SIMBAD: a sequence-independent molecular-replacement pipeline.

Area of Science:

• Crystallography
• Structural Biology
• Computational Biology

Background:

• Molecular replacement (MR) traditionally relies on sequence similarity to identify search models for phasing unknown structures.
• Sequence-based methods can fail when structural homology is low or conformational diversity is high.
• Identifying suitable search models is crucial for solving macromolecular structures via crystallography.

Purpose of the Study:

• To present SIMBAD, a novel sequence-independent pipeline for molecular replacement (MR).
• To enable the identification of suitable MR search models using crystallographic data directly.
• To address challenges in MR, including contaminant crystallization and unsequenced targets.

Main Methods:

• SIMBAD implements a three-step pipeline for MR search model identification.
• Step 1: Lattice-parameter search against the Protein Data Bank (PDB) for crystal form homology.
• Step 2: Screening for crystallized contaminants using experimental data.
• Step 3: Brute-force search using MoRDa MR software for difficult cases.

Main Results:

• SIMBAD successfully identifies MR search models independent of sequence homology.
• The pipeline can detect and handle cases of contaminant crystallization and mistaken identity.
• SIMBAD has solved previously intractable crystallographic structures in early-access testing.

Conclusions:

• SIMBAD offers a robust alternative to sequence-dependent MR search model identification.
• The sequence-independent approach expands the applicability of MR to a wider range of targets.
• SIMBAD facilitates the solution of challenging macromolecular structures, including unsequenced and contaminated samples.