Farnesyltransferase inhibitor lonafarnib suppresses respiratory syncytial virus infection by blocking conformational change of fusion glycoprotein.

Respiratory syncytial virus (RSV) is the major cause of bronchiolitis and pneumonia in young children and the elderly. There are currently no approved RSV-specific therapeutic small molecules available. Using high-throughput antiviral screening, we identified an oral drug, the prenylation inhibitor lonafarnib, which showed potent inhibition of the RSV fusion process. Lonafarnib exhibited antiviral activity against both the RSV A and B genotypes and showed low cytotoxicity in HEp-2 and human primary bronchial epithelial cells (HBEC). Time-of-addition and pseudovirus assays demonstrated that lonafarnib inhibits RSV entry, but has farnesyltransferase-independent antiviral efficacy. Cryo-electron microscopy revealed that lonafarnib binds to a triple-symmetric pocket within the central cavity of the RSV F metastable pre-fusion conformation. Mutants at the RSV F sites interacting with lonafarnib showed resistance to lonafarnib but remained fully sensitive to the neutralizing monoclonal antibody palivizumab. Furthermore, lonafarnib dose-dependently reduced the replication of RSV in BALB/c mice. Collectively, lonafarnib could be a potential fusion inhibitor for RSV infection.

High-throughput structure determination of an intrinsically disordered protein using cell-free protein crystallization.

Intrinsically disordered proteins (IDPs) play a crucial role in various biological phenomena, dynamically changing their conformations in response to external environmental cues. To gain a deeper understanding of these proteins, it is essential to identify the determinants that fix their structures at the atomic level. Here, we developed a pipeline for rapid crystal structure analysis of IDP using a cell-free protein crystallization (CFPC) method. Through this approach, we successfully demonstrated the determination of the structure of an IDP to uncover the key determinants that stabilize its conformation. Specifically, we focused on the 11-residue fragment of c-Myc, which forms an α-helix through dimerization with a binding partner protein. This fragment was strategically recombined with an in-cell crystallizing protein and was expressed in a cell-free system. The resulting crystal structures of the c-Myc fragment were successfully determined at a resolution of 1.92 Å and we confirmed that they are identical to the structures of the complex with the native binding partner protein. This indicates that the environment of the scaffold crystal can fix the structure of c-Myc. Significantly, these crystals were obtained directly from a small reaction mixture (30 µL) incubated for only 72 h. Analysis of eight crystal structures derived from 22 mutants revealed two hydrophobic residues as the key determinants responsible for stabilizing the α-helical structure. These findings underscore the power of our CFPC screening method as a valuable tool for determining the structures of challenging target proteins and elucidating the essential molecular interactions that govern their stability.

GATSol, an enhanced predictor of protein solubility through the synergy of 3D structure graph and large language modeling.

BACKGROUND: Protein solubility is a critically important physicochemical property closely related to protein expression. For example, it is one of the main factors to be considered in the design and production of antibody drugs and a prerequisite for realizing various protein functions. Although several solubility prediction models have emerged in recent years, many of these models are limited to capturing information embedded in one-dimensional amino acid sequences, resulting in unsatisfactory predictive performance. RESULTS: In this study, we introduce a novel Graph Attention network-based protein Solubility model, GATSol, which represents the 3D structure of proteins as a protein graph. In addition to the node features of amino acids extracted by the state-of-the-art protein large language model, GATSol utilizes amino acid distance maps generated using the latest AlphaFold technology. Rigorous testing on independent eSOL and the Saccharomyces cerevisiae test datasets has shown that GATSol outperforms most recently introduced models, especially with respect to the coefficient of determination R2, which reaches 0.517 and 0.424, respectively. It outperforms the current state-of-the-art GraphSol by 18.4% on the S. cerevisiae_test set. CONCLUSIONS: GATSol captures 3D dimensional features of proteins by building protein graphs, which significantly improves the accuracy of protein solubility prediction. Recent advances in protein structure modeling allow our method to incorporate spatial structure features extracted from predicted structures into the model by relying only on the input of protein sequences, which simplifies the entire graph neural network prediction process, making it more user-friendly and efficient. As a result, GATSol may help prioritize highly soluble proteins, ultimately reducing the cost and effort of experimental work. The source code and data of the GATSol model are freely available at https://github.com/binbinbinv/GATSol .

Conformational Dynamic Studies of Prokaryotic Potassium Channels Explored by Homo-FRET Methodologies.

Fluorescence techniques have been widely used to shed light over the structure-function relationship of potassium channels for the last 40-50 years. In this chapter, we describe how a Förster resonance energy transfer between identical fluorophores (homo-FRET) approach can be applied to study the gating behavior of the prokaryotic channel KcsA. Two different gates have been described to control the K+ flux across the channel's pore, the helix-bundle crossing and the selectivity filter, located at the opposite sides of the channel transmembrane section. Both gates can be studied individually or by using a double-reporter system. Due to its homotetrameric structural arrangement, KcsA presents a high degree of symmetry that fulfills the first requisite to calculate intersubunit distances through this technique. The results obtained through this work have helped to uncover the conformational plasticity of the selectivity filter under different experimental conditions and the importance of its allosteric coupling to the opening of the activation (inner) gate. This biophysical approach usually requires low protein concentration and presents high sensitivity and reproducibility, complementing the high-resolution structural information provided by X-ray crystallography, cryo-EM, and NMR studies.

Human Kir2.1 Potassium Channel: Protocols for Cryo-EM Data Processing and Molecular Dynamics Simulations.

Kir channels are potassium (K+) channels responsible for the mechanism of inward rectification, which plays a fundamental role in maintaining the resting membrane potential. There are seven Kir subfamilies, and their opening and closing mechanism is regulated by different regulatory factors. Genetically inherited defects in Kir channels are responsible for several rare human diseases, and for most of them, there are currently no effective therapeutic treatments. High-resolution structural information is not available for several members within the Kir subfamilies. Recently, our group achieved a significant breakthrough by utilizing cryo-EM single-particle analysis to elucidate the first structure of the human Kir2.1 channel. We present here the data processing protocol of the cryo-EM data of the human Kir2.1 channel, which is applicable to the structural determination of other ion channels by cryo-EM single-particle analysis. We also introduce a protocol designed to assess the structural heterogeneity within the cryo-EM data, allowing for the identification of other possible protein structure conformations present in the collected data. Moreover, we present a protocol for conducting all-atom molecular dynamics (MD) simulations for K+ channels, which can be incorporated into various membrane models to simulate different environments. We also propose some methods for analyzing the MD simulations, with a particular emphasis on assessing the local mobility of protein residues.

Kinetics and mapping of Ca-driven calmodulin conformations on skeletal and cardiac muscle ryanodine receptors.

Calmodulin transduces [Ca2+] information regulating the rhythmic Ca2+ cycling between the sarcoplasmic reticulum and cytoplasm during contraction and relaxation in cardiac and skeletal muscle. However, the structural dynamics by which calmodulin modulates the sarcoplasmic reticulum Ca2+ release channel, the ryanodine receptor, at physiologically relevant [Ca2+] is unknown. Using fluorescence lifetime FRET, we resolve different structural states of calmodulin and Ca2+-driven shifts in the conformation of calmodulin bound to ryanodine receptor. Skeletal and cardiac ryanodine receptor isoforms show different calmodulin-ryanodine receptor conformations, as well as binding and structural kinetics with 0.2-ms resolution, which reflect different functional roles of calmodulin. These FRET methods provide insight into the physiological calmodulin-ryanodine receptor structural states, revealing additional distinct structural states that complement cryo-EM models that are based on less physiological conditions. This technology will drive future studies on pathological calmodulin-ryanodine receptor interactions and dynamics with other important ryanodine receptor bound modulators.

Structures of wild-type and a constitutively closed mutant of connexin26 shed light on channel regulation by CO2.

Connexins allow intercellular communication by forming gap junction channels (GJCs) between juxtaposed cells. Connexin26 (Cx26) can be regulated directly by CO2. This is proposed to be mediated through carbamylation of K125. We show that mutating K125 to glutamate, mimicking the negative charge of carbamylation, causes Cx26 GJCs to be constitutively closed. Through cryo-EM we observe that the K125E mutation pushes a conformational equilibrium towards the channel having a constricted pore entrance, similar to effects seen on raising the partial pressure of CO2. In previous structures of connexins, the cytoplasmic loop, important in regulation and where K125 is located, is disordered. Through further cryo-EM studies we trap distinct states of Cx26 and observe density for the cytoplasmic loop. The interplay between the position of this loop, the conformations of the transmembrane helices and the position of the N-terminal helix, which controls the aperture to the pore, provides a mechanism for regulation.

FoldPAthreader: predicting protein folding pathway using a novel folding force field model derived from known protein universe.

Protein folding has become a tractable problem with the significant advances in deep learning-driven protein structure prediction. Here we propose FoldPAthreader, a protein folding pathway prediction method that uses a novel folding force field model by exploring the intrinsic relationship between protein evolution and folding from the known protein universe. Further, the folding force field is used to guide Monte Carlo conformational sampling, driving the protein chain fold into its native state by exploring potential intermediates. On 30 example targets, FoldPAthreader successfully predicts 70% of the proteins whose folding pathway is consistent with biological experimental data.

Role of N343 glycosylation on the SARS-CoV-2 S RBD structure and co-receptor binding across variants of concern.

Glycosylation of the SARS-CoV-2 spike (S) protein represents a key target for viral evolution because it affects both viral evasion and fitness. Successful variations in the glycan shield are difficult to achieve though, as protein glycosylation is also critical to folding and structural stability. Within this framework, the identification of glycosylation sites that are structurally dispensable can provide insight into the evolutionary mechanisms of the shield and inform immune surveillance. In this work, we show through over 45 µs of cumulative sampling from conventional and enhanced molecular dynamics (MD) simulations, how the structure of the immunodominant S receptor binding domain (RBD) is regulated by N-glycosylation at N343 and how this glycan's structural role changes from WHu-1, alpha (B.1.1.7), and beta (B.1.351), to the delta (B.1.617.2), and omicron (BA.1 and BA.2.86) variants. More specifically, we find that the amphipathic nature of the N-glycan is instrumental to preserve the structural integrity of the RBD hydrophobic core and that loss of glycosylation at N343 triggers a specific and consistent conformational change. We show how this change allosterically regulates the conformation of the receptor binding motif (RBM) in the WHu-1, alpha, and beta RBDs, but not in the delta and omicron variants, due to mutations that reinforce the RBD architecture. In support of these findings, we show that the binding of the RBD to monosialylated ganglioside co-receptors is highly dependent on N343 glycosylation in the WHu-1, but not in the delta RBD, and that affinity changes significantly across VoCs. Ultimately, the molecular and functional insight we provide in this work reinforces our understanding of the role of glycosylation in protein structure and function and it also allows us to identify the structural constraints within which the glycosylation site at N343 can become a hotspot for mutations in the SARS-CoV-2 S glycan shield.

Targeting the protein folding transition state by mutation: Large scale (un)folding rate accelerations without altering native stability.

Proteins are constantly undergoing folding and unfolding transitions, with rates that determine their homeostasis in vivo and modulate their biological function. The ability to optimize these rates without affecting overall native stability is hence highly desirable for protein engineering and design. The great challenge is, however, that mutations generally affect folding and unfolding rates with inversely complementary fractions of the net free energy change they inflict on the native state. Here we address this challenge by targeting the folding transition state (FTS) of chymotrypsin inhibitor 2 (CI2), a very slow and stable two-state folding protein with an FTS known to be refractory to change by mutation. We first discovered that the CI2's FTS is energetically taxed by the desolvation of several, highly conserved, charges that form a buried salt bridge network in the native structure. Based on these findings, we designed a CI2 variant that bears just four mutations and aims to selectively stabilize the FTS. This variant has >250-fold faster rates in both directions and hence identical native stability, demonstrating the success of our FTS-centric design strategy. With an optimized FTS, CI2 also becomes 250-fold more sensitive to proteolytic degradation by its natural substrate chymotrypsin, and completely loses its activity as inhibitor. These results indicate that CI2 has been selected through evolution to have a very unstable FTS in order to attain the kinetic stability needed to effectively function as protease inhibitor. Moreover, the CI2 case showcases that protein (un)folding rates can critically pivot around a few key residues-interactions, which can strongly modify the general effects of known structural factors such as domain size and fold topology. From a practical standpoint, our results suggest that future efforts should perhaps focus on identifying such critical residues-interactions in proteins as best strategy to significantly improve our ability to predict and engineer protein (un)folding rates.

Structural study for substrate recognition of human N-terminal glutamine amidohydrolase 1 in the arginine N-degron pathway.

The N-degron pathway determines the half-life of proteins by selectively destabilizing the proteins bearing N-degrons. N-terminal glutamine amidohydrolase 1 (NTAQ1) plays an essential role in the arginine N-degron (Arg/N-degron) pathway as an initializing enzyme via the deamidation of the N-terminal (Nt) glutamine (Gln). However, the Nt-serine-bound conformation of hNTAQ1 according to the previously identified crystal structure suggests the possibility of other factors influencing the recognition of Nt residues by hNTAQ1. Hence, in the current study, we aimed to further elucidate the substrate recognition of hNTAQ1; specifically, we explored 12 different substrate-binding conformations of hNTAQ1 depending on the subsequent residue of Nt-Gln. Results revealed that hNTAQ1 primarily interacts with the protein Nt backbone, instead of the side chain, for substrate recognition. Here, we report that the Nt backbone of proteins appears to be a key component of hNTAQ1 function and is the main determinant of substrate recognition. Moreover, not all second residues from Nt-Gln, but rather distinctive and charged residues, appeared to aid in detecting substrate recognition. These new findings define the substrate-recognition process of hNTAQ1 and emphasize the importance of the subsequent Gln residue in the Nt-Gln degradation system. Our extensive structural and biochemical analyses provide insights into the substrate specificity of the N-degron pathway and shed light on the mechanism underlying hNTAQ1 substrate recognition. An improved understanding of the protein degradation machinery could aid in developing therapies to promote overall health through enhanced protein regulation, such as targeted protein therapies.

Temperature-dependent structural changes in xylanase II from Trichoderma longibrachiatum.

Endo-ß-1,4-xylanases degrade heteroxylans that constitute the lignocellulosic plant cell wall. This enzyme is widely used in the food, paper, textile, and biorefinery industries. Temperature affects the optimum activity of xylanase and is an important factor in its application. Various structural analyses of xylanase have been performed, but its structural influence by temperature is not fully elucidated. To better understand the structural influence of xylanase due to temperature, the crystal structure of xylanase II from Trichoderma longibrachiatum (TloXynII) at room and cryogenic temperatures was determined at 2.1 and 1.9 Å resolution, respectively. The room-temperature structure of TloXynII (TloXynIIRT) showed a B-factor value 2.09 times higher than that of the cryogenic-temperature structure of TloXynII (TloXynIICryo). Subtle movement of the catalytic and substrate binding residues was observed between TloXynIIRT and TloXynIICryo. In TloXynIIRT, the thumb domain exhibited high flexibility, whereas in TloXynIICryo, the finger domain exhibited high flexibility. The substrate binding cleft of TloXynIIRT was narrower than that of TloXynIICryo, indicating a distinct finger domain conformation. Numerous water molecule networks were observed in the substrate binding cleft of TloXynIICryo, whereas only a few water molecules were observed in TloXynIIRT. These structural analyses expand our understanding of the temperature-dependent conformational changes in xylanase.

CLEAPA: a framework for exploring the conformational landscape of cryo-EM using energy-aware pathfinding algorithm.

MOTIVATION: Cryo-electron microscopy (cryo-EM) is a powerful technique for studying macromolecules and holds the potential for identifying kinetically preferred transition sequences between conformational states. Typically, these sequences are explored within two-dimensional energy landscapes. However, due to the complexity of biomolecules, representing conformational changes in two dimensions can be challenging. Recent advancements in reconstruction models have successfully extracted structural heterogeneity from cryo-EM images using higher-dimension latent space. Nonetheless, creating high-dimensional conformational landscapes in the latent space and then searching for preferred paths continues to be a formidable task. RESULTS: This study introduces an innovative framework for identifying preferred trajectories within high-dimensional conformational landscapes. Our method encompasses the search for the minimum energy path in the graph, where edge weights are determined based on the energy estimation at each node using local density. The effectiveness of this approach is demonstrated by identifying accurate transition states in both synthetic and real-world datasets featuring continuous conformational changes. AVAILABILITY AND IMPLEMENTATION: The CLEAPA package is available at https://github.com/tengyulin/energy_aware_pathfinding/.

Inhibition and transport mechanisms of the ABC transporter hMRP5.

Human multidrug resistance protein 5 (hMRP5) effluxes anticancer and antivirus drugs, driving multidrug resistance. To uncover the mechanism of hMRP5, we determine six distinct cryo-EM structures, revealing an autoinhibitory N-terminal peptide that must dissociate to permit subsequent substrate recruitment. Guided by these molecular insights, we design an inhibitory peptide that could block substrate entry into the transport pathway. We also identify a regulatory motif, comprising a positively charged cluster and hydrophobic patches, within the first nucleotide-binding domain that modulates hMRP5 localization by engaging with membranes. By integrating our structural, biochemical, computational, and cell biological findings, we propose a model for hMRP5 conformational cycling and localization. Overall, this work provides mechanistic understanding of hMRP5 function, while informing future selective hMRP5 inhibitor development. More broadly, this study advances our understanding of the structural dynamics and inhibition of ABC transporters.

Molecular surface descriptors to predict antibody developability: sensitivity to parameters, structure models, and conformational sampling.

In silico assessment of antibody developability during early lead candidate selection and optimization is of paramount importance, offering a rapid and material-free screening approach. However, the predictive power and reproducibility of such methods depend heavily on the selection of molecular descriptors, model parameters, accuracy of predicted structure models, and conformational sampling techniques. Here, we present a set of molecular surface descriptors specifically designed for predicting antibody developability. We assess the performance of these descriptors by benchmarking their correlations with an extensive array of experimentally determined biophysical properties, including viscosity, aggregation, hydrophobic interaction chromatography, human pharmacokinetic clearance, heparin retention time, and polyspecificity. Further, we investigate the sensitivity of these surface descriptors to methodological nuances, such as the choice of interior dielectric constant, hydrophobicity scales, structure prediction methods, and the impact of conformational sampling. Notably, we observe systematic shifts in the distribution of surface descriptors depending on the structure prediction method used, driving weak correlations of surface descriptors across structure models. Averaging the descriptor values over conformational distributions from molecular dynamics mitigates the systematic shifts and improves the consistency across different structure prediction methods, albeit with inconsistent improvements in correlations with biophysical data. Based on our benchmarking analysis, we propose six in silico developability risk flags and assess their effectiveness in predicting potential developability issues for a set of case study molecules.

Watching atomically resolved structural dynamics-Blinded by the light.

In a recent issue of Nature, Barends et al.1 studied the photodissociation of carboxymyoglobin with ultrafast laser pump-probe serial femtosecond crystallography experiments. They observed significant differences in heme protein structural dynamics for biologically relevant 1-photon excitation relative to high excitation leading to the absorption of several photons per heme.

Folding the human proteome using BioNeMo: A fused dataset of structural models for machine learning purposes.

Human proteins are crucial players in both health and disease. Understanding their molecular landscape is a central topic in biological research. Here, we present an extensive dataset of predicted protein structures for 42,042 distinct human proteins, including splicing variants, derived from the UniProt reference proteome UP000005640. To ensure high quality and comparability, the dataset was generated by combining state-of-the-art modeling-tools AlphaFold 2, OpenFold, and ESMFold, provided within NVIDIA's BioNeMo platform, as well as homology modeling using Innophore's CavitomiX platform. Our dataset is offered in both unedited and edited formats for diverse research requirements. The unedited version contains structures as generated by the different prediction methods, whereas the edited version contains refinements, including a dataset of structures without low prediction-confidence regions and structures in complex with predicted ligands based on homologs in the PDB. We are confident that this dataset represents the most comprehensive collection of human protein structures available today, facilitating diverse applications such as structure-based drug design and the prediction of protein function and interactions.

Structural and functional insights into the C-terminal signal domain of the Bacteroidetes type-IX secretion system.

Gram-negative bacteria from the Bacteroidota phylum possess a type-IX secretion system (T9SS) for protein secretion, which requires cargoes to have a C-terminal domain (CTD). Structurally analysed CTDs are from Porphyromonas gingivalis proteins RgpB, HBP35, PorU and PorZ, which share a compact immunoglobulin-like antiparallel 3+4 ß-sandwich (ß1-ß7). This architecture is essential as a P. gingivalis strain with a single-point mutant of RgpB disrupting the interaction of the CTD with its preceding domain prevented secretion of the protein. Next, we identified the C-terminus ('motif C-t.') and the loop connecting strands ß3 and ß4 ('motif Lß3ß4') as conserved. We generated two strains with insertion and replacement mutants of PorU, as well as three strains with ablation and point mutants of RgpB, which revealed both motifs to be relevant for T9SS function. Furthermore, we determined the crystal structure of the CTD of mirolase, a cargo of the Tannerella forsythia T9SS, which shares the same general topology as in Porphyromonas CTDs. However, motif Lß3ß4 was not conserved. Consistently, P. gingivalis could not properly secrete a chimaeric protein with the CTD of peptidylarginine deiminase replaced with this foreign CTD. Thus, the incompatibility of the CTDs between these species prevents potential interference between their T9SSs.

An α-ketoglutarate conformational switch controls iron accessibility, activation, and substrate selection of the human FTO protein.

The fat mass and obesity-associated fatso (FTO) protein is a member of the Alkb family of dioxygenases and catalyzes oxidative demethylation of N6-methyladenosine (m6A), N1-methyladenosine (m1A), 3-methylthymine (m3T), and 3-methyluracil (m3U) in single-stranded nucleic acids. It is well established that the catalytic activity of FTO proceeds via two coupled reactions. The first reaction involves decarboxylation of alpha-ketoglutarate (αKG) and formation of an oxyferryl species. In the second reaction, the oxyferryl intermediate oxidizes the methylated nucleic acid to reestablish Fe(II) and the canonical base. However, it remains unclear how binding of the nucleic acid activates the αKG decarboxylation reaction and why FTO demethylates different methyl modifications at different rates. Here, we investigate the interaction of FTO with 5-mer DNA oligos incorporating the m6A, m1A, or m3T modifications using solution NMR, molecular dynamics (MD) simulations, and enzymatic assays. We show that binding of the nucleic acid to FTO activates a two-state conformational equilibrium in the αKG cosubstrate that modulates the O2 accessibility of the Fe(II) catalyst. Notably, the substrates that provide better stabilization to the αKG conformation in which Fe(II) is exposed to O2 are demethylated more efficiently by FTO. These results indicate that i) binding of the methylated nucleic acid is required to expose the catalytic metal to O2 and activate the αKG decarboxylation reaction, and ii) the measured turnover of the demethylation reaction (which is an ensemble average over the entire sample) depends on the ability of the methylated base to favor the Fe(II) state accessible to O2.

Two distinct archaeal type IV pili structures formed by proteins with identical sequence.

Type IV pili (T4P) represent one of the most common varieties of surface appendages in archaea. These filaments, assembled from small pilin proteins, can be many microns long and serve diverse functions, including adhesion, biofilm formation, motility, and intercellular communication. Here, we determine atomic structures of two distinct adhesive T4P from Saccharolobus islandicus via cryo-electron microscopy (cryo-EM). Unexpectedly, both pili were assembled from the same pilin polypeptide but under different growth conditions. One filament, denoted mono-pilus, conforms to canonical archaeal T4P structures where all subunits are equivalent, whereas in the other filament, the tri-pilus, the same polypeptide exists in three different conformations. The three conformations in the tri-pilus are very different from the single conformation found in the mono-pilus, and involve different orientations of the outer immunoglobulin-like domains, mediated by a very flexible linker. Remarkably, the outer domains rotate nearly 180° between the mono- and tri-pilus conformations. Both forms of pili require the same ATPase and TadC-like membrane pore for assembly, indicating that the same secretion system can produce structurally very different filaments. Our results show that the structures of archaeal T4P appear to be less constrained and rigid than those of the homologous archaeal flagellar filaments that serve as helical propellers.