The folding mechanism of BBL: Plasticity of transition-state structure observed within an ultrafast folding protein family

From covalent transition states in chemistry to noncovalent in biology: from β- to Φ-value analysis of protein folding

Solving the mechanism of a chemical reaction requires determining the structures of all the ground states on the pathway and the elusive transition states linking them. 2024 is the centenary of Brønsted's landmark paper that introduced the β-value and structure-activity studies as the only experimental means to infer the structures of transition states. It involves making systematic small changes in the covalent structure of the reactants and analysing changes in activation and equilibrium-free energies. Protein engineering was introduced for an analogous procedure, Φ-value analysis, to analyse the noncovalent interactions in proteins central to biological chemistry. The methodology was developed first by analysing noncovalent interactions in transition states in enzyme catalysis. The mature procedure was then applied to study transition states in the pathway of protein folding - 'part (b) of the protein folding problem'. This review describes the development of Φ-value analysis of transition states and compares and contrasts the interpretation of β- and Φ-values and their limitations. Φ-analysis afforded the first description of transition states in protein folding at the level of individual residues. It revealed the nucleation-condensation folding mechanism of protein domains with the transition state as an expanded, distorted native structure, containing little fully formed secondary structure but many weak tertiary interactions. A spectrum of transition states with various degrees of structural polarisation was then uncovered that spanned from nucleation-condensation to the framework mechanism of fully formed secondary structure. Φ-analysis revealed how movement of the expanded transition state on an energy landscape accommodates the transition from framework to nucleation-condensation mechanisms with a malleability of structure as a unifying feature of folding mechanisms. Such movement follows the rubric of analysis of classical covalent chemical mechanisms that began with Brønsted. Φ-values are used to benchmark computer simulation, and Φ and simulation combine to describe folding pathways at atomic resolution.

Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning

Orbital-free density functional theory (OFDFT) is a quantum chemistry formulation that has a lower cost scaling than the prevailing Kohn-Sham DFT, which is increasingly desired for contemporary molecular research. However, its accuracy is limited by the kinetic energy density functional, which is notoriously hard to approximate for non-periodic molecular systems. Here we propose M-OFDFT, an OFDFT approach capable of solving molecular systems using a deep learning functional model. We build the essential non-locality into the model, which is made affordable by the concise density representation as expansion coefficients under an atomic basis. With techniques to address unconventional learning challenges therein, M-OFDFT achieves a comparable accuracy to Kohn-Sham DFT on a wide range of molecules untouched by OFDFT before. More attractively, M-OFDFT extrapolates well to molecules much larger than those seen in training, which unleashes the appealing scaling of OFDFT for studying large molecules including proteins, representing an advancement of the accuracy-efficiency trade-off frontier in quantum chemistry.

When MELD Meets GaMD: Accelerating Biomolecular Landscape Exploration

We introduce Gaussian accelerated MELD (GaMELD) as a new method for exploring the energy landscape of biomolecules. GaMELD combines the strengths of Gaussian accelerated molecular dynamics (GaMD) and modeling employing limited data (MELD) to navigate complex energy landscapes. MELD uses replica-exchange molecular simulations to integrate limited and uncertain data into simulations via Bayesian inference. MELD has been successfully applied to problems of structure prediction like protein folding and complex structure prediction. However, the computational cost for MELD simulations has limited its broader applicability. The synergy of GaMD and MELD surmounts this limitation efficiently sampling the energy landscape at a lower computational cost (reducing the computational cost by a factor of 2 to six). Effectively, GaMD is used to shift energy distributions along replicas to increase the overlap in energy distributions across replicas, facilitating a random walk in replica space. We tested GaMELD on a benchmark set of 12 small proteins that have been previously studied through MELD and conventional MD. GaMELD consistently achieves accurate predictions with fewer replicas. By increasing the efficacy of replica exchange, GaMELD effectively accelerates convergence in the conformational space, enabling improved sampling across a diverse set of systems.

Mega-scale experimental analysis of protein folding stability in biology and design

Advances in DNA sequencing and machine learning are providing insights into protein sequences and structures on an enormous scale1. However, the energetics driving folding are invisible in these structures and remain largely unknown2. The hidden thermodynamics of folding can drive disease3,4, shape protein evolution5-7 and guide protein engineering8-10, and new approaches are needed to reveal these thermodynamics for every sequence and structure. Here we present cDNA display proteolysis, a method for measuring thermodynamic folding stability for up to 900,000 protein domains in a one-week experiment. From 1.8 million measurements in total, we curated a set of around 776,000 high-quality folding stabilities covering all single amino acid variants and selected double mutants of 331 natural and 148 de novo designed protein domains 40-72 amino acids in length. Using this extensive dataset, we quantified (1) environmental factors influencing amino acid fitness, (2) thermodynamic couplings (including unexpected interactions) between protein sites, and (3) the global divergence between evolutionary amino acid usage and protein folding stability. We also examined how our approach could identify stability determinants in designed proteins and evaluate design methods. The cDNA display proteolysis method is fast, accurate and uniquely scalable, and promises to reveal the quantitative rules for how amino acid sequences encode folding stability.

Selection of representative structures from large biomolecular ensembles

Despite the incredible progress of experimental techniques, protein structure determination still remains a challenging task. Due to the rapid improvements of computer technology, simulations are often used to complement or interpret experimental data, in particular for sparse or low-resolution data. Many such in silico methods allow to obtain highly accurate models of a protein structure either de novo or via refinement of a physical model with experimental restraints. One crucial question is how to select a representative member or ensemble out of vast number of computationally generated structures. Here, we introduce such a method. As a representative task, we add co-evolutionary contact pairs as distance restraints to a physical force field and want to select a good characterization of the resulting native-like ensemble. To generate large ensembles, we run replica-exchange molecular dynamics (REMD) on five mid-sized test proteins and over a wide temperature range. High temperatures allow overcoming energetic barriers while low temperatures perform local searches of native-like conformations. The integrated bias is based on co-evolutionary contact pairs derived from a deep residual neural network to guide the simulation towards native-like conformations. We shortly compare and discuss the achieved model precision of contact-guided REMD for mid-sized proteins. Lastly, we discuss four robust ensemble-selection algorithms in great detail which are capable to extract the representative structure models with a high certainty. To assess the performance of the selection algorithms we exemplarily mimic a "blind scenario', i.e. where the target structure is unknown, and select a representative structural ensemble of native-like folds.

Downhill, Ultrafast and Fast Folding Proteins Revised

Research on the protein folding problem differentiates the protein folding process with respect to the duration of this process. The current structure encoded in sequence dogma seems to be clearly justified, especially in the case of proteins referred to as fast-folding, ultra-fast-folding or downhill. In the present work, an attempt to determine the characteristics of this group of proteins using fuzzy oil drop model is undertaken. According to the fuzzy oil drop model, a protein is a specific micelle composed of bi-polar molecules such as amino acids. Protein folding is regarded as a spherical micelle formation process. The presence of covalent peptide bonds between amino acids eliminates the possibility of free mutual arrangement of neighbors. An example would be the construction of co-micelles composed of more than one type of bipolar molecules. In the case of fast folding proteins, the amino acid sequence represents the optimal bipolarity system to generate a spherical micelle. In order to achieve the native form, it is enough to have an external force field provided by the water environment which directs the folding process towards the generation of a centric hydrophobic core. The influence of the external field can be expressed using the 3D Gaussian function which is a mathematical model of the folding process orientation towards the concentration of hydrophobic residues in the center with polar residues exposed on the surface. The set of proteins under study reveals a hydrophobicity distribution compatible with a 3D Gaussian distribution, taken as representing an idealized micelle-like distribution. The structure of the present hydrophobic core is also discussed in relation to the distribution of hydrophobic residues in a partially unfolded form.

Unfolding Transitions of Peripheral Subunit Binding Domains Show Cooperative Behavior

Characterization of native, intermediate, and denatured states is crucial for understanding the factors influencing the stability of proteins. We have carried out molecular dynamics simulations to study the unfolding of three peripheral subunit binding domains (PSBDs): E. coli BBL, Bacillus stearothermophilus E3BD, and human hbSBD, at three different temperatures: 300, 330, and 400 K, and in the presence of two solvents: water and 5 M guanidinium hydrochloride (GndCl) solution. These proteins share similar folds, with two parallel helices, maintained via a hydrophobic core comprising residues from their interconnecting loop. BBL is more sensitive to thermal and chemical denaturation in comparison to hbSBD, and E3BD is the most stable of all of the three proteins. The effect of temperature on the stability of these proteins is more pronounced in "water-only" simulations compared to that in the presence of guanidium hydrochloride in high concentrations. Our results show cooperative unfolding transitions of these proteins, which are triggered by an initial melting of the C-terminal helix H2. The consequent loss of interhelical interactions or native contacts, as observed, leads to the subsequent melting of the N-terminal helix H1.

PFDB: A standardized protein folding database with temperature correction

We constructed a standardized protein folding kinetics database (PFDB) in which the logarithmic rate constants of all listed proteins are calculated at the standard temperature (25 °C). A temperature correction based on the Eyring–Kramers equation was introduced for proteins whose folding kinetics were originally measured at temperatures other than 25 °C. We verified the temperature correction by comparing the logarithmic rate constants predicted and experimentally observed at 25 °C for 14 different proteins, and the results demonstrated improvement of the quality of the database. PFDB consists of 141 (89 two-state and 52 non-two-state) single-domain globular proteins, which has the largest number among the currently available databases of protein folding kinetics. PFDB is thus intended to be used as a standard for developing and testing future predictive and theoretical studies of protein folding. PFDB can be accessed from the following link: http://lee.kias.re.kr/~bala/PFDB.

pH-Dependent cooperativity and existence of a dry molten globule in the folding of a miniprotein BBL

Solution pH plays an important role in protein dynamics, stability, and folding; however, detailed mechanisms remain poorly understood. Here we use continuous constant pH molecular dynamics in explicit solvent with pH replica exchange to describe the pH profile of the folding cooperativity of a miniprotein BBL, which has drawn intense debate in the past. Our data reconciled the two opposing hypotheses (downhill vs. two-state) and uncovered a sparsely populated unfolding intermediate. As pH is lowered from 7 to 5, the folding barrier vanishes. As pH continues to decrease, the unfolding barrier lowers and denaturation is triggered by the protonation of Asp162, consistent with experimental evidence. Interestingly, unfolding proceeded via an intermediate, with intact secondary structure and a compact, unlocked hydrophobic core shielded from solvent, lending support to the recent hypothesis of a universal dry molten globule in protein folding. Our work demonstrates that constant pH molecular dynamics is a unique tool for testing this and other hypotheses to advance the knowledge in protein dynamics, stability, and folding.

Global analysis of protein folding using massively parallel design, synthesis, and testing

Proteins fold into unique native structures stabilized by thousands of weak interactions that collectively overcome the entropic cost of folding. Although these forces are "encoded" in the thousands of known protein structures, "decoding" them is challenging because of the complexity of natural proteins that have evolved for function, not stability. We combined computational protein design, next-generation gene synthesis, and a high-throughput protease susceptibility assay to measure folding and stability for more than 15,000 de novo designed miniproteins, 1000 natural proteins, 10,000 point mutants, and 30,000 negative control sequences. This analysis identified more than 2500 stable designed proteins in four basic folds-a number sufficient to enable us to systematically examine how sequence determines folding and stability in uncharted protein space. Iteration between design and experiment increased the design success rate from 6% to 47%, produced stable proteins unlike those found in nature for topologies where design was initially unsuccessful, and revealed subtle contributions to stability as designs became increasingly optimized. Our approach achieves the long-standing goal of a tight feedback cycle between computation and experiment and has the potential to transform computational protein design into a data-driven science.

Zinc clasp-based reversible toolset for selective metal-mediated protein heterodimerization

Zinc clasp motif derived from natural Zn(ii)-mediated interaction of CD4 co-receptor and Lck protein tyrosine kinase was used for specific and efficient protein heterodimerization. Optimized set of peptide tags forms highly stable complex in the selective heterodimer framework. Utility of obtained toolset demonstrates high specificity, Zn(ii)-dependent reversibility and remarkable kinetic properties.

β-Structure within the Denatured State of the Helical Protein Domain BBL

Protein denatured states are the origin of both healthy and toxic conformational species. Denatured states of ultrafast folding proteins are of interest in mechanistic studies because they are energetically close to the kinetic bottleneck of folding. However, their transient nature makes them elusive to experiment. Here, we generated the denatured state of the helical domain BBL that is poised to fold in microseconds by a single-point mutation and combined circular dichroism spectroscopy, single-molecule fluorescence fluctuation analysis, and computer simulation to characterize its structure and dynamics. Circular dichroism showed a largely unfolded ensemble with marginal helix but significant β-sheet content. Main-chain structure and dynamics were unaffected by side-chain interactions that stabilize the native state, as revealed by site-directed mutagenesis and nanosecond loop closure kinetics probed by fluorescence correlation spectroscopy. Replica-exchange and constant-temperature molecular dynamics simulations showed a highly collapsed, hydrogen-bonded denatured state containing turn and β-sheet structure and few nucleating helices in an otherwise unfolded ensemble. An irregular β-hairpin element that connects helices in the native fold was poised to be formed. The surprising observation of β-structure in regions that form helices in the native state is reconciled by a generic low-energy pathway from the northwest quadrant of Ramachandran space to the helical basin present under folding conditions, proposed recently. Our results show that, indeed, rapid nucleation of helix emanates from β-structure formed early within a collapsed ensemble of unfolded conformers.

The role of high-dimensional diffusive search, stabilization, and frustration in protein folding

Proteins are polymeric molecules with many degrees of conformational freedom whose internal energetic interactions are typically screened to small distances. Therefore, in the high-dimensional conformation space of a protein, the energy landscape is locally relatively flat, in contrast to low-dimensional representations, where, because of the induced entropic contribution to the full free energy, it appears funnel-like. Proteins explore the conformation space by searching these flat subspaces to find a narrow energetic alley that we call a hypergutter and then explore the next, lower-dimensional, subspace. Such a framework provides an effective representation of the energy landscape and folding kinetics that does justice to the essential characteristic of high-dimensionality of the search-space. It also illuminates the important role of nonnative interactions in defining folding pathways. This principle is here illustrated using a coarse-grained model of a family of three-helix bundle proteins whose conformations, once secondary structure has formed, can be defined by six rotational degrees of freedom. Two folding mechanisms are possible, one of which involves an intermediate. The stabilization of intermediate subspaces (or states in low-dimensional projection) in protein folding can either speed up or slow down the folding rate depending on the amount of native and nonnative contacts made in those subspaces. The folding rate increases due to reduced-dimension pathways arising from the mere presence of intermediate states, but decreases if the contacts in the intermediate are very stable and introduce sizeable topological or energetic frustration that needs to be overcome. Remarkably, the hypergutter framework, although depending on just a few physically meaningful parameters, can reproduce all the types of experimentally observed curvature in chevron plots for realizations of this fold.

Statistical analyses of protein folding rates from the view of quantum transition

Understanding protein folding rate is the primary key to unlock the fundamental physics underlying protein structure and its folding mechanism. Especially, the temperature dependence of the folding rate remains unsolved in the literature. Starting from the assumption that protein folding is an event of quantum transition between molecular conformations, we calculated the folding rate for all two-state proteins in a database and studied their temperature dependencies. The non-Arrhenius temperature relation for 16 proteins, whose experimental data had previously been available, was successfully interpreted by comparing the Arrhenius plot with the first-principle calculation. A statistical formula for the prediction of two-state protein folding rate was proposed based on quantum folding theory. The statistical comparisons of the folding rates for 65 two-state proteins were carried out, and the theoretical vs. experimental correlation coefficient was 0.73. Moreover, the maximum and the minimum folding rates given by the theory were consistent with the experimental results.

AAscan, PCRdesign and MutantChecker: a suite of programs for primer design and sequence analysis for high-throughput scanning mutagenesis

Scanning mutagenesis is a powerful protein engineering technique used to study protein structure-function relationship, map binding sites and design more stable proteins or proteins with altered properties. One of the time-consuming tasks encountered in application of this technique is the design of primers for site-directed mutagenesis. Here we present an open-source multi-platform software AAscan developed to design primers for this task according to a set of empirical rules such as melting temperature, overall length, length of overlap regions, and presence of GC clamps at the 3' end, for any desired substitution. We also describe additional software tools which are used to analyse a large number of sequencing results for the presence of desired mutations, as well as related software to design primers for ligation independent cloning. We have used AAscan software to design primers to make over 700 mutants, with a success rate of over 80%. We hope that the open-source nature of our software and ready availability of freeware tools used for its development will facilitate its adaptation and further development. The software is distributed under GPLv3 licence and is available at http://www.psi.ch/lbr/aascan.

Quantification of Drive-Response Relationships Between Residues During Protein Folding

Mutual correlation and cooperativity are commonly used to describe residue-residue interactions in protein folding/function. However, these metrics do not provide any information on the causality relationships between residues. Such drive-response relationships are poorly studied in protein folding/function and difficult to measure experimentally due to technical limitations. In this study, using the information theory transfer entropy (TE) that provides a direct measurement of causality between two times series, we have quantified the drive-response relationships between residues in the folding/unfolding processes of four small proteins generated by molecular dynamics simulations. Instead of using a time-averaged single TE value, the time-dependent TE is measured with the Q-scores based on residue-residue contacts and with the statistical significance analysis along the folding/unfolding processes. The TE analysis is able to identify the driving and responding residues that are different from the highly correlated residues revealed by the mutual information analysis. In general, the driving residues have more regular secondary structures, are more buried, and show greater effects on the protein stability as well as folding and unfolding rates. In addition, the dominant driving and responding residues from the TE analysis on the whole trajectory agree with those on a single folding event, demonstrating that the drive-response relationships are preserved in the non-equilibrium process. Our study provides detailed insights into the protein folding process and has potential applications in protein engineering and interpretation of time-dependent residue-based experimental observables for protein function.

Take home lessons from studies of related proteins

The 'Fold Approach' involves a detailed analysis of the folding of several topologically, structurally and/or evolutionarily related proteins. Such studies can reveal determinants of the folding mechanism beyond the gross topology, and can dissect the residues required for folding from those required for stability or function. While this approach has not yet matured to the point where we can predict the native conformation of any polypeptide chain in silico, it has been able to highlight, amongst others, the specific residues that are responsible for nucleation, pathway malleability, kinetic intermediates, chain knotting, internal friction and Paracelsus switches. Some of the most interesting discoveries have resulted from the attempt to explain differences between homologues.

The human peripheral subunit-binding domain folds rapidly while overcoming repulsive Coulomb forces

Peripheral subunit binding domains (PSBDs) are integral parts of large multienzyme complexes involved in carbohydrate metabolism. PSBDs facilitate shuttling of prosthetic groups between different catalytic subunits. Their protein surface is characterized by a high density of positive charges required for binding to subunits within the complex. Here, we investigated folding thermodynamics and kinetics of the human PSBD (HSBD) using circular dichroism and tryptophan fluorescence experiments. HSBD was only marginally stable under physiological solvent conditions but folded within microseconds via a barrier-limited apparent two-state transition, analogous to its bacterial homologues. The high positive surface-charge density of HSBD leads to repulsive Coulomb forces that modulate protein stability and folding kinetics, and appear to even induce native-state movement. The electrostatic strain was alleviated at high solution-ionic-strength by Debye-Hückel screening. Differences in ionic-strength dependent characteristics among PSBD homologues could be explained by differences in their surface charge distributions. The findings highlight the trade-off between protein function and stability during protein evolution.

The effect of electrostatics on the marginal cooperativity of an ultrafast folding protein

Proteins fold up by coordinating the different segments of their polypeptide chain through a network of weak cooperative interactions. Such cooperativity results in unfolding curves that are typically sigmoidal. However, we still do not know what factors modulate folding cooperativity or the minimal amount that ensures folding into specific three-dimensional structures. Here, we address these issues on BBL, a small helical protein that folds in microseconds via a marginally cooperative downhill process (Li, P., Oliva, F. Y., Naganathan, A. N., and Muñoz, V. (2009) Proc. Natl. Acad. Sci. USA. 106, 103-108). Particularly, we explore the effects of salt-induced screening of the electrostatic interactions in BBL at neutral pH and in acid-denatured BBL. Our results show that electrostatic screening stabilizes the native state of the neutral and protonated forms, inducing complete refolding of acid-denatured BBL. Furthermore, without net electrostatic interactions, the unfolding process becomes much less cooperative, as judged by the broadness of the equilibrium unfolding curve and the relaxation rate. Our experiments show that the marginally cooperative unfolding of BBL can still be made twice as broad while the protein retains its ability to fold into the native three-dimensional structure in microseconds. This result demonstrates experimentally that efficient folding does not require cooperativity, confirming predictions from theory and computer simulations and challenging the conventional biochemical paradigm. Furthermore, we conclude that electrostatic interactions are an important factor in determining folding cooperativity. Thus, electrostatic modulation by pH-salt and/or mutagenesis of charged residues emerges as an attractive tool for tuning folding cooperativity.

What lessons can be learned from studying the folding of homologous proteins?

The studies of the folding of structurally related proteins have proved to be a very important tool for investigating protein folding. Here we review some of the insights that have been gained from such studies. Our highlighted studies show just how such an investigation should be designed and emphasise the importance of the synergy between experiment and theory. We also stress the importance of choosing the right system carefully, exploiting the excellent structural and sequence databases at our disposal.

Direct observation of ultrafast folding and denatured state dynamics in single protein molecules

Single-molecule fluorescence resonance energy transfer (smFRET) experiments are extremely useful in studying protein folding but are generally limited to time scales of greater than approximately 100 micros and distances greater than approximately 2 nm. We used single-molecule fluorescence quenching by photoinduced electron transfer, detecting short-range events, in combination with fluorescence correlation spectroscopy (PET-FCS) to investigate folding dynamics of the small binding domain BBL with nanosecond time resolution. The kinetics of folding appeared as a 10-micros decay in the autocorrelation function, resulting from stochastic fluctuations between denatured and native conformations of individual molecules. The observed rate constants were probe independent and in excellent agreement with values derived from conventional temperature-jump (T-jump) measurements. A submicrosecond relaxation was detected in PET-FCS data that reported on the kinetics of intrachain contact formation within the thermally denatured state. We engineered a mutant of BBL that was denatured under the reaction conditions that favored folding of the parent wild type ("D(phys)"). D(phys) had the same kinetic signature as the thermally denatured state and revealed segmental diffusion with a time constant of intrachain contact formation of 500 ns. This time constant was more than 10 times faster than folding and in the range estimated to be the "speed limit" of folding. D(phys) exhibited significant deviations from a random coil. The solvent viscosity and temperature dependence of intrachain diffusion showed that chain motions were slaved by the presence of intramolecular interactions. PET-FCS in combination with protein engineering is a powerful approach to study the early events and mechanism of ultrafast protein folding.