β-Branched Amino Acids Stabilize Specific Conformations of Cyclic Hexapeptides

Cyclic peptides (CPs) are a promising class of molecules for drug development, particularly as inhibitors of protein-protein interactions. Predicting low-energy structures and global structural ensembles of individual CPs is critical for the design of bioactive molecules, but these are challenging to predict and difficult to verify experimentally. In our previous work, we used explicit-solvent molecular dynamics simulations with enhanced sampling methods to predict the global structural ensembles of cyclic hexapeptides containing different permutations of glycine, alanine, and valine. One peptide, cyclo-(VVGGVG) or P7, was predicted to be unusually well structured. In this work, we synthesized P7, along with a less well-structured control peptide, cyclo-(VVGVGG) or P6, and characterized their global structural ensembles in water using NMR spectroscopy. The NMR data revealed a structural ensemble similar to the prediction for P7 and showed that P6 was indeed much less well-structured than P7. We then simulated and experimentally characterized the global structural ensembles of several P7 analogs and discovered that β-branching at one critical position within P7 is important for overall structural stability. The simulations allowed deconvolution of thermodynamic factors that underlie this structural stabilization. Overall, the excellent correlation between simulation and experimental data indicates that our simulation platform will be a promising approach for designing well-structured CPs and also for understanding the complex interactions that control the conformations of constrained peptides and other macrocycles.     

N-terminal region of human chemokine receptor CXCR3: Structural analysis of CXCR3(1–48) by experimental and computational studies

Our study on the highly charged N-terminal peptide of the human chemokine receptor CXCR3 by spectroscopic methods in solution and by means of molecular dynamics simulations showed that the charge content modulates the intrinsic structural preference of its flexible backbone. Collectively, our findings suggest that the structural organization of a protein should be seen as a part of a continuum in which the ratio between electrostatic and hydrophobic interactions and the intrinsic flexibility are important properties used to optimize the folding. When this ratio changes and the structure is intrinsically flexible, the structural organization of the system moves along the continuum of the possible conformational states. By all this combined information, one can describe the structure of CXCR3(1–48) as an ensemble of conformations. In fact, the peptide shows stretches of negative charges embedded in a flexible sequence which can be used to maximize promiscuous interactions relevant to molecular recognition but globally the peptide appears as a poly-structured globule-like ensemble that is dynamically stabilized by H-bonds. We have approached the study of the most populated ensembles with subset selection to explain our experimental data also by evidencing that the changes into the fraction of charged residues discriminate between dynamically poly-structured states, conceivably because of small free energy barriers existing between the different conformations of CXCR3(1–48). Therefore, the overlap of a highly flexible backbone, negatively charged residues and sites which can be modified by post-translational modifications represent the structural organization that controls the molecular mechanisms underlying the biological functions carried out by CXCR3(1–48).     

A Unified Conformational Selection and Induced Fit Approach to Protein-Peptide Docking

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.     

Towards the physical basis of how intrinsic disorder mediates protein function

Intrinsically disordered proteins (IDPs) are an important class of functional proteins that is highly prevalent in biology and has broad association with human diseases. In contrast to structured proteins, free IDPs exist as heterogeneous and dynamical conformational ensembles under physiological conditions. Many concepts have been discussed on how such intrinsic disorder may provide crucial functional advantages, particularly in cellular signaling and regulation. Establishing the physical basis of these proposed phenomena requires not only detailed characterization of the disordered conformational ensembles, but also mechanistic understanding of the roles of various ensemble properties in IDP interaction and regulation. Here, we review the experimental and computational approaches that may be integrated to address many important challenges of establishing a "structural" basis of IDP function, and discuss some of the key emerging ideas on how the conformational ensembles of IDPs may mediate function, especially in coupled binding and folding interactions.     

Investigating how peptide length and a pathogenic mutation modify the structural ensemble of amyloid beta monomer

The aggregation of amyloid beta (Aβ) peptides plays an important role in the development of Alzheimer's disease. Despite extensive effort, it has been difficult to characterize the secondary and tertiary structure of the Aβ monomer, the starting point for aggregation, due to its hydrophobicity and high aggregation propensity. Here, we employ extensive molecular dynamics simulations with atomistic protein and water models to determine structural ensembles for Aβ(42), Aβ(40), and Aβ(42)-E22K (the Italian mutant) monomers in solution. Sampling of a total of >700 microseconds in all-atom detail with explicit solvent enables us to observe the effects of peptide length and a pathogenic mutation on the disordered Aβ monomer structural ensemble. Aβ(42) and Aβ(40) have crudely similar characteristics but reducing the peptide length from 42 to 40 residues reduces β-hairpin formation near the C-terminus. The pathogenic Italian E22K mutation induces helix formation in the region of residues 20-24. This structural alteration may increase helix-helix interactions between monomers, resulting in altered mechanism and kinetics of Aβ oligomerization.     

Localization of protein-binding sites within families of proteins

We address the question of whether or not the positions of protein-binding sites on homologous protein structures are conserved irrespective of the identities of their binding partners. First, for each domain family in the Structural Classification of Proteins (SCOP), protein-binding sites are extracted from our comprehensive database of structurally defined binary domain interactions (PIBASE). Second, the binding sites within each family are superposed using a structural alignment of its members. Finally, the degree of localization of binding sites within each family is quantified by comparing it with localization expected by chance. We found that 72% of the 1847 SCOP domain families in PIBASE have binding sites with localization values greater than expected by chance. Moreover, 554 (30%) of these families have localizations that are statistically significant (i.e., more than four standard deviations away from the mean expected by chance). In contrast, only 144 (8%) families have significantly low localization. The absence of a significant correlation of the binding site localization with the average sequence and structural conservations in a family suggests that localization can be helpful for describing the functional diversity of protein-protein interactions, complementing measures of sequence and structural conservation. Consideration of the binding site localization may also result in spatial restraints for the modeling of protein assembly structures.     

Structural factors that determine selectivity of a high fidelity DNA polymerase for deoxy-, dideoxy-, and ribonucleotides

In addition to discriminating against base pair mismatches, DNA polymerases exhibit a high degree of selectivity for deoxyribonucleotides over ribo- or dideoxynucleotides. It has been proposed that a single active site residue (steric gate) blocks productive binding of nucleotides containing 2'-hydroxyls. Although this steric gate plays a role in sugar moiety discrimination, its interactions do not account fully for the observed behavior of mutants. Here we present 10 high resolution crystal structures and enzyme kinetic analyses of Bacillus DNA polymerase I large fragment variants complexed with deoxy-, ribo-, and dideoxynucleotides and a DNA substrate. Taken together, these data present a more nuanced and general mechanism for nucleotide discrimination in which ensembles of intermediate conformations in the active site trap non-cognate substrates. It is known that the active site O-helix transitions from an open state in the absence of nucleotide substrates to a ternary complex closed state in which the reactive groups are aligned for catalysis. Substrate misalignment in the closed state plays a fundamental part in preventing non-cognate nucleotide misincorpation. The structures presented here show that additional O-helix conformations intermediate between the open and closed state extremes create an ensemble of binding sites that trap and misalign non-cognate nucleotides. Water-mediated interactions, absent in the fully closed state, play an important role in formation of these binding sites and can be remodeled to accommodate different non-cognate substrates. This mechanism may extend also to base pair discrimination.     

Interpretation of HDX Data by Maximum-Entropy Reweighting of Simulated Structural Ensembles

Hydrogen-deuterium exchange combined with mass spectrometry (HDX-MS) is a widely applied biophysical technique that probes the structure and dynamics of biomolecules without the need for site-directed modifications or bio-orthogonal labels. The mechanistic interpretation of HDX data, however, is often qualitative and subjective, owing to a lack of quantitative methods to rigorously translate observed deuteration levels into atomistic structural information. To help address this problem, we have developed a methodology to generate structural ensembles that faithfully reproduce HDX-MS measurements. In this approach, an ensemble of protein conformations is first generated, typically using molecular dynamics simulations. A maximum-entropy bias is then applied post hoc to the resulting ensemble such that averaged peptide-deuteration levels, as predicted by an empirical model, agree with target values within a given level of uncertainty. We evaluate this approach, referred to as HDX ensemble reweighting (HDXer), for artificial target data reflecting the two major conformational states of a binding protein. We demonstrate that the information provided by HDX-MS experiments and by the model of exchange are sufficient to recover correctly weighted structural ensembles from simulations, even when the relevant conformations are rarely observed. Degrading the information content of the target data—e.g., by reducing sequence coverage, by averaging exchange levels over longer peptide segments, or by incorporating different sources of uncertainty—reduces the structural accuracy of the reweighted ensemble but still allows for useful insights into the distinctive structural features reflected by the target data. Finally, we describe a quantitative metric to rank candidate structural ensembles according to their correspondence with target data and illustrate the use of HDXer to describe changes in the conformational ensemble of the membrane protein LeuT. In summary, HDXer is designed to facilitate objective structural interpretations of HDX-MS data and to inform experimental approaches and further developments of theoretical exchange models.     

Structural plasticity and enzyme action: crystal structures of mycobacterium tuberculosis peptidyl-tRNA hydrolase

Peptidyl-tRNA hydrolase cleaves the ester bond between tRNA and the attached peptide in peptidyl-tRNA in order to avoid the toxicity resulting from its accumulation and to free the tRNA available for further rounds in protein synthesis. The structure of the enzyme from Mycobacterium tuberculosis has been determined in three crystal forms. This structure and the structure of the enzyme from Escherichia coli in its crystal differ substantially on account of the binding of the C terminus of the E. coli enzyme to the peptide-binding site of a neighboring molecule in the crystal. A detailed examination of this difference led to an elucidation of the plasticity of the binding site of the enzyme. The peptide-binding site of the enzyme is a cleft between the body of the molecule and a polypeptide stretch involving a loop and a helix. This stretch is in the open conformation when the enzyme is in the free state as in the crystals of M. tuberculosis peptidyl-tRNA hydrolase. Furthermore, there is no physical continuity between the tRNA and the peptide-binding sites. The molecule in the E. coli crystal mimics the peptide-bound enzyme molecule. The peptide stretch referred to earlier now closes on the bound peptide. Concurrently, a channel connecting the tRNA and the peptide-binding site opens primarily through the concerted movement of two residues. Thus, the crystal structure of M. tuberculosis peptidyl-tRNA hydrolase when compared with the crystal structure of the E. coli enzyme, leads to a model of structural changes associated with enzyme action on the basis of the plasticity of the molecule.     

Characterization of the Escherichia coli SecA signal peptide-binding site

SecA signal peptide interaction is critical for initiating protein translocation in the bacterial Sec-dependent pathway. Here, we have utilized the recent nuclear magnetic resonance (NMR) and Förster resonance energy transfer studies that mapped the location of the SecA signal peptide-binding site to design and isolate signal peptide-binding-defective secA mutants. Biochemical characterization of the mutant SecA proteins showed that Ser226, Val310, Ile789, Glu806, and Phe808 are important for signal peptide binding. A genetic system utilizing alkaline phosphatase secretion driven by different signal peptides was employed to demonstrate that both the PhoA and LamB signal peptides appear to recognize a common set of residues at the SecA signal peptide-binding site. A similar system containing either SecA-dependent or signal recognition particle (SRP)-dependent signal peptides along with the prlA suppressor mutation that is defective in signal peptide proofreading activity were employed to distinguish between SecA residues that are utilized more exclusively for signal peptide recognition or those that also participate in the proofreading and translocation functions of SecA. Collectively, our data allowed us to propose a model for the location of the SecA signal peptide-binding site that is more consistent with recent structural insights into this protein translocation system.     

NMR analysis of the binding of a rhodanese peptide to a minichaperone in solution.

A detailed structural analysis of interactions between denatured proteins and GroEL is essential for an understanding of its mechanism. Minichaperones constitute an excellent paradigm for obtaining high-resolution structural information about the binding site and conformation of substrates bound to GroEL, and are particularly suitable for NMR studies. Here, we used transferred nuclear Overhauser effects to study the interaction in solution between minichaperone GroEL(193-335) and a synthetic peptide (Rho), corresponding to the N-terminal alpha-helix (residues 11 to 23) of the mitochondrial rhodanese, a protein whose in vitro refolding is mediated by minichaperones. Using a 60 kDa maltose-binding protein (MBP)-GroEL(193-335) fusion protein to increase the sensitivity of the transferred NOEs, we observed characteristic sequential and mid-range transferred nuclear Overhauser effects. The peptide adopts an alpha-helical conformation upon binding to the minichaperone. Thus the binding site of GroEL is compatible with binding of alpha-helices as well as extended beta-strands. To locate the peptide-binding site on GroEL(193-335), we analysed changes in its chemical shifts on adding an excess of Rho peptide. All residues with significant chemical shift differences are localised in helices H8 and H9. Non-specific interactions were not observed. This indicates that the peptide Rho binds specifically to minichaperone GroEL(193-335). The binding region identified by NMR in solution agrees with crystallographic studies with small peptides and with fluorescence quenching studies with denatured proteins.     

Structure-based prediction of protein-peptide specificity in Rosetta

Protein-peptide interactions mediate many of the connections in intracellular signaling networks. A generalized computational framework for atomically precise modeling of protein-peptide specificity may allow for predicting molecular interactions, anticipating the effects of drugs and genetic mutations, and redesigning molecules for new interactions. We have developed an extensible, general algorithm for structure-based prediction of protein-peptide specificity as part of the Rosetta molecular modeling package. The algorithm is not restricted to any one peptide-binding domain family and, at minimum, does not require an experimentally characterized structure of the target protein nor any information about sequence specificity; although known structural data can be incorporated when available to improve performance. We demonstrate substantial success in specificity prediction across a diverse set of peptide-binding proteins, and show how performance is affected when incorporating varying degrees of input structural data. We also illustrate how structure-based approaches can provide atomic-level insight into mechanisms of peptide recognition and can predict the effects of point mutations on peptide specificity. Shortcomings and artifacts of our benchmark predictions are explained and limits on the generality of the method are explored. This work provides a promising foundation upon which further development of completely generalized, de novo prediction of peptide specificity may progress.     

Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening

The binding of short disordered peptide stretches to globular protein domains is important for a wide range of cellular processes, including signal transduction, protein transport, and immune response. The often promiscuous nature of these interactions and the conformational flexibility of the peptide chain, sometimes even when bound, make the binding specificity of this type of protein interaction a challenge to understand. Here we develop and test a Monte Carlo-based procedure for calculating protein-peptide binding thermodynamics for many sequences in a single run. The method explores both peptide sequence and conformational space simultaneously by simulating a joint probability distribution which, in particular, makes searching through peptide sequence space computationally efficient. To test our method, we apply it to 3 different peptide-binding protein domains and test its ability to capture the experimentally determined specificity profiles. Insight into the molecular underpinnings of the observed specificities is obtained by analyzing the peptide conformational ensembles of a large number of binding-competent sequences. We also explore the possibility of using our method to discover new peptide-binding pockets on protein structures.     

Proteins at Work: A COMBINED SMALL ANGLE X-RAY SCATTERING AND THEORETICAL DETERMINATION OF THE MULTIPLE STRUCTURES INVOLVED ON THE PROTEIN KINASE FUNCTIONAL LANDSCAPE*

C-terminal Src kinase (Csk) phosphorylates and down-regulates the Src family tyrosine kinases (SFKs). Crystallographic studies of Csk found an unusual arrangement of the SH2 and SH3 regulatory domains about the kinase core, forming a compact structure. However, recent structural studies of mutant Csk in the presence of an inhibitor indicate that the enzyme accesses an expanded structure. To investigate whether wt-Csk may also access open conformations we applied small angle x-ray scattering (SAXS). We find wt-Csk frequently occupies an extended conformation where the regulatory domains are removed from the kinase core. In addition, all-atom structure-based simulations indicate Csk occupies two free energy basins. These basins correspond to ensembles of distinct global conformations of Csk: a compact structure and an extended structure. The transitions between these structures are entropically driven and accessible via thermal fluctuations that break local interactions. We further characterized the ensemble by generating theoretical scattering curves for mixed populations of conformations from both basins and compared the predicted scattering curves to the experimental profile. This population-combination analysis is more consistent with the experimental data than any rigid model. It suggests that Csk adopts a broad ensemble of conformations in solution, populating extended conformations not observed in the crystal structure that may play an important role in the regulation of Csk. The methodology developed here is broadly applicable to biological macromolecules and will provide useful information about what ensembles of conformations are consistent with the experimental data as well as the ubiquitous dynamic reversible assembly processes inherent in biology.     

Structural dynamics of the DnaK-peptide complex

The molecular chaperone DnaK recognizes and binds substrate proteins via a stretch of seven amino acid residues that is usually only exposed in unfolded proteins. The binding kinetics are regulated by the nucleotide state of DnaK, which alternates between DnaK.ATP (fast exchange) and DnaK.ADP (slow exchange). These two forms cycle with a rate mainly determined by the ATPase activity of DnaK and nucleotide exchange. The different substrate binding properties of DnaK are mainly attributed to changes of the position and mobility of a helical region in the C-terminal peptide-binding domain, the so-called LID. It closes the peptide-binding pocket and thus makes peptide binding less dynamic in the ADP-bound state, but does not (strongly) interact with peptides directly. Here, we address the question if nucleotide-dependent structural changes may be observed in the peptide-binding region that could also be connected to peptide binding kinetics and more importantly could induce structural changes in peptide stretches using the energy available from ATP hydrolysis. Model peptides containing two cysteine residues at varying positions were derived from the structurally well-documented peptide NRLLLTG and labelled with electron spin sensitive probes. Measurements of distances and mobilities of these spin labels by electron paramagnetic resonance spectroscopy (EPR) of free peptides or peptides bound to the ATP and ADP-state of DnaK, respectively, showed no significant changes of mobility nor distance of the two labels. This indicates that no structural changes that could be sensed by the probes at the position of central leucine residues located in the center of the binding region occur due to different nucleotide states. We conclude from these studies that the ATPase activity of DnaK is not connected to structural changes of the peptide-binding pocket but rather only has an effect on the LID domain or other further remote residues.     

Evidence of Conformational Selection Driving the Formation of Ligand Binding Sites in Protein-Protein Interfaces

Many protein-protein interactions (PPIs) are compelling targets for drug discovery, and in a number of cases can be disrupted by small molecules. The main goal of this study is to examine the mechanism of binding site formation in the interface region of proteins that are PPI targets by comparing ligand-free and ligand-bound structures. To avoid any potential bias, we focus on ensembles of ligand-free protein conformations obtained by nuclear magnetic resonance (NMR) techniques and deposited in the Protein Data Bank, rather than on ensembles specifically generated for this study. The measures used for structure comparison are based on detecting binding hot spots, i.e., protein regions that are major contributors to the binding free energy. The main tool of the analysis is computational solvent mapping, which explores the surface of proteins by docking a large number of small “probe” molecules. Although we consider conformational ensembles obtained by NMR techniques, the analysis is independent of the method used for generating the structures. Finding the energetically most important regions, mapping can identify binding site residues using ligand-free models based on NMR data. In addition, the method selects conformations that are similar to some peptide-bound or ligand-bound structure in terms of the properties of the binding site. This agrees with the conformational selection model of molecular recognition, which assumes such pre-existing conformations. The analysis also shows the maximum level of similarity between unbound and bound states that is achieved without any influence from a ligand. Further shift toward the bound structure assumes protein-peptide or protein-ligand interactions, either selecting higher energy conformations that are not part of the NMR ensemble, or leading to induced fit. Thus, forming the sites in protein-protein interfaces that bind peptides and can be targeted by small ligands always includes conformational selection, although other recognition mechanisms may also be involved.     

In pursuit of virtual lead optimization: pruning ensembles of receptor structures for increased efficiency and accuracy during docking

Representing receptors as ensembles of protein conformations during docking is a powerful method to approximate protein flexibility and increase the accuracy of the resulting ranked list of compounds. Unfortunately, docking compounds against a large number of ensemble members can increase computational cost and time investment. In this article, we present an efficient method to evaluate and select the most contributive ensemble members prior to docking for targets with a conserved core of residues that bind a ligand moiety. We observed that ensemble members that preserve the geometry of the active site core are most likely to place ligands in the active site with a conserved orientation, generally rank ligands correctly and increase interactions with the receptor. A relative distance approach is used to quantify the preservation of the three-dimensional interatomic distances of the conserved ligand-binding atoms and prune large ensembles quickly. In this study, we investigate dihydrofolate reductase as an example of a protein with a conserved core; however, this method for accurately selecting relevant ensemble members a priori can be applied to any system with a conserved ligand-binding core, including HIV-1 protease, kinases, and acetylcholinesterase. Representing a drug target as a pruned ensemble during in silico screening should increase the accuracy and efficiency of high-throughput analyses of lead analogs.     

A molecular dynamics study of the 41-56 beta-hairpin from B1 domain of protein G.

The structural and dynamical behavior of the 41-56 beta-hairpin from the protein G B1 domain (GB1) has been studied at different temperatures using molecular dynamics (MD) simulations in an aqueous environment. The purpose of these simulations is to establish the stability of this hairpin in view of its possible role as a nucleation site for protein folding. The conformation of the peptide in the crystallographic structure of the protein GB1 (native conformation) was lost in all simulations. The new equilibrium conformations are stable for several nanoseconds at 300K (>10 ns), 350 K (>6.5 ns), and even at 450 K (up to 2.5 ns). The new structures have very similar hairpin-like conformations with properties in agreement with available experimental nuclear Overhauser effect (NOE) data. The stability of the structure in the hydrophobic core region during the simulations is consistent with the experimental data and provides further evidence for the role played by hydrophobic interactions in hairpin structures. Essential dynamics analysis shows that the dynamics of the peptide at different temperatures spans basically the same essential subspace. The main equilibrium motions in this subspace involve large fluctuations of the residues in the turn and ends regions. Of the six interchain hydrogen bonds, the inner four remain stable during the simulations. The space spanned by the first two eigenvectors, as sampled at 450 K, includes almost all of the 47 different hairpin structures found in the database. Finally, analysis of the hydration of the 300 K average conformations shows that the hydration sites observed in the native conformation are still well hydrated in the equilibrium MD ensemble.