Folding funnels and conformational transitions via hinge-bending motions

Identification of Specific Interactions that Drive Ligand-induced Closure in Five Enzymes with Classic Domain Movements

In order to better understand ligand-induced closure in domain enzymes, open unliganded X-ray structures and closed liganded X-ray structures have been studied in five enzymes: adenylate kinase, aspartate aminotransferase, citrate synthase, liver alcohol dehydrogenase, and the catalytic subunit of cAMP-dependent protein kinase. A sequential model of ligand binding and domain closure was used to test the hypothesis that the ligand actively drives closure from an open conformation. The analysis supports the assumption that each enzyme has a dedicated binding domain to which the ligand binds first and a closing domain. In every case, a small number of residues are identified to interact with the ligand to initiate and drive domain closure. In all cases except adenylate kinase, the backbone of residues located in an interdomain-bending region (hinge site) is identified to interact with the ligand to aid in driving closure. In adenylate kinase, the side-chain of a residue located directly adjacent to a bending region drives closure. It is thought that by binding near a hinge site the ligand is able to get within interaction range of residues when the enzyme is in the open conformation. Interdomain bending regions not involved in inducing closure are involved in control, helping to determine the location of the hinge axis. Similarities have been discovered between aspartate aminotransferase and citrate synthase that only come to light in the context of their dynamical behaviour in response to binding their substrate. Similarity also exists between liver alcohol dehydrogenase and cAMP-dependent protein kinase whereby groups on NAD and ATP, respectively, mimic the backbone of a single amino acid residue in a process where a three residue segment located at the terminus of a beta-sheet, moves to form hydrogen bonds with the mimic that resemble those found in a parallel beta-sheet. This interaction helps to drive domain closure in a process that has analogy to protein folding.

Substrate-induced conformational changes in human UMP/CMP kinase

Human UMP/CMP kinase plays a crucial role in supplying precursors for nucleic acid synthesis by catalyzing the conversion of UMP, CMP, and dCMP into their diphosphate form. In addition, this kinase is an essential component of the activation cascade of medicinally relevant nucleoside analog prodrugs such as AraC, gemcitabine, and ddC. During the catalytic cycle the enzyme undergoes large conformational changes from open in the absence of substrates to closed in the presence of both phosphoryl donor and phosphoryl acceptor. Here we report the crystal structure of the substrate-free, open form of human UMP/CMP kinase. Comparison of the open structure with the closed state previously reported for the similar Dictyostelium discoideum UMP/CMP kinase reveals the conformational changes that occur upon substrate binding. We observe a classic example of induced fit where substrate-induced conformational changes in hinge residues result in rigid body movements of functional domains to form the catalytically competent state. In addition, a homology model of the human enzyme in the closed state based on the structure of D. discoideum UMP/CMP kinase aids to rationalize the substrate specificity of the human enzyme.

Nonlinear elasticity, proteinquakes, and the energy landscapes of functional transitions in proteins

Large-scale motions of biomolecules involve linear elastic deformations along low-frequency normal modes, but for function nonlinearity is essential. In addition, unlike macroscopic machines, biological machines can locally break and then reassemble during function. We present a model for global structural transformations, such as allostery, that involve large-scale motion and possible partial unfolding, illustrating the method with the conformational transition of adenylate kinase. Structural deformation between open and closed states occurs via low-frequency modes on separate reactant and product surfaces, switching from one state to the other when energetically favorable. The switching model is the most straightforward anharmonic interpolation, which allows the barrier for a process to be estimated from a linear normal mode calculation, which by itself cannot be used for activated events. Local unfolding, or cracking, occurs in regions where the elastic stress becomes too high during the transition. Cracking leads to a counterintuitive catalytic effect of added denaturant on allosteric enzyme function. It also leads to unusual relationships between equilibrium constant and rate like those seen recently in single-molecule experiments of motor proteins.

Comparison of protein fragments identified by limited proteolysis and by computational cutting of proteins

Here we present a comparison between protein fragments produced by limited proteolysis and those identified by computational cutting based on the building block folding model. The principles upon which the two methods are based are different. Limited proteolysis of natively folded proteins occurs at flexible sites and never at the level of chain segments of regular secondary structure such as alpha-helices. Therefore, the targets for limited proteolysis are locally unfolded regions. In contrast, the computational cutting algorithm considers the compactness of the fragments, their nonpolar buried surface area, and their isolatedness, that is, the surface area which was buried prior to the cutting and becomes exposed subsequently. Despite the different criteria, there is an overall correspondence between sites or regions of limited proteolysis with those identified by computational cutting. The computational cutting method has been applied to several model proteins for which detailed limited proteolysis data are available, namely apomyoglobin, cytochrome c, ribonuclease A, alpha-lactalbumin, and thermolysin. As expected, more cuts are obtained computationally than experimentally and the agreement is better when a number of proteolytic enzymes are used. For example, cytochrome c is cleaved by thermolysin at 56-57, 45-46, and at 80-81, and by proteinase K at 48-49 and 50-51. Incubation of the noncovalent and native-like complex of cytochrome c fragments 1-56 and 57-104 with proteinase K yielded the gapped protein species 1-48/57-104 and finally 1-40/57-104. Computational cutting of cytochrome c reproduced the major experimental observations, with cuts at 47, 64-65 or 65-66 and 80-81 and an unstable 32-47 region not assigned to any building block. The next step, not addressed in this work, is to probe the ability of the generated fragments to fold independently. Since both the computational algorithm and limited proteolysis attempt to dissect the protein folding problem, the general agreement between the two procedures is gratifying. This consistency allows us to propose the use of limited proteolysis to produce protein fragments that can adopt an independent folding and, therefore, to study folding intermediates. The results of the present study appear to validate the building block folding model and are in line with the proposal that protein folding is a hierarchical process, where parts constituting local minima of energy fold first, with their subsequent association and mutual stabilization to finally yield the global fold.

In vitro selection of nucleoprotein enzymes

Natural nucleic acids frequently rely on proteins for stabilization or catalytic activity. In contrast, nucleic acids selected in vitro can catalyze a wide range of reactions even in the absence of proteins. To augment selected nucleic acids with protein functionalities, we have developed a technique for the selection of protein-dependent ribozyme ligases. After randomizing a previously selected ribozyme ligase, L1, we selected variants that required one of two protein cofactors, a tyrosyl transfer RNA (tRNA) synthetase (Cyt18) or hen egg white lysozyme. The resulting nucleoprotein enzymes were activated several thousand fold by their cognate protein effectors, and could specifically recognize the structures of the native proteins. Protein-dependent ribozymes can potentially be adapted to novel assays for detecting target proteins, and the selection method's generality may allow the high-throughput identification of ribozymes capable of recognizing a sizable fraction of a proteome.

Fluctuations in ion pairs and their stabilities in proteins

This report investigates the effect of systemic protein conformational flexibility on the contribution of ion pairs to protein stability. Toward this goal, we use all NMR conformer ensembles in the Protein Data Bank (1) that contain at least 40 conformers, (2) whose functional form is monomeric, (3) that are nonredundant, and (4) that are large enough. We find 11 proteins adhering to these criteria. Within these proteins, we identify 22 ion pairs that are close enough to be classified as salt bridges. These are identified in the high-resolution crystal structures of the respective proteins or in the minimized average structures (if the crystal structures are unavailable) or, if both are unavailable, in the "most representative" conformer of each of the ensembles. We next calculate the electrostatic contribution of each such ion pair in each of the conformers in the ensembles. This results in a comprehensive study of 1,201 ion pairs, which allows us to look for consistent trends in their electrostatic contributions to protein stability in large sets of conformers. We find that the contributions of ion pairs vary considerably among the conformers of each protein. The vast majority of the ion pairs interconvert between being stabilizing and destabilizing to the structure at least once in the ensembles. These fluctuations reflect the variabilities in the location of the ion pairing residues and in the geometric orientation of these residues, both with respect to each other, and with respect to other charged groups in the remainder of the protein. The higher crystallographic B-factors for the respective side-chains are consistent with these fluctuations. The major conclusion from this study is that salt bridges observed in crystal structure may break, and new salt bridges may be formed. Hence, the overall stabilizing (or, destabilizing) contribution of an ion pair is conformer population dependent.

Transition-state ensemble in enzyme catalysis: possibility, reality, or necessity?

Proteins are not rigid structures; they are dynamic entities, with numerous conformational isomers (substates). The dynamic nature of protein structures amplifies the structural variation of the transition state for chemical reactions performed by proteins. This suggests that utilizing a transition state ensemble to describe chemical reactions involving proteins may be a useful representation. Here we re-examine the nature of the transition state of protein chemical reactions (enzyme catalysis), considering both recent developments in chemical reaction theory (Marcus theory for SN2 reactions), and protein dynamics effects. The classical theory of chemical reactions relies on the assumption that a reaction must pass through an obligatory transition-state structure. The widely accepted view of enzymatic catalysis holds that there is tight binding of the substrate to the transition-state structure, lowering the activation energy. This picture, may, however, be oversimplified. The real meaning of a transition state is a surface, not a single saddle point on the potential energy surface. In a reaction with a "loose" transition-state structure, the entire transition-state region, rather than a single saddle point, contributes to reaction kinetics. Consequently, here we explore the validity of such a model, namely, the enzymatic modulation of the transition-state surface. We examine its utility in explaining enzyme catalysis. We analyse the possibility that instead of optimizing binding to a well-defined transition-state structure, enzymes are optimized by evolution to bind efficiently with a transition-state ensemble, with a broad range of activated conformations. For enzyme catalysis, the key issue is still transition state (ensemble) stabilization. The source of the catalytic power is the modulation of the transition state. However, our definition of the transition state is the entire transition-state surface rather just than a single well-defined structure. This view of the transition-state ensemble is consistent with the nature of the protein molecule, as embodied and depicted in the protein energy landscape of folding, and binding, funnels.

Folding and binding cascades: dynamic landscapes and population shifts

Whereas previously we have successfully utilized the folding funnels concept to rationalize binding mechanisms (Ma B, Kumar S, Tsai CJ, Nussinov R, 1999, Protein Eng 12:713-720) and to describe binding (Tsai CJ, Kumar S, Ma B, Nussinov R, 1999, Protein Sci 8:1181-1190), here we further extend the concept of folding funnels, illustrating its utility in explaining enzyme pathways, multimolecular associations, and allostery. This extension is based on the recognition that funnels are not stationary; rather, they are dynamic, depending on the physical or binding conditions (Tsai CJ, Ma B, Nussinov R, 1999, Proc Natl Acad Sci USA 96:9970-9972). Different binding states change the surrounding environment of proteins. The changed environment is in turn expressed in shifted energy landscapes, with different shapes and distributions of populations of conformers. Hence, the function of a protein and its properties are not only decided by the static folded three-dimensional structure; they are determined by the distribution of its conformational substates, and in particular, by the redistributions of the populations under different environments. That is, protein function derives from its dynamic energy landscape, caused by changes in its surroundings.