On the role of the crystal environment in determining protein side-chain conformations.

By Matthew P. Jacobson, Richard A. Friesner, Zhexin Xiang, Barry Honig. Journal of Molecular Biology, 2002

1,072 citations recorded by the source corpus.

The role of crystal packing in determining the observed conformations of amino acid side-chains in protein crystals is investigated by (1) analysis of a database of proteins that have been crystallized in different unit cells (space group or unit cell dimensions) and (2) theoretical predictions of side-chain conformations with the crystal environment explicitly represented. Both of these approaches indicate that the crystal environment plays an important role in determining the conformations of polar side-chains on the surfaces of proteins. Inclusion of the crystal environment permits a more sensitive measurement of the achievable accuracy of side-chain prediction programs, when validating against structures obtained by X-ray crystallography. Our side-chain prediction program uses an all-atom force field and a Generalized Born model of solvation and is thus capable of modeling simple packing effects (i.e. van der Waals interactions), electrostatic effects, and desolvation, which are all important mechanisms by which the crystal environment impacts observed side-chain conformations. Our results are also relevant to the understanding of changes in side-chain conformation that may result from ligand docking and protein-protein association, insofar as the results reveal how side-chain conformations change in response to their local environment.

Subfields: Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ba89d0832a2a5bd61d37cd8d73ffa19a03945c1b

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Citations in the corpus

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Computational protein structure refinement: Almost there, yet still so far to go (2017, background): “79 While it may be possible to consider the crystal environment during computational structure re ﬁ nement, focusing re ﬁ nement methods too much on exactly reproducing X-ray structures distracts from capturing what is biologically most relevant.”
The VSGB 2.0 model: A next generation energy model for high resolution protein structure modeling (2011, background): “Since the role of crystal environment and ligands in protein structure prediction has been extensively discussed,13,27 their inclusion in our all-atom models was done in an automated fashion.”
Toward better refinement of comparative models: Predicting loops in inexact environments (2008, methodology): “C RMSD for each sampled loop conformation using our HLP-SS applied to loop residues 34–41 in PDB 1ALC.”
D3R Grand Challenge 2: Blind Prediction of Protein-Ligand Poses, Affinity Rankings, and Relative Binding Free Energies (2017, methodology): “…are based on a binding site alignment script provided by the Maestro Prime Suite [27] ( align-binding-sites ) that performs a secondary structure alignment of the full protein followed by an alignment using the binding site Cα atoms belonging to residues within 5 Å of the ligand atoms [28, 29].”