Exploring the different states of wild-type T-cell receptor and mutant conformational chan

Molecular dynamics simulation data of wild-type and mutant IG4 T-cell receptors interacting with the NY-ESO tumor epitope peptide. The dataset comprises six simulations totaling 6000 nanoseconds (6µs), capturing states before, during, and after antigen binding. It was produced by Sunil Kumar Tripathi and shared via paperswithcode.

Use Cases

• Analyzing conformational changes in complementarity-determining region (CDR) loops based on simulation trajectories.
• Comparing structural rigidity between wild-type and mutant TCRs based on the described induced fit mechanism.
• Investigating the role of CDRα3 and CDRβ3 loops in antigen affinity based on the described significant structural changes.
• Studying the differential dynamics of TCR α and β chain loops in antigen interaction based on the described findings.

Strengths

• Simulation data totals 6000 nanoseconds (6µs), providing a substantial timescale for analysis.
• Explicitly compares three distinct biological states: prior to antigen binding, upon binding, and after release.
• Includes both a wild-type and a mutant system, enabling comparative analysis of conformational rigidity.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file formats are unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Sunil Kumar Tripathi via paperswithcode

Collection Method

Large-scale molecular dynamics simulations performed for 1000 ns per state per system.