What is the relationship between the global structures of apo and holo proteins?

A long-standing problem in molecular biology is the determination of a complete functional conformational landscape of proteins. This includes not only proteins' native structures, but also all their respective functional states, including functionally important intermediates. Here, we reveal a signature of functionally important states in several protein families, using direct coupling analysis, which detects residue pair coevolution of protein sequence composition. This signature is exploited in a protein structure-based model to uncover conformational diversity, including hidden functional configurations. We uncovered, with high resolution (mean ∼1.9 Å rmsd for nonapo structures), different functional structural states for medium to large proteins (200-450 aa) belonging to several distinct families. The combination of direct coupling analysis and the structure-based model also predicts several intermediates or hidden states that are of functional importance. This enhanced sampling is broadly applicable and has direct implications in protein structure determination and the design of ligands or drugs to trap intermediate states.A s demonstrated by Anfinsen in 1973 (1) for small and intermediate-size proteins, amino acid sequences contain all of the necessary information to determine their native structure and function. In principle, a complete physical understanding of all molecular interactions should be sufficient to uncover not only the proteins' native structures, but also all their respective functional states, including functionally important intermediates. This landscape is required for a complete knowledge of functional mechanisms and therefore it has implications for drug discovery. Advances in computational approaches have been promising in sampling such conformational intermediates (2, 3). However, in general, computational methods are limited by uncertainties in protein models as well as insufficient computational resources to achieve proper sampling. Experimental techniques such as crystallography or NMR spectroscopy have been successful in identifying functional protein structures but only for a fraction of the complete set of known protein sequences (4, 5). Additionally, the determination of functionally important intermediate states using such methods has been challenging due to their transient nature. One idea to confront this challenge is to search for clues in genomic data (6-10). Functional states under conformational selection should leave a trace in the evolutionary history of proteins. Recent results inspired by this hypothesis have led to the development of the powerful "direct coupling analysis" (DCA), which was able to predict a large number of direct structural contacts between residues from sequences alone (11). Other useful methods have been developed to define coupling among residue pairs (12, 13). Others have also looked into correlated electrostatic mutations to study the evolution of protein topology toward minimized interaction frustration (14). Integrating the DCA-predicted co...

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“…We focus on proteins that experience large conformational changes upon ligand binding (Table S1) (28,29). Fig.…”

Section: Resultsmentioning

confidence: 99%

Coevolutionary signals across protein lineages help capture multiple protein conformations

Morcos

Jana

Hwa

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

175

195

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“…Indeed, incorporation of the receptor flexibility is a formidable challenge. Flap motion, side-chain movements, rotation of subdomains and movement of some secondary structure elements (i.e., helices) are well-documented [297,298]. However, prediction of these movements is extremely difficult in the context of high-throughput ligand docking.…”

Section: Discussionmentioning

confidence: 99%

In Silico-In Vitro Screening of Protein-Protein Interactions: Towards the Next Generation of Therapeutics

Villoutreix

Bastard²,

Spérandio³

et al. 2008

CPB

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SummaryProtein-protein interactions (PPIs) have a pivotal role in many biological processes suggesting that targeting macromolecular complexes will open new avenues for the design of the next generation of therapeutics. A wide range of "in silico methods" can be used to facilitate the design of protein-protein modulators. Among these methods, virtual ligand screening, protein-protein docking, structural predictions and druggable pocket predictions have become established techniques for hit discovery and optimization. In this review, we first summarize some key data about protein-protein interfaces and introduce some recently reported computer methods pertaining to the field. URLs for several recent free packages or servers are also provided. Then, we discuss four studies aiming at developing PPI modulators through the combination of in silico and in vitro screening experiments.3

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“…85. In our analysis, we used only those that were enzymes, which were identified based on annotation in the PDBSprotEC (86).…”

Section: Methodsmentioning

confidence: 99%

Prediction and experimental validation of enzyme substrate specificity in protein structures

Amin

Erdin

Ward³

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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Structural Genomics aims to elucidate protein structures to identify their functions. Unfortunately, the variation of just a few residues can be enough to alter activity or binding specificity and limit the functional resolution of annotations based on sequence and structure; in enzymes, substrates are especially difficult to predict. Here, large-scale controls and direct experiments show that the local similarity of five or six residues selected because they are evolutionarily important and on the protein surface can suffice to identify an enzyme activity and substrate. A motif of five residues predicted that a previously uncharacterized Silicibacter sp. protein was a carboxylesterase for short fatty acyl chains, similar to hormone-sensitive-lipase-like proteins that share less than 20% sequence identity. Assays and directed mutations confirmed this activity and showed that the motif was essential for catalysis and substrate specificity. We conclude that evolutionary and structural information may be combined on a Structural Genomics scale to create motifs of mixed catalytic and noncatalytic residues that identify enzyme activity and substrate specificity. A s the list of known genes grows exponentially, the elucidation of their function remains a major bottleneck and lags far behind the production of sequences (1-5). The best approach remains to search computationally for functionally characterized sequence homologs, ideally with greater than 50% sequence identity (6). Binding specificity, however, is sensitive to subtle amino acid differences, and the transfer of substrate between related enzymes is prone to errors when sequence identity is below 65-80% (7-9). These thresholds vary from case to case: Some orthologs will maintain identical functions down to 25% sequence identify (9), whereas paralogs can take on highly diverse activities (10). Other difficulties that plague annotation transfer between homologs are that individual small molecules may each bind to multiple and distinct molecular pockets (11), that different residues can support similar chemistries (12), and that activity can vary even when catalytic residues are conserved (13-18). To raise annotation accuracy, Structural Genomics (19) made structural information widely available and spurred the development of annotation methods dependent on local chemical and physical environments (20), sequence and structural comparisons (21), or 3D templates (22). In the case of the latter, these methods search between proteins for local structural similarities over a few signature residues that represent the telltale parts of a functional site, so-called "3D templates" (3,14,18,(22)(23)(24). The residue composition of 3D templates is critical, however, and derived from experiments (25) or from analyses of functional sites and determinants (14,15,26). The sensitivity and specificity of template-based annotations still needs to be established experimentally (27, 28), but retrospective controls suggest they often predict enzyme catalytic activity (14,16,17,29,30...

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What is the relationship between the global structures of apo and holo proteins?

Cited by 68 publications

References 75 publications

Coevolutionary signals across protein lineages help capture multiple protein conformations

Coevolutionary signals across protein lineages help capture multiple protein conformations

In Silico-In Vitro Screening of Protein-Protein Interactions: Towards the Next Generation of Therapeutics

Prediction and experimental validation of enzyme substrate specificity in protein structures

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