Protein structural alignment for detection of maximally conserved regions

Crystal structures of full length DENV4 NS2B-NS3 reveal the dynamic interaction between NS2B and NS3

Flavivirus is a genus of the Flaviviridae family which includes significant emerging and re-emerging human disease-causing arboviruses such as dengue and Zika viruses. Flaviviral non-structural protein 3 (NS3) protease-helicase plays essential roles in viral replication and is an attractive antiviral target. A construct which connects the cytoplasmic cofactor region of NS2B and NS3 protease with an artificial glycine-rich flexible linker has been widely used for structural, biochemical and drug-screening studies. The effect of this linker on the dynamics and enzymatic activity of the protease has been studied by several biochemical and NMR methods but the findings remained inconclusive. Here, we designed and carried out a comparative study of constructs of NS2B cofactor joined to the full length DENV4 NS3 in three different ways, namely bNS2B₄₇NS3 (bivalent), eNS2B₄₇NS3(enzymatically cleavable) and gNS2B₄₇NS3 (glycine-rich linker). We report the crystal structures of linked and unlinked NS2B₄₇-NS3 constructs in their free state and in complex with bovine pancreatic trypsin inhibitor (BPTI). These structures demonstrate that the NS2B cofactor predominantly adopts a closed conformation in complex with full-length NS3. The glycine-rich linker between NS2B and NS3 may promote the open conformation which interferes with protease activity. This negative impact on the enzyme structure and function is restricted to the protease activity as the ATPase activity is not affected in vitro.

BAYESIAN PROTEIN STRUCTURE ALIGNMENT

The analysis of the three-dimensional structure of proteins is an important topic in molecular biochemistry. Structure plays a critical role in defining the function of proteins and is more strongly conserved than amino acid sequence over evolutionary timescales. A key challenge is the identification and evaluation of structural similarity between proteins; such analysis can aid in understanding the role of newly discovered proteins and help elucidate evolutionary relationships between organisms. Computational biologists have developed many clever algorithmic techniques for comparing protein structures, however, all are based on heuristic optimization criteria, making statistical interpretation somewhat difficult. Here we present a fully probabilistic framework for pairwise structural alignment of proteins. Our approach has several advantages, including the ability to capture alignment uncertainty and to estimate key "gap" parameters which critically affect the quality of the alignment. We show that several existing alignment methods arise as maximum a posteriori estimates under specific choices of prior distributions and error models. Our probabilistic framework is also easily extended to incorporate additional information, which we demonstrate by including primary sequence information to generate simultaneous sequence-structure alignments that can resolve ambiguities obtained using structure alone. This combined model also provides a natural approach for the difficult task of estimating evolutionary distance based on structural alignments. The model is illustrated by comparison with well-established methods on several challenging protein alignment examples.

Gaussian-weighted RMSD superposition of proteins: a structural comparison for flexible proteins and predicted protein structures

Many proteins contain flexible structures such as loops and hinged domains. A simple root mean square deviation (RMSD) alignment of two different conformations of the same protein can be skewed by the difference between the mobile regions. To overcome this problem, we have developed a novel method to overlay two protein conformations by their atomic coordinates using a Gaussian-weighted RMSD (wRMSD) fit. The algorithm is based on the Kabsch least-squares method and determines an optimal transformation between two molecules by calculating the minimal weighted deviation between the two coordinate sets. Unlike other techniques that choose subsets of residues to overlay, all atoms are included in the wRMSD overlay. Atoms that barely move between the two conformations will have a greater weighting than those that have a large displacement. Our superposition tool has produced successful alignments when applied to proteins for which two conformations are known. The transformation calculation is heavily weighted by the coordinates of the static region of the two conformations, highlighting the range of flexibility in the overlaid structures. Lastly, we show how wRMSD fits can be used to evaluate predicted protein structures. Comparing a predicted fold to its experimentally determined target structure is another case of comparing two protein conformations of the same sequence, and the degree of alignment directly reflects the quality of the prediction.

The cAMP binding domain: an ancient signaling module

cAMP-binding domains from several different proteins were analyzed to determine the properties and interactions of this recognition motif. Systematic computational analyses, including structure-based sequence comparison, surface matching, affinity grid analysis, and analyses of the ligand protein interactions were carried out. These analyses show distinctive roles of the sugar phosphate and the adenine in the cAMP-binding module. We propose that the cAMP-binding regulatory proteins function by providing an allosteric system in which the presence or absence of cAMP produces a substantial structural change through the loss of hydrophobic interactions with the adenine ring and consequent repositioning of the C helix. The modified positioning of the helix in turn is recognized by a protein-binding event, completing the allostery.