Accurate Modeling of Protein Conformation by Automatic Segment Matching
Overview
Molecular Biology
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Segment match modeling uses a data base of highly refined known protein X-ray structures to build an unknown target structure from its amino acid sequence and the atomic coordinates of a few of its atoms (generally only the C alpha atoms). The target structure is first broken into a set of short segments. The data base is then searched for matching segments, which are fitted onto the framework of the target structure. Three criteria are used for choosing a matching data base segment: amino acid sequence similarity, conformational similarity (atomic co-ordinates), and compatibility with the target structure (van der Waals' interactions). The new method works surprisingly well: for eight test proteins ranging in size from 46 to 323 residues, the all-atom root-mean-square deviation of the modeled structures is between 0.93 A and 1.73 A (the average is 1.26 A). Deviations of this magnitude are comparable with those found for protein co-ordinates before and after refinement against X-ray data or for co-ordinates of the same protein in different crystal packings. These results are insensitive to errors in the C alpha positions or to missing C alpha atoms: accurate models can be built with C alpha errors of up to 1 A or by using only half the C alpha atoms. The fit to the X-ray structures is improved significantly by building several independent models based on different random choices and then averaging co-ordinates; this novel concept has general implications for other modeling tasks. The segment match modeling method is fully automatic, yields a complete set of atomic co-ordinates without any human intervention and is efficient (14 s/residue on the Silicon Graphics 4D/25 Personal Iris workstation.
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Smith D Methods Mol Biol. 2022; 2553:79-94.
PMID: 36227540 DOI: 10.1007/978-1-0716-2617-7_5.
Kinematic Reconstruction of Cyclic Peptides and Protein Backbones from Partial Data.
Hassan M, Coutsias E J Chem Inf Model. 2021; 61(10):4975-5000.
PMID: 34570494 PMC: 10129052. DOI: 10.1021/acs.jcim.1c00453.
Yu M, Zhang T, Zhang W, Sun Q, Li H, Li J Front Mol Biosci. 2021; 7:628551.
PMID: 33569392 PMC: 7868326. DOI: 10.3389/fmolb.2020.628551.
Ziegler S, Mallinson S, St John P, Bomble Y Comput Struct Biotechnol J. 2021; 19:214-225.
PMID: 33425253 PMC: 7772369. DOI: 10.1016/j.csbj.2020.11.052.