"DFG-flip" in the insulin receptor kinase is facilitated by a helical intermediate state of the activation loop

Spontaneous Dimerization and Distinct Packing Modes of Transmembrane Domains in Receptor Tyrosine Kinases

The insulin receptor (IR) and the insulin-like growth factor-1 receptor (IGF1R) are homodimeric transmembrane glycoproteins that transduce signals across the membrane on binding of extracellular peptide ligands. The structures of IR/IGF1R fragments in apo and liganded states have revealed that the extracellular subunits of these receptors adopt Λ-shaped configurations to which are connected the intracellular tyrosine kinase (TK) domains. The binding of peptide ligands induces structural transitions in the extracellular subunits leading to potential dimerization of transmembrane domains (TMDs) and autophosphorylation in TKs. However, the activation mechanisms of IR/IGF1R, especially the role of TMDs in coordinating signal-inducing structural transitions, remain poorly understood, in part due to the lack of structures of full-length receptors in apo or liganded states. While atomistic simulations of IR/IGF1R TMDs showed that these domains can dimerize in single component membranes, spontaneous unbiased dimerization in a plasma membrane having physiologically representative lipid composition has not been observed. We address this limitation by employing coarse-grained (CG) molecular dynamics simulations to probe the dimerization propensity of IR/IGF1R TMDs. We observed that TMDs in both receptors spontaneously dimerized independent of their initial orientations in their dissociated states, signifying their natural propensity for dimerization. In the dimeric state, IR TMDs predominantly adopted X-shaped configurations with asymmetric helical packing and significant tilt relative to the membrane normal, while IGF1R TMDs adopted symmetric V-shaped or parallel configurations with either no tilt or a small tilt relative to the membrane normal. Our results suggest that IR/IGF1R TMDs spontaneously dimerize and adopt distinct dimerized configurations.

Allosteric Boost by TAB1 on the TAK1 Kinase Favorably Sculpts the Thermodynamic Landscape of Activation

The intricate mechanisms of allosteric regulation in kinases are of general interest to the scientific community for potential therapeutic implications. However, the diversity among kinases and their regulatory routes requires a case-by-case study to widen the repertoire of known mechanisms. The present study achieves this by understanding TAK1 kinase activation by TAB1 as a model phenomenon for the first time. Despite the known capacity of TAK1 to switch between its inactive ("DFG-out") and active-like ("DFG-in") conformations, the questionable role of TAB1 in offering an energetic favor to this has been addressed here using sequential combination of enhanced sampling methods like targeted molecular dynamics (TMD) and Gaussian accelerated molecular dynamics (GaMD). It reveals how a minimal domain of TAB1 sufficiently acts like a "catalytic gear" by favorably sculpting TAK1's thermodynamic landscape (potential of mean force in 2D) that accelerates "in"-"out" conformational switching of the conserved DFG motif. Standard molecular dynamics simulations (∼5 μs) reveal that TAB1 fascinatingly exploits the "lever-like" αF helix of TAK1 kinase domain to remotely propel the DFG motif via subtle helical "unfolding-folding" modifications within the kinase activation loop. The presence of two charged residues on terminal poles of αF helix imparts it, with this unique "lever-like" utility, and this turns out to be one important signature of co-evolution between TAK1 and TAB1. The entire mechanism of TAB1's impact transduction, which is found to be analogous to the moves in the popular "Chinese checker" game, gives a clear proof of the "dynamics-driven allostery" concept in kinases. The findings further benchmark TAK1's known autophosphorylation capacity. A novel insight into kinase allostery is thus provided, which potentiates investigation of similar capacities in other kinases.

The Conformational Transition Pathways and Hidden Intermediates in DFG-Flip Process of c-Met Kinase Revealed by Metadynamics Simulations

Protein kinases intrinsically translate their conformations between active and inactive states, which is key to their enzymatic activities. The conformational flipping of the three-residue conservative motif, Asp-Phe-Gly (DFG), is crucial for many kinases' biological functions. Obtaining a detailed demonstration of the DFG flipping process and its corresponding dynamical and thermodynamical features could broaden our understanding of kinases' conformation-activity relationship. In this study, we employed metadynamics simulation, a widely used enhanced sampling technique, to analyze the conformational transition pathways of the DFG flipping for the c-Met kinase. The corresponding free energy landscape suggested two distinct transition pathways between the "DFG-in" and "DFG-out" states of the DFG-flip from c-Met. On the basis of the orientation direction of the F1223 residue, we correspondingly named the two pathways the "DFG-up" path, featuring forming a commonly discovered "DFG-up" transition state, and the "DFG-down" path, a unique transition pathway with F1223 rotating along the opposite direction away from the hydrophobic cavity. The free energies along the two pathways were then calculated using the Path Collective Variable (PCV) metadynamics simulation. The simulation results showed that, though having similar free energy barriers, the free energy cuve for the DFG-down path suggested a two-step conformational transition mechanism, while that for the DFG-up path showed the one-step transition feature. The c-Met DFG flipping mechanism and the new intermediate state discovered in this work could provide a deeper understanding of the conformation-activity relationship for c-Met and, possibly, reveal a new conformational state as the drug target for c-Met and other similar kinases.

A Companion Guide to the String Method with Swarms of Trajectories: Characterization, Performance, and Pitfalls

The string method with swarms of trajectories (SMwST) is an algorithm that identifies a physically meaningful transition pathway─a one-dimensional curve, embedded within a high-dimensional space of selected collective variables. The SMwST algorithm leans on a series of short, unbiased molecular dynamics simulations spawned at different locations of the discretized path, from whence an average dynamic drift is determined to evolve the string toward an optimal pathway. However conceptually simple in both its theoretical formulation and practical implementation, the SMwST algorithm is computationally intensive and requires a careful choice of parameters for optimal cost-effectiveness in applications to challenging problems in chemistry and biology. In this contribution, the SMwST algorithm is presented in a self-contained manner, discussing with a critical eye its theoretical underpinnings, applicability, inherent limitations, and use in the context of path-following free-energy calculations and their possible extension to kinetics modeling. Through multiple simulations of a prototypical polypeptide, combining the search of the transition pathway and the computation of the potential of mean force along it, several practical aspects of the methodology are examined with the objective of optimizing the computational effort, yet without sacrificing accuracy. In light of the results reported here, we propose some general guidelines aimed at improving the efficiency and reliability of the computed pathways and free-energy profiles underlying the conformational transitions at hand.

Progress in Simulation Studies of Insulin Structure and Function

Insulin is a peptide hormone known for chiefly regulating glucose level in blood among several other metabolic processes. Insulin remains the most effective drug for treating diabetes mellitus. Insulin is synthesized in the pancreatic β-cells where it exists in a compact hexameric architecture although its biologically active form is monomeric. Insulin exhibits a sequence of conformational variations during the transition from the hexamer state to its biologically-active monomer state. The structural transitions and the mechanism of action of insulin have been investigated using several experimental and computational methods. This review primarily highlights the contributions of molecular dynamics (MD) simulations in elucidating the atomic-level details of conformational dynamics in insulin, where the structure of the hormone has been probed as a monomer, dimer, and hexamer. The effect of solvent, pH, temperature, and pressure have been probed at the microscopic scale. Given the focus of this review on the structure of the hormone, simulation studies involving interactions between the hormone and its receptor are only briefly highlighted, and studies on other related peptides (e.g., insulin-like growth factors) are not discussed. However, the review highlights conformational dynamics underlying the activities of reported insulin analogs and mimetics. The future prospects for computational methods in developing promising synthetic insulin analogs are also briefly highlighted.

TYROSINE KINASES: COMPLEX MOLECULAR SYSTEMS CHALLENGING COMPUTATIONAL METHODOLOGIES

Classical molecular dynamics (MD) simulations based on atomic models play an increasingly important role in a wide range of applications in physics, biology, and chemistry. Nonetheless, generating genuine knowledge about biological systems using MD simulations remains challenging. Protein tyrosine kinases are important cellular signaling enzymes that regulate cell growth, proliferation, metabolism, differentiation, and migration. Due to the large conformational changes and long timescales involved in their function, these kinases present particularly challenging problems to modern computational and theoretical frameworks aimed at elucidating the dynamics of complex biomolecular systems. Markov state models have achieved limited success in tackling the broader conformational ensemble and biased methods are often employed to examine specific long timescale events. Recent advances in machine learning continue to push the limitations of current methodologies and provide notable improvements when integrated with the existing frameworks. A broad perspective is drawn from a critical review of recent studies.

String Method with Swarms-of-Trajectories, Mean Drifts, Lag Time, and Committor

The kinetics of a dynamical system comprising two metastable states is formulated in terms of a finite-time propagator in phase space (position and velocity) adapted to the underdamped Langevin equation. Dimensionality reduction to a subspace of collective variables yields familiar expressions for the propagator, committor, and steady-state flux. A quadratic expression for the steady-state flux between the two metastable states can serve as a robust variational principle to determine an optimal approximate committor expressed in terms of a set of collective variables. The theoretical formulation is exploited to clarify the foundation of the string method with swarms-of-trajectories, which relies on the mean drift of short trajectories to determine the optimal transition pathway. It is argued that the conditions for Markovity within a subspace of collective variables may not be satisfied with an arbitrary short time-step and that proper kinetic behaviors appear only when considering the effective propagator for longer lag times. The effective propagator with finite lag time is amenable to an eigenvalue-eigenvector spectral analysis, as elaborated previously in the context of position-based Markov models. The time-correlation functions calculated by swarms-of-trajectories along the string pathway constitutes a natural extension of these developments. The present formulation provides a powerful theoretical framework to characterize the optimal pathway between two metastable states of a system.

Computational studies of anaplastic lymphoma kinase mutations reveal common mechanisms of oncogenic activation

High-risk tumors are genomically heterogeneous, harboring gene amplifications and mutations. The activation status of mutated proteins in cancer can profoundly impact disease progression, patient response, and drug sensitivity. Yet, outside of a few hotspot mutations, functional studies of clinically observed mutations are not commonly pursued. We report a combined experimental profiling and computational analysis of the effects of clinically observed and “test” mutations in the kinase domain of anaplastic lymphoma kinase (ALK), a known oncogenic driver in pediatric neuroblastoma. We find that the activation status of the mutated protein is a good indicator of the transforming ability in NIH 3T3 cells. We also report biophysical as well as data-driven models with predictive power to profile these mutant kinases in silico.

Kinases play important roles in diverse cellular processes, including signaling, differentiation, proliferation, and metabolism. They are frequently mutated in cancer and are the targets of a large number of specific inhibitors. Surveys of cancer genome atlases reveal that kinase domains, which consist of 300 amino acids, can harbor numerous (150 to 200) single-point mutations across different patients in the same disease. This preponderance of mutations—some activating, some silent—in a known target protein make clinical decisions for enrolling patients in drug trials challenging since the relevance of the target and its drug sensitivity often depend on the mutational status in a given patient. We show through computational studies using molecular dynamics (MD) as well as enhanced sampling simulations that the experimentally determined activation status of a mutated kinase can be predicted effectively by identifying a hydrogen bonding fingerprint in the activation loop and the αC-helix regions, despite the fact that mutations in cancer patients occur throughout the kinase domain. In our study, we find that the predictive power of MD is superior to a purely data-driven machine learning model involving biochemical features that we implemented, even though MD utilized far fewer features (in fact, just one) in an unsupervised setting. Moreover, the MD results provide key insights into convergent mechanisms of activation, primarily involving differential stabilization of a hydrogen bond network that engages residues of the activation loop and αC-helix in the active-like conformation (in >70% of the mutations studied, regardless of the location of the mutation).

Analysis of Charged Peptide Loop-Flipping across a Lipid Bilayer Using the String Method with Swarms of Trajectories

The hydrophobic core of the lipid bilayer is conventionally considered a barrier to the translocation of charged species such that the translocation of even single ions occurs on long time scales. In contrast, experiments have revealed that some materials, including peptides, proteins, and nanoparticles, can translocate multiple charged moieties across the bilayer on experimentally relevant time scales. Understanding the molecular mechanisms underlying this behavior is challenging because resolving corresponding free-energy landscapes with molecular simulation techniques is computationally expensive. To address this challenge, we use atomistic molecular dynamics simulations with the swarms-of-trajectories (SOT) string method to analyze charge translocation pathways across single-component lipid bilayers as a function of multiple collective variables. We first demonstrate that the SOT string method can reproduce the free-energy barrier for the translocation of a charged lysine amino acid analogue in good agreement with the literature. We then obtain minimum free-energy pathways for the translocation, or flipping, of charged peptide loops across the lipid bilayer by utilizing trajectories from prior temperature-accelerated molecular dynamics (TAMD) simulations as initial configurations. The corresponding potential of mean force calculations reveal that the protonation of a central membrane-exposed aspartate residue substantially reduces the free-energy barrier for flipping charged loops by modulating the water content of the bilayer. These results provide new insight into the thermodynamics underlying loop-flipping processes and highlight how the combination of TAMD and the SOT string method can be used to understand complex charge translocation mechanisms.

Simulating ion channel activation mechanisms using swarms of trajectories

Atomic-level studies of protein activity represent a significant challenge as a result of the complexity of conformational changes occurring on wide-ranging timescales, often greatly exceeding that of even the longest simulations. A prime example is the elucidation of protein allosteric mechanisms, where localized perturbations transmit throughout a large macromolecule to generate a response signal. For example, the conversion of chemical to electrical signals during synaptic neurotransmission in the brain is achieved by specialized membrane proteins called pentameric ligand-gated ion channels. Here, the binding of a neurotransmitter results in a global conformational change to open an ion-conducting pore across the nerve cell membrane. X-ray crystallography has produced static structures of the open and closed states of the proton-gated GLIC pentameric ligand-gated ion channel protein, allowing for atomistic simulations that can uncover changes related to activation. We discuss a range of enhanced sampling approaches that could be used to explore activation mechanisms. In particular, we describe recent application of an atomistic string method, based on Roux's "swarms of trajectories" approach, to elucidate the sequence and interdependence of conformational changes during activation. We illustrate how this can be combined with transition analysis and Brownian dynamics to extract thermodynamic and kinetic information, leading to understanding of what controls ion channel function. © 2019 Wiley Periodicals, Inc.

Structural Characterization of the Aurora Kinase B "DFG-flip" Using Metadynamics

Aurora kinase B (AKB), a Ser/Thr kinase that plays a crucial role in mitosis, is overexpressed in several cancers. Clinical inhibitors targeting AKB bind to the active DFG "in" conformation of the kinase. It would be beneficial, however, to understand if AKB is susceptible to type II kinase inhibitors that bind to the inactive, DFG "out" conformation, since type II inhibitors achieve higher kinome selectivity and higher potency in vivo. The DFG "out" conformation of AKB is not yet experimentally determined which makes the design of type II inhibitors exceedingly difficult. An alternate approach is to simulate the DFG "out" conformation from the experimentally determined DFG "in" conformation using atomistic molecular dynamics (MD) simulation. In this work, we employed metadynamics (MTD) approach to simulate the DFG "out" conformation of AKB by choosing the appropriate collective variables. We examined structural changes during the DFG-flip and determined the interactions crucial to stabilize the kinase in active and inactive states. Interestingly, the MTD approach also identified a unique transition state (DFG "up"), which can be targeted by small molecule inhibitors. Structural insights about these conformations is essential for structure-guided design of next-generation AKB inhibitors. This work also emphasizes the usefulness of MTD simulations in predicting macromolecular conformational changes at reduced computational costs.

Energetics of Flap Opening in HIV-1 Protease: String Method Calculations

HIV-1 protease (PR) is the viral protein responsible for virion maturation, and its mechanisms of action remain incompletely understood. PR is dimeric and contains two flexible, symmetry-related flaps, which act as a gate to inhibit access to the binding pocket and hold the polypeptide substrate in the binding pocket once bound. Wide flap opening, a conformational change assumed to be necessary for substrate binding, is a rare event in the closed and bound form. In this study, we use molecular dynamics (MD) simulations and advanced MD techniques including temperature acceleration and string method in collective variables to study the conformational changes associated with substrate unbinding of both wild-type and F99Y mutant PR. The F99Y mutation is shown via MD to decouple the closing of previously unrecognized distal pockets from substrate unbinding. To determine whether or not the F99Y mutation affects the energetic cost of wide flap opening, we use string method in collective variables to determine the minimum free-energy mechanism for wide flap opening in concert with distal pocket closing. The results indicate that the major energetic cost in flap opening is disengagement of the two flap-tip Ile50 residues from each other and is not affected by the F99Y mutation.

Investigating Phosphorylation-Induced Conformational Changes in WNK1 Kinase by Molecular Dynamics Simulations

The With-No-Lysine (WNK) kinase is considered to be a master regulator for various cation-chloride cotransporters involved in maintaining cell-volume and ion homeostasis. Here, we have investigated the phosphorylation-induced structural dynamics of the WNK1 kinase bound to an inhibitor via atomistic molecular dynamics simulations. Results from our simulations show that the phosphorylation at Ser³⁸² could stabilize the otherwise flexible activation loop (A-loop). The intrahelix salt-bridge formed between Arg²⁶⁴ and Glu²⁶⁸ in the unphosphorylated system is disengaged after the phosphorylation, and Glu²⁶⁸ reorients itself and forms a stable salt-bridge with Arg³⁴⁸. The dynamic cross-correlation analysis shows that phosphorylation diminishes anticorrelated motions and increases correlated motions between different domains. Structural network analysis reveals that the phosphorylation causes structural rearrangements and shortens the communication path between the αC-helix and catalytic loop, making the binding pocket more suitable for accommodating the ligand. Overall, we have characterized the structural changes in the WNK kinase because of phosphorylation in the A-loop, which might help in designing rational drugs.

Diffusion network of CO in FeFe-Hydrogenase

FeFe-hydrogenase is an efficient enzyme to produce H₂ under optimal conditions. However, the activity of this enzyme is highly sensitive to the presence of inhibitory gases CO and O₂ that cause irreversible damage to the active site. Therefore, a detailed knowledge of the diffusion pathways of these inhibitory gases is necessary to develop strategies for designing novel enzymes that are tolerant to these gases. In this work, we studied the diffusion pathways of CO in the CpI FeFe-hydrogenase from Clostridium pasteurianum. Specifically, we used several enhanced sampling and free-energy simulation methods to reconstruct a three-dimensional free-energy surface for CO diffusion which revealed 45 free-energy minima forming an interconnected network of pathways. We discovered multiple pathways of minimal free-energy as diffusion portals for CO and found that previously suggested hydrophobic pathways are not thermodynamically favorable for CO diffusion. We also observed that the global minimum in the free-energy surface is located in the vicinity of the active-site metal cluster, the H-cluster, which suggests a high-affinity for CO near the active site. Among 19 potential residues that we propose as candidates for future mutagenesis studies, 11 residues are shared with residues that have been previously proposed to increase the tolerance of this enzyme for O₂. We hypothesize that these shared candidate residues are potentially useful for designing new variants of this enzyme that are tolerant to both inhibitory gases.

Characterizing the Molecular Mechanisms for Flipping Charged Peptide Flanking Loops across a Lipid Bilayer

The cell membrane largely prevents the passive diffusion of charged molecules due to the large free energy barrier associated with translocating charged groups across the hydrophobic lipid bilayer core. Despite this barrier, some peptides can interconvert between transmembrane and surface-adsorbed states by "flipping" charged flanking loops across the bilayer on a surprisingly rapid second-minute time scale. The transmembrane helices of some multispanning membrane proteins undergo similar reorientation processes, suggesting that loop-flipping may be a mechanism for regulating membrane protein topology; however, the molecular mechanisms underlying this behavior remain unknown. In this work, we study the loop-flipping behavior exhibited by a peptide with a hydrophobic transmembrane helix, charged flanking loops, and a central, membrane-exposed aspartate residue of varying protonation state. We utilize all-atom temperature accelerated molecular dynamics simulations to predict the likelihood of loop-flipping without predefining specific loop-flipping pathways. We demonstrate that this approach can identify multiple possible flipping pathways, with the prevalence of each pathway depending on the protonation state of the central residue. In particular, we find that a charged central residue facilitates loop-flipping by stabilizing membrane water defects, enabling the "self-catalysis" of charge translocation. These findings provide detailed molecular-level insights into charged loop-flipping pathways that may generalize to other charge translocation processes, such as lipid flip-flop or the large-scale conformational rearrangements of multispanning membrane proteins.

Tyrosine Kinase Activation and Conformational Flexibility: Lessons from Src-Family Tyrosine Kinases

Protein kinases are enzymes that catalyze the covalent transfer of the γ-phosphate of an adenosine triphosphate (ATP) molecule onto a tyrosine, serine, threonine, or histidine residue in the substrate and thus send a chemical signal to networks of downstream proteins. They are important cellular signaling enzymes that regulate cell growth, proliferation, metabolism, differentiation, and migration. Unregulated protein kinase activity is often associated with a wide range of diseases, therefore making protein kinases major therapeutic targets. A prototypical system of central interest to understand the regulation of kinase activity is provided by tyrosine kinase c-Src, which belongs to the family of Src-related non-receptor tyrosine kinases (SFKs). Although the broad picture of autoinhibition via the regulatory domains and via the phosphorylation of the C-terminal tail is well characterized from a structural point of view, a detailed mechanistic understanding at the atomic-level is lacking. Advanced computational methods based on all-atom molecular dynamics (MD) simulations are employed to advance our understanding of tyrosine kinase activation. The computational studies suggest that the isolated kinase domain (KD) is energetically most favorable in the inactive conformation when the activation loop (A-loop) of the KD is not phosphorylated. The KD makes transient visits to a catalytically competent active-like conformation. The process of bimolecular trans-autophosphorylation of the A-loop eventually locks the KD in the active state. Activating point mutations may act by slightly increasing the population of the active-like conformation, enhancing the availability of the A-loop to be phosphorylated. The Src-homology 2 (SH2) and Src-homology 3 (SH3) regulatory domains, depending upon their configuration, either promote the inactive or the active state of the kinase domain. In addition to the roles played by the SH3, SH2, and KD, the Src-homology 4-Unique domain (SH4-U) region also serves as a key moderator of substrate specificity and kinase function. Thus, a fundamental understanding of the conformational propensity of the SH4-U region and how this affects the association to the membrane surface are likely to lead to the discovery of new intermediate states and alternate strategies for inhibition of kinase activity for drug discovery. The existence of a multitude of KD conformations poses a great challenge aimed at the design of specific inhibitors. One promising computational strategy to explore the conformational flexibility of the KD is to construct Markov state models from aggregated MD data.

Dynamic, structural and thermodynamic basis of insulin-like growth factor 1 kinase allostery mediated by activation loop phosphorylation

Despite the importance of kinases' catalytic activity regulation in cell signaling, detailed mechanisms underlying their activity regulation are poorly understood. Herein, using insulin-like growth factor 1 receptor kinase (IGF-1RK) as a model, the mechanisms of kinase regulation by its activation loop (A-loop) phosphorylation were investigated through molecular dynamics (MD) and alchemical free energy simulations. Analyses of the simulation results and free energy landscapes determined for the entire catalytic cycle of the kinase revealed that A-loop phosphorylation affects each step in the IGF-1RK catalytic cycle, including conformational change, substrate binding/product release and catalytic phosphoryl transfer. Specifically, the conformational equilibrium of the kinase is shifted by 13.2 kcal mol-1 to favor the active conformation after A-loop phosphorylation, which increases substrate binding affinity of the activated kinase. This free energy shift is achieved primarily via destabilization of the inactive conformation. The free energy of the catalytic reaction is also changed by 3.3 kcal mol-1 after the phosphorylation and in the end, facilitates product release. Analyses of MD simulations showed that A-loop phosphorylation produces these energetic effects by perturbing the side chain interactions around each A-loop tyrosine. These interaction changes are propagated to the remainder of the kinase to modify the orientations and dynamics of the αC-helix and A-loop, and together yield the observed free energy changes. Since many protein kinases share similar interactions identified in this work, the mechanisms of kinase allostery and catalysis unraveled here can be applicable to them.

From Type I to Type II: Design, Synthesis, and Characterization of Potent Pyrazin-2-ones as DFG-Out Inhibitors of PDGFRβ

Reversible protein kinase inhibitors that bind in the ATP cleft can be classified as type I or type II binders. Of these, type I inhibitors address the active form, whereas type II inhibitors typically lock the kinase in an inactive form. At the molecular level, the conformation of the flexible activation loop holding the key DFG motif controls access to the ATP site, thereby determining an active or inactive kinase state. Accordingly, type I and type II kinase inhibitors bind to so-called DFG-in or DFG-out conformations, respectively. Based on our former study on highly selective platelet-derived growth factor receptor β (PDGFRβ) pyrazin-2-one type I inhibitors, we expanded this scaffold toward the deep pocket, yielding the highly potent and effective type II inhibitor 5 (4-[(4-methylpiperazin-1-yl)methyl]-N-[3-[[6-oxo-5-(3,4,5-trimethoxyphenyl)-1H-pyrazin-3-yl]methyl]phenyl]benzamide). In vitro characterization, including selectivity panel data from activity-based assays (300 kinases) and affinity-based assays (97 kinases) of these PDGFRβ type I (1; 5-(4-hydroxy-3-methoxy-phenyl)-3-(3,4,5-trimethoxyphenyl)-1H-pyrazin-2-one) and II (5) inhibitors showing the same pyrazin-2-one chemotype are compared. Implications are discussed regarding the data for selectivity and efficacy of type I and type II ligands.

Building Graphs To Describe Dynamics, Kinetics, and Energetics in the d-ALa:d-Lac Ligase VanA

The d-Ala:d-Lac ligase, VanA, plays a critical role in the resistance of vancomycin. Indeed, it is involved in the synthesis of a peptidoglycan precursor, to which vancomycin cannot bind. The reaction catalyzed by VanA requires the opening of the so-called “ω-loop”, so that the substrates can enter the active site. Here, the conformational landscape of VanA is explored by an enhanced sampling approach: the temperature-accelerated molecular dynamics (TAMD). Analysis of the molecular dynamics (MD) and TAMD trajectories recorded on VanA permits a graphical description of the structural and kinetics aspects of the conformational space of VanA, where the internal mobility and various opening modes of the ω-loop play a major role. The other important feature is the correlation of the ω-loop motion with the movements of the opposite domain, defined as containing the residues A149–Q208. Conformational and kinetic clusters have been determined and a path describing the ω-loop opening was extracted from these clusters. The determination of this opening path, as well as the relative importance of hydrogen bonds along the path, permit one to propose some key residue interactions for the kinetics of the ω-loop opening.

Perturbation Approaches for Exploring Protein Binding Site Flexibility to Predict Transient Binding Pockets

Simulations of the long-time scale motions of a ligand binding pocket in a protein may open up new perspectives for the design of compounds with steric or chemical properties differing from those of known binders. However, slow motions of proteins are difficult to access using standard molecular dynamics (MD) simulations and are thus usually neglected in computational drug design. Here, we introduce two nonequilibrium MD approaches to identify conformational changes of a binding site and detect transient pockets associated with these motions. The methods proposed are based on the rotamerically induced perturbation (RIP) MD approach, which employs perturbation of side-chain torsional motion for initiating large-scale protein movement. The first approach, Langevin-RIP (L-RIP), entails a series of short Langevin MD simulations, each starting with perturbation of one of the side-chains lining the binding site of interest. L-RIP provides extensive sampling of conformational changes of the binding site. In less than 1 ns of MD simulation with L-RIP, we observed distortions of the α-helix in the ATP binding site of HSP90 and flipping of the DFG loop in Src kinase. In the second approach, RIPlig, a perturbation is applied to a pseudoligand placed in different parts of a binding pocket, which enables flexible regions of the binding site to be identified in a small number of 10 ps MD simulations. The methods were evaluated for four test proteins displaying different types and degrees of binding site flexibility. Both methods reveal all transient pocket regions in less than a total of 10 ns of simulations, even though many of these regions remained closed in 100 ns conventional MD. The proposed methods provide computationally efficient tools to explore binding site flexibility and can aid in the functional characterization of protein pockets, and the identification of transient pockets for ligand design.

Allosteric inhibition of c-Met kinase in sub-microsecond molecular dynamics simulations induced by its inhibitor, tivantinib

Molecular dynamics simulations showed that conformation transition of c-Met from DFG-in to DFG-out may accomplish rapidly in the presence of tivantinib. A unique binding mode of tivantinib was found to be critical for this “DFG-flip”.

Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review

Molecular Dynamics simulations are a powerful approach to study biomolecular conformational changes or protein-ligand, protein-protein, and protein-DNA/RNA interactions. Straightforward applications, however, are often hampered by incomplete sampling, since in a typical simulated trajectory the system will spend most of its time trapped by high energy barriers in restricted regions of the configuration space. Over the years, several techniques have been designed to overcome this problem and enhance space sampling. Here, we review a class of methods that rely on the idea of extending the set of dynamical variables of the system by adding extra ones associated to functions describing the process under study. In particular, we illustrate the Temperature Accelerated Molecular Dynamics (TAMD), Logarithmic Mean Force Dynamics (LogMFD), and Multiscale Enhanced Sampling (MSES) algorithms. We also discuss combinations with techniques for searching reaction paths. We show the advantages presented by this approach and how it allows to quickly sample important regions of the free-energy landscape via automatic exploration.

Temperature Accelerated Molecular Dynamics with Soft-Ratcheting Criterion Orients Enhanced Sampling by Low-Resolution Information

Many proteins exhibit an equilibrium between multiple conformations, some of them being characterized only by low-resolution information. Visiting all conformations is a demanding task for computational techniques performing enhanced but unfocused exploration of collective variable (CV) space. Otherwise, pulling a structure toward a target condition biases the exploration in a way difficult to assess. To address this problem, we introduce here the soft-ratcheting temperature-accelerated molecular dynamics (sr-TAMD), where the exploration of CV space by TAMD is coupled to a soft-ratcheting algorithm that filters the evolving CV values according to a predefined criterion. Any low resolution or even qualitative information can be used to orient the exploration. We validate this technique by exploring the conformational space of the inactive state of the catalytic domain of the adenyl cyclase AC from Bordetella pertussis. The domain AC gets activated by association with calmodulin (CaM), and the available crystal structure shows that in the complex the protein has an elongated shape. High-resolution data are not available for the inactive, CaM-free protein state, but hydrodynamic measurements have shown that the inactive AC displays a more globular conformation. Here, using as CVs several geometric centers, we use sr-TAMD to enhance CV space sampling while filtering for CV values that correspond to centers moving close to each other, and we thus rapidly visit regions of conformational space that correspond to globular structures. The set of conformations sampled using sr-TAMD provides the most extensive description of the inactive state of AC up to now, consistent with available experimental information.

Theoretical and computational studies of peptides and receptors of the insulin family

Synergistic interactions among peptides and receptors of the insulin family are required for glucose homeostasis, normal cellular growth and development, proliferation, differentiation and other metabolic processes. The peptides of the insulin family are disulfide-linked single or dual-chain proteins, while receptors are ligand-activated transmembrane glycoproteins of the receptor tyrosine kinase (RTK) superfamily. Binding of ligands to the extracellular domains of receptors is known to initiate signaling via activation of intracellular kinase domains. While the structure of insulin has been known since 1969, recent decades have seen remarkable progress on the structural biology of apo and liganded receptor fragments. Here, we review how this useful structural information (on ligands and receptors) has enabled large-scale atomically-resolved simulations to elucidate the conformational dynamics of these biomolecules. Particularly, applications of molecular dynamics (MD) and Monte Carlo (MC) simulation methods are discussed in various contexts, including studies of isolated ligands, apo-receptors, ligand/receptor complexes and intracellular kinase domains. The review concludes with a brief overview and future outlook for modeling and computational studies in this family of proteins.

Dynamical insights of Mnk2 kinase activation by phosphorylation to facilitate inhibitor discovery

Aim: Mitogen-activated protein kinase-interacting kinases (Mnks) are emerging anticancer targets. Mnks feature unique structural features, enhancing their importance for selective inhibitor discovery. Nonetheless, the lack of structural details obstruct the development of selective Mnk inhibitors. Results: We disclose the first complete structure model of the activated state of Mnk2. Using all-atom accelerated molecular dynamics, we also demonstrate that its activation by phosphorylation grants access to distinct activation loop conformations, steering the inactive-to-active conformational transformation. Then we propose the binding mode of CGP57380 to active Mnk2, and evaluate key interactions that could be critical for future Mnk-targeted inhibitors. Conclusion: Critical insights of the Mnk2 activation process are gained, while providing a platform for designing Mnk-targeted anticancer agents.

Computational study of the "DFG-flip" conformational transition in c-Abl and c-Src tyrosine kinases

Protein tyrosine kinases are crucial to cellular signaling pathways regulating cell growth, proliferation, metabolism, differentiation, and migration. To maintain normal regulation of cellular signal transductions, the activities of tyrosine kinases are also highly regulated. The conformation of a three-residue motif Asp-Phe-Gly (DFG) near the N-terminus of the long “activation” loop covering the catalytic site is known to have a critical impact on the activity of c-Abl and c-Src tyrosine kinases. A conformational transition of the DFG motif can switch the enzyme from an active (DFG-in) to an inactive (DFG-out) state. In the present study, the string method with swarms-of-trajectories was used to computationally determine the reaction pathway connecting the two end-states, and umbrella sampling calculations were carried out to characterize the thermodynamic factors affecting the conformations of the DFG motif in c-Abl and c-Src kinases. According to the calculated free energy landscapes, the DFG-out conformation is clearly more favorable in the case of c-Abl than that of c-Src. The calculations also show that the protonation state of the aspartate residue in the DFG motif strongly affects the in/out conformational transition in c-Abl, although it has a much smaller impact in the case of c-Src due to local structural differences.

Computational Recipe for Efficient Description of Large-Scale Conformational Changes in Biomolecular Systems

Characterizing large-scale structural transitions in biomolecular systems poses major technical challenges to both experimental and computational approaches. On the computational side, efficient sampling of the configuration space along the transition pathway remains the most daunting challenge. Recognizing this issue, we introduce a knowledge-based computational approach toward describing large-scale conformational transitions using (i) nonequilibrium, driven simulations combined with work measurements and (ii) free energy calculations using empirically optimized biasing protocols. The first part is based on designing mechanistically relevant, system-specific reaction coordinates whose usefulness and applicability in inducing the transition of interest are examined using knowledge-based, qualitative assessments along with nonequilirbrium work measurements which provide an empirical framework for optimizing the biasing protocol. The second part employs the optimized biasing protocol resulting from the first part to initiate free energy calculations and characterize the transition quantitatively. Using a biasing protocol fine-tuned to a particular transition not only improves the accuracy of the resulting free energies but also speeds up the convergence. The efficiency of the sampling will be assessed by employing dimensionality reduction techniques to help detect possible flaws and provide potential improvements in the design of the biasing protocol. Structural transition of a membrane transporter will be used as an example to illustrate the workings of the proposed approach.

Conformational Transition Pathways of Epidermal Growth Factor Receptor Kinase Domain from Multiple Molecular Dynamics Simulations and Bayesian Clustering

The epidermal growth factor receptor (EGFR) is aberrantly activated in various cancer cells and an important target for cancer treatment. Deep understanding of EGFR conformational changes between the active and inactive states is of pharmaceutical interest. Here we present a strategy combining multiply targeted molecular dynamics simulations, unbiased molecular dynamics simulations, and Bayesian clustering to investigate transition pathways during the activation/inactivation process of EGFR kinase domain. Two distinct pathways between the active and inactive forms are designed, explored, and compared. Based on Bayesian clustering and rough two-dimensional free energy surfaces, the energy-favorable pathway is recognized, though DFG-flip happens in both pathways. In addition, another pathway with different intermediate states appears in our simulations. Comparison of distinct pathways also indicates that disruption of the Lys745-Glu762 interaction is critically important in DFG-flip while movement of the A-loop significantly facilitates the conformational change. Our simulations yield new insights into EGFR conformational transitions. Moreover, our results verify that this approach is valid and efficient in sampling of protein conformational changes and comparison of distinct pathways.

Temperature-accelerated molecular dynamics gives insights into globular conformations sampled in the free state of the AC catalytic domain

The catalytic domain of the adenyl cyclase (AC) toxin from Bordetella pertussis is activated by interaction with calmodulin (CaM), resulting in cAMP overproduction in the infected cell. In the X-ray crystallographic structure of the complex between AC and the C terminal lobe of CaM, the toxin displays a markedly elongated shape. As for the structure of the isolated protein, experimental results support the hypothesis that more globular conformations are sampled, but information at atomic resolution is still lacking. Here, we use temperature-accelerated molecular dynamics (TAMD) simulations to generate putative all-atom models of globular conformations sampled by CaM-free AC. As collective variables, we use centers of mass coordinates of groups of residues selected from the analysis of standard molecular dynamics (MD) simulations. Results show that TAMD allows extended conformational sampling and generates AC conformations that are more globular than in the complexed state. These structures are then refined via energy minimization and further unrestrained MD simulations to optimize inter-domain packing interactions, thus resulting in the identification of a set of hydrogen bonds present in the globular conformations.

Exploring the conformational transitions of biomolecular systems using a simple two-state anisotropic network model

Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results.

Many biomolecules are like tiny molecular machines that need to change their shapes and visit many states to perform their biological functions. For a complete molecular understanding of a biological process, one needs to have information on the relevant stable states of the system in question, as well as the pathways by which the system travels from one state to another. We report here an efficient computational method that uses the knowledge of experimental structures of a pair of stable states in order to construct an energetically favoravle pathway between them. We adopt a simple representation of the molecular system by replacing the atoms with beads connected by springs and constructing an energy function with two minima around the end-states. We searched for the structure with highest energy that the system is most likely to visit during the transition and created two paths starting from this structure and proceeding toward the end-states. The combined result of these two paths is the minimum energy pathway between the two stable states. We apply this method to study important structural changes in one enzyme and three large proteins that transport small molecules and ions across the cell membrane.

Conformational changes in acetylcholine binding protein investigated by temperature accelerated molecular dynamics

Despite the large number of studies available on nicotinic acetylcholine receptors, a complete account of the mechanistic aspects of their gating transition in response to ligand binding still remains elusive. As a first step toward dissecting the transition mechanism by accelerated sampling techniques, we study the ligand-induced conformational changes of the acetylcholine binding protein (AChBP), a widely accepted model for the full receptor extracellular domain. Using unbiased Molecular Dynamics (MD) and Temperature Accelerated Molecular Dynamics (TAMD) simulations we investigate the AChBP transition between the apo and the agonist-bound state. In long standard MD simulations, both conformations of the native protein are stable, while the agonist-bound structure evolves toward the apo one if the orientation of few key sidechains in the orthosteric cavity is modified. Conversely, TAMD simulations initiated from the native conformations are able to produce the spontaneous transition. With respect to the modified conformations, TAMD accelerates the transition by at least a factor 10. The analysis of some specific residue-residue interactions points out that the transition mechanism is based on the disruption/formation of few key hydrogen bonds. Finally, while early events of ligand dissociation are observed already in standard MD, TAMD accelerates the ligand detachment and, at the highest TAMD effective temperature, it is able to produce a complete dissociation path in one AChBP subunit.

Comparison between Mean Forces and Swarms-of-Trajectories String Methods

The original formulation of the string method in collective variable space is compared with a recent variant called string method with swarms-of-trajectories. The assumptions made in the original method are revisited and the significance of the minimum free energy path (MFEP) is discussed in the context of reactive events. These assumptions are compared to those made in the string method with swarms-of-trajectories, and shown to be equivalent in a certain regime: in particular an expression for the path identified by the swarms-of-trajectories method is given and shown to be closely related to the MFEP. Finally, the algorithmic aspects of both methods are compared.

Conformational dynamics of a regulator of G-protein signaling protein reveals a mechanism of allosteric inhibition by a small molecule

Regulators of G protein signaling (RGS) proteins are key players in regulating signaling via G protein-coupled receptors. RGS proteins directly bind to the Gα-subunits of activated heterotrimeric G-proteins, and accelerate the rate of GTP hydrolysis, thereby rapidly deactivating G-proteins. Using atomistic simulations and NMR spectroscopy, we have studied in molecular detail the mechanism of action of CCG-50014, a potent small molecule inhibitor of RGS4 that covalently binds to cysteine residues on RGS4. We apply temperature-accelerated molecular dynamics (TAMD) to carry out enhanced conformational sampling of apo RGS4 structures, and consistently find that the α5-α6 helix pair of RGS4 can spontaneously span open-like conformations, allowing binding of CCG-50014 to the buried side-chain of Cys95. Both NMR experiments and MD simulations reveal chemical shift perturbations in residues in the vicinity of inhibitor binding site as well as in the RGS4-Gα binding interface. Consistent with a loss of G-protein binding, GAP activity, and allosteric mechanism of action of CCG-50014, our simulations of the RGS4-Gα complex in the presence of inhibitor suggest a relatively unstable protein-protein interaction. These results have potential implications for understanding how the conformational dynamics among RGS proteins may play a key role in the sensitivity of inhibitors.

Insights into the Importance of DFD-Motif and Insertion I1 in Stabilizing the DFD-Out Conformation of Mnk2 Kinase

Human mitogen-activated protein kinases (MAPK)-interacting kinases 1 and 2 (Mnk1/2) are promising anticancer targets. Mnks possess special insertions and a DFD-motif that are distinct from other kinases. Crystallographic studies of Mnk1/2 have revealed that the DFD-motif adopts the DFG/D-out conformation in which residue F227 flips into the ATP binding pocket. This is rarely observed in other kinases. Although the DFG-out conformation has attracted great interest for designing selective inhibitors, structural requirements for binding and the mechanism governing the DFG-out conformation remain unclear. This work presents for the first time the applicability of 3D models of Mnk2 protein in studying conformational changes by utilizing homology modeling and molecular dynamics simulations. The study reveals that the interactions between residue K234 of insertion I1 and D226 of the DFD motif play a key role in inducing and stabilizing the DFD-out conformation. The structural features will aid in the rational design of Mnk2 inhibitors.

Enhanced sampling and overfitting analyses in structural refinement of nucleic acids into electron microscopy maps

Flexible fitting computational algorithms are often useful to interpret low-resolution maps of many macromolecular complexes generated by electron microscopy (EM) imaging. One such atomistic simulation technique is molecular dynamics flexible fitting (MDFF), which has been widely applied to generate structural models of large ribonucleoprotein assemblies such as the ribosome. We have previously shown that MDFF simulations of globular proteins are sensitive to the resolution of the target EM map and the strength of restraints used to preserve the secondary structure elements during fitting (Vashisth, H.; et al. Structure 2012, 20, 1453-1462). In this work, we aim to systematically examine the quality of structural models of various nucleic acids obtained via MDFF by varying the map resolution and the strength of structural restraints. We also demonstrate how an enhanced conformational sampling technique for proteins, temperature-accelerated molecular dynamics (TAMD), can be combined with MDFF for the structural refinement of nucleic acids in EM maps. Finally, we also demonstrate application of TAMD-assisted MDFF (TAMDFF) on a RNA/protein complex and suggest that TAMDFF is a viable strategy for enhanced conformational fitting in target maps of ribonucleoprotein complexes.

Native states of fast-folding proteins are kinetic traps

It has been suggested that the native state of a protein acts as a kinetic hub that can facilitate transitions between nonnative states. Using recently developed tools to quantify mediation probabilities ("hub scores"), we quantify hub-like behavior in atomic resolution trajectories for the first time. We use a data set of trajectory ensembles for 12 fast-folding proteins previously published by D. E. Shaw Research (Lindorff-Larsen, K.; et al. How Fast-Folding Proteins Fold. Science2011, 334, 517) with an aggregate simulation time of over 8.2 ms. We visualize the free-energy landscape of each molecule using configuration space networks, and show that dynamic quantities can be qualitatively understood from visual inspection of the networks. Modularity optimization is used to provide a parameter-free means of tessellating the network into a group of communities. Using hub scores, we find that the percentage of trajectories that are mediated by the native state is 31% when averaged over all molecules, and reaches a maximum of 52% for the homeodomain and chignolin. Furthermore, for these mediated transitions, we use Markov models to determine whether the native state acts as a facilitator for the transition, or as a trap (i.e., an off-pathway detour). Although instances of facilitation are found in 4 of the 12 molecules, we conclude that the native state acts primarily as a trap, which is consistent with the idea of a funnel-like landscape.

All-atom structural models of insulin binding to the insulin receptor in the presence of a tandem hormone-binding element

Insulin regulates blood glucose levels in higher organisms by binding to and activating insulin receptor (IR), a constitutively homodimeric glycoprotein of the receptor tyrosine kinase (RTK) superfamily. Therapeutic efforts in treating diabetes have been significantly impeded by the absence of structural information on the activated form of the insulin/IR complex. Mutagenesis and photo-crosslinking experiments and structural information on insulin and apo-IR strongly suggest that the dual-chain insulin molecule, unlike the related single-chain insulin-like growth factors, binds to IR in a very different conformation than what is displayed in storage forms of the hormone. In particular, hydrophobic residues buried in the core of the folded insulin molecule engage the receptor. There is also the possibility of plasticity in the receptor structure based on these data, which may in part be due to rearrangement of the so-called CT-peptide, a tandem hormone-binding element of IR. These possibilities provide opportunity for large-scale molecular modeling to contribute to our understanding of this system. Using various atomistic simulation approaches, we have constructed all-atom structural models of hormone/receptor complexes in the presence of CT in its crystallographic position and a thermodynamically favorable displaced position. In the "displaced-CT" complex, many more insulin-receptor contacts suggested by experiments are satisfied, and our simulations also suggest that R-insulin potentially represents the receptor-bound form of hormone. The results presented in this work have further implications for the design of receptor-specific agonists/antagonists.

Using enhanced sampling and structural restraints to refine atomic structures into low-resolution electron microscopy maps

For a variety of problems in structural biology, low-resolution maps generated by electron microscopy imaging are often interpreted with the help of various flexible-fitting computational algorithms. In this work, we systematically analyze the quality of final models of various proteins obtained via molecular dynamics flexible fitting (MDFF) by varying the map-resolution, strength of structural restraints, and the steering forces. We find that MDFF can be extended to understand conformational changes in lower-resolution maps if larger structural restraints and lower steering forces are used to prevent overfitting. We further show that the capabilities of MDFF can be extended by combining it with an enhanced conformational sampling method, temperature-accelerated molecular dynamics (TAMD). Specifically, either TAMD can be used to generate better starting configurations for MDFF fitting or TAMD-assisted MDFF (TAMDFF) can be performed to accelerate conformational search in atomistic simulations.

Conformational Sampling of Maltose-transporter Components in Cartesian Collective Variables is Governed by the Low-frequency Normal Modes

We have studied large-scale conformational transitions in the maltose-binding protein, and the nucleotide binding domains of a maltose-transporter using enhanced conformational sampling in Cartesian collective variables (CVs) with temperature-accelerated molecular dynamics (TAMD), and C(α)-based elastic network normal mode analysis. Significantly, every functional displacement in the TAMD-generated pathways of each protein could be rationalized via a single low-frequency soft mode, while a combination of 2 to 3 low-frequency modes were found to describe the entire conformational change suggesting that collective functional movement in TAMD trajectories is facilitated by the intrinsically accessible low-frequency normal modes. By applying a harmonic potential to facilitate functional motion in TAMD simulations, we also provide a recipe to reproducibly generate structural transitions in both proteins, which can be used to characterize large-scale conformational changes in other biomolecules.

Energetics and mechanism of the normal-to-amyloidogenic isomerization of β2-microglobulin: on-the-fly string method calculations

We use on-the-fly finite temperature string method in collective variables to study the transition from a normal to an amyloidogenic conformation of β2-microglobulin. We show that the protonation state of two histidine residues is of key importance and that under acidic (protonating) conditions, the transition to the amyloidgenic form is facilitated by both displacement of N-terminal residues to disrupt a hydrophobic pocket and by side-chain/side-chain electrostatic attraction, both of which facilitate a cis-trans prolyl isomerization. The free energy barriers for the normal-to-amyloidogenic isomerization are found to be 14.9 and 7.1 kcal/mol for the neutral and protonated cases, respectively, consistent with enhanced amyloidgenesis at low pH observed both in vitro and in hemodialysis-associated amyloidosis, and somewhat lower than experimentally determined barriers for bare prolyl cis-trans isomerization. We suggest specific mutagenesis experiments which could be used to further validate the mechanism observed.