Neutralization and Stability of SARS-CoV-2 Omicron Variant

Leveraging machine learning models for peptide-protein interaction prediction

Peptides play a pivotal role in a wide range of biological activities through participating in up to 40% protein-protein interactions in cellular processes. They also demonstrate remarkable specificity and efficacy, making them promising candidates for drug development. However, predicting peptide-protein complexes by traditional computational approaches, such as docking and molecular dynamics simulations, still remains a challenge due to high computational cost, flexible nature of peptides, and limited structural information of peptide-protein complexes. In recent years, the surge of available biological data has given rise to the development of an increasing number of machine learning models for predicting peptide-protein interactions. These models offer efficient solutions to address the challenges associated with traditional computational approaches. Furthermore, they offer enhanced accuracy, robustness, and interpretability in their predictive outcomes. This review presents a comprehensive overview of machine learning and deep learning models that have emerged in recent years for the prediction of peptide-protein interactions.

Molecular dissection of PI3Kβ synergistic activation by receptor tyrosine kinases, GβGγ, and Rho-family GTPases

Phosphoinositide 3-kinase (PI3K) beta (PI3Kβ) is functionally unique in the ability to integrate signals derived from receptor tyrosine kinases (RTKs), G-protein coupled receptors, and Rho-family GTPases. The mechanism by which PI3Kβ prioritizes interactions with various membrane-tethered signaling inputs, however, remains unclear. Previous experiments did not determine whether interactions with membrane-tethered proteins primarily control PI3Kβ localization versus directly modulate lipid kinase activity. To address this gap in our knowledge, we established an assay to directly visualize how three distinct protein interactions regulate PI3Kβ when presented to the kinase in a biologically relevant configuration on supported lipid bilayers. Using single molecule Total Internal Reflection Fluorescence (TIRF) Microscopy, we determined the mechanism controlling PI3Kβ membrane localization, prioritization of signaling inputs, and lipid kinase activation. We find that auto-inhibited PI3Kβ prioritizes interactions with RTK-derived tyrosine phosphorylated (pY) peptides before engaging either GβGγ or Rac1(GTP). Although pY peptides strongly localize PI3Kβ to membranes, stimulation of lipid kinase activity is modest. In the presence of either pY/GβGγ or pY/Rac1(GTP), PI3Kβ activity is dramatically enhanced beyond what can be explained by simply increasing membrane localization. Instead, PI3Kβ is synergistically activated by pY/GβGγ and pY/Rac1 (GTP) through a mechanism consistent with allosteric regulation.

Frequent nonhomologous replacement of replicative helicase loaders by viruses in Vibrionaceae

Several microbial genomes lack textbook-defined essential genes. If an essential gene is absent from a genome, then an evolutionarily independent gene of unknown function complements its function. Here, we identified frequent nonhomologous replacement of an essential component of DNA replication initiation, a replicative helicase loader gene, in Vibrionaceae. Our analysis of Vibrionaceae genomes revealed two genes with unknown function, named vdhL1 and vdhL2, that were substantially enriched in genomes without the known helicase-loader genes. These genes showed no sequence similarities to genes with known function but encoded proteins structurally similar with a viral helicase loader. Analyses of genomic syntenies and coevolution with helicase genes suggested that vdhL1/2 encodes a helicase loader. The in vitro assay showed that Vibrio harveyi VdhL1 and Vibrio ezurae VdhL2 promote the helicase activity of DnaB. Furthermore, molecular phylogenetics suggested that vdhL1/2 were derived from phages and replaced an intrinsic helicase loader gene of Vibrionaceae over 20 times. This high replacement frequency implies the host's advantage in acquiring a viral helicase loader gene.

Mechanisms of ligand recognition and activation of melanin-concentrating hormone receptors

Melanin-concentrating hormone (MCH) is a cyclic neuropeptide that regulates food intake, energy balance, and other physiological functions by stimulating MCHR1 and MCHR2 receptors, both of which are class A G protein-coupled receptors. MCHR1 predominately couples to inhibitory G protein, Gi/o, and MCHR2 can only couple to Gq/11. Here we present cryo-electron microscopy structures of MCH-activated MCHR1 with Gi and MCH-activated MCHR2 with Gq at the global resolutions of 3.01 Å and 2.40 Å, respectively. These structures reveal that MCH adopts a consistent cysteine-mediated hairpin loop configuration when bound to both receptors. A central arginine from the LGRVY core motif between the two cysteines of MCH penetrates deeply into the transmembrane pocket, triggering receptor activation. Integrated with mutational and functional insights, our findings elucidate the molecular underpinnings of ligand recognition and MCH receptor activation and offer a structural foundation for targeted drug design.

A conserved N-terminal motif of CUL3 contributes to assembly and E3 ligase activity of CRL3KLHL22

The CUL3-RING E3 ubiquitin ligases (CRL3s) play an essential role in response to extracellular nutrition and stress stimuli. The ubiquitin ligase function of CRL3s is activated through dimerization. However, how and why such a dimeric assembly is required for its ligase activity remains elusive. Here, we report the cryo-EM structure of the dimeric CRL3KLHL22 complex and reveal a conserved N-terminal motif in CUL3 that contributes to the dimerization assembly and the E3 ligase activity of CRL3KLHL22. We show that deletion of the CUL3 N-terminal motif impairs dimeric assembly and the E3 ligase activity of both CRL3KLHL22 and several other CRL3s. In addition, we found that the dynamics of dimeric assembly of CRL3KLHL22 generates a variable ubiquitination zone, potentially facilitating substrate recognition and ubiquitination. These findings demonstrate that a CUL3 N-terminal motif participates in the assembly process and provide insights into the assembly and activation of CRL3s.

Epigenetic memory is governed by an effector recruitment specificity toggle in Heterochromatin Protein 1

HP1 proteins are essential for establishing and maintaining transcriptionally silent heterochromatin. They dimerize, forming a binding interface to recruit diverse chromatin-associated factors. HP1 proteins are specialized and rapidly evolve, but the extent of variation required to achieve functional specialization is unknown. To investigate how changes in amino acid sequence impacts epigenetic inheritance, we performed a targeted mutagenesis screen of the S. pombe HP1 homolog, Swi6. Substitutions within an auxiliary surface adjacent to the HP1 dimerization interface produced Swi6 variants with divergent maintenance properties. Remarkably, substitutions at a single amino acid position led to the persistent gain or loss of epigenetic inheritance. These substitutions increased Swi6 chromatin occupancy in vivo and altered Swi6-protein interactions that reprogram H3K9me maintenance. We show that relatively minor changes in Swi6 amino acid composition can lead to profound changes in epigenetic inheritance which provides a redundant mechanism to evolve novel effector specificity. .

Phosphatidylinositol (4,5)-bisphosphate drives the formation of EGFR and EphA2 complexes

Receptor tyrosine kinases (RTKs) regulate many cellular functions and are important targets in pharmaceutical development, particularly in cancer treatment. EGFR and EphA2 are two key RTKs that are associated with oncogenic phenotypes. Several studies have reported functional interplay between these receptors, but the mechanism of interaction is still unresolved. Here we utilize a time-resolved fluorescence spectroscopy called PIE-FCCS to resolve EGFR and EphA2 interactions in live cells. We tested the role of ligands and found that EGF, but not ephrin A1 (EA1), stimulated hetero-multimerization between the receptors. To determine the effect of anionic lipids, we targeted phospholipase C (PLC) activity to alter the abundance of phosphatidylinositol (4,5)-bisphosphate (PIP 2 ). We found that higher PIP 2 levels increased homo-multimerization of both EGFR and EphA2, as well as hetero-multimerization. This study provides a direct characterization of EGFR and EphA2 interactions in live cells and shows that PIP 2 can have a substantial effect on the spatial organization of RTKs.

Sliding Window INteraction Grammar (SWING): a generalized interaction language model for peptide and protein interactions

The explosion of sequence data has allowed the rapid growth of protein language models (pLMs). pLMs have now been employed in many frameworks including variant-effect and peptide-specificity prediction. Traditionally, for protein-protein or peptide-protein interactions (PPIs), corresponding sequences are either co-embedded followed by post-hoc integration or the sequences are concatenated prior to embedding. Interestingly, no method utilizes a language representation of the interaction itself. We developed an interaction LM (iLM), which uses a novel language to represent interactions between protein/peptide sequences. Sliding Window Interaction Grammar (SWING) leverages differences in amino acid properties to generate an interaction vocabulary. This vocabulary is the input into a LM followed by a supervised prediction step where the LM's representations are used as features. SWING was first applied to predicting peptide:MHC (pMHC) interactions. SWING was not only successful at generating Class I and Class II models that have comparable prediction to state-of-the-art approaches, but the unique Mixed Class model was also successful at jointly predicting both classes. Further, the SWING model trained only on Class I alleles was predictive for Class II, a complex prediction task not attempted by any existing approach. For de novo data, using only Class I or Class II data, SWING also accurately predicted Class II pMHC interactions in murine models of SLE (MRL/lpr model) and T1D (NOD model), that were validated experimentally. To further evaluate SWING's generalizability, we tested its ability to predict the disruption of specific protein-protein interactions by missense mutations. Although modern methods like AlphaMissense and ESM1b can predict interfaces and variant effects/pathogenicity per mutation, they are unable to predict interaction-specific disruptions. SWING was successful at accurately predicting the impact of both Mendelian mutations and population variants on PPIs. This is the first generalizable approach that can accurately predict interaction-specific disruptions by missense mutations with only sequence information. Overall, SWING is a first-in-class generalizable zero-shot iLM that learns the language of PPIs.

The complete assembly of human LAT1-4F2hc complex provides insights into its regulation, function and localisation

The LAT1-4F2hc complex (SLC7A5-SLC3A2) facilitates uptake of essential amino acids, hormones and drugs. Its dysfunction is associated with many cancers and immune/neurological disorders. Here, we apply native mass spectrometry (MS)-based approaches to provide evidence of super-dimer formation (LAT1-4F2hc)2. When combined with lipidomics, and site-directed mutagenesis, we discover four endogenous phosphatidylethanolamine (PE) molecules at the interface and C-terminus of both LAT1 subunits. We find that interfacial PE binding is regulated by 4F2hc-R183 and is critical for regulation of palmitoylation on neighbouring LAT1-C187. Combining native MS with mass photometry (MP), we reveal that super-dimerization is sensitive to pH, and modulated by complex N-glycans on the 4F2hc subunit. We further validate the dynamic assemblies of LAT1-4F2hc on plasma membrane and in the lysosome. Together our results link PTM and lipid binding with regulation and localisation of the LAT1-4F2hc super-dimer.

Petabase-Scale Homology Search for Structure Prediction

The recent CASP15 competition highlighted the critical role of multiple sequence alignments (MSAs) in protein structure prediction, as demonstrated by the success of the top AlphaFold2-based prediction methods. To push the boundaries of MSA utilization, we conducted a petabase-scale search of the Sequence Read Archive (SRA), resulting in gigabytes of aligned homologs for CASP15 targets. These were merged with default MSAs produced by ColabFold-search and provided to ColabFold-predict. By using SRA data, we achieved highly accurate predictions (GDT_TS > 70) for 66% of the non-easy targets, whereas using ColabFold-search default MSAs scored highly in only 52%. Next, we tested the effect of deep homology search and ColabFold's advanced features, such as more recycles, on prediction accuracy. While SRA homologs were most significant for improving ColabFold's CASP15 ranking from 11th to 3rd place, other strategies contributed too. We analyze these in the context of existing strategies to improve prediction.

Balancing the Affinity and Tumor Cell Binding of a Two-in-One Antibody Simultaneously Targeting EGFR and PD-L1

The optimization of the affinity of monoclonal antibodies is crucial for the development of drug candidates, as it can impact the efficacy of the drug and, thus, the dose and dosing regimen, limit adverse effects, and reduce therapy costs. Here, we present the affinity maturation of an EGFR×PD-L1 Two-in-One antibody for EGFR binding utilizing site-directed mutagenesis and yeast surface display. The isolated antibody variants target EGFR with a 60-fold-improved affinity due to the replacement of a single amino acid in the CDR3 region of the light chain. The binding properties of the Two-in-One variants were confirmed using various methods, including BLI measurements, real-time antigen binding measurements on surfaces with a mixture of both recombinant proteins and cellular binding experiments using flow cytometry as well as real-time interaction cytometry. An AlphaFold-based model predicted that the amino acid exchange of tyrosine to glutamic acid enables the formation of a salt bridge to an arginine at EGFR position 165. This easily adaptable approach provides a strategy for the affinity maturation of bispecific antibodies with respect to the binding of one of the two antigens.

Genotype-phenotype correlation in CLCN4-related developmental and epileptic encephalopathy

CLCN4-related disorder is a rare X-linked neurodevelopmental condition with a pathogenic mechanism yet to be elucidated. CLCN4 encodes the vesicular 2Cl-/H+ exchanger ClC-4, and CLCN4 pathogenic variants frequently result in altered ClC-4 transport activity. The precise cellular and molecular function of ClC-4 remains unknown; however, together with ClC-3, ClC-4 is thought to have a role in the ion homeostasis of endosomes and intracellular trafficking. We reviewed our research database for patients with CLCN4 variants and epilepsy, and performed thorough phenotyping. We examined the functional properties of the variants in mammalian cells using patch-clamp electrophysiology, protein biochemistry, and confocal fluorescence microscopy. Three male patients with developmental and epileptic encephalopathy were identified, with differing phenotypes. Patients #1 and #2 had normal growth parameters and normal-appearing brains on MRI, while patient #3 had microcephaly, microsomia, complete agenesis of the corpus callosum and cerebellar and brainstem hypoplasia. The p.(Gly342Arg) variant of patient #1 significantly impaired ClC-4's heterodimerization capability with ClC-3 and suppressed anion currents. The p.(Ile549Leu) variant of patient #2 and p.(Asp89Asn) variant of patient #3 both shift the voltage dependency of transport activation by 20 mV to more hyperpolarizing potentials, relative to the wild-type, with p.(Asp89Asn) favouring higher transport activity. We concluded that p.(Gly342Arg) carried by patient #1 and the p.(Ile549Leu) expressed by patient #2 impair ClC-4 transport function, while the p.(Asp89Asn) variant results in a gain-of-transport function; all three variants result in epilepsy and global developmental impairment, but with differences in epilepsy presentation, growth parameters, and presence or absence of brain malformations.

Structural flexibility and heterogeneity of recombinant human glial fibrillary acidic protein (GFAP)

Glial fibrillary acidic protein (GFAP) is a promising biomarker for brain and spinal cord disorders. Recent studies have highlighted the differences in the reliability of GFAP measurements in different biological matrices. The reason for these discrepancies is poorly understood as our knowledge of the protein's 3-dimensional conformation, proteoforms, and aggregation remains limited. Here, we investigate the structural properties of GFAP under different conditions. For this, we characterized recombinant GFAP proteins from various suppliers and applied hydrogen-deuterium exchange mass spectrometry (HDX-MS) to provide a snapshot of the conformational dynamics of GFAP in artificial cerebrospinal fluid (aCSF) compared to the phosphate buffer. Our findings indicate that recombinant GFAP exists in various conformational species. Furthermore, we show that GFAP dimers remained intact under denaturing conditions. HDX-MS experiments show an overall decrease in H-bonding and an increase in solvent accessibility of GFAP in aCSF compared to the phosphate buffer, with clear indications of mixed EX2 and EX1 kinetics. To understand possible structural interface regions and the evolutionary conservation profiles, we combined HDX-MS results with the predicted GFAP-dimer structure by AlphaFold-Multimer. We found that deprotected regions with high structural flexibility in aCSF overlap with predicted conserved dimeric 1B and 2B domain interfaces. Structural property predictions combined with the HDX data show an overall deprotection and signatures of aggregation in aCSF. We anticipate that the outcomes of this research will contribute to a deeper understanding of the structural flexibility of GFAP and ultimately shed light on its behavior in different biological matrices.

Can AlphaFold's breakthrough in protein structure help decode the fundamental principles of adaptive cellular immunity?

T cells are essential immune cells responsible for identifying and eliminating pathogens. Through interactions between their T-cell antigen receptors (TCRs) and antigens presented by major histocompatibility complex molecules (MHCs) or MHC-like molecules, T cells discriminate foreign and self peptides. Determining the fundamental principles that govern these interactions has important implications in numerous medical contexts. However, reconstructing a map between T cells and their antagonist antigens remains an open challenge for the field of immunology, and success of in silico reconstructions of this relationship has remained incremental. In this Perspective, we discuss the role that new state-of-the-art deep-learning models for predicting protein structure may play in resolving some of the unanswered questions the field faces linking TCR and peptide-MHC properties to T-cell specificity. We provide a comprehensive overview of structural databases and the evolution of predictive models, and highlight the breakthrough AlphaFold provided the field.

γ-TuRC asymmetry induces local protofilament mismatch at the RanGTP-stimulated microtubule minus end

The γ-tubulin ring complex (γ-TuRC) is a structural template for de novo microtubule assembly from α/β-tubulin units. The isolated vertebrate γ-TuRC assumes an asymmetric, open structure deviating from microtubule geometry, suggesting that γ-TuRC closure may underlie regulation of microtubule nucleation. Here, we isolate native γ-TuRC-capped microtubules from Xenopus laevis egg extract nucleated through the RanGTP-induced pathway for spindle assembly and determine their cryo-EM structure. Intriguingly, the microtubule minus end-bound γ-TuRC is only partially closed and consequently, the emanating microtubule is locally misaligned with the γ-TuRC and asymmetric. In the partially closed conformation of the γ-TuRC, the actin-containing lumenal bridge is locally destabilised, suggesting lumenal bridge modulation in microtubule nucleation. The microtubule-binding protein CAMSAP2 specifically binds the minus end of γ-TuRC-capped microtubules, indicating that the asymmetric minus end structure may underlie recruitment of microtubule-modulating factors for γ-TuRC release. Collectively, we reveal a surprisingly asymmetric microtubule minus end protofilament organisation diverging from the regular microtubule structure, with direct implications for the kinetics and regulation of nucleation and subsequent modulation of microtubules during spindle assembly.

The rapid proximity labeling system PhastID identifies ATP6AP1 as an unconventional GEF for Rheb

Rheb is a small G protein that functions as the direct activator of the mechanistic target of rapamycin complex 1 (mTORC1) to coordinate signaling cascades in response to nutrients and growth factors. Despite extensive studies, the guanine nucleotide exchange factor (GEF) that directly activates Rheb remains unclear, at least in part due to the dynamic and transient nature of protein-protein interactions (PPIs) that are the hallmarks of signal transduction. Here, we report the development of a rapid and robust proximity labeling system named Pyrococcus horikoshii biotin protein ligase (PhBPL)-assisted biotin identification (PhastID) and detail the insulin-stimulated changes in Rheb-proximity protein networks that were identified using PhastID. In particular, we found that the lysosomal V-ATPase subunit ATP6AP1 could dynamically interact with Rheb. ATP6AP1 could directly bind to Rheb through its last 12 amino acids and utilizes a tri-aspartate motif in its highly conserved C-tail to enhance Rheb GTP loading. In fact, targeting the ATP6AP1 C-tail could block Rheb activation and inhibit cancer cell proliferation and migration. Our findings highlight the versatility of PhastID in mapping transient PPIs in live cells, reveal ATP6AP1's role as an unconventional GEF for Rheb, and underscore the importance of ATP6AP1 in integrating mTORC1 activation signals through Rheb, filling in the missing link in Rheb/mTORC1 activation.

Structural basis of human U5 snRNP late biogenesis and recycling

Pre-mRNA splicing by the spliceosome requires the biogenesis and recycling of its small nuclear ribonucleoprotein (snRNP) complexes, which are consumed in each round of splicing. The human U5 snRNP is the ~1 MDa 'heart' of the spliceosome and is recycled through an unknown mechanism involving major architectural rearrangements and the dedicated chaperones CD2BP2 and TSSC4. Late steps in U5 snRNP biogenesis similarly involve these chaperones. Here we report cryo-electron microscopy structures of four human U5 snRNP-CD2BP2-TSSC4 complexes, revealing how a series of molecular events primes the U5 snRNP to generate the ~2 MDa U4/U6.U5 tri-snRNP, the largest building block of the spliceosome.

Activation of CBASS Cap5 endonuclease immune effector by cyclic nucleotides

The bacterial cyclic oligonucleotide-based antiphage signaling system (CBASS) is similar to the cGAS-STING system in humans, containing an enzyme that synthesizes a cyclic nucleotide on viral infection and an effector that senses the second messenger for the antiviral response. Cap5, containing a SAVED domain coupled to an HNH DNA endonuclease domain, is the most abundant CBASS effector, yet the mechanism by which it becomes activated for cell killing remains unknown. We present here high-resolution structures of full-length Cap5 from Pseudomonas syringae (Ps) with second messengers. The key to PsCap5 activation is a dimer-to-tetramer transition, whereby the binding of second messenger to dimer triggers an open-to-closed transformation of the SAVED domains, furnishing a surface for assembly of the tetramer. This movement propagates to the HNH domains, juxtaposing and converting two HNH domains into states for DNA destruction. These results show how Cap5 effects bacterial cell suicide and we provide proof-in-principle data that the CBASS can be extrinsically activated to limit bacterial infections.

PPIscreenML: Structure-based screening for protein-protein interactions using AlphaFold

Protein-protein interactions underlie nearly all cellular processes. With the advent of protein structure prediction methods such as AlphaFold2 (AF2), models of specific protein pairs can be built extremely accurately in most cases. However, determining the relevance of a given protein pair remains an open question. It is presently unclear how to use best structure-based tools to infer whether a pair of candidate proteins indeed interact with one another: ideally, one might even use such information to screen amongst candidate pairings to build up protein interaction networks. Whereas methods for evaluating quality of modeled protein complexes have been co-opted for determining which pairings interact (e.g., pDockQ and iPTM), there have been no rigorously benchmarked methods for this task. Here we introduce PPIscreenML, a classification model trained to distinguish AF2 models of interacting protein pairs from AF2 models of compelling decoy pairings. We find that PPIscreenML out-performs methods such as pDockQ and iPTM for this task, and further that PPIscreenML exhibits impressive performance when identifying which ligand/receptor pairings engage one another across the structurally conserved tumor necrosis factor superfamily (TNFSF). Analysis of benchmark results using complexes not seen in PPIscreenML development strongly suggest that the model generalizes beyond training data, making it broadly applicable for identifying new protein complexes based on structural models built with AF2.

Functional selection in SH3-mediated activation of the PI3 kinase

The phosphoinositide-3 kinase (PI3K), a heterodimeric enzyme, plays a pivotal role in cellular metabolism and survival. Its deregulation is associated with major human diseases, particularly cancer. The p85 regulatory subunit of PI3K binds to the catalytic p110 subunit via its C-terminal domains, stabilising it in an inhibited state. Certain Src homology 3 (SH3) domains can activate p110 by binding to the proline-rich (PR) 1 motif located at the N-terminus of p85. However, the mechanism by which this N-terminal interaction activates the C-terminally bound p110 remains elusive. Moreover, the intrinsically poor ligand selectivity of SH3 domains raises the question of how they can control PI3K. Combining structural, biophysical, and functional methods, we demonstrate that the answers to both these unknown issues are linked: PI3K-activating SH3 domains engage in additional "tertiary" interactions with the C-terminal domains of p85, thereby relieving their inhibition of p110. SH3 domains lacking these tertiary interactions may still bind to p85 but cannot activate PI3K. Thus, p85 uses a functional selection mechanism that precludes nonspecific activation rather than nonspecific binding. This separation of binding and activation may provide a general mechanism for how biological activities can be controlled by promiscuous protein-protein interaction domains.

Protein engineering a PhotoRNR chimera based on a unifying evolutionary apparatus among the natural classes of ribonucleotide reductases

Ribonucleotide reductases (RNRs) are essential enzymes that catalyze the de novo transformation of nucleoside 5'-di(tri)phosphates [ND(T)Ps, where N is A, U, C, or G] to their corresponding deoxynucleotides. Despite the diversity of factors required for function and the low sequence conservation across RNRs, a unifying apparatus consolidating RNR activity is explored. We combine aspects of the protein subunit simplicity of class II RNR with a modified version of Escherichia coli class la photoRNRs that initiate radical chemistry with light to engineer a mimic of a class II enzyme. The design of this RNR involves fusing a truncated form of the active site containing α subunit with the functionally important C-terminal tail of the radical-generating β subunit to render a chimeric RNR. Inspired by a recent cryo-EM structure, a [Re] photooxidant is located adjacent to Y356[β], which is an essential component of the radical transport pathway in class I RNRs. Combination of this RNR photochimera with cytidine diphosphate (CDP), adenosine triphosphate (ATP), and light resulted in the generation of Y356• along with production of deoxycytidine diphosphate (dCDP) and cytosine. The photoproducts reflect an active site chemistry consistent with both the consensus mechanism of RNR and chemistry observed when RNR is inactivated by mechanism-based inhibitors in the active site. The enzymatic activity of the RNR photochimera in the absence of any β metallocofactor highlights the adaptability of the 10-stranded αβ barrel finger loop to support deoxynucleotide formation and accommodate the design of engineered RNRs.

State of the Interactomes: an evaluation of molecular networks for generating biological insights

Advancements in genomic and proteomic technologies have powered the use of gene and protein networks ("interactomes") for understanding genotype-phenotype translation. However, the proliferation of interactomes complicates the selection of networks for specific applications. Here, we present a comprehensive evaluation of 46 current human interactomes, encompassing protein-protein interactions as well as gene regulatory, signaling, colocalization, and genetic interaction networks. Our analysis shows that large composite networks such as HumanNet, STRING, and FunCoup are most effective for identifying disease genes, while smaller networks such as DIP and SIGNOR demonstrate strong interaction prediction performance. These findings provide a benchmark for interactomes across diverse network biology applications and clarify factors that influence network performance. Furthermore, our evaluation pipeline paves the way for continued assessment of emerging and updated interaction networks in the future.

DeepSub: Utilizing Deep Learning for Predicting the Number of Subunits in Homo-Oligomeric Protein Complexes

The molecular weight (MW) of an enzyme is a critical parameter in enzyme-constrained models (ecModels). It is determined by two factors: the presence of subunits and the abundance of each subunit. Although the number of subunits (NS) can potentially be obtained from UniProt, this information is not readily available for most proteins. In this study, we addressed this gap by extracting and curating subunit information from the UniProt database to establish a robust benchmark dataset. Subsequently, we propose a novel model named DeepSub, which leverages the protein language model and Bi-directional Gated Recurrent Unit (GRU), to predict NS in homo-oligomers solely based on protein sequences. DeepSub demonstrates remarkable accuracy, achieving an accuracy rate as high as 0.967, surpassing the performance of QUEEN. To validate the effectiveness of DeepSub, we performed predictions for protein homo-oligomers that have been reported in the literature but are not documented in the UniProt database. Examples include homoserine dehydrogenase from Corynebacterium glutamicum, Matrilin-4 from Mus musculus and Homo sapiens, and the Multimerins protein family from M. musculus and H. sapiens. The predicted results align closely with the reported findings in the literature, underscoring the reliability and utility of DeepSub.

Establishing comprehensive quaternary structural proteomes from genome sequence

A critical body of knowledge has developed through advances in protein microscopy, protein-fold modeling, structural biology software, availability of sequenced bacterial genomes, large-scale mutation databases, and genome-scale models. Based on these recent advances, we develop a computational framework that; i) identifies the oligomeric structural proteome encoded by an organism's genome from available structural resources; ii) maps multi-strain alleleomic variation, resulting in the structural proteome for a species; and iii) calculates the 3D orientation of proteins across subcellular compartments with residue-level precision. Using the platform, we; iv) compute the quaternary E. coli K-12 MG1655 structural proteome; v) use a dataset of 12,000 mutations to build Random Forest classifiers that can predict the severity of mutations; and, in combination with a genome-scale model that computes proteome allocation, vi) obtain the spatial allocation of the E. coli proteome. Thus, in conjunction with relevant datasets and increasingly accurate computational models, we can now annotate quaternary structural proteomes, at genome-scale, to obtain a molecular-level understanding of whole-cell functions.

Significance

Advancements in experimental and computational methods have revealed the shapes of multi-subunit proteins. The absence of a unified platform that maps actionable datatypes onto these increasingly accurate structures creates a barrier to structural analyses, especially at the genome-scale. Here, we describe QSPACE, a computational annotation platform that evaluates existing resources to identify the best-available structure for each protein in a user's query, maps the 3D location of actionable datatypes ( e.g. , active sites, published mutations) onto the selected structures, and uses third-party APIs to determine the subcellular compartment of all amino acids of a protein. As proof-of-concept, we deployed QSPACE to generate the quaternary structural proteome of E. coli MG1655 and demonstrate two use-cases involving large-scale mutant analysis and genome-scale modelling.

Deep learning insights into the architecture of the mammalian egg-sperm fusion synapse

A crucial event in sexual reproduction is when haploid sperm and egg fuse to form a new diploid organism at fertilization. In mammals, direct interaction between egg JUNO and sperm IZUMO1 mediates gamete membrane adhesion, yet their role in fusion remains enigmatic. We used AlphaFold to predict the structure of other extracellular proteins essential for fertilization to determine if they could form a complex that may mediate fusion. We first identified TMEM81, whose gene is expressed by mouse and human spermatids, as a protein having structural homologies with both IZUMO1 and another sperm molecule essential for gamete fusion, SPACA6. Using a set of proteins known to be important for fertilization and TMEM81, we then systematically searched for predicted binary interactions using an unguided approach and identified a pentameric complex involving sperm IZUMO1, SPACA6, TMEM81 and egg JUNO, CD9. This complex is structurally consistent with both the expected topology on opposing gamete membranes and the location of predicted N-glycans not modeled by AlphaFold-Multimer, suggesting that its components could organize into a synapse-like assembly at the point of fusion. Finally, the structural modeling approach described here could be more generally useful to gain insights into transient protein complexes difficult to detect experimentally.

Cryo-EM Structure of HRSL Domain Reveals Activating Crossed Helices at the Core of GCN2

GCN2 is a conserved receptor kinase activating the Integrated Stress Response (ISR) in eukaryotic cells. The ISR kinases detect accumulation of stress molecules and reprogram translation from basal tasks to preferred production of cytoprotective proteins. GCN2 stands out evolutionarily among all protein kinases due to the presence of a h istidyl t R NA s ynthetase-like (HRSL) domain, which arises only in GCN2 and is located next to the kinase domain. How HRSL contributes to GCN2 signaling remains unknown. Here we report a 3.2 Å cryo-EM structure of HRSL from thermotolerant yeast Kluyveromyces marxianus . This structure shows a constitutive symmetrical homodimer featuring a compact helical-bundle structure at the junction between HRSL and kinase domains, in the core of the receptor. Mutagenesis demonstrates that this junction structure activates GCN2 and indicates that our cryo-EM structure captures the active signaling state of HRSL. Based on these results, we put forward a GCN2 regulation mechanism, where HRSL drives the formation of activated kinase dimers. Remaining domains of GCN2 have the opposite role and in the absence of stress they help keep GCN2 basally inactive. This autoinhibitory activity is relieved upon stress ligand binding. We propose that the opposing action of HRSL and additional GCN2 domains thus yields a regulated ISR receptor.

Significance statement

Regulation of protein synthesis (translation) is a central mechanism by which eukaryotic cells adapt to stressful conditions. In starving cells, this translational adaptation is achieved via the receptor kinase GCN2, which stays inactive under normal conditions, but is switched on under stress. The molecular mechanism of GCN2 switching is not well understood due to the presence of a structurally and biochemically uncharacterized h istidyl t R NA s ynthetase-like domain (HRSL) at the core of GCN2. Here we use single-particle cryo-EM and biochemistry to elucidate the structure and function of HRSL. We identify a structure at the kinase/HRSL interface, which forms crossed helices and helps position GCN2 kinase domains for activation. These data clarify the molecular mechanism of GCN2 regulation.

Lipid scrambling is a general feature of protein insertases

Glycerophospholipids are synthesized primarily in the cytosolic leaflet of the endoplasmic reticulum (ER) membrane and must be equilibrated between bilayer leaflets to allow the ER and membranes derived from it to grow. Lipid equilibration is facilitated by integral membrane proteins called "scramblases." These proteins feature a hydrophilic groove allowing the polar heads of lipids to traverse the hydrophobic membrane interior, similar to a credit card moving through a reader. Nevertheless, despite their fundamental role in membrane expansion and dynamics, the identity of most scramblases has remained elusive. Here, combining biochemical reconstitution and molecular dynamics simulations, we show that lipid scrambling is a general feature of protein insertases, integral membrane proteins which insert polypeptide chains into membranes of the ER and organelles disconnected from vesicle trafficking. Our data indicate that lipid scrambling occurs in the same hydrophilic channel through which protein insertion takes place and that scrambling is abolished in the presence of nascent polypeptide chains. We propose that protein insertases could have a so-far-overlooked role in membrane dynamics as scramblases.

Nap1 and Kap114 co-chaperone H2A-H2B and facilitate targeted histone release in the nucleus

Core histones are synthesized and processed in the cytoplasm before transport into the nucleus for assembly into nucleosomes; however, they must also be chaperoned as free histones are toxic. The importin Kap114 binds and transports histone H2A-H2B into the yeast nucleus, where RanGTP facilitates H2A-H2B release. Kap114 and H2A-H2B also bind the Nap1 histone chaperone, which is found in both the cytoplasm and the nucleus, but how Nap1 and Kap114 cooperate in H2A-H2B processing and nucleosome assembly has been unclear. To understand these mechanisms, we used biochemical and structural analyses to reveal how Nap1, Kap114, H2A-H2B and RanGTP interact. We show that Kap114, H2A-H2B and a Nap1 dimer (Nap1 2 ) assemble into a 1:1:1 ternary complex. Cryogenic electron microscopy revealed two distinct Kap114/Nap1 2 /H2A-H2B structures: one of H2A-H2B sandwiched between Nap1 2 and Kap114, and another in which Nap1 2 bound to the Kap114·H2A-H2B complex without contacting H2A-H2B. Another Nap1 2 ·H2A-H2B·Kap114·Ran GTP structure reveals the nuclear complex. Mutagenesis revealed shared critical interfaces in all three structures. Consistent with structural findings, DNA competition experiments demonstrated that Kap114 and Nap1 2 together chaperone H2A-H2B better than either protein alone. When RanGTP is present, Kap114's chaperoning activity diminishes. However, the presence of Nap1 2 within the Nap1 2 ·H2A-H2B·Kap114·Ran GTP quaternary complex restores its ability to chaperone H2A-H2B. This complex effectively deposits H2A-H2B into nucleosomes. Together, these findings suggest that Kap114 and Nap12 provide a sheltered path from cytoplasm to nucleus, facilitating the transfer of H2A-H2B from Kap114 to Nap1 2 , ultimately directing its specific deposition into nucleosomes.

Structure-Based Protein Assembly Simulations Including Various Binding Sites and Conformations

Many biological functions are mediated by large complexes formed by multiple proteins and other cellular macromolecules. Recent progress in experimental structure determination, as well as in integrative modeling and protein structure prediction using deep learning approaches, has resulted in a rapid increase in the number of solved multiprotein assemblies. However, the assembly process of large complexes from their components is much less well-studied. We introduce a rapid computational structure-based (SB) model, GoCa, that allows to follow the assembly process of large multiprotein complexes based on a known native structure. Beyond existing SB Go̅-type models, it distinguishes between intra- and intersubunit interactions, allowing us to include coupled folding and binding. It accounts automatically for the permutation of identical subunits in a complex and allows the definition of multiple minima (native) structures in the case of proteins that undergo global transitions during assembly. The model is successfully tested on several multiprotein complexes. The source code of the GoCa program including a tutorial is publicly available on Github: https://github.com/ZachariasLab/GoCa. We also provide a web source that allows users to quickly generate the necessary input files for a GoCa simulation: https://goca.t38webservices.nat.tum.de.

Prediction of the essential intermolecular contacts for side-binding of VASP on F-actin

Vasodilator-stimulated phosphoprotein (VASP) family proteins play a crucial role in mediating the actin network architecture in the cytoskeleton. The Ena/VASP homology 2 (EVH2) domain in each of the four identical arms of the tetrameric VASP consists of a loading poly-Pro region, a G-actin-binding domain (GAB), and an F-actin-binding domain (FAB). Together, the poly-Pro, GAB, and FAB domains allow VASP to bind to sides of actin filaments in a bundle, and recruit profilin-G-actin to processively elongate the filaments. The atomic resolution structure of the ternary complex, consisting of the loading poly-Pro region and GAB domain of VASP with profilin-actin, has been solved over a decade ago; however, a detailed structure of the FAB-F-actin complex has not been resolved to date. Experimental insights, based on homology of the FAB domain with the C region of WASP, have been used to hypothesize that the FAB domain binds to the cleft between subdomains 1 and 3 of F-actin. Here, in order to develop our understanding of the VASP-actin complex, we first augment known structural information about the GAB domain binding to actin with the missing FAB domain-actin structure, which we predict using homology modeling and docking simulations. In earlier work, we used mutagenesis and kinetic modeling to study the role of domain-level binding-unbinding kinetics of Ena/VASP on actin filaments in a bundle, specifically on the side of actin filaments. We further look at the nature of the side-binding of the FAB domain of VASP at the atomistic level using our predicted structure, and tabulate effective mutation sites on the FAB domain that would disrupt the VASP-actin complex. We test the binding affinity of Ena with mutated FAB domain using total internal reflection fluorescence microscopy experiments. The binding affinity of VASP is affected significantly for the mutant, providing additional support for our predicted structure.

PAbFold: Linear Antibody Epitope Prediction using AlphaFold2

Defining the binding epitopes of antibodies is essential for understanding how they bind to their antigens and perform their molecular functions. However, while determining linear epitopes of monoclonal antibodies can be accomplished utilizing well-established empirical procedures, these approaches are generally labor- and time-intensive and costly. To take advantage of the recent advances in protein structure prediction algorithms available to the scientific community, we developed a calculation pipeline based on the localColabFold implementation of AlphaFold2 that can predict linear antibody epitopes by predicting the structure of the complex between antibody heavy and light chains and target peptide sequences derived from antigens. We found that this AlphaFold2 pipeline, which we call PAbFold, was able to accurately flag known epitope sequences for several well-known antibody targets (HA / Myc) when the target sequence was broken into small overlapping linear peptides and antibody complementarity determining regions (CDRs) were grafted onto several different antibody framework regions in the single-chain antibody fragment (scFv) format. To determine if this pipeline was able to identify the epitope of a novel antibody with no structural information publicly available, we determined the epitope of a novel anti-SARS-CoV-2 nucleocapsid targeted antibody using our method and then experimentally validated our computational results using peptide competition ELISA assays. These results indicate that the AlphaFold2-based PAbFold pipeline we developed is capable of accurately identifying linear antibody epitopes in a short time using just antibody and target protein sequences. This emergent capability of the method is sensitive to methodological details such as peptide length, AlphaFold2 neural network versions, and multiple-sequence alignment database. PAbFold is available at https://github.com/jbderoo/PAbFold.

Staphylococcus aureus FtsZ and PBP4 bind to the conformationally dynamic N-terminal domain of GpsB

In the Firmicutes phylum, GpsB is a membrane associated protein that coordinates peptidoglycan synthesis with cell growth and division. Although GpsB has been studied in several bacteria, the structure, function, and interactome of Staphylococcus aureus GpsB is largely uncharacterized. To address this knowledge gap, we solved the crystal structure of the N-terminal domain of S. aureus GpsB, which adopts an atypical, asymmetric dimer, and demonstrates major conformational flexibility that can be mapped to a hinge region formed by a three-residue insertion exclusive to Staphylococci. When this three-residue insertion is excised, its thermal stability increases, and the mutant no longer produces a previously reported lethal phenotype when overexpressed in Bacillus subtilis. In S. aureus, we show that these hinge mutants are less functional and speculate that the conformational flexibility imparted by the hinge region may serve as a dynamic switch to fine-tune the function of the GpsB complex and/or to promote interaction with its various partners. Furthermore, we provide the first biochemical, biophysical, and crystallographic evidence that the N-terminal domain of GpsB binds not only PBP4, but also FtsZ, through a conserved recognition motif located on their C-termini, thus coupling peptidoglycan synthesis to cell division. Taken together, the unique structure of S. aureus GpsB and its direct interaction with FtsZ/PBP4 provide deeper insight into the central role of GpsB in S. aureus cell division.

Generalized biomolecular modeling and design with RoseTTAFold All-Atom

Deep-learning methods have revolutionized protein structure prediction and design but are presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which combines a residue-based representation of amino acids and DNA bases with an atomic representation of all other groups to model assemblies that contain proteins, nucleic acids, small molecules, metals, and covalent modifications, given their sequences and chemical structures. By fine-tuning on denoising tasks, we developed RFdiffusion All-Atom (RFdiffusionAA), which builds protein structures around small molecules. Starting from random distributions of amino acid residues surrounding target small molecules, we designed and experimentally validated, through crystallography and binding measurements, proteins that bind the cardiac disease therapeutic digoxigenin, the enzymatic cofactor heme, and the light-harvesting molecule bilin.

Evolutionary analysis reveals the role of a non-catalytic domain of peptidyl arginine deiminase 2 in transcriptional regulation

Peptidyl arginine deiminases (PADIs) catalyze protein citrullination, a post-translational conversion of arginine to citrulline. The most widely expressed member of this family, PADI2, regulates cellular processes that impact several diseases. We hypothesized that we could gain new insights into PADI2 function through a systematic evolutionary and structural analysis. Here, we identify 20 positively selected PADI2 residues, 16 of which are structurally exposed and maintain PADI2 interactions with cognate proteins. Many of these selected residues reside in non-catalytic regions of PADI2. We validate the importance of a prominent loop in the middle domain that encompasses PADI2 L162, a residue under positive selection. This site is essential for interaction with the transcription elongation factor (P-TEFb) and mediates the active transcription of the oncogenes c-MYC, and CCNB1, as well as impacting cellular proliferation. These insights could be key to understanding and addressing the role of the PADI2 c-MYC axis in cancer progression.

Structural determinants for activation of the Tau kinase CDK5 by the serotonin receptor 5-HT7R

BACKGROUND

Multiple neurodegenerative diseases are induced by the formation and deposition of protein aggregates. In particular, the microtubule-associated protein Tau leads to the development of so-called tauopathies characterized by the aggregation of hyperphosphorylated Tau within neurons. We recently showed that the constitutive activity of the serotonin receptor 7 (5-HT7R) is required for Tau hyperphosphorylation and aggregation through activation of the cyclin-dependent kinase 5 (CDK5). We also demonstrated physical interaction between 5-HT7R and CDK5 at the plasma membrane suggesting that the 5-HT7R/CDK5 complex is an integral part of the signaling network involved in Tau-mediated pathology.

METHODS

Using biochemical, microscopic, molecular biological, computational and AI-based approaches, we investigated structural requirements for the formation of 5-HT7R/CDK5 complex.

RESULTS

We demonstrated that 5-HT7R domains responsible for coupling to Gs proteins are not involved in receptor interaction with CDK5. We also created a structural model of the 5-HT7R/CDK5 complex and refined the interaction interface. The model predicted two conserved phenylalanine residues, F278 and F281, within the third intracellular loop of 5-HT7R to be potentially important for complex formation. While site-directed mutagenesis of these residues did not influence Gs protein-mediated receptor signaling, replacement of both phenylalanines by alanine residues significantly reduced 5-HT7R/CDK5 interaction and receptor-mediated CDK5 activation, leading to reduced Tau hyperphosphorylation and aggregation. Molecular dynamics simulations of 5-HT7R/CDK5 complex for wild-type and receptor mutants confirmed binding interface stability of the initial model.

CONCLUSIONS

Our results provide a structural basis for the development of novel drugs targeting the 5-HT7R/CDK5 interaction interface for the selective treatment of Tau-related disorders, including frontotemporal dementia and Alzheimer's disease.

Type I interferon regulation by USP18 is a key vulnerability in cancer

Precise regulation of Type I interferon signaling is crucial for combating infection and cancer while avoiding autoimmunity. Type I interferon signaling is negatively regulated by USP18. USP18 cleaves ISG15, an interferon-induced ubiquitin-like modification, via its canonical catalytic function, and inhibits Type I interferon receptor activity through its scaffold role. USP18 loss-of-function dramatically impacts immune regulation, pathogen susceptibility, and tumor growth. However, prior studies have reached conflicting conclusions regarding the relative importance of catalytic versus scaffold function. Here, we develop biochemical and cellular methods to systematically define the physiological role of USP18. By comparing a patient-derived mutation impairing scaffold function (I60N) to a mutation disrupting catalytic activity (C64S), we demonstrate that scaffold function is critical for cancer cell vulnerability to Type I interferon. Surprisingly, we discovered that human USP18 exhibits minimal catalytic activity, in stark contrast to mouse USP18. These findings resolve human USP18's mechanism-of-action and enable USP18-targeted therapeutics.

Click, Compute, Create: A Review of Web-based Tools for Enzyme Engineering

Enzyme engineering, though pivotal across various biotechnological domains, is often plagued by its time-consuming and labor-intensive nature. This review aims to offer an overview of supportive in silico methodologies for this demanding endeavor. Starting from methods to predict protein structures, to classification of their activity and even the discovery of new enzymes we continue with describing tools used to increase thermostability and production yields of selected targets. Subsequently, we discuss computational methods to modulate both, the activity as well as selectivity of enzymes. Last, we present recent approaches based on cutting-edge machine learning methods to redesign enzymes. With exception of the last chapter, there is a strong focus on methods easily accessible via web-interfaces or simple Python-scripts, therefore readily useable for a diverse and broad community.

NFATC2IP is a mediator of SUMO-dependent genome integrity

The post-translational modification of proteins by SUMO is crucial for cellular viability and mammalian development in part due to the contribution of SUMOylation to genome duplication and repair. To investigate the mechanisms underpinning the essential function of SUMO, we undertook a genome-scale CRISPR/Cas9 screen probing the response to SUMOylation inhibition. This effort identified 130 genes whose disruption reduces or enhances the toxicity of TAK-981, a clinical-stage inhibitor of the SUMO E1-activating enzyme. Among the strongest hits, we validated and characterized NFATC2IP, an evolutionarily conserved protein related to the fungal Esc2 and Rad60 proteins that harbors tandem SUMO-like domains. Cells lacking NFATC2IP are viable but are hypersensitive to SUMO E1 inhibition, likely due to the accumulation of mitotic chromosome bridges and micronuclei. NFATC2IP primarily acts in interphase and associates with nascent DNA, suggesting a role in the postreplicative resolution of replication or recombination intermediates. Mechanistically, NFATC2IP interacts with the SMC5/6 complex and UBC9, the SUMO E2, via its first and second SUMO-like domains, respectively. AlphaFold-Multimer modeling suggests that NFATC2IP positions and activates the UBC9-NSMCE2 complex, the SUMO E3 ligase associated with SMC5/SMC6. We conclude that NFATC2IP is a key mediator of SUMO-dependent genomic integrity that collaborates with the SMC5/6 complex.

Oligomeric assembly of the C-terminal and transmembrane region of SARS-CoV-2 nsp3

As for all single-stranded, positive-sense RNA (+RNA) viruses, intracellular RNA synthesis relies on extensive remodeling of host cell membranes that leads to the formation of specialized structures. In the case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) coronavirus causing COVID-19, endoplasmic reticulum membranes are modified, resulting in the formation of double-membrane vesicles (DMVs), which contain the viral dsRNA intermediate and constitute membrane-bound replication organelles. The non-structural and transmembrane protein nsp3 is a key player in the biogenesis of DMVs and, therefore, represents an interesting antiviral target. However, as an integral transmembrane protein, it is challenging to express for structural biology. The C-terminus of nsp3 encompasses all the membrane-spanning, -interacting, and -remodeling elements. By using a cell-free expression system, we successfully produced the C-terminal region of nsp3 (nsp3C) and reconstituted purified nsp3C into phospholipid nanodiscs, opening the way for structural studies. Negative-stain transmission electron microscopy revealed the presence of nsp3C oligomers very similar to the region abutting and spanning the membrane on the cytosolic side of DMVs in a recent subtomogram average of the SARS-CoV-2 nsp3-4 pore (1). AlphaFold-predicted structural models fit particularly well with our experimental data and support a pore-forming hexameric assembly. Altogether, our data give unprecedented clues to understand the structural organization of nsp3, the principal component that shapes the molecular pore that spans the DMVs and is required for the export of RNA in vivo.

IMPORTANCE

Membrane remodeling is at the heart of intracellular replication for single-stranded, positive-sense RNA viruses. In the case of coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), this leads to the formation of a network of double-membrane vesicles (DMVs). Targeting DMV biogenesis offers promising prospects for antiviral therapies. This requires a better understanding of the molecular mechanisms and proteins involved. Three non-structural proteins (nsp3, nsp4, and nsp6) direct the intracellular membrane rearrangements upon SARS-CoV-2 infection. All of them contain transmembrane helices. The nsp3 component, the largest and multi-functional protein of the virus, plays an essential role in this process. Aiming to understand its structural organization, we used a cell-free protein synthesis assay to produce and reconstitute the C-terminal part of nsp3 (nsp3C) including transmembrane domains into phospholipid nanodiscs. Our work reveals the oligomeric organization of one key player in the biogenesis of SARS-CoV-2 DMVs, providing basis for the design of future antiviral strategies.

Evolutionary Conservation in Protein-Protein Interactions and Structures of the Elongator Sub-Complex ELP456 from Arabidopsis and Yeast

The Elongator complex plays a pivotal role in the wobble uridine modification of the tRNA anticodon. Comprising two sets of six distinct subunits, namely, Elongator proteins (ELP1-ELP6) and associated proteins, the holo-Elongator complex demonstrates remarkable functional and structural conservation across eukaryotes. However, the precise details of the evolutionary conservation of the holo-Elongator complex and its individual sub-complexes (i.e., ELP123; ELP456) in plants remain limited. In this study, we conducted an in vivo analysis of protein-protein interactions among Arabidopsis ELP4, ELP5, and ELP6 proteins. Additionally, we predicted their structural configurations and performed a comparative analysis with the structure of the yeast Elp456 sub-complex. Protein-protein interaction analysis revealed that AtELP4 interacts with AtELP6 but not directly with AtELP5. Furthermore, we found that the Arabidopsis Elongator-associated protein, Deformed Roots and Leaves 1 (DRL1), did not directly bind to AtELP proteins. The structural comparison of the ELP456 sub-complex between Arabidopsis and yeast demonstrated high similarity, encompassing the RecA-ATPase fold and the positions of hydrogen bonds, despite their relatively low sequence homology. Our findings suggest that Arabidopsis ELP4, ELP5, and ELP6 proteins form a heterotrimer, with ELP6 serving as a bridge, indicating high structural conservation between the ELP456 sub-complexes from Arabidopsis and yeast.

Trace gas oxidation sustains energy needs of a thermophilic archaeon at suboptimal temperatures

Diverse aerobic bacteria use atmospheric hydrogen (H2) and carbon monoxide (CO) as energy sources to support growth and survival. Such trace gas oxidation is recognised as a globally significant process that serves as the main sink in the biogeochemical H2 cycle and sustains microbial biodiversity in oligotrophic ecosystems. However, it is unclear whether archaea can also use atmospheric H2. Here we show that a thermoacidophilic archaeon, Acidianus brierleyi (Thermoproteota), constitutively consumes H2 and CO to sub-atmospheric levels. Oxidation occurs across a wide range of temperatures (10 to 70 °C) and enhances ATP production during starvation-induced persistence under temperate conditions. The genome of A. brierleyi encodes a canonical CO dehydrogenase and four distinct [NiFe]-hydrogenases, which are differentially produced in response to electron donor and acceptor availability. Another archaeon, Metallosphaera sedula, can also oxidize atmospheric H2. Our results suggest that trace gas oxidation is a common trait of Sulfolobales archaea and may play a role in their survival and niche expansion, including during dispersal through temperate environments.

One substrate many enzymes virtual screening uncovers missing genes of carnitine biosynthesis in human and mouse

The increasing availability of experimental and computational protein structures entices their use for function prediction. Here we develop an automated procedure to identify enzymes involved in metabolic reactions by assessing substrate conformations docked to a library of protein structures. By screening AlphaFold-modeled vitamin B6-dependent enzymes, we find that a metric based on catalytically favorable conformations at the enzyme active site performs best (AUROC Score=0.84) in identifying genes associated with known reactions. Applying this procedure, we identify the mammalian gene encoding hydroxytrimethyllysine aldolase (HTMLA), the second enzyme of carnitine biosynthesis. Upon experimental validation, we find that the top-ranked candidates, serine hydroxymethyl transferase (SHMT) 1 and 2, catalyze the HTMLA reaction. However, a mouse protein absent in humans (threonine aldolase; Tha1) catalyzes the reaction more efficiently. Tha1 did not rank highest based on the AlphaFold model, but its rank improved to second place using the experimental crystal structure we determined at 2.26 Å resolution. Our findings suggest that humans have lost a gene involved in carnitine biosynthesis, with HTMLA activity of SHMT partially compensating for its function.

Predictomes: A classifier-curated database of AlphaFold-modeled protein-protein interactions

Protein-protein interactions (PPIs) are ubiquitous in biology, yet a comprehensive structural characterization of the PPIs underlying biochemical processes is lacking. Although AlphaFold-Multimer (AF-M) has the potential to fill this knowledge gap, standard AF-M confidence metrics do not reliably separate relevant PPIs from an abundance of false positive predictions. To address this limitation, we used machine learning on well curated datasets to train a Structure Prediction and Omics informed Classifier called SPOC that shows excellent performance in separating true and false PPIs, including in proteome-wide screens. We applied SPOC to an all-by-all matrix of nearly 300 human genome maintenance proteins, generating ~40,000 predictions that can be viewed at predictomes.org, where users can also score their own predictions with SPOC. High confidence PPIs discovered using our approach suggest novel hypotheses in genome maintenance. Our results provide a framework for interpreting large scale AF-M screens and help lay the foundation for a proteome-wide structural interactome.

Essential and virulence-related protein interactions of pathogens revealed through deep learning

Identification of bacterial protein-protein interactions and predicting the structures of the complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here, we developed a deep learning-based pipeline that leverages residue-residue coevolution and protein structure prediction to systematically identify and structurally characterize protein-protein interactions at the proteome-wide scale. Using this pipeline, we searched through 78 million pairs of proteins across 19 human bacterial pathogens and identified 1923 confidently predicted complexes involving essential genes and 256 involving virulence factors. Many of these complexes were not previously known; we experimentally tested 12 such predictions, and half of them were validated. The predicted interactions span core metabolic and virulence pathways ranging from post-transcriptional modification to acid neutralization to outer membrane machinery and should contribute to our understanding of the biology of these important pathogens and the design of drugs to combat them.

Regulation by the RNA-binding protein Unkempt at its effector interface

How RNA-binding proteins (RBPs) convey regulatory instructions to the core effectors of RNA processing is unclear. Here, we document the existence and functions of a multivalent RBP-effector interface. We show that the effector interface of a conserved RBP with an essential role in metazoan development, Unkempt, is mediated by a novel type of 'dual-purpose' peptide motifs that can contact two different surfaces of interacting proteins. Unexpectedly, we find that the multivalent contacts do not merely serve effector recruitment but are required for the accuracy of RNA recognition by Unkempt. Systems analyses reveal that multivalent RBP-effector contacts can repurpose the principal activity of an effector for a different function, as we demonstrate for the reuse of the central eukaryotic mRNA decay factor CCR4-NOT in translational control. Our study establishes the molecular assembly and functional principles of an RBP-effector interface.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

Proteasome hyperactivation rewires the proteome enhancing stress resistance, proteostasis, lipid metabolism and ERAD in C. elegans

Proteasome dysfunction is implicated in the pathogenesis of neurodegenerative diseases and age-related proteinopathies. Using a C. elegans model, we demonstrate that 20S proteasome hyperactivation, facilitated by 20S gate-opening, accelerates the targeting of intrinsically disordered proteins. This leads to increased protein synthesis, extensive rewiring of the proteome and transcriptome, enhanced oxidative stress defense, accelerated lipid metabolism, and peroxisome proliferation. It also promotes ER-associated degradation (ERAD) of aggregation-prone proteins, such as alpha-1 antitrypsin (ATZ) and various lipoproteins. Notably, our results reveal that 20S proteasome hyperactivation suggests a novel role in ERAD with broad implications for proteostasis-related disorders, simultaneously affecting lipid homeostasis and peroxisome proliferation. Furthermore, the enhanced cellular capacity to mitigate proteostasis challenges, alongside unanticipated acceleration of lipid metabolism is expected to contribute to the longevity phenotype of this mutant. Remarkably, the mechanism of longevity induced by 20S gate opening appears unique, independent of known longevity and stress-resistance pathways. These results support the therapeutic potential of 20S proteasome activation in mitigating proteostasis-related disorders broadly and provide new insights into the complex interplay between proteasome activity, cellular health, and aging.

Genome Mining for New Enzyme Chemistry

A revolution in the field of biocatalysis has enabled scalable access to compounds of high societal values using enzymes. The construction of biocatalytic routes relies on the reservoir of available enzymatic transformations. A review of uncharacterized proteins predicted from genomic sequencing projects shows that a treasure trove of enzyme chemistry awaits to be uncovered. This Review highlights enzymatic transformations discovered through various genome mining methods and showcases their potential future applications in biocatalysis.

ReLo is a simple and rapid colocalization assay to identify and characterize direct protein-protein interactions

The characterization of protein-protein interactions (PPIs) is fundamental to the understanding of biochemical processes. Many methods have been established to identify and study direct PPIs; however, screening and investigating PPIs involving large or poorly soluble proteins remains challenging. Here, we introduce ReLo, a simple, rapid, and versatile cell culture-based method for detecting and investigating interactions in a cellular context. Our experiments demonstrate that ReLo specifically detects direct binary PPIs. Furthermore, we show that ReLo bridging experiments can also be used to determine the binding topology of subunits within multiprotein complexes. In addition, ReLo facilitates the identification of protein domains that mediate complex formation, allows screening for interfering point mutations, and it is sensitive to drugs that mediate or disrupt an interaction. In summary, ReLo is a simple and rapid alternative for the study of PPIs, especially when studying structurally complex proteins or when established methods fail.

Substrate recruitment via eIF2γ enhances catalytic efficiency of a holophosphatase that terminates the integrated stress response

Dephosphorylation of pSer51 of the α subunit of translation initiation factor 2 (eIF2αP) terminates signaling in the integrated stress response (ISR). A trimeric mammalian holophosphatase comprised of a protein phosphatase 1 (PP1) catalytic subunit, the conserved C-terminally located ~70 amino acid core of a substrate-specific regulatory subunit (PPP1R15A/GADD34 or PPP1R15B/CReP) and G-actin (an essential cofactor) efficiently dephosphorylate eIF2αP in vitro. Unlike their viral or invertebrate counterparts, with whom they share the conserved 70 residue core, the mammalian PPP1R15s are large proteins of more than 600 residues. Genetic and cellular observations point to a functional role for regions outside the conserved core of mammalian PPP1R15A in dephosphorylating its natural substrate, the eIF2 trimer. We have combined deep learning technology, all-atom molecular dynamics simulations, X-ray crystallography, and biochemistry to uncover binding of the γ subunit of eIF2 to a short helical peptide repeated four times in the functionally important N terminus of human PPP1R15A that extends past its conserved core. Binding entails insertion of Phe and Trp residues that project from one face of an α-helix formed by the conserved repeats of PPP1R15A into a hydrophobic groove exposed on the surface of eIF2γ in the eIF2 trimer. Replacing these conserved Phe and Trp residues with Ala compromises PPP1R15A function in cells and in vitro. These findings suggest mechanisms by which contacts between a distant subunit of eIF2 and elements of PPP1R15A distant to the holophosphatase active site contribute to dephosphorylation of eIF2αP by the core PPP1R15 holophosphatase and to efficient termination of the ISR in mammals.