SCN as a local probe of protein structural dynamics.

The dynamics of lysozyme is probed by attaching -SCN to all alanine residues. The one-dimensional infrared spectra exhibit frequency shifts in the position of the maximum absorption of 4 cm-1, which is consistent with experiments in different solvents and indicates moderately strong interactions of the vibrational probe with its environment. Isotopic substitution 12C → 13C leads to a redshift by -47 cm-1, which agrees quantitatively with experiments for CN-substituted copper complexes in solution. The low-frequency, far-infrared part of the protein spectra contains label-specific information in the difference spectra when compared with the wild type protein. Depending on the position of the labels, local structural changes are observed. For example, introducing the -SCN label at Ala129 leads to breaking of the α-helical structure with concomitant change in the far-infrared spectrum. Finally, changes in the local hydration of SCN-labeled alanine residues as a function of time can be related to the reorientation of the label. It is concluded that -SCN is potentially useful for probing protein dynamics, both in the high-frequency part (CN-stretch) and in the far-infrared part of the spectrum.

Riemannian geometry for efficient analysis of protein dynamics data.

An increasingly common viewpoint is that protein dynamics datasets reside in a nonlinear subspace of low conformational energy. Ideal data analysis tools should therefore account for such nonlinear geometry. The Riemannian geometry setting can be suitable for a variety of reasons. First, it comes with a rich mathematical structure to account for a wide range of geometries that can be modeled after an energy landscape. Second, many standard data analysis tools developed for data in Euclidean space can be generalized to Riemannian manifolds. In the context of protein dynamics, a conceptual challenge comes from the lack of guidelines for constructing a smooth Riemannian structure based on an energy landscape. In addition, computational feasibility in computing geodesics and related mappings poses a major challenge. This work considers these challenges. The first part of the paper develops a local approximation technique for computing geodesics and related mappings on Riemannian manifolds in a computationally feasible manner. The second part constructs a smooth manifold and a Riemannian structure that is based on an energy landscape for protein conformations. The resulting Riemannian geometry is tested on several data analysis tasks relevant for protein dynamics data. In particular, the geodesics with given start- and end-points approximately recover corresponding molecular dynamics trajectories for proteins that undergo relatively ordered transitions with medium-sized deformations. The Riemannian protein geometry also gives physically realistic summary statistics and retrieves the underlying dimension even for large-sized deformations within seconds on a laptop.

An integrative structural study of the human full-length RAD52 at 2.2 Å resolution.

Human RAD52 (RAD52) is a DNA-binding protein involved in many DNA repair mechanisms and genomic stability maintenance. In the last few years, this protein was discovered to be a promising novel pharmacological target for anticancer strategies. Although the interest in RAD52 has exponentially grown in the previous decade, most information about its structure and mechanism still needs to be elucidated. Here, we report the 2.2 Å resolution cryo-EM reconstruction of the full-length RAD52 (FL-RAD52) protein. This allows us to describe the hydration shell of the N-terminal region of FL-RAD52, which is structured in an undecamer ring. Water molecules coordinate with protein residues to promote stabilization inside and among the protomers and within the inner DNA binding cleft to drive protein-DNA recognition. Additionally, through a multidisciplinary approach involving SEC-SAXS and computational methods, we comprehensively describe the highly flexible and dynamic organization of the C-terminal portion of FL-RAD52. This work discloses unprecedented structural details on the FL-RAD52, which will be critical for characterizing its mechanism of action and inhibitor development, particularly in the context of novel approaches to synthetic lethality and anticancer drug discovery.

Computational studies on the catalytic potential of the double active site for enzyme engineering.

Proteins possessing double active sites have the potential to revolutionise enzyme design strategies. This study extensively explored an enzyme that contains both a natural active site (NAS) and an engineered active site (EAS), focusing on understanding its structural and functional properties. Metadynamics simulations were employed to investigate how substrates interacted with their respective active sites. The results revealed that both the NAS and EAS exhibited similar minimum energy states, indicating comparable binding affinities. However, it became apparent that the EAS had a weaker binding site for the substrate due to its smaller pocket and constrained conformation. Interestingly, the EAS also displayed dynamic behaviour, with the substrate observed to move outside the pocket, suggesting the possibility of substrate translocation. To gain further insights, steered molecular dynamics (SMD) simulations were conducted to study the conformational changes of the substrate and its interactions with catalytic residues. Notably, the substrate adopted distinct conformations, including near-attack conformations, in both the EAS and NAS. Nevertheless, the NAS demonstrated superior binding minima for the substrate compared to the EAS, reinforcing the observation that the engineered active site was less favourable for substrate binding due to its limitations. The QM/MM (Quantum mechanics and molecular mechanics) analyses highlight the energy disparity between NAS and EAS. Specifically, EAS exhibited elevated energy levels due to its engineered active site being located on the surface. This positioning exposes the substrate to solvents and water molecules, adding to the energy challenge. Consequently, the engineered enzyme did not provide a significant advantage in substrate binding over the single active site protein. Further, the investigation of internal channels and tunnels within the protein shed light on the pathways facilitating transport between the two active sites. By unravelling the complex dynamics and functional characteristics of this double-active site protein, this study offers valuable insights into novel strategies of enzyme engineering. These findings establish a solid foundation for future research endeavours aimed at harnessing the potential of double-active site proteins in diverse biotechnological applications.

Rescaling protein-protein interactions improves Martini 3 for flexible proteins in solution.

Multidomain proteins with flexible linkers and disordered regions play important roles in many cellular processes, but characterizing their conformational ensembles is difficult. We have previously shown that the coarse-grained model, Martini 3, produces too compact ensembles in solution, that may in part be remedied by strengthening protein-water interactions. Here, we show that decreasing the strength of protein-protein interactions leads to improved agreement with experimental data on a wide set of systems. We show that the 'symmetry' between rescaling protein-water and protein-protein interactions breaks down when studying interactions with or within membranes; rescaling protein-protein interactions better preserves the binding specificity of proteins with lipid membranes, whereas rescaling protein-water interactions preserves oligomerization of transmembrane helices. We conclude that decreasing the strength of protein-protein interactions improves the accuracy of Martini 3 for IDPs and multidomain proteins, both in solution and in the presence of a lipid membrane.

Structural basis of adenine nucleotides regulation and neurodegenerative pathology in ClC-3 exchanger.

The ClC-3 chloride/proton exchanger is both physiologically and pathologically critical, as it is potentiated by ATP to detect metabolic energy level and point mutations in ClC-3 lead to severe neurodegenerative diseases in human. However, why this exchanger is differentially modulated by ATP, ADP or AMP and how mutations caused gain-of-function remains largely unknow. Here we determine the high-resolution structures of dimeric wildtype ClC-3 in the apo state and in complex with ATP, ADP and AMP, and the disease-causing I607T mutant in the apo and ATP-bounded state by cryo-electron microscopy. In combination with patch-clamp recordings and molecular dynamic simulations, we reveal how the adenine nucleotides binds to ClC-3 and changes in ion occupancy between apo and ATP-bounded state. We further observe I607T mutation induced conformational changes and augments in current. Therefore, our study not only lays the structural basis of adenine nucleotides regulation in ClC-3, but also clearly indicates the target region for drug discovery against ClC-3 mediated neurodegenerative diseases.

AlphaFold2-based prediction of the co-condensation propensity of proteins.

The process of protein phase separation into liquid condensates has been implicated in the formation of membraneless organelles (MLOs), which selectively concentrate biomolecules to perform essential cellular functions. Although the importance of this process in health and disease is increasingly recognized, the experimental identification of proteins forming MLOs remains a complex challenge. In this study, we addressed this problem by harnessing the power of AlphaFold2 to perform computational predictions of the conformational properties of proteins from their amino acid sequences. We thus developed the CoDropleT (co-condensation into droplet transformer) method of predicting the propensity of co-condensation of protein pairs. The method was trained by combining experimental datasets of co-condensing proteins from the CD-CODE database with curated negative datasets of non-co-condensing proteins. To illustrate the performance of the method, we applied it to estimate the propensity of proteins to co-condense into MLOs. Our results suggest that CoDropleT could facilitate functional and therapeutic studies on protein condensation by predicting the composition of protein condensates.

Comprehensive classification of TP53 somatic missense variants based on their impact on p53 structural stability.

Somatic variation is a major type of genetic variation contributing to human diseases including cancer. Of the vast quantities of somatic variants identified, the functional impact of many somatic variants, in particular the missense variants, remains unclear. Lack of the functional information prevents the translation of rich variation data into clinical applications. We previously developed a method named Ramachandran Plot-Molecular Dynamics Simulations (RP-MDS), aiming to predict the function of germline missense variants based on their effects on protein structure stability, and successfully applied to predict the deleteriousness of unclassified germline missense variants in multiple cancer genes. We hypothesized that regardless of their different genetic origins, somatic missense variants and germline missense variants could have similar effects on the stability of their affected protein structure. As such, the RP-MDS method designed for germline missense variants should also be applicable to predict the function of somatic missense variants. In the current study, we tested our hypothesis by using the somatic missense variants in TP53 as a model. Of the 397 somatic missense variants analyzed, RP-MDS predicted that 195 (49.1%) variants were deleterious as they significantly disturbed p53 structure. The results were largely validated by using a p53-p21 promoter-green fluorescent protein (GFP) reporter gene assay. Our study demonstrated that deleterious somatic missense variants can be identified by referring to their effects on protein structural stability.

Benchmarking Methods for PROTAC Ternary Complex Structure Prediction.

Proteolysis targeting chimeras (PROTACs) are bifunctional compounds that recruit an E3 ligase to a target protein to induce ubiquitination and degradation of the target. Rational optimization of PROTAC requires a structural model of the ternary complex. In the absence of an experimental structure, computational tools have emerged that attempt to predict PROTAC ternary complexes. Here, we systematically benchmark three commonly used tools: PRosettaC, MOE, and ICM. We find that these PROTAC-focused methods produce an array of ternary complex structures, including some that are observed experimentally, but also many that significantly deviate from the crystal structure. Molecular dynamics simulations show that PROTAC complexes may exist in a multiplicity of configurational states and question the use of experimentally observed structures as a reference for accurate predictions. The pioneering computational tools benchmarked here highlight the promises and challenges in the field and may be more valuable when guided by clear structural and biophysical data. The benchmarking data set that we provide may also be valuable for evaluating other and future computational tools for ternary complex modeling.

Bayesian reweighting of biomolecular structural ensembles using heterogeneous cryo-EM maps with the cryoENsemble method.

Cryogenic electron microscopy (cryo-EM) has emerged as a powerful method for the determination of structures of complex biological molecules. The accurate characterisation of the dynamics of such systems, however, remains a challenge. To address this problem, we introduce cryoENsemble, a method that applies Bayesian reweighting to conformational ensembles derived from molecular dynamics simulations to improve their agreement with cryo-EM data, thus enabling the extraction of dynamics information. We illustrate the use of cryoENsemble to determine the dynamics of the ribosome-bound state of the co-translational chaperone trigger factor (TF). We also show that cryoENsemble can assist with the interpretation of low-resolution, noisy or unaccounted regions of cryo-EM maps. Notably, we are able to link an unaccounted part of the cryo-EM map to the presence of another protein (methionine aminopeptidase, or MetAP), rather than to the dynamics of TF, and model its TF-bound state. Based on these results, we anticipate that cryoENsemble will find use for challenging heterogeneous cryo-EM maps for biomolecular systems encompassing dynamic components.

Systematic computer-aided disulfide design as a general strategy to stabilize prefusion class I fusion proteins.

Numerous enveloped viruses, such as coronaviruses, influenza, and respiratory syncytial virus (RSV), utilize class I fusion proteins for cell entry. During this process, the proteins transition from a prefusion to a postfusion state, undergoing substantial and irreversible conformational changes. The prefusion conformation has repeatedly shown significant potential in vaccine development. However, the instability of this state poses challenges for its practical application in vaccines. While non-native disulfides have been effective in maintaining the prefusion structure, identifying stabilizing disulfide bonds remains an intricate task. Here, we present a general computational approach to systematically identify prefusion-stabilizing disulfides. Our method assesses the geometric constraints of disulfide bonds and introduces a ranking system to estimate their potential in stabilizing the prefusion conformation. We hypothesized that disulfides restricting the initial stages of the conformational switch could offer higher stability to the prefusion state than those preventing unfolding at a later stage. The implementation of our algorithm on the RSV F protein led to the discovery of prefusion-stabilizing disulfides that supported our hypothesis. Furthermore, the evaluation of our top design as a vaccine candidate in a cotton rat model demonstrated robust protection against RSV infection, highlighting the potential of our approach for vaccine development.

CREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learning.

Computational and machine learning approaches to model the conformational landscape of macrocyclic peptides have the potential to enable rational design and optimization. However, accurate, fast, and scalable methods for modeling macrocycle geometries remain elusive. Recent deep learning approaches have significantly accelerated protein structure prediction and the generation of small-molecule conformational ensembles, yet similar progress has not been made for macrocyclic peptides due to their unique properties. Here, we introduce CREMP, a resource generated for the rapid development and evaluation of machine learning models for macrocyclic peptides. CREMP contains 36,198 unique macrocyclic peptides and their high-quality structural ensembles generated using the Conformer-Rotamer Ensemble Sampling Tool (CREST). Altogether, this new dataset contains nearly 31.3 million unique macrocycle geometries, each annotated with energies derived from semi-empirical extended tight-binding (xTB) DFT calculations. Additionally, we include 3,258 macrocycles with reported passive permeability data to couple conformational ensembles to experiment. We anticipate that this dataset will enable the development of machine learning models that can improve peptide design and optimization for novel therapeutics.

Evidence that the SARS-CoV-2 S protein undergoes a conformational change at the Golgi complex that leads to the formation of virus neutralising antibody binding epitopes in the S1 protein subunit.

Recombinant SARS-CoV-2 S protein expression was examined in Vero cells by imaging using the human monoclonal antibody panel (PD4, PD5, sc23, and sc29). The PD4 and sc29 antibodies recognised conformational specific epitopes in the S2 protein subunit at the Endoplasmic reticulum and Golgi complex. While PD5 and sc23 detected conformationally specific epitopes in the S1 protein subunit at the Golgi complex, only PD5 recognised the receptor binding domain (RBD). A comparison of the staining patterns of PD5 with non-conformationally specific antibodies that recognises the S1 subunit and RBD suggested the PD5 recognised a conformational structure within the S1 protein subunit. Our data suggests the antibody binding epitopes recognised by the human monoclonal antibodies formed at different locations in the secretory pathway during S protein transport, but a conformational change in the S1 protein subunit at the Golgi complex formed antibody binding epitopes that are recognised by virus neutralising antibodies.

The crystal structure of Acinetobacter baumannii bacterioferritin reveals a heteropolymer of bacterioferritin and ferritin subunits.

Iron storage proteins, e.g., vertebrate ferritin, and the ferritin-like bacterioferritin (Bfr) and bacterial ferritin (Ftn), are spherical, hollow proteins that catalyze the oxidation of Fe2+ at binuclear iron ferroxidase centers (FOC) and store the Fe3+ in their interior, thus protecting cells from unwanted Fe3+/Fe2+ redox cycling and storing iron at concentrations far above the solubility of Fe3+. Vertebrate ferritins are heteropolymers of H and L subunits with only the H subunits having FOC. Bfr and Ftn were thought to coexist in bacteria as homopolymers, but recent evidence indicates these molecules are heteropolymers assembled from Bfr and Ftn subunits. Despite the heteropolymeric nature of vertebrate and bacterial ferritins, structures have been determined only for recombinant proteins constituted by a single subunit type. Herein we report the structure of Acinetobacter baumannii bacterioferritin, the first structural example of a heteropolymeric ferritin or ferritin-like molecule, assembled from completely overlapping Ftn homodimers harboring FOC and Bfr homodimers devoid of FOC but binding heme. The Ftn homodimers function by catalyzing the oxidation of Fe2+ to Fe3+, while the Bfr homodimers bind a cognate ferredoxin (Bfd) which reduces the stored Fe3+ by transferring electrons via the heme, enabling Fe2+ mobilization to the cytosol for incorporation in metabolism.

SoDCoD: a comprehensive database of Cu/Zn superoxide dismutase conformational diversity caused by ALS-linked gene mutations and other perturbations.

A structural alteration in copper/zinc superoxide dismutase (SOD1) is one of the common features caused by amyotrophic lateral sclerosis (ALS)-linked mutations. Although a large number of SOD1 variants have been reported in ALS patients, the detailed structural properties of each variant are not well summarized. We present SoDCoD, a database of superoxide dismutase conformational diversity, collecting our comprehensive biochemical analyses of the structural changes in SOD1 caused by ALS-linked gene mutations and other perturbations. SoDCoD version 1.0 contains information about the properties of 188 types of SOD1 mutants, including structural changes and their binding to Derlin-1, as well as a set of genes contributing to the proteostasis of mutant-like wild-type SOD1. This database provides valuable insights into the diagnosis and treatment of ALS, particularly by targeting conformational alterations in SOD1. Database URL: https://fujisawagroup.github.io/SoDCoDweb/.

Differential Effects of Sequence-Local versus Nonlocal Charge Patterns on Phase Separation and Conformational Dimensions of Polyampholytes as Model Intrinsically Disordered Proteins.

Conformational properties of intrinsically disordered proteins (IDPs) are governed by a sequence-ensemble relationship. To differentiate the impact of sequence-local versus sequence-nonlocal features of an IDP's charge pattern on its conformational dimensions and its phase-separation propensity, the charge "blockiness" κ and the nonlocality-weighted sequence charge decoration (SCD) parameters are compared for their correlations with isolated-chain radii of gyration (Rgs) and upper critical solution temperatures (UCSTs) of polyampholytes modeled by random phase approximation, field-theoretic simulation, and coarse-grained molecular dynamics. SCD is superior to κ in predicting Rg because SCD accounts for effects of contact order, i.e., nonlocality, on dimensions of isolated chains. In contrast, κ and SCD are comparably good, though nonideal, predictors of UCST because frequencies of interchain contacts in the multiple-chain condensed phase are less sensitive to sequence positions than frequencies of intrachain contacts of an isolated chain, as reflected by κ correlating better with condensed-phase interaction energy than SCD.

Wet Conformation of Prion-Like Domain and Intimate Correlation of Hydration and Conformational Fluctuations.

Proteins with prion-like domains (PLDs) are involved in neurodegeneration-associated aggregation and are prevalent in liquid-like membrane-less organelles. These PLDs contain amyloidogenic stretches but can maintain dynamic disordered conformations, even in the condensed phase. However, the molecular mechanism underlying such intricate conformational properties of PLDs remains elusive. Here we employed molecular dynamics simulations to investigate the conformational properties of a prototypical PLD system (i.e., FUS PLD). According to our simulation results, PLD adopts a wet collapsed conformation, wherein most residues maintain sufficient hydration with the abundance of internal water. These internal water molecules can rapidly exchange between the protein interior and the bulk, enabling intensive coupling of the entire protein with its hydration environment. The dynamic exchange of water molecules is intimately correlated to the overall conformational fluctuations of PLD. Furthermore, the abundance of dynamic internal water suppresses the formation of aggregation-prone ordered structures. These results collectively elucidate the crucial role of internal water in sustaining the dynamic disordered conformation of the PLD and inhibiting its aggregation propensity.

Structure of the human dopamine transporter and mechanisms of inhibition.

The neurotransmitter dopamine has central roles in mood, appetite, arousal and movement1. Despite its importance in brain physiology and function, and as a target for illicit and therapeutic drugs, the human dopamine transporter (hDAT) and mechanisms by which it is inhibited by small molecules and Zn2+ are without a high-resolution structural context. Here we determine the structure of hDAT in a tripartite complex with the competitive inhibitor and cocaine analogue, (-)-2-ß-carbomethoxy-3-ß-(4-fluorophenyl)tropane2 (ß-CFT), the non-competitive inhibitor MRS72923 and Zn2+ (ref. 4). We show how ß-CFT occupies the central site, approximately halfway across the membrane, stabilizing the transporter in an outward-open conformation. MRS7292 binds to a structurally uncharacterized allosteric site, adjacent to the extracellular vestibule, sequestered underneath the extracellular loop 4 (EL4) and adjacent to transmembrane helix 1b (TM1b), acting as a wedge, precluding movement of TM1b and closure of the extracellular gate. A Zn2+ ion further stabilizes the outward-facing conformation by coupling EL4 to EL2, TM7 and TM8, thus providing specific insights into how Zn2+ restrains the movement of EL4 relative to EL2 and inhibits transport activity.

Dopamine reuptake and inhibitory mechanisms in human dopamine transporter.

The dopamine transporter has a crucial role in regulation of dopaminergic neurotransmission by uptake of dopamine into neurons and contributes to the abuse potential of psychomotor stimulants1-3. Despite decades of study, the structure, substrate binding, conformational transitions and drug-binding poses of human dopamine transporter remain unknown. Here we report structures of the human dopamine transporter in its apo state, and in complex with the substrate dopamine, the attention deficit hyperactivity disorder drug methylphenidate, and the dopamine-uptake inhibitors GBR12909 and benztropine. The dopamine-bound structure in the occluded state precisely illustrates the binding position of dopamine and associated ions. The structures bound to drugs are captured in outward-facing or inward-facing states, illuminating distinct binding modes and conformational transitions during substrate transport. Unlike the outward-facing state, which is stabilized by cocaine, GBR12909 and benztropine stabilize the dopamine transporter in the inward-facing state, revealing previously unseen drug-binding poses and providing insights into how they counteract the effects of cocaine. This study establishes a framework for understanding the functioning of the human dopamine transporter and developing therapeutic interventions for dopamine transporter-related disorders and cocaine addiction.

Benchmarking of AlphaFold2 accuracy self-estimates as indicators of empirical model quality and ranking: a comparison with independent model quality assessment programmes.

MOTIVATION: Despite an increase in protein modelling accuracy following the development of AlphaFold2, there remains an accuracy gap between predicted and observed model quality assessment (MQA) scores. In CASP15, variations in AlphaFold2 model accuracy prediction were noticed for quaternary models of very similar observed quality. In this study, we compare plDDT and pTM to their observed counterparts the local distance difference test (lDDT) and TM-score for both tertiary and quaternary models to examine whether reliability is retained across the scoring range under normal modelling conditions and in situations where AlphaFold2 functionality is customized. We also explore plDDT and pTM ranking accuracy in comparison with the published independent MQA programmes ModFOLD9 and ModFOLDdock. RESULTS: plDDT was found to be an accurate descriptor of tertiary model quality compared to observed lDDT-Cα scores (Pearson r = 0.97), and achieved a ranking agreement true positive rate (TPR) of 0.34 with observed scores, which ModFOLD9 could not improve. However, quaternary structure accuracy was reduced (plDDT r = 0.67, pTM r = 0.70) and significant overprediction was seen with both scores for some lower quality models. Additionally, ModFOLDdock was able to improve upon AF2-Multimer model ranking compared to TM-score (TPR 0.34) and oligo-lDDT score (TPR 0.43). Finally, evidence is presented for increased variability in plDDT and pTM when using custom template recycling, which is more pronounced for quaternary structures. AVAILABILITY AND IMPLEMENTATION: The ModFOLD9 and ModFOLDdock quality assessment servers are available at https://www.reading.ac.uk/bioinf/ModFOLD/ and https://www.reading.ac.uk/bioinf/ModFOLDdock/, respectively. A docker image is available at https://hub.docker.com/r/mcguffin/multifold.