Old fold in a new X-ray diffraction dataset? Low-resolution molecular replacement using representative structural...

Area of Science:

• Structural Biology
• X-ray Crystallography
• Protein Structure Determination

Background:

• Structural genomics initiatives have greatly increased protein structure data in the Protein Data Bank.
• The majority of determined protein structures (>85%) exhibit known folds, with novel folds being rare.
• Enzymes often utilize common structural scaffolds, contributing to the prevalence of known folds.

Purpose of the Study:

• To evaluate a method for analyzing proteins with known folds in new structural genomics datasets.
• To demonstrate an effective strategy for solving the phase problem in X-ray crystallography for proteins with existing fold information.

Main Methods:

• A fold detection strategy utilizing secondary structure signatures.
• Molecular replacement (MR) with a minimalist model derived from fold information.
• Application to three common protein folds: triosephosphate isomerase (TIM), adenine nucleotide alpha hydrolase-like (HUP), and RNA recognition motif (RRM).

Main Results:

• The proposed method successfully solves the X-ray crystallography phase problem without heavy atom derivatives or multiple anomalous dispersion (MAD).
• The strategy is effective for the "old fold in a new dataset" scenario common in structural genomics.
• Phase information obtainable from a single domain within a multidomain structure was estimated.

Conclusions:

• Fold detection combined with minimalist molecular replacement is a viable approach for structure determination in structural genomics.
• This method reduces the reliance on traditional, more complex phasing techniques.
• The study provides insights into leveraging existing structural knowledge for new protein structure determination.