Switching Protein Conformational Substates by Protonation and Mutation

Conformational switches in human RNA binding proteins involved in neurodegeneration

Conformational switching in RNA binding proteins (RBPs) is crucial for regulation of RNA processing and transport. Dysregulation or mutations in RBPs and broad RNA processing abnormalities are related to many human diseases including neurodegenerative disorders. Here, we review the role of protein-RNA conformational switches in RBP-RNA complexes. RBP-RNA complexes exhibit wide range of conformational switching depending on the RNA molecule and its ability to induce conformational changes in its partner RBP. We categorize the conformational switches into three groups: rigid body, semi-flexible and full flexible. We also investigate conformational switches in large cellular assemblies including ribosome, spliceosome and RISC complexes. In addition, the role of intrinsic disorder in RBP-RNA conformational switches is discussed. We have also discussed the effect of different disease-causing mutations on conformational switching of proteins associated with neurodegenerative diseases. We believe that this study will enhance our understanding on the role of protein-RNA conformational switches. Furthermore, the availability of a large number of atomic structures of RBP-RNA complexes in near future would facilitate to create a complete repertoire of human RBP-RNA conformational switches.

Biochemical and biophysical characterization of biosynthetic arginine decarboxylase from Thermus thermophilus

The biosynthetic arginine decarboxylase in Thermus thermophilus is responsible for producing spermidine, a polyamine with numerous biological applications in humans. The arginine decarboxylase has significant applications in biotechnology industries, suggesting the need to evaluate its biochemical and biophysical characteristics at the molecular level. In this study, both in vitro and in silico methods were employed to investigate the structural and functional behavior of the arginine decarboxylase protein. In in vitro, MALDI-TOF, size exclusion, and assay studies were performed to examine the nature and activity of the protein. The MALDI-TOF analysis confirmed the purified protein as biosynthetic arginine decarboxylase. The assay results revealed that the Pyridoxal 5'-Phosphate (PLP) cofactor plays a crucial role in enhancing enzyme activity by producing agmatine (a by-product of spermidine). Further, optimum enzyme activity was observed at 50 °C, suggesting the extremophilic nature of the enzyme. Unlike other proteins, this enzyme displayed optimal activity at both acidic and basic pH, demonstrating its sensitivity to pH changes. Furthermore, the addition of divalent ions like Mg 2+ increased the rate of reaction. In in silico, structure modeling, and comparative molecular dynamics simulation studies were used to assess the protein stability and behavior at different pH and temperature conditions. The findings of this study could be applied to improve enzyme production in the industry.

Accurate prediction of protein folding mechanisms by simple structure-based statistical mechanical models

Recent breakthroughs in highly accurate protein structure prediction using deep neural networks have made considerable progress in solving the structure prediction component of the 'protein folding problem'. However, predicting detailed mechanisms of how proteins fold into specific native structures remains challenging, especially for multidomain proteins constituting most of the proteomes. Here, we develop a simple structure-based statistical mechanical model that introduces nonlocal interactions driving the folding of multidomain proteins. Our model successfully predicts protein folding processes consistent with experiments, without the limitations of protein size and shape. Furthermore, slight modifications of the model allow prediction of disulfide-oxidative and disulfide-intact protein folding. These predictions depict details of the folding processes beyond reproducing experimental results and provide a rationale for the folding mechanisms. Thus, our physics-based models enable accurate prediction of protein folding mechanisms with low computational complexity, paving the way for solving the folding process component of the 'protein folding problem'.

Computational Investigation of Mechanisms for pH Modulation of Human Chloride Channels

Many transmembrane proteins are modulated by intracellular or extracellular pH. Investigation of pH dependence generally proceeds by mutagenesis of a wide set of amino acids, guided by properties such as amino-acid conservation and structure. Prediction of pKas can streamline this process, allowing rapid and effective identification of amino acids of interest with respect to pH dependence. Commencing with the calcium-activated chloride channel bestrophin 1, the carboxylate ligand structure around calcium sites relaxes in the absence of calcium, consistent with a measured lack of pH dependence. By contrast, less relaxation in the absence of calcium in TMEM16A, and maintenance of elevated carboxylate sidechain pKas, is suggested to give rise to pH-dependent chloride channel activity. This hypothesis, modulation of calcium/proton coupling and pH-dependent activity through the extent of structural relaxation, is shown to apply to the well-characterised cytosolic proteins calmodulin (pH-independent) and calbindin D9k (pH-dependent). Further application of destabilised, ionisable charge sites, or electrostatic frustration, is made to other human chloride channels (that are not calcium-activated), ClC-2, GABAA, and GlyR. Experimentally determined sites of pH modulation are readily identified. Structure-based tools for pKa prediction are freely available, allowing users to focus on mutagenesis studies, construct hypothetical proton pathways, and derive hypotheses such as the model for control of pH-dependent calcium activation through structural flexibility. Predicting altered pH dependence for mutations in ion channel disorders can support experimentation and, ultimately, clinical intervention.

Temperature-dependent hydrogen deuterium exchange shows impact of analog binding on adenosine deaminase flexibility but not embedded thermal networks

The analysis of hydrogen deuterium exchange by mass spectrometry as a function of temperature and mutation has emerged as a generic and efficient tool for the spatial resolution of protein networks that are proposed to function in the thermal activation of catalysis. In this work, we extend temperature-dependent hydrogen deuterium exchange from apo-enzyme structures to protein-ligand complexes. Using adenosine deaminase as a prototype, we compared the impacts of a substrate analog (1-deaza-adenosine) and a very tight-binding inhibitor/transition state analog (pentostatin) at single and multiple temperatures. At a single temperature, we observed different hydrogen deuterium exchange-mass spectrometry properties for the two ligands, as expected from their 106-fold differences in strength of binding. By contrast, analogous patterns for temperature-dependent hydrogen deuterium exchange mass spectrometry emerge in the presence of both 1-deaza-adenosine and pentostatin, indicating similar impacts of either ligand on the enthalpic barriers for local protein unfolding. We extended temperature-dependent hydrogen deuterium exchange to a function-altering mutant of adenosine deaminase in the presence of pentostatin and revealed a protein thermal network that is highly similar to that previously reported for the apo-enzyme (Gao et al., 2020, JACS 142, 19936-19949). Finally, we discuss the differential impacts of pentostatin binding on overall protein flexibility versus site-specific thermal transfer pathways in the context of models for substrate-induced changes to a distributed protein conformational landscape that act in synergy with embedded protein thermal networks to achieve efficient catalysis.

Active site center redesign increases protein stability preserving catalysis in thioredoxin

The stabilization of natural proteins is a long-standing desired goal in protein engineering. Optimizing the hydrophobicity of the protein core often results in extensive stability enhancements. However, the presence of totally or partially buried catalytic charged residues, essential for protein function, has limited the applicability of this strategy. Here, focusing on the thioredoxin, we aimed to augment protein stability by removing buried charged residues in the active site without loss of catalytic activity. To this end, we performed a charged-to-hydrophobic substitution of a buried and functional group, resulting in a significant stability increase yet abolishing catalytic activity. Then, to simulate the catalytic role of the buried ionizable group, we designed a combinatorial library of variants targeting a set of seven surface residues adjacent to the active site. Notably, more than 50% of the library variants restored, to some extent, the catalytic activity. The combination of experimental study of 2% of the library with the prediction of the whole mutational space by partial least squares regression revealed that a single point mutation at the protein surface is sufficient to fully restore the catalytic activity without thermostability cost. As a result, we engineered one of the highest thermal stabilities reported for a protein with a natural occurring fold (137°C). Further, our hyperstable variant preserves the catalytic activity both in vitro and in vivo.

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.

Modification of the N-terminal FWKG-αH1 element of potyviral HC-Pro affects its multiple functions and generates effective attenuated mutants for cross-protection

Control of plant viruses by cross-protection is limited by the availability of effective protective strains. Incorporation of an NIa-protease processing site in the extreme N-terminal region of the helper component protease (HC-Pro) of turnip mosaic virus (TuMV) resulted in a mutant virus TuHN^D I that induced highly attenuated symptoms. Recombination analysis verified that two variations, F7I mutation and amino acid 7-upstream-deletion, in HC-Pro co-determined TuHN^D I attenuation. TuHN^D I provided complete protection to Nicotiana benthamiana and Brassica campestris subsp. chinensis plants against infection by the severe parental strain. Aphid transmission tests revealed that TuHN^D I was not aphid-transmissible. An RNA silencing suppression (RSS) assay by agroinfiltration suggested the RSS-defective nature of the mutant HC-Pro. In the context (amino acids 3-17) encompassing the two variations of HC-Pro, we uncovered an FWKG-α-helix 1 (αH1) element that influenced the functions of aphid transmission and RSS, whose motifs were located far downstream. We further demonstrated that HC-Pro F7 was a critical residue on αH1 for HC-Pro functions and that reinstating αH1 in the RSS-defective HC-Pro of TuHN^D I restored the protein's RSS function. Yeast two-hybrid and bimolecular fluorescence complementation assays indicated the FWKG-αH1 element as an integral part of the HC-Pro self-interaction domain. The possibility of regulation of the mechanistically independent functions of RSS and aphid transmission by the FWKG-αH1 element is discussed. Extension of TuMV HC-Pro FWKG-αH1 variations to another potyvirus, zucchini yellow mosaic virus, also generated nonaphid-transmissible cross-protective mutant viruses. Hence, the modification of the FWKG-αH1 element can generate effective attenuated viruses for the control of potyviruses by cross-protection.

The Physical Basis for pH Sensitivity in Biomolecular Structure and Function, With Application to the Spike Protein of SARS-CoV-2

Since pH sensitivity has a fundamental role in biology, much effort has been committed to establishing physical models to rationalize and predict pH dependence from molecular structures. Two of the key challenges are to accurately calculate ionizable group solvation and hydration and then to apply this modeling to all conformations relevant to the process in question. Explicit solvent methods coupled to molecular dynamics simulation are increasingly complementing lower resolution implicit solvent techniques, but equally, the scale of biological data acquisition leaves a role for high-throughput modeling. Additionally, determination of ranges of structures for a system allows sampling of key stages in solvation. In a review of the area, it is emphasized that pH sensors in biology beyond the most obvious candidate (histidine side chain, with an unshifted pK a near neutral pH) should be considered; that modeling can benefit from other concepts in bioinformatics, in particular modulation of interactions and function in families of homologs; and that it can also be beneficial to incorporate as many experimental structures as possible, to mitigate against small variations in conformation and to analyze larger, functional, conformational changes. These aspects are then demonstrated with new work on the spike protein of SARS-CoV-2, looking at the pH dependence of variants, including prediction of a change in the balance of locked, closed, and open forms at neutral pH for the Omicron variant spike protein.

Protein-sol pKa: prediction of electrostatic frustration, with application to coronaviruses

Motivation

Evolution couples differences in ambient pH to biological function through protonatable groups, in particular, those that switch from buried to exposed and alter protonation state in doing so. We present a tool focusing on structure-based discovery and display of these groups.

Results

Since prediction of buried group pKas is computationally intensive, solvent accessibility of ionizable groups is displayed, from which the user can iteratively select pKa calculation centers. Results are color-coded, with emphasis on buried groups. Utility is demonstrated with benchmarking against known pH sensing sites in influenza virus hemagglutinin and in variants of murine hepatitis virus, a coronavirus. A pair of histidine residues, which are conserved in coronavirus spike proteins, are predicted to be electrostatically frustrated at acidic pH in both pre- and post-fusion conformations. We suggest that an intermediate expanded conformation at endosomal pH could relax the frustration, allowing histidine protonation and facilitating conformational conversion of coronavirus spike protein.

Availability and implementation

This tool is available at http://www.protein-sol.manchester.ac.uk/pka/.

Protonation-Induced Dynamic Allostery in PDZ Domain: Evidence of Perturbation-Independent Universal Response Network

Dynamic allostery is a relatively new paradigm where certain external perturbations may lead to modulation of conformational dynamics at a distant part of a protein without significant changes in the overall structure. While most well-characterized examples of dynamic allostery involve binding with other entities like small molecules, peptides, or nucleic acids, in this work we demonstrate that chemical modifications like protonation may lead to significant dynamical allosteric response in a PDZ domain protein. Tuning the protonation states of two histidine residues (H317 and H372), we identify the allosteric pathways responsible for the dynamic response. Interestingly, the same set of residues that constitute the allosteric response network upon ligand binding seem to be responsible for protonation-induced dynamic allostery. Thus, we propose the existence of an inherent universal response network in signaling proteins, where the same set of residues can respond to varying types of external perturbations in terms of rearrangement of hydrogen-bonded network and redistribution of electrostatic interaction energies.

Downhill (Un)Folding Coupled to Binding as a Mechanism for Engineering Broadband Protein Conformational Transducers

Canonical proteins fold and function as conformational switches that toggle between their folded (on) and unfolded (off) states, a mechanism that also provides the basis for engineering transducers for biosensor applications. One of the limitations of such transducers, however, is their relatively narrow operational range, limited to ligand concentrations 20-fold below or above their C₅₀. Previously, we discovered that certain fast-folding proteins lose/gain structure gradually (downhill folding), which led us to postulate their operation as conformational rheostats capable of processing inputs/outputs in analog fashion. Conformational rheostats could make transducers with extended sensitivity. Here we investigate this hypothesis by engineering pH transducing into the naturally pH insensitive, downhill folding protein gpW. Particularly, we engineered histidine grafts into its hydrophobic core to induce unfolding via histidine ionization. We designed and tested the effects of ionization via computational modeling and studied experimentally the four most promising single grafts and two double grafts. All tested mutants become reversible pH transducers in the 4-9 range, and their response increases proportionally to how buried the histidine graft is. Importantly, the pH-dependent reversible (un)folding occurs in rheostatic fashion, so the engineered transducers can detect up to 6 orders of magnitude in [H⁺] for single grafts, and even more for double grafts. Our results demonstrate that downhill (un)folding coupled to binding produces the gradual, analog responses to the ligand (here H⁺) that are expected of conformational rheostats, and which make them a powerful mechanism for engineering transducers with sensitivity over many orders of magnitude in ligand concentration (broadband).

Thermodynamics and folding landscapes of large proteins from a statistical mechanical model

Statistical mechanical models that afford an intermediate resolution between macroscopic chemical models and all-atom simulations have been successful in capturing folding behaviors of many small single-domain proteins. However, the applicability of one such successful approach, the Wako-Saitô-Muñoz-Eaton (WSME) model, is limited by the size of the protein as the number of conformations grows exponentially with protein length. In this work, we surmount this size limitation by introducing a novel approximation that treats stretches of 3 or 4 residues as blocks, thus reducing the phase space by nearly three orders of magnitude. The performance of the 'bWSME' model is validated by comparing the predictions for a globular enzyme (RNase H) and a repeat protein (IκBα), against experimental observables and the model without block approximation. Finally, as a proof of concept, we predict the free-energy surface of the 370-residue, multi-domain maltose binding protein and identify an intermediate in good agreement with single-molecule force-spectroscopy measurements. The bWSME model can thus be employed as a quantitative predictive tool to explore the conformational landscapes of large proteins, extract the structural features of putative intermediates, identify parallel folding paths, and thus aid in the interpretation of both ensemble and single-molecule experiments.

A binding cooperativity switch driven by synergistic structural swelling of an osmo-regulatory protein pair

Uropathogenic E. coli experience a wide range of osmolarity conditions before and after successful infection. Stress-responsive regulatory proteins in bacteria, particularly proteins of the Hha family and H-NS, a transcription repressor, sense such osmolarity changes and regulate transcription through unknown mechanisms. Here we use an array of experimental probes complemented by molecular simulations to show that Cnu, a member of the Hha protein family, acts as an exquisite molecular sensor of solvent ionic strength. The osmosensory behavior of Cnu involves a fine-tuned modulation of disorder in the fourth helix and the three-dimensional structure in a graded manner. Order-disorder transitions in H-NS act synergistically with molecular swelling of Cnu contributing to a salt-driven switch in binding cooperativity. Thus, sensitivity to ambient conditions can be imprinted at the molecular level by tuning not just the degree of order in the protein conformational ensemble but also through population redistributions of higher-order molecular complexes.

The bacterial protein Cnu together with the transcription repressor H-NS regulate expression of virulence factors in an osmo-sensitive manner. Here authors show that the structure of Cnu swells with decreasing ionic strength driving the oligomerization of H-NS and regulating osmo-sensory response.