On the role of native contact cooperativity in protein folding.

The consistency of energy landscape theory predictions with available experimental data, as well as direct evidence from molecular simulations, have shown that protein folding mechanisms are largely determined by the contacts present in the native structure. As expected, native contacts are generally energetically favorable. However, there are usually at least as many energetically favorable nonnative pairs owing to the greater number of possible nonnative interactions. This apparent frustration must therefore be reduced by the greater cooperativity of native interactions. In this work, we analyze the statistics of contacts in the unbiased all-atom folding trajectories obtained by Shaw and coworkers, focusing on the unfolded state. By computing mutual cooperativities between contacts formed in the unfolded state, we show that native contacts form the most cooperative pairs, while cooperativities among nonnative or between native and nonnative contacts are typically much less favorable or even anticooperative. Furthermore, we show that the largest network of cooperative interactions observed in the unfolded state consists mainly of native contacts, suggesting that this set of mutually reinforcing interactions has evolved to stabilize the native state.

FRETpredict: a Python package for FRET efficiency predictions using rotamer libraries.

Förster resonance energy transfer (FRET) is a widely-used and versatile technique for the structural characterization of biomolecules. Here, we introduce FRETpredict, an easy-to-use Python software to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses a rotamer library approach to describe the FRET probes covalently bound to the protein. The software efficiently and flexibly operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We provide access to rotamer libraries for many commonly used dyes and linkers and describe a general methodology to generate new rotamer libraries for FRET probes. We demonstrate the performance and accuracy of the software for different types of systems: a rigid peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). FRETpredict is open source (GPLv3) and is available at github.com/KULL-Centre/FRETpredict and as a Python PyPI package at pypi.org/project/FRETpredict .

Extreme dynamics in a biomolecular condensate.

Proteins and nucleic acids can phase-separate in the cell to form concentrated biomolecular condensates1-4. The functions of condensates span many length scales: they modulate interactions and chemical reactions at the molecular scale5, organize biochemical processes at the mesoscale6 and compartmentalize cells4. Understanding the underlying mechanisms of these processes will require detailed knowledge of the rich dynamics across these scales7. The mesoscopic dynamics of biomolecular condensates have been extensively characterized8, but their behaviour at the molecular scale has remained more elusive. Here, as an example of biomolecular phase separation, we study complex coacervates of two highly and oppositely charged disordered human proteins9. Their dense phase is 1,000 times more concentrated than the dilute phase, and the resulting percolated interaction network10 leads to a bulk viscosity 300 times greater than that of water. However, single-molecule spectroscopy optimized for measurements within individual droplets reveals that at the molecular scale, the disordered proteins remain exceedingly dynamic, with their chain configurations interconverting on submicrosecond timescales. Massive all-atom molecular dynamics simulations reproduce the experimental observations and explain this apparent discrepancy: the underlying interactions between individual charged side chains are short-lived and exchange on a pico- to nanosecond timescale. Our results indicate that, despite the high macroscopic viscosity of phase-separated systems, local biomolecular rearrangements required for efficient reactions at the molecular scale can remain rapid.

Theoretical and Data-Driven Approaches for Biomolecular Condensates.

Biomolecular condensation processes are increasingly recognized as a fundamental mechanism that living cells use to organize biomolecules in time and space. These processes can lead to the formation of membraneless organelles that enable cells to perform distinct biochemical processes in controlled local environments, thereby supplying them with an additional degree of spatial control relative to that achieved by membrane-bound organelles. This fundamental importance of biomolecular condensation has motivated a quest to discover and understand the molecular mechanisms and determinants that drive and control this process. Within this molecular viewpoint, computational methods can provide a unique angle to studying biomolecular condensation processes by contributing the resolution and scale that are challenging to reach with experimental techniques alone. In this Review, we focus on three types of dry-lab approaches: theoretical methods, physics-driven simulations and data-driven machine learning methods. We review recent progress in using these tools for probing biomolecular condensation across all three fields and outline the key advantages and limitations of each of the approaches. We further discuss some of the key outstanding challenges that we foresee the community addressing next in order to develop a more complete picture of the molecular driving forces behind biomolecular condensation processes and their biological roles in health and disease.

FRETpredict: A Python package for FRET efficiency predictions using rotamer libraries.

Here, we introduce FRETpredict, a Python software program to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses an established Rotamer Library Approach to describe the FRET probes covalently bound to the protein. The software efficiently operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We demonstrate the performance and accuracy of the software for different types of systems: a relatively structured peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). We also describe a general approach to generate new rotamer libraries for FRET probes of interest. FRETpredict is open source (GPLv3) and is available at github.com/KULL-Centre/FRETpredict and as a Python PyPI package at pypi.org/project/FRETpredict.

Design of a Protein with Improved Thermal Stability by an Evolution-Based Generative Model.

Efficient design of functional proteins with higher thermal stability remains challenging especially for highly diverse sequence variants. Considering the evolutionary pressure on protein folds, sequence design optimizing evolutionary fitness could help designing folds with higher stability. Using a generative evolution fitness model trained to capture variation patterns in natural sequences, we designed artificial sequences of a proteinaceous inhibitor of pectin methylesterase enzymes. These inhibitors have considerable industrial interest to avoid phase separation in fruit juice manufacturing or reduce methanol in distillates, averting chromatographic passages triggering unwanted aroma loss. Six out of seven designs with up to 30 % divergence to other inhibitor sequences are functional and two have improved thermal stability. This method can improve protein stability expanding functional protein sequence space, with traits valuable for industrial applications and scientific research.

Real-time Exchange of the Lipid-bound Intermediate and Post-fusion States of the HIV-1 gp41 Ectodomain.

The envelope glycoprotein gp41 of the HIV-1 virus mediates its entry into the host cell. During this process, gp41 undergoes large conformational changes and the energy released in the remodeling events is utilized to overcome the barrier associated with fusing the viral and host membranes. Although the structural intermediates of this fusion process are attractive targets for drug development, no detailed high-resolution structural information or quantitative thermodynamic characterization are available. By measuring the dynamic equilibrium between the lipid-bound intermediate and the post-fusion six-helical bundle (6HB) states of the gp41 ectodomain in the presence of bilayer membrane mimetics, we derived both the reaction kinetics and energies associated with these two states by solution NMR spectroscopy. At equilibrium, an exchange time constant of about 12 seconds at 38 °C is observed, and the post-fusion conformation is energetically more stable than the lipid-bound state by 3.4 kcal mol-1. The temperature dependence of the kinetics indicates that the folding occurs through a high-energy transition state which may resemble a 5HB structure. The energetics and kinetics of gp41 folding in the context of membrane bilayers provide a molecular basis for an improved understanding of viral membrane fusion.

Tuning Formation of Protein-DNA Coacervates by Sequence and Environment.

The high concentration of nucleic acids and positively charged proteins in the cell nucleus provides many possibilities for complex coacervation. We consider a prototypical mixture of nucleic acids together with the polycationic C-terminus of histone H1 (CH1). Using a minimal coarse-grained model that captures the shape, flexibility, and charge distributions of the molecules, we find that coacervates are readily formed at physiological ionic strengths, in agreement with experiment, with a progressive increase in local ordering at low ionic strength. Variation of the positions of charged residues in the protein tunes phase separation: for well-mixed or only moderately blocky distributions of charge, there is a modest increase of local ordering with increasing blockiness that is also associated with an increased propensity to phase separate. This ordering is also associated with a slowdown of rotational and translational diffusion in the dense phase. However, for more extreme blockiness (and consequently higher local charge density), we see a qualitative change in the condensed phase to become a segregated structure with a dramatically increased ordering of the DNA. Naturally occurring proteins with these sequence properties, such as protamines in sperm cells, are found to be associated with very dense packing of nucleic acids.

Release of linker histone from the nucleosome driven by polyelectrolyte competition with a disordered protein.

Highly charged intrinsically disordered proteins are essential regulators of chromatin structure and transcriptional activity. Here we identify a surprising mechanism of molecular competition that relies on the pronounced dynamical disorder present in these polyelectrolytes and their complexes. The highly positively charged human linker histone H1.0 (H1) binds to nucleosomes with ultrahigh affinity, implying residence times incompatible with efficient biological regulation. However, we show that the disordered regions of H1 retain their large-amplitude dynamics when bound to the nucleosome, which enables the highly negatively charged and disordered histone chaperone prothymosin α to efficiently invade the H1-nucleosome complex and displace H1 via a competitive substitution mechanism, vastly accelerating H1 dissociation. By integrating experiments and simulations, we establish a molecular model that rationalizes the remarkable kinetics of this process structurally and dynamically. Given the abundance of polyelectrolyte sequences in the nuclear proteome, this mechanism is likely to be widespread in cellular regulation.

Analysis of Molecular Dynamics Simulations of Protein Folding.

Unbiased molecular dynamics simulations of proteins can now capture spontaneous folding events. This provides a wealth of data reflecting information on folding mechanism, but raises the challenge of interpreting it in a meaningful way. Here, I describe how such simulations can be used to identify reactive states and reaction coordinates for describing folding, and how folding dynamics can be captured by projection onto those coordinates. Methods are described for quantifying the interactions important for defining the folding mechanism, and for comparison of simulations with experimental mechanistic probes, such as ϕ-values.

Single-molecule Detection of Ultrafast Biomolecular Dynamics with Nanophotonics.

Single-molecule Förster resonance energy transfer (FRET) is a versatile technique for probing the structure and dynamics of biomolecules even in heterogeneous ensembles. However, because of the limited fluorescence brightness per molecule and the relatively long fluorescence lifetimes, probing ultrafast structural dynamics in the nanosecond time scale has thus far been very challenging. Here, we demonstrate that nanophotonic fluorescence enhancement in zero-mode waveguides enables measurements of previously inaccessible low-nanosecond dynamics by dramatically improving time resolution and reduces data acquisition times by more than an order of magnitude. As a prototypical example, we use this approach to probe the dynamics of a short intrinsically disordered peptide that were previously inaccessible with single-molecule FRET measurements. We show that we are now able to detect the low-nanosecond correlations in this peptide, and we obtain a detailed interpretation of the underlying distance distributions and dynamics in conjunction with all-atom molecular dynamics simulations, which agree remarkably well with the experiments. We expect this combined approach to be widely applicable to the investigation of very rapid biomolecular dynamics.

Atomic view of cosolute-induced protein denaturation probed by NMR solvent paramagnetic relaxation enhancement.

The cosolvent effect arises from the interaction of cosolute molecules with a protein and alters the equilibrium between native and unfolded states. Denaturants shift the equilibrium toward the latter, while osmolytes stabilize the former. The molecular mechanism whereby cosolutes perturb protein stability is still the subject of considerable debate. Probing the molecular details of the cosolvent effect is experimentally challenging as the interactions are very weak and transient, rendering them invisible to most conventional biophysical techniques. Here, we probe cosolute-protein interactions by means of NMR solvent paramagnetic relaxation enhancement together with a formalism we recently developed to quantitatively describe, at atomic resolution, the energetics and dynamics of cosolute-protein interactions in terms of a concentration normalized equilibrium average of the interspin distance, [Formula: see text], and an effective correlation time, τc The system studied is the metastable drkN SH3 domain, which exists in dynamic equilibrium between native and unfolded states, thereby permitting us to probe the interactions of cosolutes with both states simultaneously under the same conditions. Two paramagnetic cosolute denaturants were investigated, one neutral and the other negatively charged, differing in the presence of a carboxyamide group versus a carboxylate. Our results demonstrate that attractive cosolute-protein backbone interactions occur largely in the unfolded state and some loop regions in the native state, electrostatic interactions reduce the [Formula: see text] values, and temperature predominantly impacts interactions with the unfolded state. Thus, destabilization of the native state in this instance arises predominantly as a consequence of interactions of the cosolutes with the unfolded state.

Treatment of sickle cell disease by increasing oxygen affinity of hemoglobin.

The issue of treating sickle cell disease with drugs that increase hemoglobin oxygen affinity has come to the fore with the US Food and Drug Administration approval in 2019 of voxelotor, the only antisickling drug approved since hydroxyurea in 1998. Voxelotor reduces sickling by increasing the concentration of the nonpolymerizing, high oxygen affinity R (oxy) conformation of hemoglobin S (HbS). Treatment of sickle cell patients with voxelotor increases Hb levels and decreases indicators of hemolysis, but with no indication as yet that it reduces the frequency of pain episodes. In this study, we used the allosteric model of Monod, Wyman, and Changeux to simulate whole-blood oxygen dissociation curves and red cell sickling in the absence and presence of voxelotor under the in vivo conditions of rapid oxygen pressure decreases. Our modeling agrees with results of experiments using a new robust assay, which shows the large, expected decrease in sickling from the drug. The modeling indicates, however, that the increase in oxygen delivery from reduced sickling is largely offset by the increase in oxygen affinity. The net result is that the drug increases overall oxygen delivery only at the very lowest oxygen pressures. However, reduction of sickling mitigates red cell damage and explains the observed decrease in hemolysis. More importantly, our modeling of in vivo oxygen dissociation, sickling, and oxygen delivery suggests that drugs that increase fetal Hb or decrease mean corpuscular hemoglobin concentration (MCHC) should be more therapeutically effective than drugs that increase oxygen affinity.

The ribosome modulates folding inside the ribosomal exit tunnel.

Proteins commonly fold co-translationally at the ribosome, while the nascent chain emerges from the ribosomal exit tunnel. Protein domains that are sufficiently small can even fold while still located inside the tunnel. However, the effect of the tunnel on the folding dynamics of these domains is not well understood. Here, we combine optical tweezers with single-molecule FRET and molecular dynamics simulations to investigate folding of the small zinc-finger domain ADR1a inside and at the vestibule of the ribosomal tunnel. The tunnel is found to accelerate folding and stabilize the folded state, reminiscent of the effects of chaperonins. However, a simple mechanism involving stabilization by confinement does not explain the results. Instead, it appears that electrostatic interactions between the protein and ribosome contribute to the observed folding acceleration and stabilization of ADR1a.

A Data-Driven Hydrophobicity Scale for Predicting Liquid-Liquid Phase Separation of Proteins.

An accurate model for macroscale disordered assemblies of biological macromolecules such as those formed in so-called membraneless organelles would greatly assist in studying their structure, function, and dynamics. Recent evidence has suggested that liquid-liquid phase separation (LLPS) underlies the formation of membraneless organelles. While the general mechanism of exchange of macromolecule/water for macromolecule/macromolecule interactions is known to be the driving force for LLPS, the specific interactions involved are not well understood. One way that protein-water and protein-protein interactions have been understood historically is via hydrophobicity scales. However, these scales are typically optimized for describing these relative interactions in certain cases, such as protein folding or insertion of proteins into membranes. To better describe the relative interactions of proteins that undergo LLPS, we have developed a new, data-driven hydrophobicity scale. To determine the new scale, we used coarse-grained molecular dynamics simulations using the hydrophobicity scale coarse-grained model, which relates the interactions between amino acids to their hydrophobicity. Hydrophobicity values were determined via the force-balance method on a library of proteins that includes unfolded, intrinsically disordered, and phase-separating proteins (PSP). The resulting hydrophobicity scale can better predict whether a given protein will undergo LLPS at physiological conditions by using coarse-grained molecular dynamics simulations than existing hydrophobicity scales. This new scale confirms the importance of π-π interactions between amino acids as important drivers of LLPS. This new hydrophobicity scale provides a convenient and compact description of protein-protein interactions for proteins that undergo LLPS and could be used to develop new models to describe interactions between PSP and other components, such as nucleic acids.

Martini 3: a general purpose force field for coarse-grained molecular dynamics.

The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 ( http://cgmartini.nl ), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.

Estimating transition path times and shapes from single-molecule photon trajectories: A simulation analysis.

In a two-state molecular system, transition paths comprise the portions of trajectories during which the system transits from one stable state to the other. Because of their low population, it is essentially impossible to obtain information on transition paths from experiments on a large sample of molecules. However, single-molecule experiments such as laser optical tweezers or Förster resonance energy transfer (FRET) spectroscopy have allowed transition-path durations to be estimated. Here, we use molecular simulations to test the methodology for obtaining information on transition paths in single-molecule FRET by generating photon trajectories from the distance trajectories obtained in the simulation. Encouragingly, we find that this maximum likelihood analysis yields transition-path times within a factor of 2-4 of the values estimated using a good coordinate for folding, but tends to systematically underestimate them. The underestimation can be attributed partly to the fact that the large changes in the end-end distance occur mostly early in a folding trajectory. However, even if the transfer efficiency is a good reaction coordinate for folding, the assumption that the transition-path shape is a step function still leads to an underestimation of the transition-path time as defined here. We find that allowing more flexibility in the form of the transition path model allows more accurate transition-path times to be extracted and points the way toward further improvements in methods for estimating transition-path time and transition-path shape.

Mechanism of membrane-tethered mitochondrial protein synthesis.

Mitochondrial ribosomes (mitoribosomes) are tethered to the mitochondrial inner membrane to facilitate the cotranslational membrane insertion of the synthesized proteins. We report cryo-electron microscopy structures of human mitoribosomes with nascent polypeptide, bound to the insertase oxidase assembly 1-like (OXA1L) through three distinct contact sites. OXA1L binding is correlated with a series of conformational changes in the mitoribosomal large subunit that catalyze the delivery of newly synthesized polypeptides. The mechanism relies on the folding of mL45 inside the exit tunnel, forming two specific constriction sites that would limit helix formation of the nascent chain. A gap is formed between the exit and the membrane, making the newly synthesized proteins accessible. Our data elucidate the basis by which mitoribosomes interact with the OXA1L insertase to couple protein synthesis and membrane delivery.

Physics-based computational and theoretical approaches to intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) are an important class of proteins that do not fold to a well-defined three-dimensional shape but rather adopt an ensemble of inter-converting conformations. This feature makes their experimental characterization challenging and invites a theoretical and computational approach to complement experimental studies. In this review, we highlight the recent progress in developing new computational and theoretical approaches to study the structure and dynamics of monomeric and order higher assemblies of IDPs, with a particular emphasis on their phase separation into protein-rich condensates.