Rapid Photolysis-Mediated Folding of Disulfide-Rich Peptides

Structure–activity relationship studies are a highly time-consuming aspect of peptide-based drug development, particularly in the assembly of disulfide-rich peptides, which often requires multiple synthetic steps and purifications. Therefore, it is vital to develop rapid and efficient chemical methods to readily access the desired peptides. We have developed a photolysis-mediated “one-pot” strategy for regioselective disulfide bond formation. The new pairing system utilises two ortho-nitroveratryl protected cysteines to generate two disulfide bridges in less than one hour in good yield. This strategy was applied to the synthesis of complex disulfide-rich peptides such as Rho-conotoxin ρ-TIA and native human insulin.     

Diaminodiacid Bridges to Improve Folding and Tune the Bioactivity of Disulfide‐Rich Peptides

Disulfide‐rich peptides containing three or more disulfide bonds are promising therapeutic and diagnostic agents, but their preparation is often limited by the tedious and low‐yielding folding process. We found that a single cystine‐to‐diaminodiacid replacement could significantly increase the folding efficiency of disulfide‐rich peptides and thus improve their production yields. The practicality of this strategy was demonstrated by the synthesis and folding of derivatives of the μ‐conotoxin SIIIA, the preclinical hormone hepcidin, and the trypsin inhibitor EETI‐II. NMR and X‐ray crystallography studies confirmed that these derivatives of disulfide‐rich peptide retained the correct three‐dimensional conformations. Moreover, the cystine‐to‐diaminodiacid replacement enabled structural tuning, thereby leading to an EETI‐II derivative with higher bioactivity than the native peptide.     

Modulating the Folding Landscape of Superoxide Dismutase 1 with Targeted Molecular Binders

Amyotrophic lateral sclerosis, or Lou Gehrig's disease, is characterized by motor neuron death, with average survival times of two to five years. One cause of this disease is the misfolding of superoxide dismutase 1 (SOD1), a phenomenon influenced by point mutations spanning the protein. Herein, we used an epitope‐specific high‐throughput screen to identify a peptide ligand that stabilizes the SOD1 native conformation and accelerates its folding by a factor of 2.5. This strategy may be useful for fundamental studies of protein energy landscapes as well as designing new classes of therapeutics.     

An Off‐Pathway Folding Intermediate of an Acyl Carrier Protein Domain Coexists with the Folded and Unfolded States under Native Conditions

A protein can exist in multiple states under native conditions and those states with low populations are often critical to biological function and self‐assembly. To investigate the role of the minor states of an acyl carrier protein, NMR techniques were applied to determine the number of minor states and characterize their structures and kinetics. The acyl carrier protein from Micromonospora echinospora was found to exist in one major folded state (95.2 %), one unfolded state (4.1 %), and one intermediate state (0.7 %) under native conditions. The three states are in dynamic equilibrium and the intermediate state very likely adopts a native‐like structure and is an off‐pathway folding product. The intermediate state may mediate the formation of oligomers in vitro and play an important role in the recognition of partner enzymes in vivo.     

Folding versus self-assembling

Model foldable polymers with sequences of rigid hydrophobic chromophores and flexible hydrophilic tetra(ethylene glycol) were synthesized and used as a paradigm for studying molecular-folding and self-assembly phenomena. Our results demonstrate that intramolecular association or folding prevails over intermolecular interaction or self-assembling in the concentration region from 1 microM to 0.1 M. Importantly, folded polymeric nanostructures have absorption and fluorescence properties that are distinct from those of unfolded polymers or free monomers. We hypothesize that the origins of folding and self-assembly come from interactions between molecular units, and that the key parameter that regulates the on-and-off of such interactions is the distance R separating the two molecular units. Each molecular unit produces a characteristic force field, and when another molecular unit enters this field, the probability that the two units will interact increases significantly. A preliminary estimate of the radius of such a force field for the perylene tetracarboxylic diimide chromophore is about 90-120 A. As a result, phenomena associated with folding or self-assembly of molecular species are observed when these conditions are met in solution.     

Reduction of the Search Space for the Folding of Proteins at the Level of Formation and Assembly of Secondary Structures: A New View on the Solution of Levinthal′s Paradox

The complete volume of the protein conformation space is, by many orders of magnitude, smaller at the level of secondary structure elements than that at the level of amino acid residues; the latter, according to Levinthal′s estimate, scales approximately as 10^{2 L}, with L being the number of residues in the chain, whereas the former, as demonstrated in this paper, scales no faster than ～L^N, with N being the number of the secondary structure elements, which is approximately equal to L/15. This drastic decrease in the exponent (L/15 instead of 2 L) explains why sampling of the conformation space does not contradict the ability of the protein chain to find its most stable fold.     

An Electrochemical Biosensor Architecture Based on Protein Folding Supports Direct Real-Time Measurements in Whole Blood

The ability to monitor drug and biomarker concentrations in the body with high frequency and in real time would revolutionize our understanding of biology and our capacity to personalize medicine. The few in vivo molecular sensors that currently exist, however, all rely on the specific chemical or enzymatic reactivity of their targets and thus are not generalizable. In response, we demonstrate here an electrochemical sensing architecture based on binding-induced protein folding that is 1) independent of the reactivity of its targets, 2) reagentless, real-time, and with a resolution of seconds, and 3) selective enough to deploy in undiluted bodily fluids. As a proof of principle, we use the SH3 domain from human Fyn kinase to build a sensor that discriminates between the protein's peptide targets and responds rapidly and quantitatively even when challenged in whole blood. The resulting sensor architecture could drastically expand the chemical space accessible to continuous, real-time biosensors.     

Randomizing the Unfolded State of Peptides (and Proteins) by Nearest Neighbor Interactions between Unlike Residues

To explore the influence of nearest neighbors on conformational biases in unfolded peptides, we combined vibrational and 2D NMR spectroscopy to obtain the conformational distributions of selected “GxyG” host–guest peptides in aqueous solution: GDyG, GSyG, GxLG, GxVG, where x/y=A, K, L, V. Large changes of conformational propensities were observed due to nearest‐neighbor interactions, at variance with the isolated pair hypothesis. We found that protonated aspartic acid and serine lose their above‐the‐average preference for turn‐like structures in favor of polyproline II (pPII) populations in the presence of neighbors with bulky side chains. Such residues also decrease the above‐the‐average pPII preference of alanine. These observations suggest that the underlying mechanism involves a disruption of the hydration shell. Thermodynamic analysis of ³J(H^N,H^α) (T) data for each x,y residue reveals that modest changes in the conformational ensemble masks larger changes of enthalpy and entropy governing the pPII?β equilibrium indicating a significant residue dependent temperature dependence of the peptides’ conformational ensembles. These results suggest that nearest‐neighbor interactions between unlike residues act as conformational randomizers close to the enthalpy–entropy compensation temperature, eliminating intrinsic biases in favor of largely balanced pPII/β dominated ensembles at physiological temperatures.     

Amyloid Polymorphism in the Protein Folding and Aggregation Energy Landscape

Protein folding involves a large number of steps and conformations in which the folding protein samples different thermodynamic states characterized by local minima. Kinetically trapped on‐ or off‐pathway intermediates are metastable folding intermediates towards the lowest absolute energy minima, which have been postulated to be the natively folded state where intramolecular interactions dominate, and the amyloid state where intermolecular interactions dominate. However, this view largely neglects the rich polymorphism found within amyloid species. We review the protein folding energy landscape in view of recent findings identifying specific transition routes among different amyloid polymorphs. Observed transitions such as twisted ribbon→crystal or helical ribbon→nanotube, and forbidden transitions such helical ribbon?crystal, are discussed and positioned within the protein folding and aggregation energy landscape. Finally, amyloid crystals are identified as the ground state of the protein folding and aggregation energy landscape.     

Folding of Synthetic Homogeneous Glycoproteins in the Presence of a Glycoprotein Folding Sensor Enzyme

UDP‐glucose:glycoprotein glucosyltransferase (UGGT) plays a key role in recognizing folded and misfolded glycoproteins in the glycoprotein quality control system of the endoplasmic reticulum. UGGT detects misfolded glycoproteins and re‐glucosylates them as a tag for misfolded glycoproteins. A flexible model to reproduce in vitro folding of a glycoprotein in the presence of UGGT in a mixture containing correctly folded, folding intermediates, and misfolded glycoproteins is described. The data demonstrates that UGGT can re‐glucosylate all intermediates in the in vitro folding experiments, thus indicating that UGGT inspects not only final folded products, but also the glycoprotein folding intermediates.     

The Wako-Saitô-Muñoz-Eaton Model for Predicting Protein Folding and Dynamics

Despite the recent advances in the prediction of protein structures by deep neutral networks, the elucidation of protein-folding mechanisms remains challenging. A promising theory for describing protein folding is a coarse-grained statistical mechanical model called the Wako-Saitô-Muñoz-Eaton (WSME) model. The model can calculate the free-energy landscapes of proteins based on a three-dimensional structure with low computational complexity, thereby providing a comprehensive understanding of the folding pathways and the structure and stability of the intermediates and transition states involved in the folding reaction. In this review, we summarize previous and recent studies on protein folding and dynamics performed using the WSME model and discuss future challenges and prospects. The WSME model successfully predicted the folding mechanisms of small single-domain proteins and the effects of amino-acid substitutions on protein stability and folding in a manner that was consistent with experimental results. Furthermore, extended versions of the WSME model were applied to predict the folding mechanisms of multi-domain proteins and the conformational changes associated with protein function. Thus, the WSME model may contribute significantly to solving the protein-folding problem and is expected to be useful for predicting protein folding, stability, and dynamics in basic research and in industrial and medical applications.     

Neural Networks Predict Protein Folding and Structure: Artificial Intelligence Faces Biomolecular Complexity

Abstract

In the genomic era DNA sequencing is increasing our knowledge of the molecular structure of genetic codes from bacteria to man at a hyperbolic rate. Billions of nucleotides and millions of aminoacids are already filling the electronic files of the data bases presently available, which contain a tremendous amount of information on the most biologically relevant macromolecules, such as DNA. RNA and proteins. The most urgent problem originates from the need to single out the relevant information amidst a wealth of general features. Intelligent tools are therefore needed to optimise the search. Data mining for sequence analysis in biotechnology has been substantially aided by the development of new powerful methods borrowed from the machine learning approach. In this paper we discuss the application of artificial feedforward neural networks to deal with some fundamental problems tied with the folding process and the structure-function relationship in proteins.     

Combining High-Pressure Perturbation with NMR Spectroscopy for a Structural and Dynamical Characterization of Protein Folding Pathways

High-hydrostatic pressure is an alternative perturbation method that can be used to destabilize globular proteins. Generally perfectly reversible, pressure exerts local effects on regions or domains of a protein containing internal voids, contrary to heat or chemical denaturant that destabilize protein structures uniformly. When combined with NMR spectroscopy, high pressure (HP) allows one to monitor at a residue-level resolution the structural transitions occurring upon unfolding and to determine the kinetic properties of the process. The use of HP-NMR has long been hampered by technical difficulties. Owing to the recent development of commercially available high-pressure sample cells, HP-NMR experiments can now be routinely performed. This review summarizes recent advances of HP-NMR techniques for the characterization at a quasi-atomic resolution of the protein folding energy landscape.     

Chemoselective Ligation and Modification Strategies for Peptides and Proteins

The investigation of biological processes by chemical methods, commonly referred to as chemical biology, often requires chemical access to biologically relevant macromolecules such as peptides and proteins. Building upon solid‐phase peptide synthesis, investigations have focused on the development of chemoselective ligation and modification strategies to link synthetic peptides or other functional units to larger synthetic and biologically relevant macromolecules. This Review summarizes recent developments in the field of chemoselective ligation and modification strategies and illustrates their application, with examples ranging from the total synthesis of proteins to the semisynthesis of naturally modified proteins.     

How Post‐Translational Modifications Influence Amyloid Formation: A Systematic Study of Phosphorylation and Glycosylation in Model Peptides

A reciprocal relationship between phosphorylation and O‐glycosylation has been reported for many cellular processes and human diseases. The accumulated evidence points to the significant role these post‐translational modifications play in aggregation and fibril formation. Simplified peptide model systems provide a means for investigating the molecular changes associated with protein aggregation. In this study, by using an amyloid‐forming model peptide, we show that phosphorylation and glycosylation can affect folding and aggregation kinetics differently. Incorporation of phosphoserines, regardless of their quantity and position, turned out to be most efficient in preventing amyloid formation, whereas O‐glycosylation has a more subtle effect. The introduction of a single β‐galactose does not change the folding behavior of the model peptide, but does alter the aggregation kinetics in a site‐specific manner. The presence of multiple galactose residues has an effect similar to that of phosphorylation.     

金属离子对蛋白质的折叠、识别、自组装及功能的影响*

金属离子不仅影响金属蛋白的空间结构,还与生物大分子的识别、自组装等性质和生物功能密切相关。在很多蛋白质中,金属离子及其配合物可以诱导周围的肽段折叠成正确的结构,我们将其称为金属结合部位作为模板诱导的结构基序（Template-mediated structural motif,TMSM)。深入研究金属离子在蛋白质-核酸自组装体系中生物大分子交联及聚集体中的作用,对理解生命的无机化学基础具有重要意义。