How to use ITsFlexible Online

Use ITsFlexible online to predict antibody and TCR CDR3 loop flexibility from structure.

ITsFlexible predicts whether an antibody or T cell receptor CDR3 loop is likely to behave as a rigid structural element or sample multiple conformations. The Nature Machine Intelligence paper frames this as a loop-flexibility classification problem rather than a full molecular dynamics replacement, which is useful because loop plasticity strongly influences binding interpretation, docking, and immune-protein engineering.

On Neurosnap, researchers upload an Input Structure, specify the Loop Chain, and define Residue Start and Residue End for the loop under study. The Model setting distinguishes the loop-centric predictor from the anchors-based predictor that also uses flanking framework context. This workflow is well suited to candidate-antibody review, TCR modeling, and deciding whether a loop may need ensemble-aware treatment.

The service is especially valuable when a structure exists but its conformational certainty is unclear. A high flexibility call can change how researchers interpret docking failures, interface ambiguity, or unexpected sequence tolerance.

How ITsFlexible Works

The model uses a graph neural network trained on the ALL-conformations dataset, a large structural collection assembled from many experimentally observed loop states. The key scientific idea is that CDR flexibility can be learned from structural context directly, without running long simulations for every query loop.

On Neurosnap, the Loop model focuses on the geometry of the loop residues themselves, whereas the Anchors model compares the loop in the context of neighboring Fv anchor regions. That distinction matters when IMGT numbering is available and users want to emphasize either local shape or broader framework restraints.

Researchers should interpret the output as a triage signal: rigid predictions suggest a more single-state loop interpretation, while flexible predictions argue for caution when treating one static structure as definitive.

What is Neurosnap?

Neurosnap is the leading platform for bioinformatics and computational science focused on expanding access to powerful modeling and simulation tools. Because many state-of-the-art machine learning systems remain complex to install, configure, and scale, Neurosnap offers a clean, browser-based workspace that removes the burden of infrastructure management, dependency conflicts, and command-line tooling.

Built for biologists, chemists, and cross-disciplinary scientists, the platform enables advanced computational workflows without requiring expertise in software engineering or cloud architecture. Researchers can launch analyses through an intuitive interface, connect programmatically through a comprehensive API, and rely on automated resource management to scale workloads efficiently. By taking care of the underlying compute and operational complexity, Neurosnap allows teams to devote their energy to scientific progress and faster iteration. Security and data protection remain foundational principles, with clear safeguards outlined in our Terms of Use and Privacy Policy to ensure your work stays protected.

Advancing Discovery with ITsFlexible on Neurosnap

Using ITsFlexible on Neurosnap could drastically accelerate CDR3 loop flexibility prediction for antibody and TCR structure interpretation.

Immune-specific structural input: ITsFlexible is tailored to antibody and TCR loop questions rather than general protein flexibility scoring.
Large structural training set: The ALL-conformations dataset lets the model learn recurring patterns of rigid versus multi-state loop behavior.
Targeted controls: Residue Start, Residue End, and Model let researchers define exactly which loop and which context they want to score.
Ensemble-awareness cue: A predicted flexible loop tells researchers when docking, design, or binding interpretation may require more than one static conformation.

How to Use ITsFlexible on Neurosnap

To harness the capabilities of ITsFlexible, researchers can follow this streamlined workflow within Neurosnap:

Access Neurosnap: Start by logging in to the Neurosnap website.
Select Tool: From the list of available tools, choose ITsFlexible.
Provide Inputs: Provide all the inputs specified within the submission panel and optionally configure the tool as desired.
Run Tool: Submit the ITsFlexible job and Neurosnap will execute it in the cloud, automatically notifying you as soon as your results are ready.
Review Output: Explore your results through rich visualizations, including figures, plots, and interactive views designed to help you analyze findings with clarity and confidence.

Citations

Please cite the original work when using ITsFlexible in publications or research outputs.

Spoendlin, F.C., FernÃ¡ndez-Quintero, M.L., Raghavan, S.S.R. et al. Predicting the conformational flexibility of antibody and T cell receptor complementarity-determining regions. Nat Mach Intell (2025). https://doi.org/10.1038/s42256-025-01131-6

Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/

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