Protein folding problem: enigma, paradox, solution

Fluorescence phasor analysis: basic principles and biophysical applications

Fluorescence is one of the most widely used techniques in biological sciences. Its exceptional sensitivity and versatility make it a tool of first choice for quantitative studies in biophysics. The concept of phasors, originally introduced by Charles Steinmetz in the late nineteenth century for analyzing alternating current circuits, has since found applications across diverse disciplines, including fluorescence spectroscopy. The main idea behind fluorescence phasors was posited by Gregorio Weber in 1981. By analyzing the complementary nature of pulse and phase fluorometry data, he shows that two magnitudes-denoted as G and S-derived from the frequency-domain fluorescence measurements correspond to the real and imaginary parts of the Fourier transform of the fluorescence intensity in the time domain. This review provides a historical perspective on how the concept of phasors originates and how it integrates into fluorescence spectroscopy. We discuss their fundamental algebraic properties, which enable intuitive model-free analysis of fluorescence data despite the complexity of the underlying phenomena. Some applications in molecular biophysics illustrate the power of this approach in studying diverse phenomena, including protein folding, protein interactions, phase transitions in lipid mixtures, and formation of high-order structures in nucleic acids.

How proteins manage to fold and how chaperones manage to assist the folding

This review presents the current understanding of (i) spontaneous self-organization of spatial structures of protein molecules, and (ii) possible ways of chaperones' assistance to this process. Specifically, we overview the most important features of spontaneous folding of proteins (mostly, of the single-domain water-soluble globular proteins): the choice of the unique protein structure among zillions of alternatives, the nucleation of the folding process, and phase transitions within protein molecules. We consider the main experimental facts on protein folding, both in vivo and in vitro, of both kinetic and thermodynamic nature. We discuss the famous Levinthal's paradox of protein folding and its solution, theoretical models of protein folding and unfolding, and the dependence of the rates of these processes on the protein chain length. Special attention is paid to relatively small, single-domain, and water-soluble globular proteins whose structure and folding are much better studied and understood than those of large proteins, especially membrane or fibrous proteins. Lastly, we describe the chaperone-assisted protein folding with an emphasis on the chaperones' ability to prevent proteins from their irreversible aggregation. Since the possible assistance mechanisms connected with chaperones are still debatable, experimental data useful in selecting the most likely mechanisms of chaperone-assisted protein folding are presented.

AlphaFold and what is next: bridging functional, systems and structural biology

INTRODUCTION

The DeepMind's AlphaFold (AF) has revolutionized biomedical and biocience research by providing both experts and non-experts with an invaluable tool for predicting protein structures. However, while AF is highly effective for predicting structures of rigid and globular proteins, it is not able to fully capture the dynamics, conformational variability, and interactions of proteins with ligands and other biomacromolecules.

AREAS COVERED

In this review, we present a comprehensive overview of the latest advancements in 3D model predictions for biomacromolecules using AF. We also provide a detailed analysis its of strengths and limitations, and explore more recent iterations, modifications, and practical applications of this strategy. Moreover, we map the path forward for expanding the landscape of AF toward predicting structures of every protein and peptide, and their interactions in the proteome in the most physiologically relevant form. This discussion is based on an extensive literature search performed using PubMed and Google Scholar.

EXPERT OPINION

While significant progress has been made to enhance AF's modeling capabilities, we argue that a combined approach integrating both various in silico and in vitro methods will be most beneficial for the future of structural biology, bridging the gaps between static and dynamic features of proteins and their functions.

Life and death of Yfh1: how cool is cold denaturation

Yeast frataxin (Yfh1) is a small natural protein from yeast that has the unusual property of undergoing cold denaturation at temperatures above the freezing point of water when under conditions of low ionic strength. This peculiarity, together with remarkable resilience, allows the determination, for the whole protein as well as for individual residues, of the stability curve, that is the temperature dependence of the free energy difference between the unfolded and folded forms. The ease of measuring stability curves without the need to add denaturants or introduce ad hoc destabilizing mutations makes this protein an ideal 'tool' for investigating the influence of many environmental factors on protein stability. The present review aims at recapitulating all the open questions that Yfh1 has helped to address, including understanding the differences and commonalities of the cold, heat and pressure unfolded states. This protein thus offers a unique tool for studying aspects of protein stability so far been considered difficult to assess and provides important guidelines that could allow the identification of other similar systems.

Computational approach based on freely accessible tools for antimicrobial drug design

Antimicrobial drug development is crucial for public health, especially with the emergence of pandemics and drug resistance that prompts the search for new therapeutic resources. In this context, in silico assays consist of a valuable approach in the rational drug design because they enable a faster and more cost-effective identification of drug candidates compared to in vitro screening. However, once a potential drug is identified, in vitro and in vivo assays are essential to verify the expected activity of the compound and advance it through the subsequent stages of drug development. This work aims to outline an in silico protocol that utilizes only freely available computational tools for identifying new potential antimicrobial agents, which is also suitable in the broad spectrum of drug design. Additionally, this paper reviews relevant computational methods in this context and provides a summary of information concerning the protein-ligand interaction.

Origins of Life: The Protein Folding Problem all over again?

How did specific useful protein sequences arise from simpler molecules at the origin of life? This seemingly needle-in-a-haystack problem has remarkably close resemblance to the old Protein Folding Problem, for which the solution is now known from statistical physics. Based on the logic that Origins must have come only after there was an operative evolution mechanism-which selects on phenotype, not genotype-we give a perspective that proteins and their folding processes are likely to have been the primary driver of the early stages of the origin of life.

Step Forward Cross Validation for Bioactivity Prediction: Out of Distribution Validation in Drug Discovery

Recent advances in machine learning methods for materials science have significantly enhanced accurate predictions of the properties of novel materials. Here, we explore whether these advances can be adapted to drug discovery by addressing the problem of prospective validation - the assessment of the performance of a method on out-of-distribution data. First, we tested whether k-fold n-step forward cross-validation could improve the accuracy of out-of-distribution small molecule bioactivity predictions. We found that it is more helpful than conventional random split cross-validation in describing the accuracy of a model in real-world drug discovery settings. We also analyzed discovery yield and novelty error, finding that these two metrics provide an understanding of the applicability domain of models and an assessment of their ability to predict molecules with desirable bioactivity compared to other small molecules. Based on these results, we recommend incorporating a k-fold n-step forward cross-validation and these metrics when building state-of-the-art models for bioactivity prediction in drug discovery.

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.

The dynamic-process characterization and prediction of synthetic gene circuits by dynamic delay model

Differential equation models are widely used to describe genetic regulations, predict multicomponent regulatory circuits, and provide quantitative insights. However, it is still challenging to quantitatively link the dynamic behaviors with measured parameters in synthetic circuits. Here, we propose a dynamic delay model (DDM) which includes two simple parts: the dynamic determining part and the doses-related steady-state-determining part. The dynamic determining part is usually supposed as the delay time but without a clear formula. For the first time, we give the detail formula of the dynamic determining function and provide a method for measuring all parameters of synthetic elements (include 8 activators and 5 repressors) by microfluidic system. Three synthetic circuits were built to show that the DDM can notably improve the prediction accuracy and can be used in various synthetic biology applications.

Mechanisms of SNARE proteins in membrane fusion

Soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) are a family of small conserved eukaryotic proteins that mediate membrane fusion between organelles and with the plasma membrane. SNAREs are directly or indirectly anchored to membranes. Prior to fusion, complementary SNAREs assemble between membranes with the aid of accessory proteins that provide a scaffold to initiate SNARE zippering, pulling the membranes together and mediating fusion. Recent advances have enabled the construction of detailed models describing bilayer transitions and energy barriers along the fusion pathway and have elucidated the structures of SNAREs complexed in various states with regulatory proteins. In this Review, we discuss how these advances are yielding an increasingly detailed picture of the SNARE-mediated fusion pathway, leading from first contact between the membranes via metastable non-bilayer intermediates towards the opening and expansion of a fusion pore. We describe how SNARE proteins assemble into complexes, how this assembly is regulated by accessory proteins and how SNARE complexes overcome the free energy barriers that prevent spontaneous membrane fusion.

K-Pro: Kinetics Data on Proteins and Mutants

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

Analysis of the Structural Dynamics of Proteins in the Ligand-Unbound and -Bound States by Diffracted X-ray Tracking

Although many protein structures have been determined at atomic resolution, the majority of them are static and represent only the most stable or averaged structures in solution. When a protein binds to its ligand, it usually undergoes fluctuation and changes its conformation. One attractive method for obtaining an accurate view of proteins in solution, which is required for applications such as the rational design of proteins and structure-based drug design, is diffracted X-ray tracking (DXT). DXT can detect the protein structural dynamics on a timeline via gold nanocrystals attached to the protein. Here, the structure dynamics of single-chain Fv antibodies, helix bundle-forming de novo designed proteins, and DNA-binding proteins in both ligand-unbound and ligand-bound states were analyzed using the DXT method. The resultant mean square angular displacements (MSD) curves in both the tilting and twisting directions clearly demonstrated that structural fluctuations were suppressed upon ligand binding, and the binding energies determined using the angular diffusion coefficients from the MSD agreed well with the binding thermodynamics determined using isothermal titration calorimetry. In addition, the size of gold nanocrystals is discussed, which is one of the technical concerns of DXT.

Protein folding rate evolution upon mutations

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

A Study of a Protein-Folding Machine: Transient Rotation of the Polypeptide Backbone Facilitates Rapid Folding of Protein Domains in All-Atom Molecular Dynamics Simulations

Molecular dynamics simulations of protein folding typically consider the polypeptide chain at equilibrium and in isolation from the cellular components. We argue that in order to understand protein folding as it occurs in vivo, it should be modeled as an active, energy-dependent process, in which the cellular protein-folding machine directly manipulates the polypeptide. We conducted all-atom molecular dynamics simulations of four protein domains, whose folding from the extended state was augmented by the application of rotational force to the C-terminal amino acid, while the movement of the N-terminal amino acid was restrained. We have shown earlier that such a simple manipulation of peptide backbone facilitated the formation of native structures in diverse α-helical peptides. In this study, the simulation protocol was modified, to apply the backbone rotation and movement restriction only for a short time at the start of simulation. This transient application of a mechanical force to the peptide is sufficient to accelerate, by at least an order of magnitude, the folding of four protein domains from different structural classes to their native or native-like conformations. Our in silico experiments show that a compact stable fold may be attained more readily when the motions of the polypeptide are biased by external forces and constraints.

Biophysical Reviews: And the winner is …

This Editorial (Vol. 15 Issue 2-Regular Issue) first announces the winner of the 2023 Michèle Auger Award for Young Scientists' Independent Research before then going on to describe the contents of the current Issue. The Editorial closes with a discussion of the pros and cons of writing in the formulation of scientific ideas.

Molecular Peptide Grafting as a Tool to Create Novel Protein Therapeutics

The study of peptides (synthetic or corresponding to discrete regions of proteins) has facilitated the understanding of protein structure-activity relationships. Short peptides can also be used as powerful therapeutic agents. However, the functional activity of many short peptides is usually substantially lower than that of their parental proteins. This is (as a rule) due to their diminished structural organization, stability, and solubility often leading to an enhanced propensity for aggregation. Several approaches have emerged to overcome these limitations, which are aimed at imposing structural constraints into the backbone and/or sidechains of the therapeutic peptides (such as molecular stapling, peptide backbone circularization and molecular grafting), therefore enforcing their biologically active conformation and thus improving their solubility, stability, and functional activity. This review provides a short summary of approaches aimed at enhancing the biological activity of short functional peptides with a particular focus on the peptide grafting approach, whereby a functional peptide is inserted into a scaffold molecule. Intra-backbone insertions of short therapeutic peptides into scaffold proteins have been shown to enhance their activity and render them a more stable and biologically active conformation.

Biophysical Reviews: Turning the page from 2022 to 2023

This Editorial (vol. 15 issue 1-Regular Issue featuring an Issue Focus on the "100th Anniversary of Har Gobind Khorana") first describes the issue contents before providing both, a look back at some journal highlights from 2022, and a look forward to what we can expect from 2023. The Editorial closes with a roundup of new journal access features and an acknowledgement of those supporting the journal.

Computational biophysics and structural biology of proteins-a Special Issue in honor of Prof. Haruki Nakamura's 70th birthday

Receiving his initial training jointly in theoretical and applied physics at the University of Tokyo, Professor Haruki Nakamura has had a long and eventful scientific career, along the way helping to shape the way that biophysics is carried out in Japan. Concentrating his research efforts on the simulation of protein structure and function, he has, over his career arc, acted as director of the Institute for Protein Research (Osaka, Japan), director of the Protein Data Bank of Japan (PDBj), president of the Biophysical Society of Japan (BSJ), president of the Protein Science Society of Japan (PSSJ), and group leader and professor of Bioinformatics and Computational Structural Biology at Osaka University. In 2022, Prof. Haruki Nakamura turned 70 years old, and to mark this occasion, his scientific colleagues from around the world have combined their efforts to produce this Festschrift Issue of the IUPAB Biophysical Reviews journal around the theme of the computational biophysics and structural biology of proteins.