Insights into the biased activity of dextromethorphan and haloperidol towards SARS-CoV-2 NSP6: in silico binding mechanistic analysis

Abstract

The outbreak of novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus continually led to infect a large population worldwide. SARS-CoV-2 utilizes its NSP6 and Orf9c proteins to interact with sigma receptors that are implicated in lipid remodeling and ER stress response, to infect cells. The drugs targeting the sigma receptors, sigma-1 and sigma-2, have emerged as effective candidates to reduce viral infectivity, and some of them are in clinical trials against COVID-19. The antipsychotic drug, haloperidol, exerts remarkable antiviral activity, but, at the same time, the sigma-1 benzomorphan agonist, dextromethorphan, showed pro-viral activity. To explore the potential mechanisms of biased binding and activity of the two drugs, haloperidol and dextromethorphan towards NSP6, we herein utilized molecular docking-based molecular dynamics simulation studies. Our extensive analysis of the protein-drug interactions, structural and conformational dynamics, residual frustrations, and molecular switches of NSP6-drug complexes indicates that dextromethorphan binding leads to structural destabilization and increase in conformational dynamics and energetic frustrations. On the other hand, the strong binding of haloperidol leads to minimal structural and dynamical perturbations to NSP6. Thus, the structural insights of stronger binding affinity and favorable molecular interactions of haloperidol towards viral NSP6 suggests that haloperidol can be potentially explored as a candidate drug against COVID-19. KEY MESSAGES: •Inhibitors of sigma receptors are considered as potent drugs against COVID-19. •Antipsychotic drug, haloperidol, binds strongly to NSP6 and induces the minimal changes in structure and dynamics of NSP6. •Dextromethorphan, agonist of sigma receptors, binding leads to overall destabilization of NSP6. •These two drugs bind with NSP6 differently and also induce differences in the structural and conformational changes that explain their different mechanisms of action. •Haloperidol can be explored as a candidate drug against COVID-19.

Keywords: COVID-19; Dextromethorphan; Haloperidol; Molecular docking; Molecular dynamics; NSP6.

Fig. 1

Three-dimensional model structure of SARS-CoV-2 NSP6 generated by AlphaFold. The transmembrane helices predicted through THHMM server

Fig. 2

Molecular docking interactions of two drugs with SARS-CoV-2 NSP6 protein. Schematic representation of interactions made by a dextromethorphan and b haloperidol with NSP6 and their corresponding Ligplot+

Fig. 3

Probability distributions of structural parameters of NSP6 systems. a Cα-RMSD. b Radius of gyration (Rg). c SASA. d RMSF for NSP6 (green), NSP6-haloperidol (blue), and NSP6-dextromethorphan (red)

Fig. 4

Secondary structures of NSP6 systems. Time evolution of the secondary structure profiles a NSP6, b NSP6-haloperidol, and c NSP6-dextromethorphan complexes

Fig. 5

Principal component analysis. a Projection of the motion of the protein in phase space along the PC1 and PC2 for over 100 ns of MD simulation at 300°K. b Average Eigen RMSF values for NSP6 systems were predicted for PC1. The color code for the figure is: NSP6 (black), NSP6-haloperidol (green), and NSP6-dextromethorphan (red)

Fig. 6

The free energy landscape (FEL) of the simulated NSP6 systems based on the principal component analysis. a NSP6. b NSP6-haloperidol. c NSP6-dextromethorphan. The color bar represents the free energy value according to kcal mol⁻¹. Dark blue spots indicate the energy minima and energetically favored protein conformations, and yellow spots indicate the unfavorable high-energy conformations

Fig. 7

The per-residue binding free energy decomposition for the simulated NSP6-haloperidol (blue) and NSP6-dextromethorphan (red). The free energy values ≥ 0.1 kcal/mol contributes more to the binding interaction

Fig. 8

Dynamic cross-correlation map (DCCM) of the Cα atoms around their mean positions computed through the DynaMut web server during the simulation. a NSP6. b NSP6-haloperidol. c NSP6-dextromethorphan complexes. The degrees of the correlation motions and anti-correlation motions are represented in blue and red, respectively. The degrees of motions correspond to the color bar

Fig. 9

Frustration analysis in NSP6-drug complexes. The changes in residual frustration are distributed along the structural regions of NSP6. a The changes in minimal frustration values in NSP6-drug complex. b The changes in highly frustration values in NSP6-drug complex. The secondary structural regions are represented as: H-α-helix and S-β-strands

Fig. 10

The structural snapshots of NSP6-drug complex observed during the MD simulation (0 ns, 25 ns, 50 ns, 100 ns) for the most abundant structure of a–d NSP6-dextromethorphan and e–h NSP6-haloperidol