Modern Kinetics and Mechanism of Protein Folding: A Retrospective

Computed Vibrational Heat Capacities for Gas-Phase Biomolecular Ions

Collision induced dissociation (CID) and collision induced unfolding (CIU) experiments are important tools for determining the structures of and differences between biomolecular complexes with mass spectrometry. However, quantitative comparison of CID/CIU data acquired on different platforms or even using different regions of the same instrument can be very challenging due to differences in gas identity and pressure, electric fields, and other experimental parameters. In principle, these can be reconciled by a detailed understanding of how ions heat, cool, and dissociate or unfold in time as a function of these parameters. Fundamental information needed to model these processes for different ion types and masses is their heat capacity as a function of the internal (i.e., vibrational) temperature. Here, we use quantum computational theory to predict average heat capacities as a function of temperature for a variety of model biomolecule types from 100 to 3000 K. On a degree-of-freedom basis, these values are remarkably invariant within each biomolecule type and can be used to estimate heat capacities of much larger biomolecular ions. We also explore effects of ion heating, cooling, and internal energy distribution as a function of time using a home-built program (IonSPA). We observe that these internal energy distributions can be nearly Boltzmann for larger ions (greater than a few kDa) through most of the CID/CIU kinetic window after a brief (few-μs) induction period. These results should be useful in reconciling CID/CIU results across different instrument platforms and under different experimental conditions, as well as in designing instrumentation and experiments to control CID/CIU behavior.

Importance of Inter-residue Contacts for Understanding Protein Folding and Unfolding Rates, Remote Homology, and Drug Design

Inter-residue interactions in protein structures provide valuable insights into protein folding and stability. Understanding these interactions can be helpful in many crucial applications, including rational design of therapeutic small molecules and biologics, locating functional protein sites, and predicting protein-protein and protein-ligand interactions. The process of developing machine learning models incorporating inter-residue interactions has been improved recently. This review highlights the theoretical models incorporating inter-residue interactions in predicting folding and unfolding rates of proteins. Utilizing contact maps to depict inter-residue interactions aids researchers in developing computer models for detecting remote homologs and interface residues within protein-protein complexes which, in turn, enhances our knowledge of the relationship between sequence and structure of proteins. Further, the application of contact maps derived from inter-residue interactions is highlighted in the field of drug discovery. Overall, this review presents an extensive assessment of the significant models that use inter-residue interactions to investigate folding rates, unfolding rates, remote homology, and drug development, providing potential future advancements in constructing efficient computational models in structural biology.

NADH-dependent CO2 reductase on graphite for capacitive electrocatalytic interfacing mediated by solid-binding peptide

NAD+/NADH-dependent CO2 reductase (CR) adapted from Candida methylica (E.C. 1.17.1.9) was introduced with a non-native graphite-specific peptide (Gr; IMVTESSDYSSY) as molecular binder to modify the native enzyme (CR-WT) with peptide insertion at N, C and NC terminus (CR-GrN, CR-GrC and CR-GrNC) to assess the influence of site-specific fusion on electrode binding. Graphite surface-binding activity relative to the electrode topography was evaluated for both native and synthetic CRs to establish the enzyme-electrode interfacing potentiality for efficient electron channelling. Impact of site-specific peptide fusion and amino-acids positioning was assessed for the active site binding availability and adsorption/desorption capability towards competent CO2-based redox catalysis. Solid-binding peptide and graphite surface interactive ability on direct electron transfer was studied with structural, enzymatic and electrochemical characterizations for efficient CO2 electrosynthesis. Overall, enzymatic CO2 reduction to formate based on interactive potentiality of enzyme-electrode complex with peptide modifications and graphite surface towards possibility of bioelectronics upscaling was depicted.

Hydrogen/Deuterium Exchange Mass Spectrometry: Fundamentals, Limitations, and Opportunities

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) probes dynamic motions of proteins by monitoring the kinetics of backbone amide deuteration. Dynamic regions exhibit rapid HDX, while rigid segments are more protected. Current data readouts focus on qualitative comparative observations (such as "residues X to Y become more protected after protein exposure to ligand Z"). At present, it is not possible to decode HDX protection patterns in an atomistic fashion. In other words, the exact range of protein motions under a given set of conditions cannot be uncovered, leaving space for speculative interpretations. Amide back exchange is an under-appreciated problem, as the widely used (m-m0)/(m100-m0) correction method can distort HDX kinetic profiles. Future data analysis strategies require a better fundamental understanding of HDX events, going beyond the classical Linderstrøm-Lang model. Combined with experiments that offer enhanced spatial resolution and suppressed back exchange, it should become possible to uncover the exact range of motions exhibited by a protein under a given set of conditions. Such advances would provide a greatly improved understanding of protein behavior in health and disease.

Rate-Engineered Plasmon-Enhanced Fluorescence for Real-Time Microsecond Dynamics of Single Biomolecules

Single-molecule fluorescence has revealed a wealth of biochemical processes but does not give access to submillisecond dynamics involved in transient interactions and molecular dynamics. Here we overcome this bottleneck and demonstrate record-high photon count rates of >107 photons/s from single plasmon-enhanced fluorophores. This is achieved by combining two conceptual novelties: first, we balance the excitation and decay rate enhancements by the antenna's volume, resulting in maximum fluorescence intensity. Second, we enhance the triplet decay rate using a multicomponent surface chemistry that minimizes microsecond blinking. We demonstrate applications to two exemplary molecular processes: we first reveal transient encounters and hybridization of DNA with a 1 μs temporal resolution. Second, we exploit the field gradient around the nanoparticle as a molecular ruler to reveal microsecond intramolecular dynamics of multivalent complexes. Our results pave the way toward real-time microsecond studies of biochemical processes using an implementation compatible with existing single-molecule fluorescence methods.

Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular dynamics simulations offer detailed trajectories of protein motions. Computational methods applied to X-ray crystallography and cryo-electron microscopy (cryo-EM) have enabled the exploration of protein dynamics, capturing conformational ensembles that were previously unattainable. The integration of machine learning, exemplified by AlphaFold2, has accelerated structure prediction and dynamics analysis. These approaches have revealed the importance of protein dynamics in allosteric regulation, enzyme catalysis, and intrinsically disordered proteins. The shift towards ensemble representations of protein structures and the application of single-molecule techniques have further enhanced our ability to capture the dynamic nature of proteins. Understanding protein dynamics is essential for elucidating biological mechanisms, designing drugs, and developing novel biocatalysts, marking a significant paradigm shift in structural biology and drug discovery.

bio2Byte Tools deployment as a Python package and Galaxy tool to predict protein biophysical properties

SUMMARY

We introduce a unified Python package for the prediction of protein biophysical properties, streamlining previous tools developed by the Bio2Byte research group. This suite facilitates comprehensive assessments of protein characteristics, incorporating predictors for backbone and sidechain dynamics, local secondary structure propensities, early folding, long disorder, beta-sheet aggregation, and fused in sarcoma (FUS)-like phase separation. Our package significantly eases the integration and execution of these tools, enhancing accessibility for both computational and experimental researchers.

AVAILABILITY AND IMPLEMENTATION

The suite is available on the Python Package Index (PyPI): https://pypi.org/project/b2bTools/ and Bioconda: https://bioconda.github.io/recipes/b2btools/README.html for Linux and macOS systems, with Docker images hosted on Biocontainers: https://quay.io/repository/biocontainers/b2btools?tab=tags&tag=latest and Docker Hub: https://hub.docker.com/u/bio2byte. Online deployments are available on Galaxy Europe: https://usegalaxy.eu/root?tool_id=b2btools_single_sequence and our online server: https://bio2byte.be/b2btools/. The source code can be found at https://bitbucket.org/bio2byte/b2btools_releases.

Quantifying Microsecond Solution-Phase Conformational Dynamics of a DNA Hairpin at the Single-Molecule Level

Quantifying the rapid conformational dynamics of biological systems is fundamental to understanding the mechanism. However, biomolecules are complex, often containing static and dynamic heterogeneity, thus motivating the use of single-molecule methods, particularly those that can operate in solution. In this study, we measure microsecond conformational dynamics of solution-phase DNA hairpins at the single-molecule level using an anti-Brownian electrokinetic (ABEL) trap. Different conformational states were distinguished by their fluorescence lifetimes, and kinetic parameters describing transitions between these states were determined using two-dimensional fluorescence lifetime correlation (2DFLCS) analysis. Rather than combining fluorescence signals from the entire data set ensemble, long observation times of individual molecules allowed ABEL-2DFLCS to be performed on each molecule independently, yielding the underlying distribution of the system's kinetic parameters. ABEL-2DFLCS on the DNA hairpins resolved an underlying heterogeneity of fluorescence lifetimes and provided signatures of two-state exponential dynamics with rapid ( Collapse

Key Words

• conformational dynamics
• single-molecule spectroscopy
• förster correlation spectroscopy
• nucleic acid hairpin
• fluorescence resonance energy transfer

Collapse

MESH Headings Collapse

Grants

• R01 GM136981 NIGMS NIH HHS
• National Institute of General Medical Sciences
• Morino Foundation for Molecular Science
• Japan Society for the Promotion of Science

Collapse

Affiliation(s)

Alexander K. Foote Department of Chemistry, University of Wisconsin—Madison, Madison, Wisconsin 53706, United States
Kunihiko Ishii Molecular Spectroscopy Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan Ultrafast Spectroscopy Research Team, RIKEN Center for Advanced Photonics (RAP), 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
Brendan Cullinane Department of Chemistry, University of Wisconsin—Madison, Madison, Wisconsin 53706, United States
Tahei Tahara Molecular Spectroscopy Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan Ultrafast Spectroscopy Research Team, RIKEN Center for Advanced Photonics (RAP), 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
Randall H. Goldsmith Department of Chemistry, University of Wisconsin—Madison, Madison, Wisconsin 53706, United States

Collapse

Collaborators Collapse

A Stochastic Landscape Approach for Protein Folding State Classification

Protein folding is a critical process that determines the functional state of proteins. Proper folding is essential for proteins to acquire their functional three-dimensional structures and execute their biological role, whereas misfolded proteins can lead to various diseases, including neurodegenerative disorders like Alzheimer's and Parkinson's. Therefore, a deeper understanding of protein folding is vital for understanding disease mechanisms and developing therapeutic strategies. This study introduces the Stochastic Landscape Classification (SLC), an innovative, automated, nonlearning algorithm that quantitatively analyzes protein folding dynamics. Focusing on collective variables (CVs) - low-dimensional representations of complex dynamical systems like molecular dynamics (MD) of macromolecules - the SLC approach segments the CVs into distinct macrostates, revealing the protein folding pathway explored by MD simulations. The segmentation is achieved by analyzing changes in CV trends and clustering these segments using a standard density-based spatial clustering of applications with noise (DBSCAN) scheme. Applied to the MD-based CV trajectories of Chignolin and Trp-Cage proteins, the SLC demonstrates apposite accuracy, validated by comparing standard classification metrics against ground-truth data. These metrics affirm the efficacy of the SLC in capturing intricate protein dynamics and offer a method to evaluate and select the most informative CVs. The practical application of this technique lies in its ability to provide a detailed, quantitative description of protein folding processes, with significant implications for understanding and manipulating protein behavior in industrial and pharmaceutical contexts.

Understanding the heterogeneity intrinsic to protein folding

Relating the native fold of a protein to its amino acid sequence remains a fundamental problem in biology. While computer algorithms have demonstrated recently their prowess in predicting what structure a particular amino acid sequence will fold to, an understanding of how and why a specific protein fold is achieved remains elusive. A major challenge is to define the role of conformational heterogeneity during protein folding. Recent experimental studies, utilizing time-resolved FRET, hydrogen-exchange coupled to mass spectrometry, and single-molecule force spectroscopy, often in conjunction with simulation, have begun to reveal how conformational heterogeneity evolves during folding, and whether an intermediate ensemble of defined free energy consists of different sub-populations of molecules that may differ significantly in conformation, energy and entropy.

Counter-Intuitive Features of Particle Dynamics in Nanopores

Using the framework of a continuous diffusion model based on the Smoluchowski equation, we analyze particle dynamics in the confinement of a transmembrane nanopore. We briefly review existing analytical results to highlight consequences of interactions between the channel nanopore and the translocating particles. These interactions are described within a minimalistic approach by lumping together multiple physical forces acting on the particle in the pore into a one-dimensional potential of mean force. Such radical simplification allows us to obtain transparent analytical results, often in a simple algebraic form. While most of our findings are quite intuitive, some of them may seem unexpected and even surprising at first glance. The focus is on five examples: (i) attractive interactions between the particles and the nanopore create a potential well and thus cause the particles to spend more time in the pore but, nevertheless, increase their net flux; (ii) if the potential well-describing particle-pore interaction occupies only a part of the pore length, the mean translocation time is a non-monotonic function of the well length, first increasing and then decreasing with the length; (iii) when a rectangular potential well occupies the entire nanopore, the mean particle residence time in the pore is independent of the particle diffusivity inside the pore and depends only on its diffusivity in the bulk; (iv) although in the presence of a potential bias applied to the nanopore the "downhill" particle flux is higher than the "uphill" one, the mean translocation times and their distributions are identical, i.e., independent of the translocation direction; and (v) fast spontaneous gating affects nanopore selectivity when its characteristic time is comparable to that of the particle transport through the pore.

K-Pro: Kinetics Data on Proteins and Mutants

The study of protein folding plays a crucial role in improving our understanding of protein function and of the relationship between genetics and phenotypes. In particular, understanding the thermodynamics and kinetics of the folding process is important for uncovering the mechanisms behind human disorders caused by protein misfolding. To address this issue, it is essential to collect and curate experimental kinetic and thermodynamic data on protein folding. K-Pro is a new database designed for collecting and storing experimental kinetic data on monomeric proteins, with a two-state folding mechanism. With 1,529 records from 62 proteins corresponding to 65 structures, K-Pro contains various kinetic parameters such as the logarithm of the folding and unfolding rates, Tanford's β and the ϕ values. When available, the database also includes thermodynamic parameters associated with the kinetic data. K-Pro features a user-friendly interface that allows browsing and downloading kinetic data of interest. The graphical interface provides a visual representation of the protein and mutants, and it is cross-linked to key databases such as PDB, UniProt, and PubMed. K-Pro is open and freely accessible through https://folding.biofold.org/k-pro and supports the latest versions of popular browsers.

Probing the inner local density of complex macromolecules by pyrene excimer formation

The direct relationship existing between the average rate constant 〈k〉 for pyrene excimer formation and the local concentration [Py]loc of ground-state pyrenyl labels covalently attached to a macromolecule was established for 55 pyrene-labeled macromolecules (PyLM). These PyLM belonged to three different families of macromolecules with the first representing short monodisperse linear chains end-labeled with pyrene (polystyrene, poly(ethylene oxide), and poly(N-isopropyl acrylamide)), the second representing long polydisperse linear chains randomly labeled with pyrene (poly(methyl acrylate), poly(methyl methacrylate), polystyrene, poly(butyl methacrylate), poly(methoxyethyl methacrylate), and poly(N-isopropyl acrylamide)), and the third being comprised of two series of pyrene end-labeled low generation dendrimers with a bis(hydroxymethyl)propionic acid or a polyamidoamine backbone. The assumption, that the polymeric segments probed by an excited pyrenyl label covalently attached to one of these macromolecules obeyed Gaussian statistics, enabled the calculation of their square root average squared end-to-end distance (LPy), which was applied to calculate [Py]loc. The log-log plots of 〈k〉 as a function of [Py]loc yielded straight lines with a slope of unity for all families of macromolecules studied in four different organic solvents demonstrating the validity and generality of the 〈k〉-vs.-[Py]loc relationship. Since an experimentalist knows how the the pyrenyl labels are covalently attached onto a macromolecule, [Py]loc offers a means to probe the local density of a macromolecule, which can be employed to characterize its conformation in solution. Consequently, the 〈k〉-vs.-[Py]loc relationship provides a novel experimental means to probe the conformation of macromolecules which should establish pyrene excimer formation as an appealing method for conformational studies of macromolecules in solution, which should nicely complement scattering techniques.

Toward a Benchmark for Markov State Models: The Folding of HP35

Adopting a 300 μs long MD trajectory of the folding of villin headpiece (HP35) by D. E. Shaw Research, we recently constructed a Markov state model (MSM) based on inter-residue contacts. The model reproduces the folding time and predicts that the native basin and unfolded region consist of metastable substates that are structurally well-characterized. Recognizing the need to establish well-defined benchmark problems, we study to what extent and in what sense this MSM can be employed as a reference model. Hence, we test the robustness of the MSM by comparing it to models that use alternative combinations of features, dimensionality reduction methods, and clustering schemes. The study suggests some main characteristics of the folding of HP35 that should be reproduced by other competitive models. Moreover, the discussion reveals which parts of the MSM workflow matter most for the considered problem and illustrates the promises and pitfalls of state-based models for the interpretation of biomolecular simulations.

Protein folding rate evolution upon mutations

Despite the spectacular success of cutting-edge protein fold prediction methods, many critical questions remain unanswered, including why proteins can reach their native state in a biologically reasonable time. A satisfactory answer to this simple question could shed light on the slowest folding rate of proteins as well as how mutations-amino-acid substitutions and/or post-translational modifications-might affect it. Preliminary results indicate that (i) Anfinsen's dogma validity ensures that proteins reach their native state on a reasonable timescale regardless of their sequence or length, and (ii) it is feasible to determine the evolution of protein folding rates without accounting for epistasis effects or the mutational trajectories between the starting and target sequences. These results have direct implications for evolutionary biology because they lay the groundwork for a better understanding of why, and to what extent, mutations-a crucial element of evolution and a factor influencing it-affect protein evolvability. Furthermore, they may spur significant progress in our efforts to solve crucial structural biology problems, such as how a sequence encodes its folding.

Studying micro to millisecond protein dynamics using simple amide 15N CEST experiments supplemented with major-state R2 and visible peak-position constraints

Over the last decade amide 15N CEST experiments have emerged as a popular tool to study protein dynamics that involves exchange between a 'visible' major state and sparsely populated 'invisible' minor states. Although initially introduced to study exchange between states that are in slow exchange with each other (typical exchange rates of, 10 to 400 s-1), they are now used to study interconversion between states on the intermediate to fast exchange timescale while still using low to moderate (5 to 350 Hz) 'saturating' B1 fields. The 15N CEST experiment is very sensitive to exchange as the exchange delay TEX can be quite long (~0.5 s) allowing for a large number of exchange events to occur making it a very powerful tool to detect minor sates populated ([Formula: see text]) to as low as 1%. When systems are in fast exchange and the 15N CEST data has to be described using a model that contains exchange, the exchange parameters are often poorly defined because the [Formula: see text] versus [Formula: see text] and [Formula: see text] versus exchange rate ([Formula: see text]) plots can be quite flat with shallow or no minima and the analysis of such 15N CEST data can lead to wrong estimates of the exchange parameters due to the presence of 'spurious' minima. Here we show that the inclusion of experimentally derived constraints on the intrinsic transverse relaxation rates and the inclusion of visible state peak-positions during the analysis of amide 15N CEST data acquired with moderate B1 values (~50 to ~350 Hz) results in convincing minima in the [Formula: see text] versus [Formula: see text] and the [Formula: see text] versus [Formula: see text] plots even when exchange occurs on the 100 μs timescale. The utility of this strategy is demonstrated on the fast-folding Bacillus stearothermophilus peripheral subunit binding domain that folds with a rate constant ~104 s-1. Here the analysis of 15N CEST data alone results in [Formula: see text] versus [Formula: see text] and [Formula: see text] versus [Formula: see text] plots that contain shallow minima, but the inclusion of visible-state peak positions and restraints on the intrinsic transverse relaxation rates of both states during the analysis of the 15N CEST data results in pronounced minima in the [Formula: see text] versus [Formula: see text] and [Formula: see text] versus [Formula: see text] plots and precise exchange parameters even in the fast exchange regime ([Formula: see text]~5). Using this strategy we find that the folding rate constant of PSBD is invariant (~10,500 s-1) from 33.2 to 42.9 °C while the unfolding rates (~70 to ~500 s-1) and unfolded state populations (~0.7 to ~4.3%) increase with temperature. The results presented here show that protein dynamics occurring on the 10 to 104 s-1 timescale can be studied using amide 15N CEST experiments.

Evolutionary conservation of amino acids contributing to the protein folding transition state

The question of whether amino acids critical to protein folding kinetics are evolutionarily conserved has been investigated intensively in the past, but no consensus has yet been reached. Recently, we have demonstrated that the transition state, dictating folding kinetics, is characterized as the state of maximum dynamic cooperativity, i.e., the state of maximum correlations between amino acid contact formations. Here, we investigate the evolutionary conservation of those amino acids contributing significantly to the dynamic cooperativity. We find a strong indication of a new kind of relationship-necessary but not sufficient causality-between the evolutionary conservation and the dynamic cooperativity: larger contributions to the dynamic cooperativity arise from more conserved residues, but not vice versa. This holds for all the protein systems for which long folding simulation trajectories are available. To our knowledge, this is the first systematic demonstration of any kind of evolutionary conservation of amino acids relevant to folding kinetics.

Predicting non-equilibrium folding behavior of polymer chains using the steepest-entropy-ascent quantum thermodynamic framework

The steepest-entropy-ascent quantum thermodynamic (SEAQT) framework is used to explore the influence of heating and cooling on polymer chain folding kinetics. The framework predicts how a chain moves from an initial non-equilibrium state to stable equilibrium along a unique thermodynamic path. The thermodynamic state is expressed by occupation probabilities corresponding to the levels of a discrete energy landscape. The landscape is generated using the Replica Exchange Wang-Landau method applied to a polymer chain represented by a sequence of hydrophobic and polar monomers with a simple hydrophobic-polar amino acid model. The chain conformation evolves as energy shifts among the levels of the energy landscape according to the principle of steepest entropy ascent. This principle is implemented via the SEAQT equation of motion. The SEAQT framework has the benefit of providing insight into structural properties under non-equilibrium conditions. Chain conformations during heating and cooling change continuously without sharp transitions in morphology. The changes are more drastic along non-equilibrium paths than along quasi-equilibrium paths. The SEAQT-predicted kinetics are fitted to rates associated with the experimental intensity profiles of cytochrome c protein folding with Rouse dynamics.

Functional, pathogenic, and pharmacological roles of protein folding intermediates

Protein expression and function in eukaryotic cells are tightly harmonized processes modulated by the combination of different layers of regulation, including transcription, processing, stability, and translation of messenger RNA, as well as assembly, maturation, sorting, recycling, and degradation of polypeptides. Integrating all these pathways and the protein quality control machinery, deputed to avoid the production and accumulation of aberrantly folded proteins, determines protein homeostasis. Over the last decade, the combined development of accurate time-resolved experimental techniques and efficient computer simulations has opened the possibility of investigating biological mechanisms at atomic resolution with physics-based models. A meaningful example is the reconstruction of protein folding pathways at atomic resolution, which has enabled the characterization of the folding kinetics of biologically relevant globular proteins consisting of a few hundred amino acids. Combining these innovative computational technologies with rigorous experimental approaches reveals the existence of non-native metastable states transiently appearing along the folding process of such proteins. Here, we review the primary evidence indicating that these protein folding intermediates could play roles in disparate biological processes, from the posttranslational regulation of protein expression to disease-relevant protein misfolding mechanisms. Finally, we discuss how the information encoded into protein folding pathways could be exploited to design an entirely new generation of pharmacological agents capable of promoting the selective degradation of protein targets.

Single-Molecule Optical Biosensing: Recent Advances and Future Challenges

In recent years, the sensitivity and specificity of optical sensors has improved tremendously due to improvements in biochemical functionalization protocols and optical detection systems. As a result, single-molecule sensitivity has been reported in a range of biosensing assay formats. In this Perspective, we summarize optical sensors that achieve single-molecule sensitivity in direct label-free assays, sandwich assays, and competitive assays. We describe the advantages and disadvantages of single-molecule assays and summarize future challenges in the field including their optical miniaturization and integration, multimodal sensing capabilities, accessible time scales, and compatibility with real-life matrices such as biological fluids. We conclude by highlighting the possible application areas of optical single-molecule sensors that include not only healthcare but also the monitoring of the environment and industrial processes.

GB1 hairpin kinetics: capturing the folding pathway with molecular dynamics, replica exchange and optimal dimensionality reduction

We have performed molecular dynamics (MD) and replica-exchange (REMD) simulations of folding of the GB1 hairpin peptide in aqueous solution. REMD results were consistent with a cooperative zipper folding model. 120 μ s MD trajectories at 320 K yielded relaxation times of 1.8 μ s and 100 ns, with the slower assigned to global folding. The MD folding/unfolding transitions also followed the cooperative zipper model, specifying nucleation at the central turn followed by consecutive hydrogen bond formation. Formation of hydrogen bonds and hydrophobic contacts were highly correlated. Coarse-grained kinetic models constructed with the Optimal Dimensionality Reduction (ODR) approach found a folding time of 3.3 μ s and unfolding time of 4.0 μ s . Additionally, relaxation times in the 130-170 ns range could be assigned to formation of the transition state and off-path intermediates. The unfolded state was the most highly populated and, significantly, most heterogenous, assembling the largest number of microstates, primarily composed of extended and turn structures. The folded state was also heterogenous, but a to a lesser degree, involving the fully folded and partially folded in-register hairpins at early stages of the zipper pathway. The transition state corresponded to the nucleated hairpin, with central turn and first beta-sheet hydrogen bond, while the off-path intermediates were off-register partial hairpins. Our simulation results were in excellent agreement with experimental data on folded fraction, relaxation time and folding mechanism. The new findings from this work suggest a highly cooperative zipper folding mechanism, nascent hairpin transition state and ∼100 ns relaxation related to intermediate formation.Communicated by Ramaswamy H. Sarma.

Drug discovery by a basic research scientist

I was fortunate to do my military service during the Vietnam era as a medical officer at the National Institutes of Health (NIH) in Bethesda, Maryland. My first research at NIH was concerned with making a variety of optical measurements on nucleic acid bases and proteins, including single crystal spectra in linearly polarized light and near infrared circular dichroism, interpreting the spectra using molecular orbital and crystal field theories. What I do now is drug discovery, a field at the opposite end of the scientific spectrum. This article gives a brief account of my transition from spectroscopy to sickle cell hemoglobin polymerization to protein folding to drug discovery for treating sickle cell disease. My lab recently developed a high throughput assay to screen the 12,657 compounds of the California Institute of Biomedical Research ReFrame drug repurposing library. This is a precious library because the compounds have either been FDA approved or have been tested in clinical trials. Since the 1970s numerous agents have been reported in the literature to inhibit HbS polymerization and/or sickling with only one successful drug, hydroxyurea, and another of dubious value, voxelotor, even though it has been approved by the FDA. Our screen has discovered 106 anti-sickling agents in the ReFrame compound library. We estimate that as many as 21 of these compounds could become oral drugs for treating sickle cell disease because they inhibit at concentrations typical of the free concentrations of oral drugs in human serum.

Conformational dynamics modulating electron transfer

Diffusional dynamics of the donor-acceptor distance are responsible for the appearance of a new time scale of diffusion over the distance of electronic tunneling in electron-transfer reactions. The distance dynamics compete with the medium polarization dynamics in the dynamics-controlled electron-transfer kinetics. The pre-exponential factor of the electron-transfer rate constant switches, at the crossover distance, between a distance-independent, dynamics-controlled plateau and exponential distance decay. The crossover between two regimes is controlled by an effective relaxation time slowed down by a factor exponentially depending on the variance of the donor-acceptor displacement. Flexible donor-acceptor complexes must show a greater tendency for dynamics-controlled electron transfer. Energy chains based on electron transport are best designed by placing the redox cofactors near the crossover distance.

An Outlook on the Complexity of Protein Morphogenesis in Health and Disease

The study of the mechanisms whereby proteins achieve their native functionally competent conformation has been a key issue in molecular biosciences over the last 6 decades. Nevertheless, there are several debated issues and open problems concerning some aspects of this fundamental problem. By considering the emerging complexity of the so-called “native state,” we attempt hereby to propose a personal account on some of the key topics in the field, ranging from the relationships between misfolding and diseases to the significance of protein disorder. Finally, we briefly describe the recent and exciting advances in predicting protein structures from their amino acid sequence.

Heterogeneity in Protein Folding and Unfolding Reactions

Proteins have dynamic structures that undergo chain motions on time scales spanning from picoseconds to seconds. Resolving the resultant conformational heterogeneity is essential for gaining accurate insight into fundamental mechanistic aspects of the protein folding reaction. The use of high-resolution structural probes, sensitive to population distributions, has begun to enable the resolution of site-specific conformational heterogeneity at different stages of the folding reaction. Different states populated during protein folding, including the unfolded state, collapsed intermediate states, and even the native state, are found to possess significant conformational heterogeneity. Heterogeneity in protein folding and unfolding reactions originates from the reduced cooperativity of various kinds of physicochemical interactions between various structural elements of a protein, and between a protein and solvent. Heterogeneity may arise because of functional or evolutionary constraints. Conformational substates within the unfolded state and the collapsed intermediates that exchange at rates slower than the subsequent folding steps give rise to heterogeneity on the protein folding pathways. Multiple folding pathways are likely to represent distinct sequences of structure formation. Insight into the nature of the energy barriers separating different conformational states populated during (un)folding can also be obtained by resolving heterogeneity.

Extraction of kinetics from equilibrium distributions of states using the Metropolis Monte Carlo method

The Metropolis Monte Carlo (MMC) method is used to extract reaction kinetics from a given equilibrium distribution of states of a complex system. The approach is illustrated by the folding/unfolding reaction for two proteins: a model β-hairpin and α-helical protein α_{3}D. For the β-hairpin, the free energy surfaces (FESs) and free energy profiles (FEPs) are employed as the equilibrium distributions of states, playing a role of the potentials of mean force to determine the acceptance probabilities of new states in the MMC simulations. Based on the FESs and PESs for a set of temperatures that were simulated with the molecular dynamics (MD) method, the MMC simulations are performed to extract folding/unfolding rates. It has been found that the rate constants and first-passage time (FPT) distributions obtained in the MMC simulations change with temperature in good agreement with those from the MD simulations. For α_{3}D protein, whose equilibrium folding/unfolding was studied with the single-molecule FRET method [Chung et al., J. Phys. Chem. A 115, 3642 (2011)1089-563910.1021/jp1009669], the FRET-efficiency histograms at different denaturant concentrations were used as the equilibrium distributions of protein states. It has been found that the rate constants for folding and unfolding obtained in the MMC simulations change with denaturant concentration in reasonable agreement with the constants that were extracted from the photon trajectories on the basis of theoretical models. The simulated FPT distributions are single-exponential, which is consistent with the assumption of two-state kinetics that was made in the theoretical models. The promising feature of the present approach is that it is based solely on the equilibrium distributions of states, without introducing any additional parameters to perform simulations, which suggests its applicability to other complex systems.

Conformational exchange of the Zα domain of human RNA editing enzyme ADAR1 studied by NMR spectroscopy

Z-DNA binding proteins (ZBPs) play important roles in RNA editing, innate immune responses, and viral infections. Numerous studies have implicated a role for conformational motions during ZBPs binding upon DNA, but the quantitative intrinsic conformational exchanges of ZBP have not been elucidated. To understand the correlation between the biological function and dynamic feature of the Zα domains of human ADAR1 (hZα_ADAR1), we have performed the ¹⁵N backbone amide Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion experiments on the free hZα_ADAR1 at two different magnetic fields at 35 °C. The robust inter-dependence of parameters in the global fitting process using multi-magnetic field CPMG profiles allows us characterizing the dynamic properties of conformational changes in hZα_ADAR1. This study found that free hZα_ADAR1 exhibited the conformational exchange with a k_ex of 5784 s^-1 between the states "A" (89% population) and "B" (11% population). The different hydrophobic interactions among helices α1, α2, and α3 between these two states might correlate with efficient Z-DNA binding achieved by the hydrogen bonding interactions between its side-chains and the phosphate backbone of Z-DNA.

The A39G FF domain folds on a volcano-shaped free energy surface via separate pathways

Conformational dynamics play critical roles in protein folding, misfolding, function, misfunction, and aggregation. While detecting and studying the different conformational states populated by protein molecules on their free energy surfaces (FESs) remain a challenge, NMR spectroscopy has emerged as an invaluable experimental tool to explore the FES of a protein, as conformational dynamics can be probed at atomic resolution over a wide range of timescales. Here, we use chemical exchange saturation transfer (CEST) to detect "invisible" minor states on the energy landscape of the A39G mutant FF domain that exhibited "two-state" folding kinetics in traditional experiments. Although CEST has mostly been limited to studies of processes with rates between ∼5 to 300 s^-1 involving sparse states with populations as low as ∼1%, we show that the line broadening that is often associated with minor state dips in CEST profiles can be exploited to inform on additional conformers, with lifetimes an order of magnitude shorter and populations close to 10-fold smaller than what typically is characterized. Our analysis of CEST profiles that exploits the minor state linewidths of the 71-residue A39G FF domain establishes a folding mechanism that can be described in terms of a four-state exchange process between interconverting states spanning over two orders of magnitude in timescale from ∼100 to ∼15,000 μs. A similar folding scheme is established for the wild-type domain as well. The study shows that the folding of this small domain proceeds through a pair of sparse, partially structured intermediates via two discrete pathways on a volcano-shaped FES.

Temperature and Guanidine Hydrochloride Effects on the Folding Thermodynamics of WW Domain and Variants

We used simulations based on an all-atom Go model to calculate the folding temperatures (T_fs) and free energies (ΔGs) of two variants of the WW domain, which is a small all-β-sheet protein. The results, without adjusting any parameter, are in good agreement with experiments, thus validating the simulations. We then used the molecular transfer model to predict the changes in the ΔGs and T_fs as the guanidine hydrochloride concentration is varied. The predictions can be readily tested in experiments.