High-resolution comparative modeling with RosettaCM

One HA stalk topping multiple heads as a novel influenza vaccine

Classic chimeric hemagglutinin (cHA) was designed to induce immune responses against the conserved stalk domain of HA. However, it is unclear whether combining more than one HA head domain onto one stalk domain is immunogenic and further induce immune responses against influenza viruses. Here, we constructed numerous novel cHAs comprising two or three fuzed head domains from different subtypes grafted onto one stalk domain, designated as cH1-H3, cH1-H7, cH1-H3-H7, and cH1-H7-H3. The three-dimensional structures of these novel cHAs were modelled using bioinformatics simulations. Structural analysis showed that the intact neutralizing epitopes were exposed in cH1-H7 and were predicted to be immunogenic. The immunogenicity of the cHAs constructs was evaluated in mice using a chimpanzee adenoviral vector (AdC68) vaccine platform. The results demonstrated that cH1-H7 expressed by AdC68 (AdC68-cH1-H7) induced the production of high levels of binding antibodies, neutralizing antibodies, and hemagglutinin inhibition antibodies against homologous pandemic H1N1, drifted seasonal H1N1, and H7N9 virus. Moreover, vaccinated mice were fully protected from a lethal challenge with the aforementioned influenza viruses. Hence, cH1-H7 cHAs with potent immunogenicity might be a potential novel vaccine to provide protection against different subtypes of influenza virus.

Functional characterization of a cystatin A from the bat Myotis davidii

Myotis davidii cystatin A (MdCSTA), a stefin A-like from the Chinese native bat species M. davidii, was expressed as a recombinant protein and functionally characterized as a strong inhibitor of the cysteine proteases papain, human cathepsins L and B and the tick cathepsin L-like BmCL1. Despite the highly conserved amino acid sequences among stefins A from different vertebrates, MdCSTA presents a Methionine-2 residue at the N-terminal region and the second binding loop (pos 73-79) that differs from human stefin A (HsCSTA) and might be related to the lower inhibition constant (Ki) value presented by this inhibitor in comparison to human stefin A inhibition to cathepsin B. Therefore, to investigate the importance of these variable regions in cathepsin B inhibition, recombinant stefins A MdCSTA and HsCSTA containing mutations at the second amino acid residue and second binding loop were expressed and evaluated in kinetic assays. Enzymatic inhibition assays with cathepsin B revealed that switching the amino acid residues at position 2 and second binding loop region between bat and human CSTAs improved the HsCSTA's and reduced MdCSTA's inhibitory activity. Additionally, molecular docking analysis estimated lower energy values for the complex between MdCSTA-cathepsin B, in comparison to human CSTA-cathepsin B, while the mutants presented intermediate values, suggesting that other regions might contribute to the higher inhibitory activity against cathepsin B by MdCSTA. In conclusion, MdCSTA, the first bat's stefin A-like inhibitor to be functionally characterized, presented a higher inhibitory activity against cathepsin B in comparison to the human inhibitor, which is partially related to the glutamine-rich second binding loop and Met-2. Further structural analysis should be performed to elucidate potential inhibitor effects on cysteine proteinases.

Structure of anellovirus-like particles reveal a mechanism for immune evasion

Anelloviruses are nonpathogenic viruses that comprise a major portion of the human virome. Despite being ubiquitous in the human population, anelloviruses (ANVs) remain poorly understood. Basic features of the virus, such as the identity of its capsid protein and the structure of the viral particle, have been unclear until now. Here, we use cryogenic electron microscopy to describe the first structure of an ANV-like particle. The particle, formed by 60 jelly roll domain-containing ANV capsid proteins, forms an icosahedral particle core from which spike domains extend to form a salient part of the particle surface. The spike domains come together around the 5-fold symmetry axis to form crown-like features. The base of the spike domain, the P1 subdomain, shares some sequence conservation between ANV strains while a hypervariable region, forming the P2 subdomain, is at the spike domain apex. We propose that this structure renders the particle less susceptible to antibody neutralization by hiding vulnerable conserved domains while exposing highly diverse epitopes as immunological decoys, thereby contributing to the immune evasion properties of anelloviruses. These results shed light on the structure of anelloviruses and provide a framework to understand their interactions with the immune system.

Characterization of a Novel Monoclonal Antibody with High Affinity and Specificity against Aflatoxins: A Discovery from Rosetta Antibody-Ligand Computational Simulation

Aflatoxin B1 (AFB1) accumulates in crops, where it poses a threat to human health. To detect AFB1, anti-AFB1 monoclonal antibodies have been developed and are widely used. While the sensitivity and specificity of these antibodies have been extensively studied, information regarding the atomic-level docking of AFB1 (and its derivatives) with these antibodies is limited. Such information is crucial for understanding the key interactions that are required for high affinity and specificity in aflatoxin binding. First, a 3D comparative model of anti-AFB1 antibody (Ab-4B5G6) was predicted from the sequence using RosettaAntibody. We then utilized RosettaLigand to dock AFB1 onto ten homology models, producing a total of 10,000 binding modes. Interestingly, the best-scoring mode predicted strong interactions involving four sites within the heavy chain: ALA33, ASN52, HIS95, and TRP99. Importantly, these strong binding interactions exclusively involve the variable domain of the heavy chain. The best-scoring mode with AFB1 was also obtained through AF multimer combined with RosettaLigand, and two interactions at TRP and HIS were consistent with those found by Rosetta antibody-ligand computational simulation. The role of tryptophan in π interactions in antibodies was confirmed through mutation experiments, and the resulting mutant (W99A) exhibited a >1000-fold reduction in binding affinity for AFB1 and analogs, indicating the effect of tryptophan on the stability of CDR-H3 region. Additionally, we evaluated the binding of two glycolic acid-derived molecular derivatives (with impaired hydrogen bonding potential), and these derivatives (AFB2-GA and AFG2-GA) demonstrated a very weak binding affinity for Ab-4B5G6. The heavy chain was successfully isolated, and its sensitivity and specificity were consistent with those of the intact antibody. The homology models of variable heavy (VH) single-domain antibodies were established by RosettaAntibody, and the docking analysis revealed the same residues, including Ala, His, and Trp. Compared to the potential binding mode of fragment variable (FV) region, the results from a model of VH indicated that there are seven models involved in hydrophobic interaction with TYR32, which is usually referred to as polar amino acid and has both hydrophobic and hydrophilic features depending on the circumstances. Our work encompasses the entire process of Rosetta antibody-ligand computational simulation, highlighting the significance of variable heavy domain structural design in enhancing molecular interactions.

Possibility of two-dimensional ordering of cryptochrome 4a from European robin

Cryptochrome (Cry) in some species could act as a quantum senser to detect the inclination angle of geomagnetic field, the function of which attributes the magnetic sensitivity of spins of unpaired electrons in radical pair (RP) in CRY generated by blue light irradiation. However, the effect of blue light on the structure and molecular behavior of Cry has not been well investigated. We conducted the size exclusion chromatography (SEC) and small-angle X-ray scattering (SAXS) analyses to inspect the molecular structure and behavior of cryptochrome 4a (ErCry4a) from European robin, a representative magnetosensory animal. The results indicated that ErCry4a could form flat-shape oligomers. Moreover, blue light irradiation induced the contraction of the ErCry4a molecule at the monomer scale and simultaneously accelerated the two-dimensional oligomerization of ErCry4a. This oligomerization may enhance the regularity of the two-dimensional arrangement of ErCry4a molecules, providing a positive effect for detecting the inclination angle.

Effect of E134K pathogenic mutation of SMN protein on SMN-SmD1 interaction, with implication in spinal muscular atrophy: A molecular dynamics study

Spinal muscular atrophy (SMA) is a disease that results from mutations in the Survival of Motor Neuron (SMN) gene 1, leading to muscle atrophy due to motor neurons degeneration. SMN plays a crucial role in the assembly of spliceosomal small nuclear ribonucleoprotein complexes via binding to the arginine-glycine rich C-terminal tails of Sm proteins recognized by SMN Tudor domain. E134K Tudor mutation, cause of the more severe type I SMA, compromises the SMN-Sm interaction without a perturbation of the domain fold. By molecular dynamics simulations, we investigated the mechanism of Tudor-SmD1 interaction, and the effects on it of E134K mutation. It was observed that E134 is crucial to catch the positive dimethylated arginines (DMRs) of the SmD1 tail that, wrapping around the acidic Tudor surface, enters a central DMR into an aromatic cage. The flexible cage residue Y130 must be blocked from the wrapped tail to assure a stable binding. The charge inversion in E134K mutation causes the loss of a critical anchor point, disfavoring the tail wrapping and leaving Y130 free to swing, leading to DMR detachments and exposition of the C-terminal region of the tail. This could suggest new hypotheses regarding a possible autoimmune response by anti-Sm autoantibodies.

Spotlight on plasticity-related genes: Current insights in health and disease

The development of the central nervous system is highly complex, involving numerous developmental processes that must take place with high spatial and temporal precision. This requires a series of complex and well-coordinated molecular processes that are tighly controlled and regulated by, for example, a variety of proteins and lipids. Deregulations in these processes, including genetic mutations, can lead to the most severe maldevelopments. The present review provides an overview of the protein family Plasticity-related genes (PRG1-5), including their role during neuronal differentiation, their molecular interactions, and their participation in various diseases. As these proteins can modulate the function of bioactive lipids, they are able to influence various cellular processes. Furthermore, they are dynamically regulated during development, thus playing an important role in the development and function of synapses. First studies, conducted not only in mouse experiments but also in humans, revealed that mutations or dysregulations of these proteins lead to changes in lipid metabolism, resulting in severe neurological deficits. In recent years, as more and more studies have shown their involvement in a broad range of diseases, the complexity and broad spectrum of known and as yet unknown interactions between PRGs, lipids, and proteins make them a promising and interesting group of potential novel therapeutic targets.

Efficient biotransformation of naringenin to naringenin α-glucoside, a novel α-glucosidase inhibitor, by amylosucrase from Deinococcus wulumuquiensis

Amylosucrase (ASase) efficiently biosynthesizes α-glucoside using flavonoids as acceptor molecules and sucrose as a donor molecule. Here, ASase from Deinococcus wulumuqiensis (DwAS) biosynthesized more naringenin α-glucoside (NαG) with sucrose and naringenin as donor and acceptor molecules, respectively, than other ASases from Deinococcus sp. The biotransformation rate of DwAS to NαG was 21.3% compared to 7.1-16.2% for other ASases. Docking simulations showed that the active site of DwAS was more accessible to naringenin than those of others. The 217th valine in DwAS corresponded to the 221st isoleucine in Deinococcus geothermalis AS (DgAS), and the isoleucine possibly prevented naringenin from accessing the active site. The DwAS-V217I mutant had a significantly lower biosynthetic rate of NαG than DwAS. The kcat/Km value of DwAS with naringenin as the donor was significantly higher than that of DgAS and DwAS-V217I. In addition, NαG inhibited human intestinal α-glucosidase more efficiently than naringenin.

Divergent folding-mediated epistasis among unstable membrane protein variants

Many membrane proteins are prone to misfolding, which compromises their functional expression at the plasma membrane. This is particularly true for the mammalian gonadotropin-releasing hormone receptor GPCRs (GnRHR). We recently demonstrated that evolutionary GnRHR modifications appear to have coincided with adaptive changes in cotranslational folding efficiency. Though protein stability is known to shape evolution, it is unclear how cotranslational folding constraints modulate the synergistic, epistatic interactions between mutations. We therefore compared the pairwise interactions formed by mutations that disrupt the membrane topology (V276T) or tertiary structure (W107A) of GnRHR. Using deep mutational scanning, we evaluated how the plasma membrane expression of these variants is modified by hundreds of secondary mutations. An analysis of 251 mutants in three genetic backgrounds reveals that V276T and W107A form distinct epistatic interactions that depend on both the severity and the mechanism of destabilization. V276T forms predominantly negative epistatic interactions with destabilizing mutations in soluble loops. In contrast, W107A forms positive interactions with mutations in both loops and transmembrane domains that reflect the diminishing impacts of the destabilizing mutations in variants that are already unstable. These findings reveal how epistasis is remodeled by conformational defects in membrane proteins and in unstable proteins more generally.

An in silico investigation on the binding site preference of PD-1 and PD-L1 for designing antibodies for targeted cancer therapy

Cancer control and treatment remain a significant challenge in cancer therapy and recently immune checkpoints has considered as a novel treatment strategy to develop anti-cancer drugs. Many cancer types use the immune checkpoints and its ligand, PD-1/PD-L1 pathway, to evade detection and destruction by the immune system, which is associated with altered effector function of PD-1 and PD-L1 overexpression on cancer cells to deactivate T cells. In recent years, mAbs have been employed to block immune checkpoints, therefore normalization of the anti-tumor response has enabled the scientists to develop novel biopharmaceuticals. In vivo affinity maturation of antibodies in targeted therapy has sometimes failed, and current experimental methods cannot accommodate the accurate structural details of protein-protein interactions. Therefore, determining favorable binding sites on the protein surface for modulator design of these interactions is a major challenge. In this study, we used the in silico methods to identify favorable binding sites on the PD-1 and PD-L1 and to optimize mAb variants on a large scale. At first, all the binding areas on PD-1 and PD-L1 have been identified. Then, using the RosettaDesign protocol, thousands of antibodies have been generated for 11 different regions on PD-1 and PD-L1 and then the designs with higher stability, affinity, and shape complementarity were selected. Next, molecular dynamics simulations and MM-PBSA analysis were employed to understand the dynamic, structural features of the complexes and measure the binding affinity of the final designs. Our results suggest that binding sites 1, 3 and 6 on PD-1 and binding sites 9 and 11 on PD-L1 can be regarded as the most appropriate sites for the inhibition of PD-1-PD-L1 interaction by the designed antibodies. This study provides comprehensive information regarding the potential binding epitopes on PD-1 which could be considered as hotspots for designing potential biopharmaceuticals. We also showed that mutations in the CDRs regions will rearrange the interaction pattern between the designed antibodies and targets (PD-1 and PD-L1) with improved affinity to effectively inhibit protein-protein interaction and block the immune checkpoint.

δ-Conotoxin Structure Prediction and Analysis through Large-Scale Comparative and Deep Learning Modeling Approaches

The δ-conotoxins, a class of peptides produced in the venom of cone snails, are of interest due to their ability to inhibit the inactivation of voltage-gated sodium channels causing paralysis and other neurological responses, but difficulties in their isolation and synthesis have made structural characterization challenging. Taking advantage of recent breakthroughs in computational algorithms for structure prediction that have made modeling especially useful when experimental data is sparse, this work uses both the deep-learning-based algorithm AlphaFold and comparative modeling method RosettaCM to model and analyze 18 previously uncharacterized δ-conotoxins derived from piscivorous, vermivorous, and molluscivorous cone snails. The models provide useful insights into the structural aspects of these peptides and suggest features likely to be significant in influencing their binding and different pharmacological activities against their targets, with implications for drug development. Additionally, the described protocol provides a roadmap for the modeling of similar disulfide-rich peptides by these complementary methods.

Proteostasis Landscapes of Selective versus Poorly Responsive CFTR Variants Reveals Structural Vulnerabilities to Correction

Cystic Fibrosis (CF) is a lethal genetic disorder caused by variants in CF transmembrane conductance regulator (CFTR). Many disease variants are treatable with corrector compounds, which enhance the folding and trafficking of CFTR. However, correctors fail to elicit a response for every CFTR variant. Approximately 3% of persons with CF harbor poorly responsive CFTR variants. Here, we reveal that a group of poorly responsive variants overlap with selectively responsive variants in a critical domain interface (nucleotide-binding domain 1/intracellular loop 4 - NBD1/ICL4). Affinity purification mass spectrometry proteomics was used to profile the protein homeostasis (proteostasis) changes of CFTR variants during corrector treatment to assess modulated interactions with protein folding and maturation pathways. Responsive variant interactions converged on similar proteostasis pathways during correction. In contrast, poorly responsive variants subtly diverged, revealing a partial restoration of protein quality control surveillance and a capacity to correct some mutations. Computational structural modeling showed that corrector VX-445 failed to confer enough NBD1 stability to poorly responsive variants. NBD1 secondary stabilizing mutations rescued poorly responsive variants, revealing structural vulnerabilities in NBD1 required for treating poor responders. Our study provides a framework for discerning the underlying protein quality control and structural defects of CFTR variants not reached with existing drugs. These insights can help expand therapeutics to all susceptible CFTR variants to enhance personalized medicine efforts.

Mechanism of phage sensing and restriction by toxin-antitoxin-chaperone systems

Toxin-antitoxins (TAs) are prokaryotic two-gene systems composed of a toxin neutralized by an antitoxin. Toxin-antitoxin-chaperone (TAC) systems additionally include a SecB-like chaperone that stabilizes the antitoxin by recognizing its chaperone addiction (ChAD) element. TACs mediate antiphage defense, but the mechanisms of viral sensing and restriction are unexplored. We identify two Escherichia coli antiphage TAC systems containing host inhibition of growth (HigBA) and CmdTA TA modules, HigBAC and CmdTAC. HigBAC is triggered through recognition of the gpV major tail protein of phage λ. Chaperone HigC recognizes gpV and ChAD via analogous aromatic molecular patterns, with gpV outcompeting ChAD to trigger toxicity. For CmdTAC, the CmdT ADP-ribosyltransferase toxin modifies mRNA to halt protein synthesis and limit phage propagation. Finally, we establish the modularity of TACs by creating a hybrid broad-spectrum antiphage system combining the CmdTA TA warhead with a HigC chaperone phage sensor. Collectively, these findings reveal the potential of TAC systems in broad-spectrum antiphage defense.

De novo design of pH-responsive self-assembling helical protein filaments

Biological evolution has led to precise and dynamic nanostructures that reconfigure in response to pH and other environmental conditions. However, designing micrometre-scale protein nanostructures that are environmentally responsive remains a challenge. Here we describe the de novo design of pH-responsive protein filaments built from subunits containing six or nine buried histidine residues that assemble into micrometre-scale, well-ordered fibres at neutral pH. The cryogenic electron microscopy structure of an optimized design is nearly identical to the computational design model for both the subunit internal geometry and the subunit packing into the fibre. Electron, fluorescent and atomic force microscopy characterization reveal a sharp and reversible transition from assembled to disassembled fibres over 0.3 pH units, and rapid fibre disassembly in less than 1 s following a drop in pH. The midpoint of the transition can be tuned by modulating buried histidine-containing hydrogen bond networks. Computational protein design thus provides a route to creating unbound nanomaterials that rapidly respond to small pH changes.

Computational evaluation of efflux pump homologues and lignans as potent inhibitors against multidrug-resistant Salmonella typhi

Typhoid fever, caused by Salmonella enterica serovar typhi, presents a substantial global health threat, particularly in regions with limited healthcare infrastructure. The rise of multidrug-resistant strains of S. typhi exacerbates this challenge, severely compromising conventional treatment efficacy due to over activity of efflux pumps. In our study, a comprehensive exploration of two fundamental aspects to combat MDR in S. typhi is carried out; i.e. employing advanced bioinformatics analyses and AlphaFold AI, We successfully identified and characterised a putative homologue, ABC-TPA, reminiscent of the P-glycoprotein (P-gp) known for its role in multidrug resistance in diverse pathogens. This discovery provides a critical foundation for understanding the potential mechanisms driving antibiotic resistance in S. typhi. Furthermore, employing computational methodologies, We meticulously assessed the potential of lignans, specifically Schisandrin A, B, and C, as promising Efflux Pump Inhibitors (EPIs) against the identified P-gp homologue in S. typhi. Noteworthy findings revealed robust binding interactions of Schisandrin A and B with the target protein, indicating substantial inhibitory capabilities. In contrast, Schisandrin C exhibited instability, showing varied effectiveness among the evaluated lignans. Pharmacokinetics and toxicity predictions underscored the favourable attributes of Schisandrin A, including prolonged action duration. Furthermore, high systemic stability and demanished toxicity profile of SA and SB present their therapeutic efficacy against MDR. This comprehensive investigation not only elucidates potential therapeutic strategies against MDR strains of S. typhi but also highlights the relevance of computational approaches in identifying and evaluating promising candidates. These findings lay a robust foundation for future empirical studies to address the formidable challenges antibiotic resistance poses in this clinically significant infectious diseases.

Molecular Basis of MC1R Activation: Mutation-Induced Alterations in Structural Dynamics

The MC1R protein is a receptor found in melanocytes that plays a role in melanin synthesis. Mutations in this protein can impact hair color, skin tone, tanning ability, and increase the risk of skin cancer. The MC1R protein is activated by the alpha-melanocyte-stimulating hormone (α-MSH). Previous studies have shown that mutations affect the interaction between MC1R and α-MSH; however, the mechanism behind this process is poorly understood. Our study aims to shed light on this mechanism using molecular dynamics (MD) simulations to analyze the Asp84Glu and Asp294His variants. We simulated both the wild-type (WT) protein and the mutants with and without ligand. Our results reveal that mutations induce unique conformations during state transitions, hindering the switch between active and inactive states and decreasing cellular levels of cAMP. Interestingly, Asp294His showed increased ligand affinity but decreased protein activity, highlighting that tighter binding does not always lead to increased activation. Our study provides insights into the molecular mechanisms underlying the impact of MC1R mutations on protein activity.

Polymorphism in the leucine-rich repeats of TLR7 in different breeds of chicken and in silico analysis of its effect on TLR7 structure and function

Chicken toll-like receptor 7 (chTLR7) is a viral sensing pattern recognition receptor and detects ssRNA. The ligand binding site comprises leucine-rich repeats (LRRs) located in the ectodomain of chTLR7. Hence, any polymorphism in the binding site would modify its functional interaction with the ligand, resulting in varied strength of immune response. This study first aimed to compare the single nucleotide polymorphisms (SNPs) associated with the ligand binding site of TLR7 in three indigenous chicken breeds namely Aseel, Kadaknath, Nicobari along with an exotic breed White Leghorn. Four synonymous SNPs (P123P, I171I, N339N and L421L) and four non-synonymous SNPs (I121V, S135T, F356S and S447G) were identified among various breeds. We employed in silico tools to screen the pathogenic nsSNPs and one nsSNP was identified as having potential impact on chTLR7 protein. Moreover, sequence and structure-based methods were used to determine the effect of nsSNPs on protein stability. It revealed I121V, F356S, and S447G as decreasing the stability while S135T increasing the stability of chTLR7. Additionally, docking analysis confirmed that I121V and F356S reduced the binding affinity of ligands (R-848 and polyU) to chTLR7 protein. The results suggest that the nsSNPs found in this study could alter the ligand binding of chTLR7 and modify the immune response between different breeds further contributing to disease susceptibility or resistance. Further, in vitro and in vivo studies are needed to analyze the effect of these SNPs on susceptibility or resistance against various viral diseases in poultry.

Structural basis of tolvaptan binding to the vasopressin V2 receptor

The vasopressin V2 receptor (V2R) is a validated therapeutic target for autosomal dominant polycystic kidney disease (ADPKD), with tolvaptan being the first FDA-approved antagonist. Herein, we used Gaussian accelerated molecular dynamics simulations to investigate the spontaneous binding of tolvaptan to both active and inactive V2R conformations at the atomic-level. Overall, the binding process consists of two stages. Tolvaptan binds initially to extracellular loops 2 and 3 (ECL2/3) before overcoming an energy barrier to enter the pocket. Our simulations result highlighted key residues (e.g., R181, Y205, F287, F178) involved in this process, which were experimentally confirmed by site-directed mutagenesis. This work provides structural insights into tolvaptan-V2R interactions, potentially aiding the design of novel antagonists for V2R and other G protein-coupled receptors.

FilamentID reveals the composition and function of metabolic enzyme polymers during gametogenesis

Gamete formation and subsequent offspring development often involve extended phases of suspended cellular development or even dormancy. How cells adapt to recover and resume growth remains poorly understood. Here, we visualized budding yeast cells undergoing meiosis by cryo-electron tomography (cryoET) and discovered elaborate filamentous assemblies decorating the nucleus, cytoplasm, and mitochondria. To determine filament composition, we developed a "filament identification" (FilamentID) workflow that combines multiscale cryoET/cryo-electron microscopy (cryoEM) analyses of partially lysed cells or organelles. FilamentID identified the mitochondrial filaments as being composed of the conserved aldehyde dehydrogenase Ald4ALDH2 and the nucleoplasmic/cytoplasmic filaments as consisting of acetyl-coenzyme A (CoA) synthetase Acs1ACSS2. Structural characterization further revealed the mechanism underlying polymerization and enabled us to genetically perturb filament formation. Acs1 polymerization facilitates the recovery of chronologically aged spores and, more generally, the cell cycle re-entry of starved cells. FilamentID is broadly applicable to characterize filaments of unknown identity in diverse cellular contexts.

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.

Apprehensions and emerging solutions in ML-based protein structure prediction

The three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the structure is known, the molecular mechanism of protein function can be understood in more detail and obtained information utilized in biotechnological, diagnostics, and therapeutic applications. Over the past five years, machine learning (ML)-based modeling has pushed protein structure prediction to the next level with AlphaFold in the front line, predicting the structure for hundreds of millions of proteins. Further advances recently report promising ML-based approaches for solving remaining challenges by incorporating functionally important metals, co-factors, post-translational modifications, structural dynamics, and interdomain and multimer interactions in the structure prediction process.

Functionality of chimeric TssA proteins in the type VI secretion system reveals sheath docking specificity within their N-terminal domains

The genome of Pseudomonas aeruginosa encodes three type VI secretion systems, each comprising a dozen distinct proteins, which deliver toxins upon T6SS sheath contraction. The least conserved T6SS component, TssA, has variations in size which influence domain organisation and structure. Here we show that the TssA Nt1 domain interacts directly with the sheath in a specific manner, while the C-terminus is essential for oligomerisation. We built chimeric TssA proteins by swapping C-termini and showed that these can be functional even when made of domains from different TssA sub-groups. Functional specificity requires the Nt1 domain, while the origin of the C-terminal domain is more permissive for T6SS function. We identify two regions in short TssA proteins, loop and hairpin, that contribute to sheath binding. We propose a docking mechanism of TssA proteins with the sheath, and a model for how sheath assembly is coordinated by TssA proteins from this position.

The Kir2.1E299V mutation increases atrial fibrillation vulnerability while protecting the ventricles against arrhythmias in a mouse model of short QT syndrome type 3

AIMS

Short QT syndrome type 3 (SQTS3) is a rare arrhythmogenic disease caused by gain-of-function mutations in KCNJ2, the gene coding the inward rectifier potassium channel Kir2.1. We used a multidisciplinary approach and investigated arrhythmogenic mechanisms in an in-vivo model of de-novo mutation Kir2.1E299V identified in a patient presenting an extremely abbreviated QT interval and paroxysmal atrial fibrillation.

METHODS AND RESULTS

We used intravenous adeno-associated virus-mediated gene transfer to generate mouse models, and confirmed cardiac-specific expression of Kir2.1WT or Kir2.1E299V. On ECG, the Kir2.1E299V mouse recapitulated the QT interval shortening and the atrial-specific arrhythmia of the patient. The PR interval was also significantly shorter in Kir2.1E299V mice. Patch-clamping showed extremely abbreviated action potentials in both atrial and ventricular Kir2.1E299V cardiomyocytes due to a lack of inward-going rectification and increased IK1 at voltages positive to -80 mV. Relative to Kir2.1WT, atrial Kir2.1E299V cardiomyocytes had a significantly reduced slope conductance at voltages negative to -80 mV. After confirming a higher proportion of heterotetrameric Kir2.x channels containing Kir2.2 subunits in the atria, in-silico 3D simulations predicted an atrial-specific impairment of polyamine block and reduced pore diameter in the Kir2.1E299V-Kir2.2WT channel. In ventricular cardiomyocytes, the mutation increased excitability by shifting INa activation and inactivation in the hyperpolarizing direction, which protected the ventricle against arrhythmia. Moreover, Purkinje myocytes from Kir2.1E299V mice manifested substantially higher INa density than Kir2.1WT, explaining the abbreviation in the PR interval.

CONCLUSION

The first in-vivo mouse model of cardiac-specific SQTS3 recapitulates the electrophysiological phenotype of a patient with the Kir2.1E299V mutation. Kir2.1E299V eliminates rectification in both cardiac chambers but protects against ventricular arrhythmias by increasing excitability in both Purkinje-fiber network and ventricles. Consequently, the predominant arrhythmias are supraventricular likely due to the lack of inward rectification and atrial-specific reduced pore diameter of the Kir2.1E299V-Kir2.2WT heterotetramer.

Use of phosphotyrosine-containing peptides to target SH2 domains: Antagonist peptides of the Crk/CrkL-p130Cas axis

Protein-protein interactions between SH2 domains and segments of proteins that include a post-translationally phosphorylated tyrosine residue (pY) underpin numerous signal transduction cascades that allow cells to respond to their environment. Dysregulation of the writing, erasing, and reading of these posttranslational modifications is a hallmark of human disease, notably cancer. Elucidating the precise role of the SH2 domain-containing adaptor proteins Crk and CrkL in tumor cell migration and invasion is challenging because there are no specific and potent antagonists available. Crk and CrkL SH2s interact with a region of the docking protein p130Cas containing 15 potential pY-containing tetrapeptide motifs. This chapter summarizes recent efforts toward peptide antagonists for this Crk/CrkL-p130Cas interaction. We describe our protocol for recombinant expression and purification of Crk and CrkL SH2s for functional assays and our procedure to determine the consensus binding motif from the p130Cas sequence. To develop a more potent antagonist, we employ methods often associated with structure-based drug design. Computational docking using Rosetta FlexPepDock, which accounts for peptides having a greater number of conformational degrees of freedom than small organic molecules that typically constitute libraries, provides quantitative docking metrics to prioritize candidate peptides for experimental testing. A battery of biophysical assays, including fluorescence polarization, differential scanning fluorimetry and saturation transfer difference nuclear magnetic resonance spectroscopy, were employed to assess the candidates. In parallel, GST pulldown competition assays characterized protein-protein binding in vitro. Taken together, our methodology yields peptide antagonists of the Crk/CrkL-p130Cas axis that will be used to validate targets, assess druggability, foster in vitro assay development, and potentially serve as lead compounds for therapeutic intervention.

ALDELE: All-Purpose Deep Learning Toolkits for Predicting the Biocatalytic Activities of Enzymes

Rapidly predicting enzyme properties for catalyzing specific substrates is essential for identifying potential enzymes for industrial transformations. The demand for sustainable production of valuable industry chemicals utilizing biological resources raised a pressing need to speed up biocatalyst screening using machine learning techniques. In this research, we developed an all-purpose deep-learning-based multiple-toolkit (ALDELE) workflow for screening enzyme catalysts. ALDELE incorporates both structural and sequence representations of proteins, alongside representations of ligands by subgraphs and overall physicochemical properties. Comprehensive evaluation demonstrated that ALDELE can predict the catalytic activities of enzymes, and particularly, it identifies residue-based hotspots to guide enzyme engineering and generates substrate heat maps to explore the substrate scope for a given biocatalyst. Moreover, our models notably match empirical data, reinforcing the practicality and reliability of our approach through the alignment with confirmed mutation sites. ALDELE offers a facile and comprehensive solution by integrating different toolkits tailored for different purposes at affordable computational cost and therefore would be valuable to speed up the discovery of new functional enzymes for their exploitation by the industry.

N4BP1 functions as a dimerization-dependent linear ubiquitin reader which regulates TNF signalling

Signalling through TNFR1 modulates proinflammatory gene transcription and programmed cell death, and its impairment causes autoimmune diseases and cancer. NEDD4-binding protein 1 (N4BP1) is a critical suppressor of proinflammatory cytokine production that acts as a regulator of innate immune signalling and inflammation. However, our current understanding about the molecular properties that enable N4BP1 to exert its suppressive potential remain limited. Here, we show that N4BP1 is a novel linear ubiquitin reader that negatively regulates NFκB signalling by its unique dimerization-dependent ubiquitin-binding module that we named LUBIN. Dimeric N4BP1 strategically positions two non-selective ubiquitin-binding domains to ensure preferential recognition of linear ubiquitin. Under proinflammatory conditions, N4BP1 is recruited to the nascent TNFR1 signalling complex, where it regulates duration of proinflammatory signalling in LUBIN-dependent manner. N4BP1 deficiency accelerates TNFα-induced cell death by increasing complex II assembly. Under proapoptotic conditions, caspase-8 mediates proteolytic processing of N4BP1, resulting in rapid degradation of N4BP1 by the 26 S proteasome, and acceleration of apoptosis. In summary, our findings demonstrate that N4BP1 dimerization creates a novel type of ubiquitin reader that selectively recognises linear ubiquitin which enables the timely and coordinated regulation of TNFR1-mediated inflammation and cell death.

The Prediction of LptA and LptC Protein-Protein Interactions and Virtual Screening for Potential Inhibitors

Antibiotic resistance in Gram-negative bacteria remains one of the most pressing challenges to global public health. Blocking the transportation of lipopolysaccharides (LPS), a crucial component of the outer membrane of Gram-negative bacteria, is considered a promising strategy for drug discovery. In the transportation process of LPS, two components of the LPS transport (Lpt) complex, LptA and LptC, are responsible for shuttling LPS across the periplasm to the outer membrane, highlighting their potential as targets for antibacterial drug development. In the current study, a protein-protein interaction (PPI) model of LptA and LptC was constructed, and a molecular screening strategy was employed to search a protein-protein interaction compound library. The screening results indicated that compound 18593 exhibits favorable binding free energy with LptA and LptC. In comparison with the molecular dynamics (MD) simulations on currently known inhibitors, compound 18593 shows more stable target binding ability at the same level. The current study suggests that compound 18593 may exhibit an inhibitory effect on the LPS transport process, making it a promising hit compound for further research.

Discovery of Protease-Activated Receptor 4 (PAR4)-Tethered Ligand Antagonists Using Ultralarge Virtual Screening

Here, we demonstrate a structure-based small molecule virtual screening and lead optimization pipeline using a homology model of a difficult-to-drug G-protein-coupled receptor (GPCR) target. Protease-activated receptor 4 (PAR4) is activated by thrombin cleavage, revealing a tethered ligand that activates the receptor, making PAR4 a challenging target. A virtual screen of a make-on-demand chemical library yielded a one-hit compound. From the single-hit compound, we developed a novel series of PAR4 antagonists. Subsequent lead optimization via simultaneous virtual library searches and structure-based rational design efforts led to potent antagonists of thrombin-induced activation. Interestingly, this series of antagonists was active against PAR4 activation by the native protease thrombin cleavage but not the synthetic PAR4 agonist peptide AYPGKF.

Nardilysin-regulated scission mechanism activates polo-like kinase 3 to suppress the development of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) develops through step-wise genetic and molecular alterations including Kras mutation and inactivation of various apoptotic pathways. Here, we find that development of apoptotic resistance and metastasis of KrasG12D-driven PDAC in mice is accelerated by deleting Plk3, explaining the often-reduced Plk3 expression in human PDAC. Importantly, a 41-kDa Plk3 (p41Plk3) that contains the entire kinase domain at the N-terminus (1-353 aa) is activated by scission of the precursor p72Plk3 at Arg354 by metalloendopeptidase nardilysin (NRDC), and the resulting p32Plk3 C-terminal Polo-box domain (PBD) is removed by proteasome degradation, preventing the inhibition of p41Plk3 by PBD. We find that p41Plk3 is the activated form of Plk3 that regulates a feed-forward mechanism to promote apoptosis and suppress PDAC and metastasis. p41Plk3 phosphorylates c-Fos on Thr164, which in turn induces expression of Plk3 and pro-apoptotic genes. These findings uncover an NRDC-regulated post-translational mechanism that activates Plk3, establishing a prototypic regulation by scission mechanism.

DNA binding analysis of rare variants in homeodomains reveals homeodomain specificity-determining residues

Homeodomains (HDs) are the second largest class of DNA binding domains (DBDs) among eukaryotic sequence-specific transcription factors (TFs) and are the TF structural class with the largest number of disease-associated mutations in the Human Gene Mutation Database (HGMD). Despite numerous structural studies and large-scale analyses of HD DNA binding specificity, HD-DNA recognition is still not fully understood. Here, we analyze 92 human HD mutants, including disease-associated variants and variants of uncertain significance (VUS), for their effects on DNA binding activity. Many of the variants alter DNA binding affinity and/or specificity. Detailed biochemical analysis and structural modeling identifies 14 previously unknown specificity-determining positions, 5 of which do not contact DNA. The same missense substitution at analogous positions within different HDs often exhibits different effects on DNA binding activity. Variant effect prediction tools perform moderately well in distinguishing variants with altered DNA binding affinity, but poorly in identifying those with altered binding specificity. Our results highlight the need for biochemical assays of TF coding variants and prioritize dozens of variants for further investigations into their pathogenicity and the development of clinical diagnostics and precision therapies.

Comparative assessment of different anti-CD147/Basigin 2 antibodies as a potential therapeutic anticancer target by molecular modeling and dynamic simulation

Cluster of differentiation 147 (CD147) is an attractive target for anticancer therapy since it is pivotal in developing and progressing several of malignant tumors in the context of its high expression levels. Although anti-CD147 antibodies by different laboratories are designed for the Ig-like domains of CD147, there is a demand to provide priority among these anti-CD147 antibodies for developing of therapeutic anti-CD147 antibody before experimental validations. This study uses molecular docking and dynamic simulation techniques to compare the binding modes and affinities of nine antibody models against the Ig-like domains of CD147. After obtaining the model antibodies by homology modeling via Robetta, we predicted the CDRs of nine antibodies and the epitopes of CD147 to reach more accurate results for antigen affinity in molecular docking. Next, from HADDOCK 2.4., we meticulously handpicked the most superior model clusters (Z-Score: - 2.5 to - 1.2) and identified that meplazumab had higher affinities according to the success rate as the percentage of a scoring scale. We achieved stable simulations of CD147-antibody interaction. Our outcomes hold hypothetical importance for further experimental cancer research on the design and development of the relevant model antibodies.

Defining Biological and Biochemical Functions of Noncanonical SET Domain Proteins

Within the SET domain superfamily of lysine methyltransferases, there is a well-conserved subfamily, frequently referred to as the Set3 SET domain subfamily, which contain noncanonical SET domains carrying divergent amino acid sequences. These proteins are implicated in diverse biological processes including stress responses, cell differentiation, and development, and their disruption is linked to diseases including cancer and neurodevelopmental disorders. Interestingly, biochemical and structural analysis indicates that they do not possess catalytic methyltransferase activity. At the molecular level, Set3 SET domain proteins appear to play critical roles in the regulation of gene expression, particularly repression and heterochromatin maintenance, and in some cases, via scaffolding other histone modifying activities at chromatin. Here, we explore the common and unique functions among Set3 SET domain subfamily proteins and analyze what is known about the specific contribution of the conserved SET domain to functional roles of these proteins, as well as propose areas of investigation to improve understanding of this important, noncanonical subfamily of proteins.

Inhibitory protein-protein interactions of the SIRT1 deacetylase are choreographed by post-translational modification

Regulation of SIRT1 activity is vital to energy homeostasis and plays important roles in many diseases. We previously showed that insulin triggers the epigenetic regulator DBC1 to prime SIRT1 for repression by the multifunctional trafficking protein PACS-2. Here, we show that liver DBC1/PACS-2 regulates the diurnal inhibition of SIRT1, which is critically important for insulin-dependent switch in fuel metabolism from fat to glucose oxidation. We present the x-ray structure of the DBC1 S1-like domain that binds SIRT1 and an NMR characterization of how the SIRT1 N-terminal region engages DBC1. This interaction is inhibited by acetylation of K112 of DBC1 and stimulated by the insulin-dependent phosphorylation of human SIRT1 at S162 and S172, catalyzed sequentially by CK2 and GSK3, resulting in the PACS-2-dependent inhibition of nuclear SIRT1 enzymatic activity and translocation of the deacetylase in the cytoplasm. Finally, we discuss how defects in the DBC1/PACS-2-controlled SIRT1 inhibitory pathway are associated with disease, including obesity and non-alcoholic fatty liver disease.

Structural basis of Acinetobacter type IV pili targeting by an RNA virus

Acinetobacters pose a significant threat to human health, especially those with weakened immune systems. Type IV pili of acinetobacters play crucial roles in virulence and antibiotic resistance. Single-stranded RNA bacteriophages target the bacterial retractile pili, including type IV. Our study delves into the interaction between Acinetobacter phage AP205 and type IV pili. Using cryo-electron microscopy, we solve structures of the AP205 virion with an asymmetric dimer of maturation proteins, the native Acinetobacter type IV pili bearing a distinct post-translational pilin cleavage, and the pili-bound AP205 showing its maturation proteins adapted to pilin modifications, allowing each phage to bind to one or two pili. Leveraging these results, we develop a 20-kilodalton AP205-derived protein scaffold targeting type IV pili in situ, with potential for research and diagnostics.

A cucumber protein, Phloem Phosphate Stress-Repressed 1, rapidly degrades in response to a phosphate stress condition

Under depleted external phosphate (Pi), many plant species adapt to this stress by initiating downstream signaling cascades. In plants, the vascular system delivers nutrients and signaling agents to control physiological and developmental processes. Currently, limited information is available regarding the direct role of phloem-borne long-distance signals in plant growth and development under Pi stress conditions. Here, we report on the identification and characterization of a cucumber protein, Cucumis sativus Phloem Phosphate Stress-Repressed 1 (CsPPSR1), whose level in the phloem translocation stream rapidly responds to imposed Pi-limiting conditions. CsPPSR1 degradation is mediated by the 26S proteasome; under Pi-sufficient conditions, CsPPSR1 is stabilized by its phosphorylation within the sieve tube system through the action of CsPPSR1 kinase. Further, we discovered that CsPPSR1 kinase was susceptible to Pi starvation-induced degradation in the sieve tube system. Our findings offer insight into a molecular mechanism underlying the response of phloem-borne proteins to Pi-limited stress conditions.

Recent Advances in Automated Structure-Based De Novo Drug Design

As the number of determined and predicted protein structures and the size of druglike 'make-on-demand' libraries soar, the time-consuming nature of structure-based computer-aided drug design calls for innovative computational algorithms. De novo drug design introduces in silico heuristics to accelerate searching in the vast chemical space. This review focuses on recent advances in structure-based de novo drug design, ranging from conventional fragment-based methods, evolutionary algorithms, and Metropolis Monte Carlo methods to deep generative models. Due to the historical limitation of de novo drug design generating readily available drug-like molecules, we highlight the synthetic accessibility efforts in each category and the benchmarking strategies taken to validate the proposed framework.

Rational Design of TDP-43 Derived α-Helical Peptide Inhibitors: An In Silico Strategy to Prevent TDP-43 Aggregation in Neurodegenerative Disorders

TDP-43, an essential RNA/DNA-binding protein, is central to the pathology of neurodegenerative diseases, such as amyotrophic lateral sclerosis and frontotemporal dementia. Pathological mislocalization and aggregation of TDP-43 disrupt RNA splicing, mRNA stability, and mRNA transport, thereby impairing neuronal function and survival. The formation of amyloid-like TDP-43 filaments is largely facilitated by the destabilization of an α-helical segment within the disordered C-terminal region. In this study, we hypothesized that preventing the destabilization of the α-helical domain could potentially halt the growth of these pathological filaments. To explore this, we utilized a range of in silico techniques to design and evaluate peptide-based therapeutics that bind to pathological TDP-43 amyloid-like filament crystal structures and resist β sheet conversion. Our computational approaches, including biophysical and secondary structure property prediction, molecular docking, 3D structure prediction, and molecular dynamics simulations, were used to assess the structure, stability, and binding affinity of these peptides in relation to pathological TDP-43 filaments. The results of our in silico analyses identified a selection of promising peptides which displayed a stable α-helical structure, exhibited an increased number of intramolecular hydrogen bonds within the helical domain, and demonstrated high binding affinities for pathological TDP-43 amyloid-like filaments. Molecular dynamics simulations provided further support for the structural and thermodynamic stability of these peptides, as they exhibited lower root-mean-square deviation and more favorable free energy landscapes over 300 ns. These findings establish α-helical propensity peptides as potential lead molecules for the development of novel therapeutics against TDP-43 aggregation. This structure-based computational approach for the rational design of peptide inhibitors opens a new direction in the search for effective interventions for ALS, FTD, and other related neurodegenerative diseases. The peptides identified as the most promising candidates in this study are currently subject to further testing and validation through both in vitro and in vivo experiments.

Bio-Chemoinformatics-Driven Analysis of nsp7 and nsp8 Mutations and Their Effects on Viral Replication Protein Complex Stability

The nonstructural proteins 7 and 8 (nsp7 and nsp8) of SARS-CoV-2 are highly important proteins involved in the RNA-dependent polymerase (RdRp) protein replication complex. In this study, we analyzed the global mutation of nsp7 and nsp8 in 2022 and 2023 and analyzed the effects of mutation on the viral replication protein complex using bio-chemoinformatics. Frequently occurring variants are found to be single amino acid mutations for both nsp7 and nsp8. The most frequently occurring mutations for nsp7 which include L56F, L71F, S25L, M3I, D77N, V33I and T83I are predicted to cause destabilizing effects, whereas those in nsp8 are predicted to cause stabilizing effects, with the threonine to isoleucine mutation (T89I, T145I, T123I, T148I, T187I) being a frequent mutation. A conserved domain database analysis generated critical interaction residues for nsp7 (Lys-7, His-36 and Asn-37) and nsp8 (Lys-58, Pro-183 and Arg-190), which, according to thermodynamic calculations, are prone to destabilization. Trp-29, Phe-49 of nsp7 and Trp-154, Tyr-135 and Phe-15 of nsp8 cause greater destabilizing effects to the protein complex based on a computational alanine scan suggesting them as possible new target sites. This study provides an intensive analysis of the mutations of nsp7 and nsp8 and their possible implications for viral complex stability.

Mechanism of Mutation-Induced Effects on the Catalytic Function of TEV Protease: A Molecular Dynamics Study

Tobacco etch virus protease (TEVp) is wildly exploited for various biotechnological applications. These applications take advantage of TEVp's ability to cleave specific substrate sequences to study protein function and interactions. A major limitation of this enzyme is its relatively slow catalytic rate. In this study, MD simulations were conducted on TEV enzymes and known highly active mutants (eTEV and uTEV3) to explore the relationship between mutation, conformation, and catalytic function. The results suggest that mutations distant from the active site can influence the substrate-binding pocket through interaction networks. MD analysis of eTEV demonstrates that, by stabilizing the orientation of the substrate at the catalytic site, mutations that appropriately enlarge the substrate-binding pocket will be beneficial for Kcat, enhancing the catalytic efficiency of the enzyme. On the contrary, mutations in uTEV3 reduced the flexibility of the active pocket and increased the hydrogen bonding between the substrate and enzyme, resulting in higher affinity. At the same time, the MD simulation demonstrates that mutations outside of the active site residues could affect the dynamic movement of the binding pocket by altering residue networks and communication pathways, thereby having a profound impact on reactivity. These findings not only provide a molecular mechanistic explanation for the excellent mutants, but also serve as a guiding framework for rational computational design.

Structural dynamics of influenza A (H1N1) hemagglutinin protein: a comparative study of Indian (2018) isolate with its evolutionary neighbor, Californian (2009) strain

This work highlights the structure and dynamics of two trimeric HA proteins of the H1N1 virus from different origins, the pandemic Californian (HACal) and its closest Indian neighbor (HAInd), reported in 2009 and 2018, respectively. Because of mutation, HAInd acquires new N-glycosylation and epitope binding sites along with mutations at RBD, which might trigger an altered viral-host interaction mechanism. Molecular dynamics simulations performed on HA trimers for a period of 250 ns reveal the highly dynamic nature of HACal trimers inherited by the flexibility of HA monomers. In the trimer, the dynamics of one monomer are more pronounced compared to others, and the enhanced dynamics of RBD especially gain attention as they plays a key role during fusion. Conversely, the mutant HAInd trimer effectively establishes more H-bond interactions, and accordingly, the trimer undergoes more stabilized dynamics with a relatively lower amplitude of RBD dynamics, as endorsed by the reduced RMSD, Rg, and SASA variations. The cooperative and anti-cooperative motions dissected for the subdomains of both strains also reveal a prominent anticorrelative motion of RBD against other subdomains. In agreement, the free energy landscape of stable HAInd is also characterized by a single lowest wide energy basin instead of the two minimum energy basins of the HACal trimer. In essence, the mutant HAInd acquires a highly stable conformation with novel functional features, which calls for (i) further investigation on the emerging mutation-mediated variation in viral-host binding mechanism and (ii) the need for further design of site-specific potential inhibitors to face future challenges.Communicated by Ramaswamy H. Sarma.

A general computational design strategy for stabilizing viral class I fusion proteins

Many pathogenic viruses rely on class I fusion proteins to fuse their viral membrane with the host cell membrane. To drive the fusion process, class I fusion proteins undergo an irreversible conformational change from a metastable prefusion state to an energetically more stable postfusion state. Mounting evidence underscores that antibodies targeting the prefusion conformation are the most potent, making it a compelling vaccine candidate. Here, we establish a computational design protocol that stabilizes the prefusion state while destabilizing the postfusion conformation. With this protocol, we stabilize the fusion proteins of the RSV, hMPV, and SARS-CoV-2 viruses, testing fewer than a handful of designs. The solved structures of these designed proteins from all three viruses evidence the atomic accuracy of our approach. Furthermore, the humoral response of the redesigned RSV F protein compares to that of the recently approved vaccine in a mouse model. While the parallel design of two conformations allows the identification of energetically sub-optimal positions for one conformation, our protocol also reveals diverse molecular strategies for stabilization. Given the clinical significance of viruses using class I fusion proteins, our algorithm can substantially contribute to vaccine development by reducing the time and resources needed to optimize these immunogens.

Recent Progress of Protein Tertiary Structure Prediction

The prediction of three-dimensional (3D) protein structure from amino acid sequences has stood as a significant challenge in computational and structural bioinformatics for decades. Recently, the widespread integration of artificial intelligence (AI) algorithms has substantially expedited advancements in protein structure prediction, yielding numerous significant milestones. In particular, the end-to-end deep learning method AlphaFold2 has facilitated the rise of structure prediction performance to new heights, regularly competitive with experimental structures in the 14th Critical Assessment of Protein Structure Prediction (CASP14). To provide a comprehensive understanding and guide future research in the field of protein structure prediction for researchers, this review describes various methodologies, assessments, and databases in protein structure prediction, including traditionally used protein structure prediction methods, such as template-based modeling (TBM) and template-free modeling (FM) approaches; recently developed deep learning-based methods, such as contact/distance-guided methods, end-to-end folding methods, and protein language model (PLM)-based methods; multi-domain protein structure prediction methods; the CASP experiments and related assessments; and the recently released AlphaFold Protein Structure Database (AlphaFold DB). We discuss their advantages, disadvantages, and application scopes, aiming to provide researchers with insights through which to understand the limitations, contexts, and effective selections of protein structure prediction methods in protein-related fields.

Elucidating molecular mechanisms of protoxin-II state-specific binding to the human NaV1.7 channel

Human voltage-gated sodium (hNaV) channels are responsible for initiating and propagating action potentials in excitable cells, and mutations have been associated with numerous cardiac and neurological disorders. hNaV1.7 channels are expressed in peripheral neurons and are promising targets for pain therapy. The tarantula venom peptide protoxin-II (PTx2) has high selectivity for hNaV1.7 and is a valuable scaffold for designing novel therapeutics to treat pain. Here, we used computational modeling to study the molecular mechanisms of the state-dependent binding of PTx2 to hNaV1.7 voltage-sensing domains (VSDs). Using Rosetta structural modeling methods, we constructed atomistic models of the hNaV1.7 VSD II and IV in the activated and deactivated states with docked PTx2. We then performed microsecond-long all-atom molecular dynamics (MD) simulations of the systems in hydrated lipid bilayers. Our simulations revealed that PTx2 binds most favorably to the deactivated VSD II and activated VSD IV. These state-specific interactions are mediated primarily by PTx2's residues R22, K26, K27, K28, and W30 with VSD and the surrounding membrane lipids. Our work revealed important protein-protein and protein-lipid contacts that contribute to high-affinity state-dependent toxin interaction with the channel. The workflow presented will prove useful for designing novel peptides with improved selectivity and potency for more effective and safe treatment of pain.

Modeling and Analysis of HIV-1 Pol Polyprotein as a Case Study for Predicting Large Polyprotein Structures

Acquired immunodeficiency syndrome (AIDS) is caused by human immunodeficiency virus (HIV). HIV protease, reverse transcriptase, and integrase are targets of current drugs to treat the disease. However, anti-viral drug-resistant strains have emerged quickly due to the high mutation rate of the virus, leading to the demand for the development of new drugs. One attractive target is Gag-Pol polyprotein, which plays a key role in the life cycle of HIV. Recently, we found that a combination of M50I and V151I mutations in HIV-1 integrase can suppress virus release and inhibit the initiation of Gag-Pol autoprocessing and maturation without interfering with the dimerization of Gag-Pol. Additional mutations in integrase or RNase H domain in reverse transcriptase can compensate for the defect. However, the molecular mechanism is unknown. There is no tertiary structure of the full-length HIV-1 Pol protein available for further study. Therefore, we developed a workflow to predict the tertiary structure of HIV-1 NL4.3 Pol polyprotein. The modeled structure has comparable quality compared with the recently published partial HIV-1 Pol structure (PDB ID: 7SJX). Our HIV-1 NL4.3 Pol dimer model is the first full-length Pol tertiary structure. It can provide a structural platform for studying the autoprocessing mechanism of HIV-1 Pol and for developing new potent drugs. Moreover, the workflow can be used to predict other large protein structures that cannot be resolved via conventional experimental methods.

Divergent Folding-Mediated Epistasis Among Unstable Membrane Protein Variants

Many membrane proteins are prone to misfolding, which compromises their functional expression at the plasma membrane. This is particularly true for the mammalian gonadotropin-releasing hormone receptor GPCRs (GnRHR). We recently demonstrated that evolutionary GnRHR modifications appear to have coincided with adaptive changes in cotranslational folding efficiency. Though protein stability is known to shape evolution, it is unclear how cotranslational folding constraints modulate the synergistic, epistatic interactions between mutations. We therefore compared the pairwise interactions formed by mutations that disrupt the membrane topology (V276T) or tertiary structure (W107A) of GnRHR. Using deep mutational scanning, we evaluated how the plasma membrane expression of these variants is modified by hundreds of secondary mutations. An analysis of 251 mutants in three genetic backgrounds reveals that V276T and W107A form distinct epistatic interactions that depend on both the severity and the mechanism of destabilization. V276T forms predominantly negative epistatic interactions with destabilizing mutations in soluble loops. In contrast, W107A forms positive interactions with mutations in both loops and transmembrane domains that reflect the diminishing impacts of the destabilizing mutations in variants that are already unstable. These findings reveal how epistasis is remodeled by conformational defects in membrane proteins and in unstable proteins more generally.

Binding order of substrate and cofactor in sulfonamide monooxygenase during sulfa drug degradation: in silico studies

For decades, sulfonamide antibiotics have been used across industries such as agriculture and animal husbandry. However, the use and inadvertent misuse of these antibiotics have resulted in the advent of sulfonamide-drug-resistant strains due to antibiotic pollution. Enzymatic bioremediation of antibiotics remains a potential emerging solution to combat antibiotic pollution. Here, we propose an enzymatic model for the degradation of sulfonamides by Microbacterium sp. We have employed a multi-pronged computational strategy involving - protein structure modelling, ligand docking and molecular dynamics simulations to decipher a plausible binding order for the enzymatic degradation of sulfonamides by the bacterial sulfonamide monooxygenase, SulX. Our results enable us to predict that this degradation is achieved through the sequential binding of the antibiotic sulfonamide followed by the reduced flavin cofactor FMNH2, thereby laying the computational foundation for further advancements in enzyme-mediated degradation of the antibiotic. We also provide a list of experiments which may be performed to verify and follow-up on our in-silico studies.Communicated by Ramaswamy H. Sarma.

DEMO-EM2: assembling protein complex structures from cryo-EM maps through intertwined chain and domain fitting

The breakthrough in cryo-electron microscopy (cryo-EM) technology has led to an increasing number of density maps of biological macromolecules. However, constructing accurate protein complex atomic structures from cryo-EM maps remains a challenge. In this study, we extend our previously developed DEMO-EM to present DEMO-EM2, an automated method for constructing protein complex models from cryo-EM maps through an iterative assembly procedure intertwining chain- and domain-level matching and fitting for predicted chain models. The method was carefully evaluated on 27 cryo-electron tomography (cryo-ET) maps and 16 single-particle EM maps, where DEMO-EM2 models achieved an average TM-score of 0.92, outperforming those of state-of-the-art methods. The results demonstrate an efficient method that enables the rapid and reliable solution of challenging cryo-EM structure modeling problems.

Elf1 promotes Rad26's interaction with lesion-arrested Pol II for transcription-coupled repair

Transcription-coupled nucleotide excision repair (TC-NER) is a highly conserved DNA repair pathway that removes bulky lesions in the transcribed genome. Cockayne syndrome B protein (CSB), or its yeast ortholog Rad26, has been known for decades to play important roles in the lesion-recognition steps of TC-NER. Another conserved protein ELOF1, or its yeast ortholog Elf1, was recently identified as a core transcription-coupled repair factor. How Rad26 distinguishes between RNA polymerase II (Pol II) stalled at a DNA lesion or other obstacles and what role Elf1 plays in this process remains unknown. Here, we present cryo-EM structures of Pol II-Rad26 complexes stalled at different obstacles that show that Rad26 uses a common mechanism to recognize a stalled Pol II, with additional interactions when Pol II is arrested at a lesion. A cryo-EM structure of lesion-arrested Pol II-Rad26 bound to Elf1 revealed that Elf1 induces further interactions between Rad26 and a lesion-arrested Pol II. Biochemical and genetic data support the importance of the interplay between Elf1 and Rad26 in TC-NER initiation. Together, our results provide important mechanistic insights into how two conserved transcription-coupled repair factors, Rad26/CSB and Elf1/ELOF1, work together at the initial lesion recognition steps of transcription-coupled repair.

Membrane platform protein PulF of the Klebsiella type II secretion system forms a trimeric ion channel essential for endopilus assembly and protein secretion

IMPORTANCE

Type IV pili and type II secretion systems are members of the widespread type IV filament (T4F) superfamily of nanomachines that assemble dynamic and versatile surface fibers in archaea and bacteria. The assembly and retraction of T4 filaments with diverse surface properties and functions require the plasma membrane platform proteins of the GspF/PilC superfamily. Generally considered dimeric, platform proteins are thought to function as passive transmitters of the mechanical energy generated by the ATPase motor, to somehow promote insertion of pilin subunits into the nascent pilus fibers. Here, we generate and experimentally validate structural predictions that support the trimeric state of a platform protein PulF from a type II secretion system. The PulF trimers form selective proton or sodium channels which might energize pilus assembly using the membrane potential. The conservation of the channel sequence and structural features implies a common mechanism for all T4F assembly systems. We propose a model of the oligomeric PulF-PulE ATPase complex that provides an essential framework to investigate and understand the pilus assembly mechanism.

Tissue factor binds to and inhibits interferon-α receptor 1 signaling

Tissue factor (TF), which is a member of the cytokine receptor family, promotes coagulation and coagulation-dependent inflammation. TF also exerts protective effects through unknown mechanisms. Here, we showed that TF bound to interferon-α receptor 1 (IFNAR1) and antagonized its signaling, preventing spontaneous sterile inflammation and maintaining immune homeostasis. Structural modeling and direct binding studies revealed binding of the TF C-terminal fibronectin III domain to IFNAR1, which restricted the expression of interferon-stimulated genes (ISGs). Podocyte-specific loss of TF in mice (PodΔF3) resulted in sterile renal inflammation, characterized by JAK/STAT signaling, proinflammatory cytokine expression, disrupted immune homeostasis, and glomerulopathy. Inhibiting IFNAR1 signaling or loss of Ifnar1 expression in podocytes attenuated these effects in PodΔF3 mice. As a heteromer, TF and IFNAR1 were both inactive, while dissociation of the TF-IFNAR1 heteromer promoted TF activity and IFNAR1 signaling. These data suggest that the TF-IFNAR1 heteromer is a molecular switch that controls thrombo-inflammation.