Hi Xin, Predict and build uses process predicted model to estimate suitable VRMS values from the pLDDT values in a processed chain to be used in MR. Process predicted model first converts average pLDDT to estimated RMS error using an empirical formula from RoseTTAFold: rmsd_est = 1.5 * exp(4*(0.7-pLDDT)) where pLDDT is fractional (0 to 1) Then it uses a second empirical formula to suggest a value of VRMS based on the RMS error: vrms = vrms_from_rmsd_slope * rms + vrms_from_rmsd_intercept where the slope is 1 and intercept is 0.25 A. All the best, Tom T On Sun, Aug 10, 2025 at 9:49 PM [email protected] wrote:

Dear All, I hope this email finds you well. While reviewing the MR-related output files generated by Phenix PredictAndBuild (see attached screenshot), I noticed that an RMS value is set in the Phaser input section. I found that in certain cases this parameter can have a significant impact on MR results. Could you kindly advise how this RMS value is determined or calculated within Phenix PredictAndBuild? [??????] Thank you very much for your time and guidance.

Best regards,

Xin Zhang

School of Biomedical Sciences,

The University of Hong Kong

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-- Thomas C Terwilliger Laboratory Fellow, Los Alamos National Laboratory Senior Scientist, New Mexico Consortium 100 Entrada Dr, Los Alamos, NM 87544 Email: [email protected] Tel: 505-431-0010