Computational protocol: Integrative modelling of TIR domain-containing adaptor molecule inducing interferon-β (TRIF) provides insights into its autoinhibited state

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Protocol publication

[…] A series of dockings were attempted to identify a putative docked pose between the N-terminal domain and the TIR domain and to assess if the same docking pose was achieved through these different strategies and thus reduce the chances of false positives. The structure of N-terminal domain (PDB ID: 4BSX) and the representative NMR structure of the TIR domain (PDB ID: 2M1X) were used in this study. Prior to docking, the His 434 residue in the TIR domain was modified back to Proline and subsequently energy minimized in SYBYL. Two docking programs- Cluspro [] and our in-house program, CAPSDOCK (Oommen K. Mathew and R. Sowdhamini, unpublished results), were used to generate docked poses. Different strategies were employed to generate the docked poses. Blind docking of the two domains was first performed using CAPSDOCK (Oommen K. Mathew and R. Sowdhamini, unpublished results) and the top models assessed for their interface residues. This was used as a starting point, coupled with known experimental information of the TIR domain and the conserved residues on the N-terminal domain, towards obtaining a more accurate model of the docked complex. Following this, multiple semi-guided docking runs were done using Cluspro []. A different region of each domain was used for guiding the docking. For example, using the BB loop residues of TIR domain to guide, it was predicted to bind to a certain region in the vicinity of the major cleft on the N-terminal domain. Similarly, using the acidic residues lining the major cleft of N-terminal domain to guide the docking, the top poses were those in which the BB loop was present in the interface Docked poses were ranked using DockScore [] and interactions at the interface identified using PPCheck []. Both these softwares were developed in the lab. DockScore is a scoring scheme that utilizes various parameters such as the number of interfacial hydrophobic residues, spatial clustering of residues, residue conservation, number of short contacts and accessible surface area at the interface to discriminate between native and non-native poses. PPCheck calculates pseudoenergies for the various interactions operating at the protein-protein interface using distance thresholds to define a particular type of interaction. These pseudoenergies are used to quantify the strength of the protein-protein interactions. Additionally, PPCheck can also be used to identify hotspot residues. Subsequent to the analysis of the top ranked poses, further refinement was carried out by employing the HADDOCK docking program, using the N-terminal domain residues conserved in all vertebrates and the TIR domain BB loop residues to guide the docking, followed by ranking of the docked poses by DockScore, []. Interface residues were identified by PPCheck []. Electrostatic surface potential maps were generated through the APBS web server [, ]. [...] To assess the stability of the docked pose, molecular dynamics simulations were carried out using the GROMACS 54a7 force field. The complex of the N-terminal domain and TIR domain was first processed and then solvated in a rhombic dodecahedron box using the SPCE water model. The distance between the edge of the box and the protein complex was set to 10 nm. The system was energy minimized using 50,000 steps of steepest descent with a time step of 1 femtosecond and no position restraints applied. The protein complex was then restrained while the solvent around it was equilibrated for 200 ps with a time step of 2 femtoseconds in order for the system to attain a temperature of 300 K. The V-rescale thermostat [] was used for NVT equilibration. NPT equilibration was carried out using the Berendsen barostat [] for 200 ps to set the pressure to 1 bar. Prior to production MD run, the restraints on the protein complex were released. Production MD was carried out for 1 microsecond using the leap-frog integrator with the time step set to 3 femtoseconds and the Parrinello-Rahman barostat [] to maintain the pressure at 1 bar. To prevent the system from exploding due to a slightly higher timestep, certain hydrogen atoms were replaced by dummy atoms by use of the virtual sites option. The particle mesh-Ewald (PME) algorithm, with the Verlet cut-off scheme, was used for long-distance electrostatics []. The cut-off distance for long-distance electrostatics and van der Waals interactions was set to 1 nm. Bonds including heavy atom-H bonds were restrained using the LINCS algorithm []. Positions and velocities were saved every 3334 steps (10 ps). Hydrogen bonds were identified using the g_hbond tool implemented in GROMACS. The occupancy of each hydrogen bond was calculated by using a Python script, readHBmap.py, supplied for use with GROMACS trajectories. For analyses of interaction energies at the interface of the N-TIR complex, snapshots were extracted at every 1 ns, and provided as input to the PPCheck algorithm and the results of all snapshots were consolidated using short python scripts developed in the lab. […]

Pipeline specifications

Software tools Cluspro, DOCKSCORE, PPCheck, HADDOCK, GROMACS, P-LINCS
Application Protein interaction analysis
Chemicals Hydrogen