kugelman JR; Palacios G; Doerffler E; Neville S; Carra E; Clarke MO; Zhang L; Lew W; Ross B; Wang Q; Chun K; Wolfe L; Babusis D; Park Y; Stray KM; Trancheva I; Feng JY; Barauskas O; Xu Y; Wong P; Braun MR; Flint M; McMullan LK; Chen S-S; Fearns R; Swaminathan S; Mayers DL; Spiropoulou CF; Lee WA; Nichol ST; Cihlar T; Bavari S Therapeutic Efficacy of the Small Molecule GS-5734 Against Ebola Virus in Rhesus Monkeys. Nature 2016, 531, 381–385, DOI: 10.1038/nature17180. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (36).Siegel D; Hui HC; Doerffler E; Clarke MO; Chun K; Zhang L; Neville S; Carra E; Lew W; Ross B; Wang Q; Wolfe L; Jordan R; Soloveva V; Knox J; Perry J; Perron M; Stray KM; Barauskas O; Feng JY; Xu Y; Lee G; Rheingold AL; Ray AS; Bannister R; Strickley R; Swaminathan S; Lee WA; Bavari S; Cihlar T; Lo MK; Warren TK; Mackman RL Discovery and Synthesis of a Phosphoramidate Prodrug of a Pyrrolo[2,1-F][triazin-4-Amino] Adenine C-Nucleoside (GS-5734) for the Treatment of Ebola and Emerging Viruses. J. Med. Chem 2017, 60, 1648–1661, DOI: 10.1021/acs.jmedchem.6b01594. [DOI] [PubMed] [Google Scholar]
  • (37).Hillen H; Kokic G; Farnung L; Dienemann C; Tegunov D; Cramer P Structure of Replicating SARS-CoV-2 Polymerase. DOI: 10.2210/pdb6YYT/pdb, 2020. [DOI] [PubMed]
  • (38).Gao Y; Yan L; Huang Y; Liu F; Cao L; Wang T; Wang Q; Lou Z; Rao Z SARS-CoV-2 RNA-dependent RNA Polymerase in Complex With Cofactors in Reduced Condition. DOI: 10.2210/pdb7BTF/pdb, 2020. [DOI]
  • (39).Zamyatkin DF; Parra F; Machín Á; Grochulski P; Ng KK-S Binding of 2′-Amino-2′-Deoxycytidine-5′-Triphosphate to Norovirus Polymerase Induces Rearrangement of the Active Site. J. Mol. Biol 2009, 390, 10–16, DOI: 10.1016/j.jmb.2009.04.069. [DOI] [PubMed] [Google Scholar]
  • (40).Zamyatkin D; Parra F; Machin A; Grochulski P; Ng K Norovirus Polymerase+Primer/Template+CTP Complex at 6 mM MnCl2. DOI: 10.2210/pdb3H5Y/pdb, 2009. [DOI]
  • (41).Jorgensen WL; Chandrasekhar J; Madura JD; Impey RW; Klein ML Comparison of Simple Potential Functions for Simulating Liquid Water. J. Chem. Phys 1983, 79, 926–935, DOI: 10.1063/1.445869. [DOI] [Google Scholar]
  • (42).Schafmeister CEAF; Ross WS; Romanovski V LEaP. 1995.
  • (43).Maier JA; Martinez C; Kasavajhala K; Wickstrom L; Hauser KE; Simmerling C ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. J. Chem. Theory Comput 2015, 11, 3696–3713, DOI: 10.1021/acs.jctc.5b00255. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (44).Zgarbová M; Otyepka M; Šponer J; Mládek A; Banáš P; Cheatham TE; Jurečka P Refinement of the Cornell et al. Nucleic Acids Force Field Based on Reference Quantum Chemical Calculations of Glycosidic Torsion Profiles. J. Chem. Theory Comput 2011, 7, 2886–2902, DOI: 10.1021/ct200162x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (45).Banáš P; Hollas D; Zgarbová M; Jurečka P; Orozco M; Cheatham TE; Šponer J; Otyepka M Performance of Molecular Mechanics Force Fields for RNA Simulations: Stability of UUCG and GNRA Hairpins. J. Chem. Theory Comput 2010, 6, 3836–3849, DOI: 10.1021/ct100481h. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (46).Peters MB; Yang Y; Wang B; Füsti-Molnár L; Weaver MN; Merz KM Structural Survey of Zinc-Containing Proteins and Development of the Zinc AMBER Force Field (ZAFF). J. Chem. Theory Comput 2010, 6, 2935–2947, DOI: 10.1021/ct1002626. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (47).Vanquelef E; Simon S; Marquant G; Garcia E; Klimerak G; Delepine JC; Cieplak P; ; Dupradeau F-Y R.E.D. Server: A Web Service for Deriving RESP and ESP Charges and Building Force Field Libraries for New Molecules and Molecular Fragments. Nucleic Acids Res. 2011, 39, W511–W517, DOI: 10.1093/nar/gkr288. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (48).Wang F; Becker J-P; Cieplack P; Dupradeau F-Y R.E.D. Python: Object Oriented Programming for AMBER Force Fields. 2013.
  • (49).Dupradeau F-Y; Pigache A; Zaffran T; Savineau C; Lelong R; Grivel N; Lelong D; Rosanski W; Cieplak P The R.E.D. Tools: Advances in RESP and ESP Charge Derivation and Force Field Library Building. Phys. Chem. Chem. Phys 2010, 12, 7821–7839, DOI: 10.1039/C0CP00111B. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (50).Bayly CI; Cieplak P; Cornell W; Kollman PA A Well-Behaved Electrostatic Potential Based Method Using Charge Restraints for Deriving Atomic Charges: The RESP Model. J. Phys. Chem 1993, 97, 10269–10280, DOI: 10.1021/j100142a004. [DOI] [Google Scholar]
  • (51).Meagher KL; Redman LT; Carlson HA Development of Polyphosphate Parameters for Use with the AMBER Force Field. J. Comput. Chem 2003, 24, 1016–1025, DOI: 10.1002/jcc.10262. [DOI] [PubMed] [Google Scholar]
  • (52).Izaguirre JA; Sweet CR; Pande VS Biocomputing 2010; World Scientific, 2010; pp 240–251. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (53).Berendsen HJ; Postma J. v.; van Gunsteren WF; DiNola A; Haak JR Molecular Dynamics with Coupling to an External Bath. J. Chem. Phys 1984, 81, 3684–3690, DOI: 10.1063/1.448118. [DOI] [Google Scholar]
  • (54).Essmann U; Perera L; Berkowitz ML; Darden T; Lee H; Pedersen LG A Smooth Particle Mesh Ewald Method. J. Chem. Phys 1995, 103, 8577–8593, DOI: 10.1063/1.470117. [DOI] [Google Scholar]
  • (55).Roe DR; Cheatham III TE PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data. J. Chem. Theory Comput 2013, 9, 3084–3095, DOI: 10.1021/ct400341p. [DOI] [PubMed] [Google Scholar]
  • (56).Bakan A; Meireles LM; Bahar I ProDy: Protein Dynamics Inferred from Theory and Experiments. Bioinformatics 2011, 27, 1575–1577, DOI: 10.1093/bioinformatics/btr168. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (57).Contreras-García J; Johnson ER; Keinan S; Chaudret R; Piquemal J-P; Beratan DN; Yang W NCIPLOT: A Program for Plotting Non-Covalent Interaction Regions. J. Chem. Theory Comput 2011, 7, 625–632, DOI: 10.1021/ct100641a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (58).Boto RA; Peccati F; Quan C; Carbone A; Piquemal J-P; Maday Y; Contreras-García J NCIPLOT4: Fast, Robust, and Quantitative Analysis of Noncovalent Interactions. J. Chem. Theory Comput 2020, 16, 39, DOI: 10.1021/acs.jctc.0c00063. [DOI] [PubMed] [Google Scholar]
  • (59).Melo MCR; Bernardi RC; De La Fuente-Nunez C; Luthey-Schulten Z Generalized Correlation-Based Dynamical Network Analysis: A New High-Performance Approach for Identifying Allosteric Communications in Molecular Dynamics Trajectories. J. Chem. Phys 2020, 153, 44130, DOI: 10.1063/5.0018980. [DOI] [PubMed] [Google Scholar]
  • (60).Bastian M; Heymann S; Jacomy M Gephi: An Open Source Software for Exploring and Manipulating Networks. Proceedings of the International AAAI Conference on Web and Social Media 2009, 3, 361–362. [Google Scholar]
  • (61).Pettersen EF; Goddard TD; Huang CC; Couch GS; Greenblatt DM; Meng EC; Ferrin TE UCSF Chimera—A Visualization System for Exploratory Research and Analysis. J. Comput. Chem 2004, 25, 1605–1612, DOI: 10.1002/jcc.20084. [DOI] [PubMed] [Google Scholar]
  • (62).Humphrey W; Dalke A; Schulten K VMD: Visual Molecular Dynamics. J. Mol. Graphics 1996, 14, 33–38, DOI: 10.1016/0263-7855(96)00018-5. [DOI] [PubMed] [Google Scholar]
  • (63).Leddin E; Group CR; Cisneros GA CisnerosResearch/AMBER-EDA: First Release. DOI: 10.5281/zenodo.4469902, 2020. [DOI]
  • (64).Kollman PA; Massova I; Reyes C; Kuhn B; Huo S; Chong L; Lee M; Lee T; Duan Y; Wang O, Wei Donini; Cieplak P; Srinivasan J; Case DA; Cheatham TE Calculating Structures and Free Energies of Complex Molecules: Combining Molecular Mechanics and Continuum Models. Acc. Chem. Res 2000, 33, 889–897. [DOI] [PubMed] [Google Scholar]
  • (65).Wang W; Donini O; Reyes CM; Kollman PA Biomolecular Simulations: Recent Developments in Force Fields, Simulations of Enzyme Catalysis, Protein-Ligand, Protein-Protein, and Protein-Nucleic Acid Noncovalent Interactions. Annu. Rev. Bio-phys. Biomol. Struct 2001, 30, 211–243. [DOI] [PubMed] [Google Scholar]
  • (66).Wang J; Hou T; Xu X Recent Advances in Free Energy Calculations with a Combination of Molecular Mechanics and Continuum Models. Curr. Comput.-Aided Drug Des 2006, 2, 287–306. [Google Scholar]
  • (67).Homeyer N; Gohlke H Free Energy Calculations by the Molecular Mechanics Poisson–Boltzmann Surface Area Method. Mol. Inf 2012, 31, 114–122. [DOI] [PubMed] [Google Scholar]
  • (68).Miller III BR; McGee TD Jr; Swails JM; Homeyer N; Gohlke H; Roitberg AE MMPBSA.py: An Efficient Program for End-State Free Energy Calculations. J. Chem. Theory Comput 2012, 8, 3314–3321. [DOI] [PubMed] [Google Scholar]
  • (69).Hou T; Wang J; Li Y; Wang W Assessing the Performance of the MM/PBSA and MM/GBSA Methods. 1. The Accuracy of Binding Free Energy Calculations Based on Molecular Dynamics Simulations. J. Chem. Inf. Model 2011, 51, 69–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (70).Zuo Z; Weng J; Wang W Insights into the Inhibitory Mechanism of D13–9001 to the Multidrug Transporter AcrB through Molecular Dynamics Simulations. J. Phys. Chem. B 2016, 120, 2145–2154. [DOI] [PubMed] [Google Scholar]
  • (71).Li CH; Zuo ZC; Su JG; Xu XJ; Wang CX The Interactions and Recognition of Cyclic Peptide Mimetics of Tat with HIV-1 TAR RNA: A Molecular Dynamics Simulation Study. J. Biomol. Struct. Dyn 2013, 31, 276–287. [DOI] [PubMed] [Google Scholar]
  • (72).Zuo Z; Liu J Structure and Dynamics of Cas9 HNH Domain Catalytic State. Sci. Rep 2017, 7, 1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (73).Zuo Z; Smith RN; Chen Z; Agharkar AS; Snell HD; Huang R; Liu J; Gonzales EB Identification of a Unique Ca2+-Binding Site in Rat Acid-Sensing Ion Channel 3. Nat. Commun 2018, 9, 1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (74).Zhang L; Zhang D; Wang X; Yuan C; Li Y; Jia X; Gao X; Yen HL; Cheung PPH; Huang X 1′–Ribose Cyano Substitution Allows Remdesivir to Effectively Inhibit Nucleotide Addition and Proofreading During SARS-CoV-2 Viral RNA Replication. Phys. Chem. Chem. Phys 2021, 23, 5852–5863, DOI: 10.1039/d0cp05948j. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

SI
NIHMS1796627-supplement-SI.pdf (31.6MB, pdf)

Data Availability Statement

The initial structures and parameters for the non-standard incoming nucleotides used for this study, and the initial coordinates and parameter sets for all systems, are provided as part of the Supporting Information. All simulations and analysis third-party software employed are described and referenced in the methods section. The EDA software is available at: https://github.com/CisnerosResearch/AMBER-EDA

RESOURCES