I suppose you have tried to trim and partition the alphafold model according to low confidence regions using the phenix.process_predicted_model tool. It also adjust atomic B-factors of the partitioned alphafold model which should yield better results in the subsequent MR search.
Rob
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From: [email protected]
Sent: Monday, June 01, 2026 09:51
To: [email protected]
Subject: [phenixbb] Seeking Advice on Difficult MR Case: TFZ 6–8 for All Search Models, R-free ~0.50
I am working on a protein containing two domains: an N-terminal FHA domain and a C-terminal RING domain. I have collected a native dataset that extends to 2.45 Å resolution in space group P2₁2₁2 with unit-cell parameters approximately a = 46.9 Å, b = 91.9 Å, c = 165.0 Å.
I have been struggling to obtain a convincing molecular replacement solution despite trying multiple approaches.
What I have tried so far:
Full-length AlphaFold model as a search model.
Splitting the AlphaFold model into individual FHA and RING domains.
Sequential/domain-wise MR searches.
Aggressive model trimming.
Poly-alanine versions of the models.
Various combinations of domain placement strategies.
However, the results remain largely the same:
TFZ values are consistently in the range of 6–8.
LLG values are not particularly convincing.
Refinement of the best solutions leads to R-free values around 0.50 or higher.
Electron-density maps are not readily interpretable.
No solution has shown clear evidence of being correct after refinement and map inspection.
At this stage I am trying to determine whether the issue is:
Failure of MR due to domain rearrangement between the FHA and RING domains.
Incorrect number of molecules in the asymmetric unit.
Partial placement of domains that is being missed.
Crystal pathologies such as pseudo-symmetry or translational NCS.
Some other issue that I may be overlooking.
I would appreciate suggestions on:
Additional diagnostics to assess whether any of these TFZ 6–8 solutions might actually be correct.
Strategies for multi-domain MR in cases where AlphaFold-based models are unsuccessful.
Whether further model editing is likely to help.
Other MR pipelines that may be worth trying before moving to experimental phasing.
Any advice would be greatly appreciated.
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