Abstract
Proteins must move between different conformations of their native ensemble to perform their functions. Crystal structures obtained from high-resolution X-ray diffraction data reflect this heterogeneity as a spatial and temporal conformational average. Although movement between natively populated alternative conformations can be critical for characterizing molecular mechanisms, it is challenging to identify these conformations within electron density maps. Alternative side chain conformations are generally well separated into distinct rotameric conformations, but alternative backbone conformations can overlap at several atomic positions. Our model building program qFit uses mixed integer quadratic programming (MIQP) to evaluate an extremely large number of combinations of sidechain conformers and backbone fragments to locally explain the electron density. Here, we describe two major modeling enhancements to qFit: peptide flips and alternative glycine conformations. We find that peptide flips fall into four stereotypical clusters and are enriched in glycine residues at the n+1 position. The potential for insights uncovered by new peptide flips and glycine conformations is exemplified by HIV protease, where different inhibitors are associated with peptide flips in the “flap” regions adjacent to the inhibitor binding site. Our results paint a picture of peptide flips as conformational switches, often enabled by glycine flexibility, that result in dramatic local rearrangements. Our results furthermore demonstrate the power of large-scale computational analysis to provide new insights into conformational heterogeneity. Overall, improved modeling of backbone heterogeneity with high-resolution X-ray data will connect dynamics to the structure-function relationship and help drive new design strategies for inhibitors of biomedically important systems.
Highlights
Even well-folded globular proteins exhibit significant flexibility in their native state [1]
Describing the multiple conformations of proteins is important for understanding the relationship between molecular flexibility and function
Most methods for interpreting data from X-ray crystallography focus on building a single structure of the protein, PLOS Computational Biology | DOI:10.1371/journal.pcbi
Summary
Even well-folded globular proteins exhibit significant flexibility in their native state [1]. Despite advances in nuclear magnetic resonance dynamics experiments and computational simulations, accurately characterizing the nature and extent of biomolecular flexibility remains a formidable challenge [2]. While traditionally X-ray crystallography is associated with characterizing the ground state of a biomolecule, the ensemble nature of diffraction experiments means that precise details of alternative conformations can be accessed when the electron density maps are of sufficient quality and resolution [3]. These maps represent spatiotemporal averaged electron density from conformational heterogeneity across the millions of unit cells within a crystal [4, 5]
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