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We use a variety of validation techniques to guarantee high-quality and confidence in our models. These include:
pLDDT Scores: We assess the model’s local confidence-the higher the pLDDT score, the more reliable the model.
Ramachandran Plot: This checks if the model’s geometry makes sense, ensuring residues fall within acceptable areas.
ERRAT Score: It evaluates overall model quality-the lower the score, the better the quality.
MolProbity Analysis: Provides a comprehensive overview of the model’s geometry and stereochemistry, along with a detailed validation report.
Experimental Validation: We use experimental methods like X-ray crystallography, NMR spectroscopy, and Cryo-EM to further confirm the model’s accuracy.

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EMSA is a lab method that helps researchers spot and study how proteins interact with nucleic acids. Basically, you take a labeled nucleic acid probe, mix it with a protein sample, and then run it through a non-denaturing gel. If the protein binds to the probe, the combo moves slower through the gel than the free probe, making a clear band shift. You can see this shift using techniques like autoradiography, fluorescence, or chemiluminescence. This movement tells you there’s a protein-nucleic acid interaction going on, offering clues about how specific and strong the binding is.

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