Study of the Rv1417 and Rv2617c Membrane Proteins and Their Interactions with Nicotine Derivatives as Potential Inhibitors of Erp Virulence-Associated Factor in Mycobacterium tuberculosis: An In Silico Approach

Abstract

The increasing emergence of Mycobacterium tuberculosis (Mtb) strains resistant to traditional anti-tuberculosis drugs has alarmed health services worldwide. The search for new therapeutic targets and effective drugs that counteract the virulence and multiplication of Mtb represents a challenge for the scientific community. Several studies have considered the erp gene a possible therapeutic target in the last two decades, since its disruption negatively impacts Mtb multiplication. This gene encodes the exported repetitive protein (Erp), which is located in the cell wall of Mtb. In vitro studies have shown that the Erp protein interacts with two putative membrane proteins, Rv1417 and Rv2617c, and the impairment of their interactions can decrease Mtb replication. In this study, we present five nicotine analogs that can inhibit the formation of heterodimers and trimers between these proteins. Through DFT calculations, molecular dynamics, docking, and other advanced in silico techniques, we have analyzed the molecular complexes, and show the effect these compounds have on protein interactions. The results show that four of these analogs can be possible candidates to counteract the pathogenicity of Mtb. This study aims to combine research on the Erp protein as a therapeutic target in the search for new drugs that serve to create new therapies against tuberculosis disease.

Keywords: Erp; Rv1417; Rv2617c; molecular dynamics; nicotine analogs; tuberculosis.

Figure 1

Nicotine analog structures. The 2D depiction shows the different positions of the chlorine substituents. Analog molecules were renamed according to chlorine positions. Optimized structures and quantum ESP surfaces were obtained by DFT calculations using the polarizable continuum model (PCM) with water as an implicit solvent. MM-ESP surfaces were calculated using APBS methodology. On all surfaces, the different colors indicate their molecular electrostatic properties: red for the most nucleophilic zones, dark blue for the most electrophilic zones, and green for neutral.

Figure 2

Analysis of the RvP structures in the new MD simulations. (a) Indicators of structural stability. The four graphs compare the structures of this work (blue and orange lines) with those presented previously (black and green lines). (b) Surfaces of the ESP of the final RvP structures. The range of colors corresponds to that described above. (c) B-factor values mapped onto protein structures. The red color indicates high fluctuations, the white color represents average values, and the green color represents minor fluctuations. (d) High-fluctuation residues identified on the RvP structures.

Figure 3

Highly conserved pockets throughout MD simulations. (a) Rv1417 structure. (b) RV2617 structure. The heat map is built based on the number of times each residue is part of a pocket for each analyzed frame. Thus, the blue color indicates a low density of forming a pocket, the green color indicates medium probability, and the red color indicates high probability. (c,d) Residues with the highest percentage of density calculated for the structures of the RvPs.

Figure 4

Analysis of RvP–NAM interactions. (a,b) Calculation of the free binding energies for the Rv1417 and Rv2617c systems. In both systems, the purple boxes indicate the pockets where the NAMs were docked. The circles show the interaction sites of each NAM and the residues with which they have contact. The color of the surfaces corresponds to the contribution to the interaction energy of each residue: blue for favorable energies and red for unfavorable energies. The graphs represent the energy analysis per residue. The colors of the lines were only used to differentiate each NAM. (c,d) Analysis of the b-factor of the proteins interacting with the NAMs. (e,f) Effect of NAMs on the ESP of RvPs. On the left, the protein is shown without the drug, and on the right, with the drug. The color scale used is red for electronegative regions and blue for electropositive regions. The white color indicates hydrophobic areas. In both representations, the RvP–NIC system is used.

Figure 5

Analysis of the systems solvated by NAMs. (a,b) Final structures of the Sol14–NIA and Sol26–NIA systems. Proteins are shown in blue (Rv1417) and orange (Rv2617c) colors. NIA molecules are shown on magenta-colored surfaces; the lipid membrane is represented in transparent gray. (c,d) BFE values per residue mapped onto protein surfaces. Blue areas indicate favorable binding energies, and red areas represent repulsion. White areas indicate non-interacting residues. (e) Density profiles of different groups of the systems solvated by NIA. (f) Calculation of the diffusion coefficients of systems. (g) Heat maps as Circos plots of the b-factor of the different systems. Circles indicate (from the center out) protein structures and NAMs, RvPs without drugs, and systems NIA, NIB, NIC, NID, and NIE. The blue color indicates low vibration of the residue, while the red indicates high vibration. The central lines indicate the interactions between the protein residues and the different NAMs.

Figure 6

Analysis of systems solvated by NAMs. (a,c) BFE analysis of RvP–NAM binding sites. (b,d) Both subfigures show the complex formed with the NIA drug. (e) Surfaces of the ESP of the RvP structures with and without drug. Enlarged figures show binding sites. The same color codes and ranges for measurable properties used in the analyses of the complexes at the active sites are used in all figures.

Figure 7

Comparison of the interaction energies of the best 1000 RvP–Erp dimeric complexes. The energies were obtained from molecular docking calculations. (a) Energies of the dimers obtained in our previous analyses. Numbers 14 and 26 indicate the protein used as the receptor, Rv1417 or Rv2617c, respectively. (b,c) Energy for the Rv1417–Erp dimers. (d,e) Energy for the Rv2617c–Erp dimers. All graphs were built on the same scale of energy values.