Molecular and Structural Basis of Cross-Reactivity in M. tuberculosis Toxin–Antitoxin Systems
Abstract
:1. Introduction
2. Results
2.1. Comparisons of TA Interfaces Predict Cases for Potential Cross-Talk and Reveal Reasons for Insulation in Others
2.2. Templates Could Be Identified for Toxins at a Higher Confidence than Antitoxins
2.3. High Confidence Complexes Could Be Generated for Select TA Systems
2.4. Assessment of the Modelled Complexes Reveals Strengths and Limitations of Homology Modelling of TA Systems
2.5. Use of High Confidence Modelled Complexes to Explore Cross-Reactivity
2.6. In-Silico Point Mutation of Antitoxin Residues Is Predicted to Relax the Specificity
2.7. Modelled Non-Cognate TA Pairs that Fail to Show Cross-Talk in Experiments Differ in Their Interfaces
2.8. MazEF Systems from M. tuberculosis Show Weak Signals for Cross-Reactivity
3. Discussion
4. Conclusions
5. Materials and Methods
5.1. Comparative Modelling of Toxins, Antitoxins and TA Complexes
5.2. Assessment of Toxin–Antitoxin Interfaces
- Surface complementarity was checked using Sc statistics, which measures the geometric surface complementarity of protein–protein interfaces [53]. Sc depends on the relative shape of the surfaces with respect to each other and on the extent to which the interaction brings individual elements of opposing surfaces into proximity. The score ranges between 0 and 1 and the threshold is generally decided based on the shape complementarity between antigen–antibody interfaces, where the weakest shape complementarity interface is reported with Sc values between 0.64 and 0.69.
- Electrostatic surface complementarity was assessed by calculating the electrostatic potential of the proteins. Hydrogens were added to the individual proteins. Charges were assigned to the residues using PDB2PQR [54] plugin and electrostatics calculation was performed using APBS [55] plugin in Chimera 1.13.1. The molecular surface was then color based on electrostatic potential and scaled between ±10 kBT and manually inspected.
- Interaction energy between toxin and antitoxin was calculated using AnalyseComplex module from FoldX package [28]. FoldX force-field is empirical in nature with terms for de-solvation energies, coulombic interactions, van der Waal’s forces, hydrogen bonding, entropic changes, and others. All the structures were energy minimized with GROMACS v5.1 using CHARMM27 force-field and steepest descent method for either 50,000 steps or till convergence. A dodecahedron box with TIP3P water molecules was defined around the protein and the system was neutralized by adding counter ions prior to minimization. The structures were further repaired for any distorted geometry using RepairPDB module from FoldX prior to energy calculations. The complex structures were minimized iteratively till no further improvement in the energy values.
5.3. Using Structures to Explore Cross-Reactivity between Non-Cognate Toxins and Antitoxins
5.4. Prediction of Hotspot Residues at the Interface and In-Silico Mutations Using FoldX
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Complex Structures to be Compared (Vap) | IS-Score | z-Score | % Seq. Identity | No. of Aligned Contacts | RMSD (Ǻ) | p-Value |
---|---|---|---|---|---|---|
BC2–BC11 | 0.25 | 5 | 10 | 24 | 3.11 | 3.2 × 10−3 |
BC2–BC15 | 0.24 | 5 | 5 | 23 | 3.27 | 3 × 10−3 |
BC11–BC15 | 0.52 | 23 | 39 | 48 | 1.98 | 4.2 × 10−11 |
BC4–BC5 | 0.81 | 45 | 40 | 70 | 0.89 | 2.5 × 10−19 |
Complex Structure | IS-Score | z-Score | % Seq. Identity | No. of Aligned Contacts | RMSD (Å) | p-Value | Shape Complementarity for Non-Cognate Pair (Sc) |
---|---|---|---|---|---|---|---|
BC15–B11C15 | 0.57 | 24 | 70 | 40 | 1.62 | 3.8 × 10−11 | 0.67 |
BC11–B15C11 | 0.54 | 23 | 76 | 38 | 1.46 | 8.3 × 10−11 | 0.60 |
BC4–B5C4 | 0.81 | 49 | 75 | 79 | 0.25 | 2.2 × 10−21 | 0.67 |
BC5–B4C5 | 0.83 | 49 | 83 | 80 | 0.23 | 2.0 × 10−21 | 0.65 |
TA System | Sc Statistics | Interaction Energy (Kcal/mol) |
---|---|---|
VapBC3 | 0.59 | - |
VapBC4 | 0.64 | −35.04 |
VapBC21 | 0.64 | −15.83 |
MazEF3 | 0.68 & 0.445 | −17.2 |
MazEF6 | 0.67 & 0.67 | −22.2 |
MazEF9 | 0.62 & 0.65 | −16.2 |
Complex Structure | IS-Score | z-Score | % Seq. Identity | RMSD (Å) | p-Value | Shape Complementarity (Sc) |
---|---|---|---|---|---|---|
BC2–B11C2 | 0.3 | 9.5 | No residue from antitoxin | 2.9 | 7 × 10−5 | 0.60 |
BC11–B2C11 | 0.25 | 5.7 | No residue from antitoxin | 3.18 | 3.3 × 10−3 | 0.59 |
Complex Structure to be Compared (Maz) | IS-Score | z-Score | % Seq. Identity | No. of Aligned Contacts | RMSD (Å) | p-Value |
---|---|---|---|---|---|---|
EF4-EF6 | 0.16 | 1.5 | 35 | 7 | 2.38 | 1.9 × 10−1 |
EF4-EF3 | 0.45 | 16.3 | 30 | 18 | 2.39 | 7.5 × 10−8 |
EF4-EF7 | 0.12 | −0.4 | 10 | 3 | 1.78 | 0.8 × 10−1 |
EF4-EF9 | 0.16 | 0.6 | 0 | 8 | 2.75 | 3.9 × 10−1 |
EF3-EF6 | 0.15 | 0.84 | 25 | 4 | 2.32 | 3.4 × 10−1 |
EF3-EF7 | 0.13 | 0.34 | 11 | 4 | 3.52 | 5.0 × 10−1 |
EF6-EF7 | 0.20 | 3.75 | 4 | 12 | 3.00 | 2.3 × 10−2 |
EF6-EF9 | 0.38 | 15.3 | 7 | 20 | 1.56 | 2.4 × 10−7 |
EF3-EF9 | 0.14 | 0.12 | 0 | 8 | 3.81 | 5.8 × 10−1 |
EF7-EF9 | 0.18 | 2.67 | 20 | 13 | 3.13 | 6.6 × 10−2 |
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Tandon, H.; Melarkode Vattekatte, A.; Srinivasan, N.; Sandhya, S. Molecular and Structural Basis of Cross-Reactivity in M. tuberculosis Toxin–Antitoxin Systems. Toxins 2020, 12, 481. https://doi.org/10.3390/toxins12080481
Tandon H, Melarkode Vattekatte A, Srinivasan N, Sandhya S. Molecular and Structural Basis of Cross-Reactivity in M. tuberculosis Toxin–Antitoxin Systems. Toxins. 2020; 12(8):481. https://doi.org/10.3390/toxins12080481
Chicago/Turabian StyleTandon, Himani, Akhila Melarkode Vattekatte, Narayanaswamy Srinivasan, and Sankaran Sandhya. 2020. "Molecular and Structural Basis of Cross-Reactivity in M. tuberculosis Toxin–Antitoxin Systems" Toxins 12, no. 8: 481. https://doi.org/10.3390/toxins12080481