Nucleation mechanisms in protein folding

Mechanical Properties of a Solvated Biomolecule: RGD (1FUV) Peptide

The mechanical properties of proteins/peptides play an essential role in their functionalities and implications, as well as their structure and dynamic properties. Understanding mechanical properties is pivotal to our knowledge of protein folding and the molecular basis of diverse cellular processes. Herein, we present a computational approach using ab initio quantum mechanical calculations to determine the mechanical properties-such as bulk modulus, shear modulus, Young's modulus, and Poisson's ratio-of a solvated Arg-Gly-Asp (RGD) peptide model. Since this peptide serves as the RGD-directed integrin recognition site and may participate in cellular adhesion, it is considered a promising small peptide for medicinal applications. This successful approach paves the way for investigating larger and more complex biomolecules.

Simulating Crystallization in a Colloidal System Using State Predictive Information Bottleneck Based Enhanced Sampling

We investigate crystal nucleation in supersaturated colloid suspensions using enhanced molecular dynamics simulations augmented with machine learning techniques. The simulations reveal that crystallization in the model colloidal system studied here, with particles interacting through a repulsive screened Coulomb Yukawa potential, proceeds from vapor to dense liquid droplet to crystalline phases across multiple high barriers. Employing a one-dimensional reaction coordinate derived from the State Predictive Information Bottleneck framework, our simulations capture back-and-forth phase transitions across multiple barriers effectively in biased metadynamics simulations. We obtain relative free energy differences between different phases and also quantify the roles of different molecular level features in driving the phase changes.

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.

Potential Self-Peptide Inhibitors of the SARS-CoV-2 Main Protease

The SARS-CoV-2 main protease (Mpro) plays an essential role in viral replication, cleaving viral polyproteins into functional proteins. This makes Mpro an important drug target. Mpro consists of an N-terminal catalytic domain and a C-terminal α-helical domain (MproC). Previous studies have shown that peptides derived from a given protein sequence (self-peptides) can affect the folding and, in turn, the function of that protein. Since the SARS-CoV-1 MproC is known to stabilize its Mpro and regulate its function, we hypothesized that SARS-CoV-2 MproC-derived self-peptides may modulate the folding and the function of SARS-CoV-2 Mpro. To test this, we studied the folding of MproC in the presence of various self-peptides using coarse-grained structure-based models and molecular dynamics simulations. In these simulations of MproC and one self-peptide, we found that two self-peptides, the α1-helix and the loop between α4 and α5 (loop4), could replace the equivalent native sequences in the MproC structure. Replacement of either sequence in full-length Mpro should, in principle, be able to perturb Mpro function albeit through different mechanisms. Some general principles for the rational design of self-peptide inhibitors emerge: The simulations show that prefolded self-peptides are more likely to replace native sequences than those which do not possess structure. Additionally, the α1-helix self-peptide is kinetically stable and once inserted rarely exchanges with the native α1-helix, while the loop4 self-peptide is easily replaced by the native loop4, making it less useful for modulating function. In summary, a prefolded α1-derived peptide should be able to inhibit SARS-CoV-2 Mpro function.

Refolding in the modern biopharmaceutical industry

Inclusion bodies (IBs) often emerge upon overexpression of recombinant proteins in E. coli. From IBs, refolding is necessary to generate the native protein that can be further purified to obtain pure and active biologicals. This work focusses on refolding as a significant process step during biopharmaceutical manufacturing with an industrial perspective. A theoretical and historical background on protein refolding gives the reader a starting point for further insights into industrial process development. Quality requirements on IBs as starting material for refolding are discussed and further economic and ecological aspects are considered with regards to buffer systems and refolding conditions. A process development roadmap shows the development of a refolding process starting from first exploratory screening rounds to scale-up and implementation in manufacturing plant. Different aspects, with a direct influence on yield, such as the selection of chemicals including pH, ionic strength, additives, etc., and other often neglected aspects, important during scale-up, such as mixing, and gas-fluid interaction, are highlighted with the use of a quality by design (QbD) approach. The benefits of simulation sciences (process simulation and computer fluid dynamics) and process analytical technology (PAT) for seamless process development are emphasized. The work concludes with an outlook on future applications of refolding and highlights open research inquiries.

Bacterial Hsp90 predominantly buffers but does not potentiate the phenotypic effects of deleterious mutations during fluorescent protein evolution

Chaperones facilitate the folding of other ("client") proteins and can thus affect the adaptive evolution of these clients. Specifically, chaperones affect the phenotype of proteins via two opposing mechanisms. On the one hand, they can buffer the effects of mutations in proteins and thus help preserve an ancestral, premutation phenotype. On the other hand, they can potentiate the effects of mutations and thus enhance the phenotypic changes caused by a mutation. We study that how the bacterial Hsp90 chaperone (HtpG) affects the evolution of green fluorescent protein. To this end, we performed directed evolution of green fluorescent protein under low and high cellular concentrations of Hsp90. Specifically, we evolved green fluorescent protein under both stabilizing selection for its ancestral (green) phenotype and directional selection toward a new (cyan) phenotype. While Hsp90 did only affect the rate of adaptive evolution transiently, it did affect the phenotypic effects of mutations that occurred during adaptive evolution. Specifically, Hsp90 allowed strongly deleterious mutations to accumulate in evolving populations by buffering their effects. Our observations show that the role of a chaperone for adaptive evolution depends on the organism and the trait being studied.

PSSNet-An Accurate Super-Secondary Structure for Protein Segmentation

A super-secondary structure (SSS) is a spatially unique ensemble of secondary structural elements that determine the three-dimensional shape of a protein and its function, rendering SSSs attractive as folding cores. Understanding known types of SSSs is important for developing a deeper understanding of the mechanisms of protein folding. Here, we propose a universal PSSNet machine-learning method for SSS recognition and segmentation. For various types of SSS segmentation, this method uses key characteristics of SSS geometry, including the lengths of secondary structural elements and the distances between them, torsion angles, spatial positions of Cα atoms, and primary sequences. Using four types of SSSs (βαβ-unit, α-hairpin, β-hairpin, αα-corner), we showed that extensive SSS sets could be reliably selected from the Protein Data Bank and AlphaFold 2.0 database of protein structures.

Configurational entropy, transition rates, and optimal interactions for rapid folding in coarse-grained model proteins

Under certain conditions, the dynamics of coarse-grained models of solvated proteins can be described using a Markov state model, which tracks the evolution of populations of configurations. The transition rates among states that appear in the Markov model can be determined by computing the relative entropy of states and their mean first passage times. In this paper, we present an adaptive method to evaluate the configurational entropy and the mean first passage times for linear chain models with discontinuous potentials. The approach is based on event-driven dynamical sampling in a massively parallel architecture. Using the fact that the transition rate matrix can be calculated for any choice of interaction energies at any temperature, it is demonstrated how each state's energy can be chosen such that the average time to transition between any two states is minimized. The methods are used to analyze the optimization of the folding process of two protein systems: the crambin protein and a model with frustration and misfolding. It is shown that the folding pathways for both systems are comprised of two regimes: first, the rapid establishment of local bonds, followed by the subsequent formation of more distant contacts. The state energies that lead to the most rapid folding encourage multiple pathways, and they either penalize folding pathways through kinetic traps by raising the energies of trapping states or establish an escape route from the trapping states by lowering free energy barriers to other states that rapidly reach the native state.

AlphaFold, Artificial Intelligence (AI), and Allostery

AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of biological sequence data and artificial intelligence (AI). AlphaFold has appended projects and research directions. The database it has been creating promises an untold number of applications with vast potential impacts that are still difficult to surmise. AI approaches can revolutionize personalized treatments and usher in better-informed clinical trials. They promise to make giant leaps toward reshaping and revamping drug discovery strategies, selecting and prioritizing combinations of drug targets. Here, we briefly overview AI in structural biology, including in molecular dynamics simulations and prediction of microbiota-human protein-protein interactions. We highlight the advancements accomplished by the deep-learning-powered AlphaFold in protein structure prediction and their powerful impact on the life sciences. At the same time, AlphaFold does not resolve the decades-long protein folding challenge, nor does it identify the folding pathways. The models that AlphaFold provides do not capture conformational mechanisms like frustration and allostery, which are rooted in ensembles, and controlled by their dynamic distributions. Allostery and signaling are properties of populations. AlphaFold also does not generate ensembles of intrinsically disordered proteins and regions, instead describing them by their low structural probabilities. Since AlphaFold generates single ranked structures, rather than conformational ensembles, it cannot elucidate the mechanisms of allosteric activating driver hotspot mutations nor of allosteric drug resistance. However, by capturing key features, deep learning techniques can use the single predicted conformation as the basis for generating a diverse ensemble.

Interdiction in the Early Folding of the p53 DNA-Binding Domain Leads to Its Amyloid-Like Misfolding

In this article, we investigate two issues: (a) the initial contact formation events along the folding pathway of the DNA-binding domain of the tumor suppressor protein p53 (core p53); and (b) the intermolecular events leading to its conversion into a prion-like form upon incubation with peptide P8(250-257). In the case of (a), the calculations employ the sequential collapse model (SCM) to identify the segments involved in the initial contact formation events that nucleate the folding pathway. The model predicts that there are several possible initial non-local contacts of comparative stability. The most stable of these possible initial contacts involve the protein segments 159AMAIY163 and 251ILTII255, and it is the only native-like contact. Thus, it is predicted to constitute “Nature’s shortcut” to the native structure of the core domain of p53. In the case of issue (b), these findings are then combined with experimental evidence showing that the incubation of the core domain of p53 with peptide P8(250-257), which is equivalent to the native protein segment 250PILTIITL257, leads to an amyloid conformational transition. It is explained how the SCM predicts that P8(250-257) effectively interdicts in the formation of the most stable possible initial contact and, thereby, disrupts the subsequent normal folding. Interdiction by polymeric P8(250-257) seeds is also studied. It is then hypothesized that enhanced folding through one or several of the less stable contacts could play a role in P8(250-257)-promoted core p53 amyloid misfolding. These findings are compared to previous results obtained for the prion protein. Experiments are proposed to test the hypothesis presented regarding core p53 amyloid misfolding.

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.

GroEL/S overexpression helps to purge deleterious mutations and reduce genetic diversity during adaptive protein evolution

Chaperones are proteins that help other proteins fold. They also affect the adaptive evolution of their client proteins by buffering the effect of deleterious mutations and increasing the genetic diversity of evolving proteins. We study how the bacterial chaperone GroE (GroEL + GroES) affects the evolution of green fluorescent protein (GFP). To this end we subjected GFP to multiple rounds of mutation and selection for its color phenotype in four replicate E. coli populations, and studied its evolutionary dynamics through high-throughput sequencing and mutant engineering. We evolved GFP both under stabilizing selection for its ancestral (green) phenotype, and to directional selection for a new (cyan) phenotype. We did so both under low and high expression of the chaperone GroE. In contrast to previous work, we observe that GroE does not just buffer but also helps purge deleterious (fluorescence reducing) mutations from evolving populations. In doing so, GroE helps reduce the genetic diversity of evolving populations. In addition, it causes phenotypic heterogeneity in mutants with the same genotype, helping to enhance their fluorescence in some cells, and reducing it in others. Our observations show that chaperones can affect adaptive evolution in more than one way.

Slowest-first protein translation scheme: Structural asymmetry and co-translational folding

Proteins are translated from the N to the C terminus, raising the basic question of how this innate directionality affects their evolution. To explore this question, we analyze 16,200 structures from the Protein Data Bank (PDB). We find remarkable enrichment of α helices at the C terminus and β strands at the N terminus. Furthermore, this α-β asymmetry correlates with sequence length and contact order, both determinants of folding rate, hinting at possible links to co-translational folding (CTF). Hence, we propose the "slowest-first" scheme, whereby protein sequences evolved structural asymmetry to accelerate CTF: the slowest of the cooperatively folding segments are positioned near the N terminus so they have more time to fold during translation. A phenomenological model predicts that CTF can be accelerated by asymmetry in folding rate, up to double the rate, when folding time is commensurate with translation time; analysis of the PDB predicts that structural asymmetry is indeed maximal in this regime. This correspondence is greater in prokaryotes, which generally require faster protein production. Altogether, this indicates that accelerating CTF is a substantial evolutionary force whose interplay with stability and functionality is encoded in secondary structure asymmetry.

Structural characterization of the thermal unfolding pathway of human VEGFR1 D2 domain

Folding stability is a crucial feature of protein evolution and is essential for protein functions. Thus, the comprehension of protein folding mechanisms represents an important complement to protein structure and function, crucial to determine the structural basis of protein misfolding. In this context, thermal unfolding studies represent a useful tool to get a molecular description of the conformational transitions governing the folding/unfolding equilibrium of a given protein. Here, we report the thermal folding/unfolding pathway of VEGFR1D2, a member of the immunoglobulin superfamily by means of a high-resolution thermodynamic approach that combines differential scanning calorimetry with atomic-level unfolding monitored by NMR. We show how VEGFR1D2 folding is driven by an oxidatively induced disulfide pairing: the key event in the achievement of its functional structure is the formation of a small hydrophobic core that surrounds a disulfide bridge. Such a 'folding nucleus' induces the cooperative transition to the properly folded conformation supporting the hypothesis that a disulfide bond can act as a folding nucleus that eases the folding process.

Hydrogen Bonding Sequence Directed Coil-Globule Transition in Water Soluble Thermoresponsive Polymers

The origin of the coil-globule transition for water-soluble thermoresponsive polymers frequently used in nanomaterials remains elusive. Using polypropylene oxide as an example we demonstrate by means of atomistic molecular dynamics simulations that temperature-induced increase in the sequence length of monomers that are not hydrogen bonded to water drives the coil-globule transition. Longer chains statistically exhibit longer sequences which serve as nucleation sites for hydrophobic cluster formation, facilitating chain collapse at lower temperature in agreement with experimental data.

Cation folding and the thermal stability limit of the ionic liquid [BMIM+][BF4 -] under total vacuum

Molecular dynamics simulations reveal the behavior of the bimodal distribution of cation conformations (folded/unfolded) in ionic liquids based on alkylated imidazoles, such as [BMIM+][BF4 -]. The alkyl chains of the cations can fold and block interactions between the cations and anions, thereby reducing the cohesivity of the liquid. At room temperature, the folded conformations represent less than one-third of the total conformations. In contrast to the behavior observed during the thermal denaturation of proteins, in ionic liquids, the concentration of folded cations grows when the temperature increases. At the equimolar concentration, the system reaches the reported experimental temperature of thermal stability (similar to the thermal denaturation behavior). There is an outermost layer of cations at the interface that can tilt toward the interface and cover a layer of anions adsorbed at the interface. This interfacial conformation makes the system stable in transverse directions and unstable in the normal direction at temperatures in the region of thermal instability, limiting the rate of vaporization of neutral ion pairs, which are observed as rare events at temperatures as low as 773.15 K.

Regulating DNA Self-Assembly Dynamics with Controlled Nucleation

Controlling the nucleation step of a self-assembly system is essential for engineering structural complexity and dynamic behaviors. Here, we design a "frame-filling" model system that comprises one type of self-complementary DNA tile and a hosting DNA origami frame to investigate the inherent dynamics of three general nucleation modes in nucleated self-assembly: unseeded, facet, and seeded nucleation. Guided by kinetic simulation, which suggested an optimal temperature range to differentiate the individual nucleation modes, and complemented by single-molecule observations, the transition of tiles from a metastable, monomeric state to a stable, polymerized state through the three nucleation pathways was monitored by Mg²⁺-triggered kinetic measurements. The temperature-dependent kinetics for all three nucleation modes were correlated by a "nucleation-growth" model, which quantified the tendency of nucleation using an empirical nucleation number. Moreover, taking advantage of the temperature dependence of nucleation, tile assembly can be regulated externally by the hosting frame. An ultraviolet (UV)-responsive trigger was integrated into the frame to simultaneously control "when" and "where" nucleation started. Our results reveal the dynamic mechanisms of the distinct nucleation modes in DNA tile-based self-assembly and provide a general strategy for controlling the self-assembly process.

The concept of protein folding/unfolding and its impacts on human health

Proteins have evolved in specific 3D structures and play different functions in cells and determine various reactions and pathways. The newly synthesized amino acid chains once depart ribosome must crumple into three-dimensional structures so can be biologically active. This process of protein that makes a functional molecule is called protein folding. The protein folding is both a biological and a physicochemical process that depends on the sequence of it. In fact, this process occurs more complicated and in some cases and in exposure to some molecules like glucose (glycation), mistaken folding leads to amyloid structures and fatal disorders called conformational diseases. Such conditions are detected by the quality control system of the cell and these abnormal proteins undergo renovation or degradation. This scenario takes place by the chaperones, chaperonins, and Ubiquitin-proteasome complex. Understanding of protein folding mechanisms from different views including experimental and computational approaches has revealed some intermediate ensembles such as molten globule and has been subjected to biophysical and molecular biology attempts to know more about prevalent conformational diseases.

Investigating the folding mechanism of the N-terminal domain of ribosomal protein L9

Protein folding is a popular topic in the life science. However, due to the limited sampling ability of experiments and simulations, the general folding mechanism is not yet clear to us. In this work, we study the folding of the N-terminal domain of ribosomal protein L9 (NTL9) in detail by a mixing replica exchange molecular dynamics method. The simulation results are close to previous experimental observations. According to the Markov state model, the folding of the protein follows a nucleation-condensation path. Moreover, after the comparison to its 39-residue β-α-β motif, we find that the helix at the C-terminal has a great influence on the folding process of the intact protein, including the nucleation of the key residues in the transition state ensemble and the packing of the hydrophobic residues in the native state.

Helix-Coil Transition at a Glycine Following a Nascent α-Helix: A Synergetic Guidance Mechanism for Helix Growth

A detailed understanding of forces guiding the rapid folding of a polypeptide from an apparently random coil state to an ordered α-helical structure following the rate-limiting preorganization of the initial three residue backbones into helical conformation is imperative to comprehending and regulating protein folding and for the rational design of biological mimetics. However, several details of this process are still unknown. First, although the helix-coil transition was proposed to originate at the residue level (J. Chem. Phys. 1959, 31, 526-535; J. Chem. Phys. 1961, 34, 1963-1974), all helix-folding studies have only established it between time-averaged bulk states of a long-lived helix and several transiently populated random coils, along the whole helix model sequence. Second, the predominant thermodynamic forces driving either this two-state transition or the faster helix growth following helix nucleation are still unclear. Third, the conformational space of the random coil state is not well-defined unlike its corresponding α-helix. Here we investigate the restrictions placed on the conformational space of a Gly residue backbone, as a result of it immediately succeeding a nascent α-helical turn. Analyses of the temperature-dependent 1D-, 2D-NMR, FT-IR, and CD spectra and GROMACS MD simulation trajectory of a Gly residue backbone following a model α-helical turn, which is artificially rigidified by a covalent hydrogen bond surrogate, reveal that: (i) the α-helical turn guides the ϕ torsion of the Gly exclusively into either a predominantly populated entropically favored α-helical (α-ϕ) state or a scarcely populated random coil (RC-ϕ) state; (ii) the α-ϕ state of Gly in turn favors the stability of the preceding α-helical turn, while the RC-ϕ state disrupts it, revealing an entropy-driven synergetic guidance for helix growth in the residue following helix nucleation. The applicability of a current synergetic guidance mechanism to explain rapid helix growth in folded and unfolded states of proteins and helical peptides is discussed.

Exploring the role of hydrophilic amino acids in unfolding of protein in aqueous ethanol solution

Hydrophobic association is the key contributor behind the formation of well packed core of a protein which is often believed to be an important step for folding from an unfolded chain to its compact functional form. While most of the protein folding/unfolding studies have evaluated the changes in the hydrophobic interactions during chemical denaturation, the role of hydrophilic amino acids in such processes are not discussed in detail. Here we report the role of the hydrophilic amino acids behind ethanol induced unfolding of protein. Using free energy simulations, we show that chicken villin head piece (HP-36) protein unfolds gradually in presence of water-ethanol binary mixture with increasing composition of ethanol. However, upon mutation of hydrophilic amino acids by glycine while keeping the hydrophobic amino acids intact, the compact state of the protein is found to be stable at all compositions with gradual flattening of the free energy landscape upon increasing compositions. The local environment around the protein in terms of ethanol/water number significantly differs in wild type protein compared to the mutated protein. The calculated Wyman-Tanford preferential binding coefficient of ethanol for wild type protein reveals that a greater number of cosolutes (here ethanol) bind to the unfolded state compared to its folded state. However, no significant increase in binding coefficient of ethanol at the unfolded state is found for mutated protein. Local-bulk partition coefficient calculation also suggests similar scenarios. Our results reveal that the weakening of hydrophobic interactions in aqueous ethanol solution along with larger preferential binding of ethanol to the unfolded state mediated by hydrophilic amino acids combinedly helps unfolding of protein in aqueous ethanol solution.

Oligomerization of a symmetric β-trefoil protein in response to folding nucleus perturbation

Gene duplication and fusion events in protein evolution are postulated to be responsible for the common protein folds exhibiting internal rotational symmetry. Such evolutionary processes can also potentially yield regions of repetitive primary structure. Repetitive primary structure offers the potential for alternative definitions of critical regions, such as the folding nucleus (FN). In principle, more than one instance of the FN potentially enables an alternative folding pathway in the face of a subsequent deleterious mutation. We describe the targeted mutation of the carboxyl-terminal region of the (internally located) FN of the de novo designed purely-symmetric β-trefoil protein Symfoil-4P. This mutation involves wholesale replacement of a repeating trefoil-fold motif with a "blade" motif from a β-propeller protein, and postulated to trap that region of the Symfoil-4P FN in a nonproductive folding intermediate. The resulting protein (termed "Bladefoil") is shown to be cooperatively folding, but as a trimeric oligomer. The results illustrate how symmetric protein architectures have potentially diverse folding alternatives available to them, including oligomerization, when preferred pathways are perturbed.

A look back at the molten globule state of proteins: thermodynamic aspects

Interest in protein folding intermediates lies in their significance to protein folding pathways. The molten globule (MG) state is one such intermediate lying on the kinetic (and sometimes thermodynamic) pathway between native and unfolded states. Development of our qualitative and quantitative understanding of the MG state can provide deeper insight into the folding pathways and hence potentially facilitate solution of the protein folding problem. An extensive look at literature suggests that most studies into protein MG states have been largely qualitative. Attempts to obtain quantitative insights into MG states have involved application of high-sensitivity calorimetry (differential scanning calorimetry and isothermal titration calorimetry). This review addresses the progress made in this direction by discussing the knowledge gained to date, along with the future promise of calorimetry, in providing quantitative information on the structural features of MG states. Particular attention is paid to the question of whether such states share common structural features or not. The difference in the nature of the transition from the MG state to the unfolded state, in terms of cooperativity, has also been addressed and discussed.

Nature's Shortcut to Protein Folding

This Feature Article presents a view of the protein folding transition based on the hypothesis that Nature has built features within the sequences that enable a Shortcut to efficient folding. Nature's Shortcut is proposed to be the early establishment of a set of nonlocal weak contacts, constituting protein loops that significantly constrain regions of the collapsed disordered protein into a native-like low-resolution fluctuating topology of major sections of the backbone. Nature's establishment of this scaffold of nonlocal contacts is claimed to bypass what would otherwise be a nearly hopeless unaided search for the final three-dimensional structure in proteins longer than ∼100 amino acids. To support this main contention of the Feature Article, the loop hypothesis (LH) description of early folding events is experimentally tested with time-resolved Förster resonance energy transfer techniques for adenylate kinase, and the data are shown to be consistent with theoretical predictions from the sequential collapse model (SCM). The experimentally based LH and the theoretically founded SCM are argued to provide a unified picture of the role of nonlocal contacts as constituting Nature's Shortcut to protein folding. Importantly, the SCM is shown to reliably predict key nonlocal contacts utilizing only primary sequence information. This view on Nature's Shortcut is open to the protein community for further detailed assessment, including its practical consequences, by suitable application of advanced experimental and computational techniques.

Autonomous Sequences in Myoglobin Emerging from X-ray Structure of Holomyoglobin

The proposed continuous folding structure units are fundamental to analyze protein structure. Here, we could elucidate for the first time two types of hydrophobic core networks in apomyoglobin using continuous folding structure units. In myoglobin, two autonomous sequences emerged clearly. We could thus characterize the autonomous sequences using well-defined hydrophobic core networks within respective semifolds. A hydrophobic core is defined as a pair of topology-local hydrophobic amino acids in different folding structures. Hydrophobic core formation is indispensable to stabilize the different folding structures via an efficient hydrophobic interaction. Autonomous sequences in myoglobin encode tertiary structure information for semifolds. These sequences fold autonomously into small sets of continuous folding structure units to grow separate semifolds on each separate framework. The autonomous sequence can be defined as the local sequence assigned to the small set of continuous folding structure units. They create the discrete hydrophobic region in a semifold by assembly of their hydrophobic regions. Semifolds were characterized by discrete hydrophobic regions stabilized by respective type I hydrophobic core networks, which were present within each semifold. The discrete hydrophobic region of a semifold propagated itself with that of a different semifold by hydrophobic interactions in type II hydrophobic core network, which was present between different semifolds, as observed by the X-ray structures of semifolds. The most significant feature of semifolds in apomyoglobin was that they could be verified by the X-ray structure of holomyoglobin regardless of the instability of folds characteristic to autonomous sequence fragments. This work presents the first description of autonomous sequences.

Nonnative contact effects in protein folding

The folding simulations of three ββα-motifs and β-barrel structured proteins (NTL9, NuG2b, and CspA) were performed to determine the important roles of native and nonnative contacts in protein folding.

Complex Folding Landscape of Apomyoglobin at Acidic pH Revealed by Ultrafast Kinetic Analysis of Core Mutants

Under mildly acidic conditions (pH 4-4.5) apomyoglobin (apoMb) adopts a partially structured equilibrium state ( M-state) that structurally resembles a kinetic intermediate encountered at a late stage of folding to the native structure at neutral pH. We have previously reported that the M-state is formed rapidly (<1 ms) via a multistate process and thus offers a unique opportunity for exploring early stages of folding by both experimental and computational techniques. In order to gain structural insight into intermediates and barriers at the residue level, we studied the folding/unfolding kinetics of 12 apoMb mutants at pH 4.2 using fluorescence-detected ultrafast mixing techniques. Global analysis of the submillisecond folding/unfolding kinetics vs urea concentration for each variant, based on a sequential four-state mechanism ( U ⇔ I ⇔ L ⇔ M), allowed us to determine elementary rate constants and their dependence on urea concentration for most transitions. Comparison of the free energy diagrams constructed from the kinetic data of the mutants with that of wild-type apoMb yielded quantitative information on the effects of mutations on the free energy (ΔΔ G) of both intermediates and the first two kinetic barriers encountered during folding. Truncation of conserved aliphatic side chains on helices A, G, and H gives rise to a stepwise increase in ΔΔ G as the protein advances from U toward M, consistent with progressive stabilization of native-like contacts within the primary core of apoMb. Helix-helix contacts in the primary core contribute little to the first folding barrier ( U ⇔ I) and thus are not required for folding initiation but are critical for the stability of the late intermediate, L, and the M-state. Alanine substitution of hydrophobic residues at more peripheral helix-helix contact sites of the native structure, which are still absent or unstable in the M-state, shows both positive (destabilizing) and negative (stabilizing) ΔΔ G, indicating that non-native contacts are formed initially and weakened or lost as a result of subsequent structural rearrangement steps.

External release of entropy by synchronized movements of local secondary structures drives folding of a small, disulfide-bonded protein

A crucial mechanism to the formation of native, fully functional, 3D structures from local secondary structures is unraveled in this study. Through the introduction of various amino acid substitutions at four canonical β-turns in a three-fingered protein, Toxin α from Naja nigricollis, we found that the release of internal entropy to the external environment through the globally synchronized movements of local substructures plays a crucial role. Throughout the folding process, the folding species were saturated with internal entropy so that intermediates accumulated at the equilibrium state. Their relief from the equilibrium state was accomplished by the formation of a critical disulfide bridge, which could guide the synchronized movement of one of the peripheral secondary structure. This secondary structure collided with a core central structure, which flanked another peripheral secondary structure. This collision displaced the internal thermal fluctuations from the first peripheral structure to the second peripheral structure, where the displaced thermal fluctuations were ultimately released as entropy. Two protein folding processes that acted in succession were identified as the means to establish the flow of thermal fluctuations. The first process was the time-consuming assembly process, where stochastic combinations of colliding, native-like, secondary structures provided candidate structures for the folded protein. The second process was the activation process to establish the global mutual relationships of the native protein in the selected candidate. This activation process was initiated and propagated by a positive feedback process between efficient entropy release and well-packed local structures, which moved in synchronization. The molecular mechanism suggested by this experiment was assessed with a well-defined 3D structure of erabutoxin b because one of the turns that played a critical role in folding was shared with erabutoxin b.

Roles of conformational disorder and downhill folding in modulating protein-DNA recognition

Transcription factors are thought to efficiently search for their target DNA site via a combination of conventional 3D diffusion and 1D diffusion along the DNA molecule mediated by non-specific electrostatic interactions. This process requires the DNA-binding protein to quickly exchange between a search competent and a target recognition mode, but little is known as to how these two binding modes are encoded in the conformational properties of the protein. Here, we investigate this issue on the engrailed homeodomain (EngHD), a DNA-binding domain that folds ultrafast and exhibits a complex conformational behavior consistent with the downhill folding scenario. We explore the interplay between folding and DNA recognition using a coarse-grained computational model that allows us to manipulate the folding properties of the protein and monitor its non-specific and specific binding to DNA. We find that conformational disorder increases the search efficiency of EngHD by promoting a fast gliding search mode in addition to sliding. When gliding, EngHD remains loosely bound to DNA moving linearly along its length. A partially disordered EngHD also binds more dynamically to the target site, reducing the half-life of the specific complex via a spring-loaded mechanism. These findings apply to all conditions leading to partial disorder. However, we also find that at physiologically relevant temperatures EngHD is well folded and can only obtain the conformational flexibility required to accelerate 1D diffusion when it folds/unfolds within the downhill scenario (crossing a marginal free energy barrier). In addition, the conformational flexibility of native downhill EngHD enables its fast reconfiguration to lock into the specific binding site upon arrival, thereby affording finer control of the on- and off-rates of the specific complex. Our results provide key mechanistic insights into how DNA-binding domains optimize specific DNA recognition through the control of their conformational dynamics and folding mechanism.

Finding the needle in the haystack: towards solving the protein-folding problem computationally

Prediction of protein tertiary structures from amino acid sequence and understanding the mechanisms of how proteins fold, collectively known as "the protein folding problem," has been a grand challenge in molecular biology for over half a century. Theories have been developed that provide us with an unprecedented understanding of protein folding mechanisms. However, computational simulation of protein folding is still difficult, and prediction of protein tertiary structure from amino acid sequence is an unsolved problem. Progress toward a satisfying solution has been slow due to challenges in sampling the vast conformational space and deriving sufficiently accurate energy functions. Nevertheless, several techniques and algorithms have been adopted to overcome these challenges, and the last two decades have seen exciting advances in enhanced sampling algorithms, computational power and tertiary structure prediction methodologies. This review aims at summarizing these computational techniques, specifically conformational sampling algorithms and energy approximations that have been frequently used to study protein-folding mechanisms or to de novo predict protein tertiary structures. We hope that this review can serve as an overview on how the protein-folding problem can be studied computationally and, in cases where experimental approaches are prohibitive, help the researcher choose the most relevant computational approach for the problem at hand. We conclude with a summary of current challenges faced and an outlook on potential future directions.

Exploration of ligand-induced protein conformational alteration, aggregate formation, and its inhibition: A biophysical insight

The association of protein aggregates with plentiful human diseases has fascinated studies regarding the biophysical characterization of protein misfolding and ultimately their aggregate formation mechanism. Protein-ligand interaction, their mechanism, conformational changes by ligands, and protein aggregate formation have been studied upon exploiting experimental techniques and computational methodologies. Such studies for the exploration of ligand-induced conformational changes in protein, misfolding and aggregation, has confirmed drastic progresses in the study of aggregate formation pathways. This review comprises of an inclusive description of contemporary experimental techniques as well as theoretical improvements in the interpretation of the conformational properties of protein. We have also discussed various factors responsible for the microenvironment change around protein that sequentially causes amyloidoses. Biophysical techniques and cell-based assays to gain comprehensive understandings of protein-ligand interaction, protein folding, and aggregation pathways have also been described. The promising therapeutic methods used to inhibit the protein fibrillogenesis have also been discussed.

Unified understanding of folding and binding mechanisms of globular and intrinsically disordered proteins

Extensive experimental and theoretical studies have advanced our understanding of the mechanisms of folding and binding of globular proteins, and coupled folding and binding of intrinsically disordered proteins (IDPs). The forces responsible for conformational changes and binding are common in both proteins; however, these mechanisms have been separately discussed. Here, we attempt to integrate the mechanisms of coupled folding and binding of IDPs, folding of small and multi-subdomain proteins, folding of multimeric proteins, and ligand binding of globular proteins in terms of conformational selection and induced-fit mechanisms as well as the nucleation–condensation mechanism that is intermediate between them. Accumulating evidence has shown that both the rate of conformational change and apparent rate of binding between interacting elements can determine reaction mechanisms. Coupled folding and binding of IDPs occurs mainly by induced-fit because of the slow folding in the free form, while ligand binding of globular proteins occurs mainly by conformational selection because of rapid conformational change. Protein folding can be regarded as the binding of intramolecular segments accompanied by secondary structure formation. Multi-subdomain proteins fold mainly by the induced-fit (hydrophobic collapse) mechanism, as the connection of interacting segments enhances the binding (compaction) rate. Fewer hydrophobic residues in small proteins reduce the intramolecular binding rate, resulting in the nucleation–condensation mechanism. Thus, the folding and binding of globular proteins and IDPs obey the same general principle, suggesting that the coarse-grained, statistical mechanical model of protein folding is promising for a unified theoretical description of all mechanisms.

Quantifying Nonnative Interactions in the Protein-Folding Free-Energy Landscape

Protein folding is a central problem in biological physics. Energetic roughness is an important aspect that controls protein-folding stability and kinetics. The roughness is associated with conflicting interactions in the protein and is also known as frustration. Recent studies indicate that an addition of a small amount of energetic frustration may enhance folding speed for certain proteins. In this study, we have investigated the conditions under which frustration increases the folding rate. We used a Cα structure-based model to simulate a group of proteins. We found that the free-energy barrier at the transition state (ΔF) correlates with nonnative-contact variation (ΔA), and the simulated proteins are clustered according to their fold motifs. These findings are corroborated by the Clementi-Plotkin analytical model. As a consequence, the optimum frustration regime for protein folding can be predicted analytically.

An ambiguity principle for assigning protein structural domains

Ambiguity is the quality of being open to several interpretations. For an image, it arises when the contained elements can be delimited in two or more distinct ways, which may cause confusion. We postulate that it also applies to the analysis of protein three-dimensional structure, which consists in dividing the molecule into subunits called domains. Because different definitions of what constitutes a domain can be used to partition a given structure, the same protein may have different but equally valid domain annotations. However, knowledge and experience generally displace our ability to accept more than one way to decompose the structure of an object-in this case, a protein. This human bias in structure analysis is particularly harmful because it leads to ignoring potential avenues of research. We present an automated method capable of producing multiple alternative decompositions of protein structure (web server and source code available at www.dsimb.inserm.fr/sword/). Our innovative algorithm assigns structural domains through the hierarchical merging of protein units, which are evolutionarily preserved substructures that describe protein architecture at an intermediate level, between domain and secondary structure. To validate the use of these protein units for decomposing protein structures into domains, we set up an extensive benchmark made of expert annotations of structural domains and including state-of-the-art domain parsing algorithms. The relevance of our "multipartitioning" approach is shown through numerous examples of applications covering protein function, evolution, folding, and structure prediction. Finally, we introduce a measure for the structural ambiguity of protein molecules.

Protein Folding Structures: Formation of Folding Structures Based on Probability Theory

To the best of our knowledge, this is the first study that shows that the X-ray structures of proteins can be dissected into their continuous folding structure units. Each folding structure unit was designed such that both the terminal di- or tri-peptide sequences shared common sequences with the two adjacent folding structure units. To encode the folding structure information of proteins into their amino acid sequences, we proposed 44 kinds of folding elements, which covered all of the amino acids in the protein chains, and defined all folding structure units. The folding element was defined to mean a minimum structural piece, which covered the frame of the main chain of each amino acid in a protein chain. A folding structure unit of a local sequence could be fully characterized by the sequential combination of individual folding elements assigned to each amino acid. The folding structure information showed amino acid preferences in various positions in folding structure units. Folding structure formation proceeded on the basis of probability theory. Strikingly, relative formation ability analysis clearly indicated that we can decode the types and the chain length of folding structure units from the amino acid sequence of a protein.

Characterization of protein folding by a Φ-value calculation with a statistical-mechanical model

The Φ-value analysis approach provides information about transition-state structures along the folding pathway of a protein by measuring the effects of an amino acid mutation on folding kinetics. Here we compared the theoretically calculated Φ values of 27 proteins with their experimentally observed Φ values; the theoretical values were calculated using a simple statistical-mechanical model of protein folding. The theoretically calculated Φ values reflected the corresponding experimentally observed Φ values with reasonable accuracy for many of the proteins, but not for all. The correlation between the theoretically calculated and experimentally observed Φ values strongly depends on whether the protein-folding mechanism assumed in the model holds true in real proteins. In other words, the correlation coefficient can be expected to illuminate the folding mechanisms of proteins, providing the answer to the question of which model more accurately describes protein folding: the framework model or the nucleation-condensation model. In addition, we tried to characterize protein folding with respect to various properties of each protein apart from the size and fold class, such as the free-energy profile, contact-order profile, and sensitivity to the parameters used in the Φ-value calculation. The results showed that any one of these properties alone was not enough to explain protein folding, although each one played a significant role in it. We have confirmed the importance of characterizing protein folding from various perspectives. Our findings have also highlighted that protein folding is highly variable and unique across different proteins, and this should be considered while pursuing a unified theory of protein folding.

How cooperative are protein folding and unfolding transitions?

A thermodynamically and kinetically simple picture of protein folding envisages only two states, native (N) and unfolded (U), separated by a single activation free energy barrier, and interconverting by cooperative two-state transitions. The folding/unfolding transitions of many proteins occur, however, in multiple discrete steps associated with the formation of intermediates, which is indicative of reduced cooperativity. Furthermore, much advancement in experimental and computational approaches has demonstrated entirely non-cooperative (gradual) transitions via a continuum of states and a multitude of small energetic barriers between the N and U states of some proteins. These findings have been instrumental towards providing a structural rationale for cooperative versus noncooperative transitions, based on the coupling between interaction networks in proteins. The cooperativity inherent in a folding/unfolding reaction appears to be context dependent, and can be tuned via experimental conditions which change the stabilities of N and U. The evolution of cooperativity in protein folding transitions is linked closely to the evolution of function as well as the aggregation propensity of the protein. A large activation energy barrier in a fully cooperative transition can provide the kinetic control required to prevent the accumulation of partially unfolded forms, which may promote aggregation. Nevertheless, increasing evidence for barrier-less "downhill" folding, as well as for continuous "uphill" unfolding transitions, indicate that gradual non-cooperative processes may be ubiquitous features on the free energy landscape of protein folding.

Fold and flexibility: what can proteins' mechanical properties tell us about their folding nucleus?

The determination of a protein's folding nucleus, i.e. a set of native contacts playing an important role during its folding process, remains an elusive yet essential problem in biochemistry. In this work, we investigate the mechanical properties of 70 protein structures belonging to 14 protein families presenting various folds using coarse-grain Brownian dynamics simulations. The resulting rigidity profiles combined with multiple sequence alignments show that a limited set of rigid residues, which we call the consensus nucleus, occupy conserved positions along the protein sequence. These residues' side chains form a tight interaction network within the protein's core, thus making our consensus nuclei potential folding nuclei. A review of experimental and theoretical literature shows that most (above 80%) of these residues were indeed identified as folding nucleus member in earlier studies.

Controlling Allosteric Networks in Proteins

Allosteric transition, defined as conformational changes induced by ligand binding, is one of the fundamental properties of proteins. Allostery has been observed and characterized in many proteins, and has been recently utilized to control protein function via regulation of protein activity. Here, we review the physical and evolutionary origin of protein allostery, as well as its importance to protein regulation, drug discovery, and biological processes in living systems. We describe recently developed approaches to identify allosteric pathways, connected sets of pairwise interactions that are responsible for propagation of conformational change from the ligand-binding site to a distal functional site. We then present experimental and computational protein engineering approaches for control of protein function by modulation of allosteric sites. As an example of application of these approaches, we describe a synergistic computational and experimental approach to rescue the cystic-fibrosis-associated protein cystic fibrosis transmembrane conductance regulator, which upon deletion of a single residue misfolds and causes disease. This example demonstrates the power of allosteric manipulation in proteins to both elucidate mechanisms of molecular function and to develop therapeutic strategies that rescue those functions. Allosteric control of proteins provides a tool to shine a light on the complex cascades of cellular processes and facilitate unprecedented interrogation of biological systems.

Analysis of core-periphery organization in protein contact networks reveals groups of structurally and functionally critical residues

The representation of proteins as networks of interacting amino acids, referred to as protein contact networks (PCN), and their subsequent analyses using graph theoretic tools, can provide novel insights into the key functional roles of specific groups of residues. We have characterized the networks corresponding to the native states of 66 proteins (belonging to different families) in terms of their core-periphery organization. The resulting hierarchical classification of the amino acid constituents of a protein arranges the residues into successive layers - having higher core order - with increasing connection density, ranging from a sparsely linked periphery to a densely intra-connected core (distinct from the earlier concept of protein core defined in terms of the three-dimensional geometry of the native state, which has least solvent accessibility). Our results show that residues in the inner cores are more conserved than those at the periphery. Underlining the functional importance of the network core, we see that the receptor sites for known ligand molecules of most proteins occur in the innermost core. Furthermore, the association of residues with structural pockets and cavities in binding or active sites increases with the core order. From mutation sensitivity analysis, we show that the probability of deleterious or intolerant mutations also increases with the core order. We also show that stabilization centre residues are in the innermost cores, suggesting that the network core is critically important in maintaining the structural stability of the protein. A publicly available Web resource for performing core-periphery analysis of any protein whose native state is known has been made available by us at http://www.imsc.res.in/ ~sitabhra/proteinKcore/index.html.

Two independently folding units of Plasmodium profilin suggest evolution via gene fusion

Gene fusion is a common mechanism of protein evolution that has mainly been discussed in the context of multidomain or symmetric proteins. Less is known about fusion of ancestral genes to produce small single-domain proteins. Here, we show with a domain-swapped mutant Plasmodium profilin that this small, globular, apparently single-domain protein consists of two foldons. The separation of binding sites for different protein ligands in the two halves suggests evolution via an ancient gene fusion event, analogous to the formation of multidomain proteins. Finally, the two fragments can be assembled together after expression as two separate gene products. The possibility to engineer both domain-swapped dimers and half-profilins that can be assembled back to a full profilin provides perspectives for engineering of novel protein folds, e.g., with different scaffolding functions.

Contribution to the prediction of the fold code: application to immunoglobulin and flavodoxin cases

Background

Folding nucleus of globular proteins formation starts by the mutual interaction of a group of hydrophobic amino acids whose close contacts allow subsequent formation and stability of the 3D structure. These early steps can be predicted by simulation of the folding process through a Monte Carlo (MC) coarse grain model in a discrete space. We previously defined MIRs (Most Interacting Residues), as the set of residues presenting a large number of non-covalent neighbour interactions during such simulation. MIRs are good candidates to define the minimal number of residues giving rise to a given fold instead of another one, although their proportion is rather high, typically [15-20]% of the sequences. Having in mind experiments with two sequences of very high levels of sequence identity (up to 90%) but different folds, we combined the MIR method, which takes sequence as single input, with the “fuzzy oil drop” (FOD) model that requires a 3D structure, in order to estimate the residues coding for the fold. FOD assumes that a globular protein follows an idealised 3D Gaussian distribution of hydrophobicity density, with the maximum in the centre and minima at the surface of the “drop”. If the actual local density of hydrophobicity around a given amino acid is as high as the ideal one, then this amino acid is assigned to the core of the globular protein, and it is assumed to follow the FOD model. Therefore one obtains a distribution of the amino acids of a protein according to their agreement or rejection with the FOD model.

Results

We compared and combined MIR and FOD methods to define the minimal nucleus, or keystone, of two populated folds: immunoglobulin-like (Ig) and flavodoxins (Flav). The combination of these two approaches defines some positions both predicted as a MIR and assigned as accordant with the FOD model. It is shown here that for these two folds, the intersection of the predicted sets of residues significantly differs from random selection. It reduces the number of selected residues by each individual method and allows a reasonable agreement with experimentally determined key residues coding for the particular fold. In addition, the intersection of the two methods significantly increases the specificity of the prediction, providing a robust set of residues that constitute the folding nucleus.