DNA-dependent phase separation by human SSB2 (NABP1/OBFC2A) protein points to adaptations to eukaryotic genome repair processes.

Single-stranded DNA binding proteins (SSBs) are ubiquitous across all domains of life and play essential roles via stabilizing and protecting single-stranded (ss) DNA as well as organizing multiprotein complexes during DNA replication, recombination, and repair. Two mammalian SSB paralogs (hSSB1 and hSSB2 in humans) were recently identified and shown to be involved in various genome maintenance processes. Following our recent discovery of the liquid-liquid phase separation (LLPS) propensity of Escherichia coli (Ec) SSB, here we show that hSSB2 also forms LLPS condensates under physiologically relevant ionic conditions. Similar to that seen for EcSSB, we demonstrate the essential contribution of hSSB2's C-terminal intrinsically disordered region (IDR) to condensate formation, and the selective enrichment of various genome metabolic proteins in hSSB2 condensates. However, in contrast to EcSSB-driven LLPS that is inhibited by ssDNA binding, hSSB2 phase separation requires single-stranded nucleic acid binding, and is especially facilitated by ssDNA. Our results reveal an evolutionarily conserved role for SSB-mediated LLPS in the spatiotemporal organization of genome maintenance complexes. At the same time, differential LLPS features of EcSSB and hSSB2 point to functional adaptations to prokaryotic versus eukaryotic genome metabolic contexts.

One form and two functions: MBD of SETDB2 is a protein-interacting domain.

In this issue of Structure, Mahana et al.1 present their structural characterization of an annotated methyl-CpG-binding domain (MBD) from the histone H3 lysine 9 methyltransferase SETDB2. This study reveals that, rather than binding DNA as previously hypothesized, this domain instead interacts with a cystine-rich domain from C11orf46, highlighting its involvement in protein-protein interactions.

Proteasome condensate formation is driven by multivalent interactions with shuttle factors and ubiquitin chains.

Stress conditions can cause the relocalization of proteasomes to condensates in yeast and mammalian cells. The interactions that facilitate the formation of proteasome condensates, however, are unclear. Here, we show that the formation of proteasome condensates in yeast depends on ubiquitin chains together with the proteasome shuttle factors Rad23 and Dsk2. These shuttle factors colocalize to these condensates. Strains deleted for the third shuttle factor gene, DDI1, show proteasome condensates in the absence of cellular stress, consistent with the accumulation of substrates with long K48-linked ubiquitin chains that accumulate in this mutant. We propose a model where the long K48-linked ubiquitin chains function as a scaffold for the ubiquitin-binding domains of the shuttle factors and the proteasome, allowing for the multivalent interactions that further drive condensate formation. Indeed, we determined different intrinsic ubiquitin receptors of the proteasome-Rpn1, Rpn10, and Rpn13-and the Ubl domains of Rad23 and Dsk2 are critical under different condensate-inducing conditions. In all, our data support a model where the cellular accumulation of substrates with long ubiquitin chains, potentially due to reduced cellular energy, allows for proteasome condensate formation. This suggests that proteasome condensates are not simply for proteasome storage, but function to sequester soluble ubiquitinated substrates together with inactive proteasomes.

Small Molecule Antagonists of the DNA Repair ERCC1/XPA Protein-Protein Interaction.

The DNA excision repair protein ERCC1 and the DNA damage sensor protein, XPA are highly overexpressed in patient samples of cisplatin-resistant solid tumors including lung, bladder, ovarian, and testicular cancer. The repair of cisplatin-DNA crosslinks is dependent upon nucleotide excision repair (NER) that is modulated by protein-protein binding interactions of ERCC1, the endonuclease, XPF, and XPA. Thus, inhibition of their function is a potential therapeutic strategy for the selective sensitization of tumors to DNA-damaging platinum-based cancer therapy. Here, we report on new small-molecule antagonists of the ERCC1/XPA protein-protein interaction (PPI) discovered using a high-throughput competitive fluorescence polarization binding assay. We discovered a unique structural class of thiopyridine-3-carbonitrile PPI antagonists that block a truncated XPA polypeptide from binding to ERCC1. Preliminary hit-to-lead studies from compound 1 reveal structure-activity relationships (SAR) and identify lead compound 27 o with an EC50 of 4.7 µM. Furthermore, chemical shift perturbation mapping by NMR confirms that 1 binds within the same site as the truncated XPA67-80 peptide. These novel ERCC1 antagonists are useful chemical biology tools for investigating DNA damage repair pathways and provide a good starting point for medicinal chemistry optimization as therapeutics for sensitizing tumors to DNA damaging agents and overcoming resistance to platinum-based chemotherapy.

Structural characterization of the DNA binding mechanism of retinoic acid-related orphan receptor gamma.

Retinoic acid-related orphan receptor gamma (RORγ) plays critical roles in regulating various biological processes and has been linked to immunodeficiency disorders and cancers. DNA recognition is essential for RORγ to exert its functions. However, the underlying mechanism of the DNA binding by RORγ remains unclear. In this study, we present the crystal structure of the complex of RORγ1 DNA-binding domain (RORγ1-DBD)/direct repeat DNA element DR2 at 2.3 Å resolution. We demonstrate that RORγ1-DBD binds the DR2 motif as a homodimer, with the C-terminal extension (CTE) region of RORγ1-DBD contributing to the DNA recognition and the formation of dimeric interface. Further studies reveal that REV-ERB-DBD and RXR-DBD, also bind the DR2 site as a homodimer, while NR4A2-DBD binds DR2 as a monomer. Our research uncovers a binding mechanism of RORγ1 to the DR2 site and provides insights into the biological functions of RORγ1 and the broader RORs subfamily.

Genetically encoded lysine photocage for spatiotemporal control of TDP-43 nuclear import.

Intracellular aggregation of transactive response DNA binding protein of 43 kDa (TDP-43) is a hallmark of neurodegenerative diseases such as amyotrophic lateral sclerosis. While primarily a nuclear protein, TDP-43 translocates to the cytosol during cellular stress. Consequences of cytosolic accumulation of TDP-43 is difficult to evaluate in the absence of exogenous toxins. Here, we demonstrate spatiotemporal control over the nuclear import of TDP-43 by installing a photocage (ortho-nitrobenzyl ester) on a single lysine residue (K84) through amber codon suppression in HEK293T cells. Translocation of this cytosolic construct is photo-triggerable in a dose-dependent manner with 355 nm light. Interestingly, both fluid- and solid-like puncta were found based on fluorescence recovery after photobleaching experiments, similar to what is expected of stress granules and intracellular aggregates, respectively. This optogenetic method is advantageous as it is minimally perturbative and broadly applicable to other studies of protein translocation between cellular compartments.

DRBpred: A sequence-based machine learning method to effectively predict DNA- and RNA-binding residues.

DNA-binding and RNA-binding proteins are essential to an organism's normal life cycle. These proteins have diverse functions in various biological processes. DNA-binding proteins are crucial for DNA replication, transcription, repair, packaging, and gene expression. Likewise, RNA-binding proteins are essential for the post-transcriptional control of RNAs and RNA metabolism. Identifying DNA- and RNA-binding residue is essential for biological research and understanding the pathogenesis of many diseases. However, most DNA-binding and RNA-binding proteins still need to be discovered. This research explored various properties of the protein sequences, such as amino acid composition type, Position-Specific Scoring Matrix (PSSM) values of amino acids, Hidden Markov model (HMM) profiles, physiochemical properties, structural properties, torsion angles, and disorder regions. We utilized a sliding window technique to extract more information from a target residue's neighbors. We proposed an optimized Light Gradient Boosting Machine (LightGBM) method, named DRBpred, to predict DNA-binding and RNA-binding residues from the protein sequence. DRBpred shows an improvement of 112.00 %, 33.33 %, and 6.49 % for the DNA-binding test set compared to the state-of-the-art method. It shows an improvement of 112.50 %, 16.67 %, and 7.46 % for the RNA-binding test set regarding Sensitivity, Mathews Correlation Coefficient (MCC), and AUC metric.

DBPboost:A method of classification of DNA-binding proteins based on improved differential evolution algorithm and feature extraction.

DNA-binding proteins are a class of proteins that can interact with DNA molecules through physical and chemical interactions. Their main functions include regulating gene expression, maintaining chromosome structure and stability, and more. DNA-binding proteins play a crucial role in cellular and molecular biology, as they are essential for maintaining normal cellular physiological functions and adapting to environmental changes. The prediction of DNA-binding proteins has been a hot topic in the field of bioinformatics. The key to accurately classifying DNA-binding proteins is to find suitable feature sources and explore the information they contain. Although there are already many models for predicting DNA-binding proteins, there is still room for improvement in mining feature source information and calculation methods. In this study, we created a model called DBPboost to better identify DNA-binding proteins. The innovation of this study lies in the use of eight feature extraction methods, the improvement of the feature selection step, which involves selecting some features first and then performing feature selection again after feature fusion, and the optimization of the differential evolution algorithm in feature fusion, which improves the performance of feature fusion. The experimental results show that the prediction accuracy of the model on the UniSwiss dataset is 89.32%, and the sensitivity is 89.01%, which is better than most existing models.

Exploration and Application of DNA-Binding Proteins to Make a Versatile DNA-Protein Covalent-Linking Patch (D-Pclip): The Case of a Biosensing Element.

DNA-protein complexes are attractive components with broad applications in various research fields, such as DNA aptamer-enzyme complexes as biosensing elements. However, noncovalent DNA-protein complexes often decrease detection sensitivity because they are highly susceptible to environmental conditions. In this study, we developed a versatile DNA-protein covalent-linking patch (D-Pclip) for fabricating covalent and stoichiometric DNA-protein complexes. We comprehensively explored the database to determine the DNA-binding ability of the candidates and selected UdgX as the only uracil-DNA glycosylase known to form covalent bonds with DNA via uracil, with a binding efficiency >90%. We integrated a SpyTag/SpyCatcher protein-coupling system into UdgX to create a universal and convenient D-Pclip. The usability of D-Pclip was shown by preparing a stoichiometric model complex of a hemoglobin (Hb)-binding aptamer and glucose oxidase (GOx) by mixing at 4 °C. The prepared aptamer-GOx complexes detected Hb in a dose-dependent manner within the clinically required detection range in buffer and human serum without any washing procedures. D-Pclip covalently connects any uracil-inserted DNA sequence and any SpyCatcher-fused protein stoichiometrically; therefore, it has a high potential for various applications.

IκB kinase thwarts aggregation: Phosphorylating TDP-43 for degradation.

TDP-43 aggregation is a hallmark of neurodegeneration. In this issue, Iguchi et al. (https://doi.org/10.1083/jcb.202302048) report that IκB kinase (IKK), an important mediator of inflammation, phosphorylates cytoplasmic TDP-43 to promote proteasomal degradation, revealing an unexpected link between inflammation and TDP-43 homeostasis.

HybridDBRpred: improved sequence-based prediction of DNA-binding amino acids using annotations from structured complexes and disordered proteins.

Current predictors of DNA-binding residues (DBRs) from protein sequences belong to two distinct groups, those trained on binding annotations extracted from structured protein-DNA complexes (structure-trained) vs. intrinsically disordered proteins (disorder-trained). We complete the first empirical analysis of predictive performance across the structure- and disorder-annotated proteins for a representative collection of ten predictors. Majority of the structure-trained tools perform well on the structure-annotated proteins while doing relatively poorly on the disorder-annotated proteins, and vice versa. Several methods make accurate predictions for the structure-annotated proteins or the disorder-annotated proteins, but none performs highly accurately for both annotation types. Moreover, most predictors make excessive cross-predictions for the disorder-annotated proteins, where residues that interact with non-DNA ligand types are predicted as DBRs. Motivated by these results, we design, validate and deploy an innovative meta-model, hybridDBRpred, that uses deep transformer network to combine predictions generated by three best current predictors. HybridDBRpred provides accurate predictions and low levels of cross-predictions across the two annotation types, and is statistically more accurate than each of the ten tools and baseline meta-predictors that rely on averaging and logistic regression. We deploy hybridDBRpred as a convenient web server at http://biomine.cs.vcu.edu/servers/hybridDBRpred/ and provide the corresponding source code at https://github.com/jianzhang-xynu/hybridDBRpred.

Accurate prediction of protein-nucleic acid complexes using RoseTTAFoldNA.

Protein-RNA and protein-DNA complexes play critical roles in biology. Despite considerable recent advances in protein structure prediction, the prediction of the structures of protein-nucleic acid complexes without homology to known complexes is a largely unsolved problem. Here we extend the RoseTTAFold machine learning protein-structure-prediction approach to additionally predict nucleic acid and protein-nucleic acid complexes. We develop a single trained network, RoseTTAFoldNA, that rapidly produces three-dimensional structure models with confidence estimates for protein-DNA and protein-RNA complexes. Here we show that confident predictions have considerably higher accuracy than current state-of-the-art methods. RoseTTAFoldNA should be broadly useful for modeling the structure of naturally occurring protein-nucleic acid complexes, and for designing sequence-specific RNA and DNA-binding proteins.

Effective Inhibition of TDP-43 Aggregation by Native State Stabilization.

Preventing the misfolding or aggregation of transactive response DNA binding protein with 43 kDa (TDP-43) is the most actively pursued disease-modifying strategy to treat amyotrophic lateral sclerosis and other neurodegenerative diseases. In this work, we provide proof of concept that native state stabilization of TDP-43 is a viable and effective strategy for treating TDP-43 proteinopathies. Firstly, we leveraged the Cryo-EM structures of TDP-43 fibrils to design C-terminal substitutions that disrupt TDP-43 aggregation. Secondly, we showed that these substitutions (S333D/S342D) stabilize monomeric TDP-43 without altering its physiological properties. Thirdly, we demonstrated that binding native oligonucleotide ligands stabilized monomeric TDP-43 and prevented its fibrillization and phase separation in the absence of direct binding to the aggregation-prone C-terminal domain. Fourthly, we showed that the monomeric TDP-43 variant could be induced to aggregate in a controlled manner, which enabled the design and implementation of a high-throughput screening assay to identify native state stabilizers of TDP-43. Altogether, our findings demonstrate that different structural domains in TDP-43 could be exploited and targeted to develop drugs that stabilize the native state of TDP-43 and provide a platform to discover novel drugs to treat TDP-43 proteinopathies.

Intrinsically disordered regions of the Msn2 transcription factor encode multiple functions using interwoven sequence grammars.

Intrinsically disordered regions (IDRs) are abundant in eukaryotic proteins, but their sequence-function relationship remains poorly understood. IDRs of transcription factors (TFs) can direct promoter selection and recruit coactivators, as shown for the budding yeast TF Msn2. To examine how IDRs encode both these functions, we compared genomic binding specificity, coactivator recruitment, and gene induction amongst a large set of designed Msn2-IDR mutants. We find that both functions depend on multiple regions across the > 600AA IDR. Yet, transcription activity was readily disrupted by mutations that showed no effect on the Msn2 binding specificity. Our data attribute this differential sensitivity to the integration of a relaxed, composition-based code directing binding specificity with a more stringent, motif-based code controlling the recruitment of coactivators and transcription activity. Therefore, Msn2 utilizes interwoven sequence grammars for encoding multiple functions, suggesting a new IDR design paradigm of potentially general use.

Structural evidence for protein-protein interaction between the non-canonical methyl-CpG-binding domain of SETDB proteins and C11orf46.

SETDB1 and SETDB2 mediate trimethylation of histone H3 lysine 9 (H3K9), an epigenetic hallmark of repressive chromatin. They contain a non-canonical methyl-CpG-binding domain (MBD) and bifurcated SET domain, implying interplay between H3K9 trimethylation and DNA methylation in SETDB functions. Here, we report the crystal structure of human SETDB2 MBD bound to the cysteine-rich domain of a zinc-binding protein, C11orf46. SETDB2 MBD comprises the conserved MBD core and a unique N-terminal extension. Although the MBD core has the conserved basic concave surface for DNA binding, it utilizes it for recognition of the cysteine-rich domain of C11orf46. This interaction involves the conserved arginine finger motif and the unique N-terminal extension of SETDB2 MBD, with a contribution from intermolecular ß-sheet formation. Thus, the non-canonical MBD of SETDB1/2 seems to have lost methylated DNA-binding ability but gained a protein-protein interaction surface. Our findings provide insight into the molecular assembly of SETDB-associated repression complexes.

A complex network of interdomain interactions underlies the conformational ensemble of monomeric TDP-43 and modulates its phase behavior.

TAR DNA-binding protein 43 (TDP-43) is a multidomain protein involved in the regulation of RNA metabolism, and its aggregates have been observed in neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Numerous studies indicate TDP-43 can undergo liquid-liquid phase separation (LLPS) in vitro and is a component of biological condensates. Homo-oligomerization via the folded N-terminal domain (aa:1-77) and the conserved helical region (aa:319-341) of the disordered, C-terminal domain is found to be an important driver of TDP-43 phase separation. However, a comprehensive molecular view of TDP-43 phase separation, particularly regarding the nature of heterodomain interactions, is lacking due to the challenges associated with its stability and purification. Here, we utilize all-atom and coarse-grained (CG) molecular dynamics (MD) simulations to uncover the network of interdomain interactions implicated in TDP-43 phase separation. All-atom simulations uncovered the presence of transient, interdomain interactions involving flexible linkers, RNA-recognition motif (RRM) domains and a charged segment of disordered C-terminal domain (CTD). CG simulations indicate these inter-domain interactions which affect the conformational landscape of TDP-43 in the dilute phase are also prevalent in the condensed phase. Finally, sequence and surface charge distribution analysis coupled with all-atom simulations (at high salt) confirmed that the transient interdomain contacts are predominantly electrostatic in nature. Overall, our findings from multiscale simulations lead to a greater appreciation of the complex interaction network underlying the structural landscape and phase separation of TDP-43.

Structure of the WYL-domain containing transcription activator, DriD, in complex with ssDNA effector and DNA target site.

Transcription regulators play central roles in orchestrating responses to changing environmental conditions. Recently the Caulobacter crescentus transcription activator DriD, which belongs to the newly defined WYL-domain family, was shown to regulate DNA damage responses independent of the canonical SOS pathway. However, the molecular mechanisms by which DriD and other WYL-regulators sense environmental signals and recognize DNA are not well understood. We showed DriD DNA-binding is triggered by its interaction with ssDNA, which is produced during DNA damage. Here we describe the structure of the full-length C. crescentus DriD bound to both target DNA and effector ssDNA. DriD consists of an N-terminal winged-HTH (wHTH) domain, linker region, three-helix bundle, WYL-domain and C-terminal WCX-dimer domain. Strikingly, DriD binds DNA using a novel, asymmetric DNA-binding mechanism that results from different conformations adopted by the linker. Although the linker does not touch DNA, our data show that contacts it makes with the wHTH are key for specific DNA binding. The structure indicates how ssDNA-effector binding to the WYL-domain impacts wHTH DNA binding. In conclusion, we present the first structure of a WYL-activator bound to both effector and target DNA. The structure unveils a unique, asymmetric DNA binding mode that is likely conserved among WYL-activators.

Molecular Determinants of PQBP1 Binding to the HIV-1 Capsid Lattice.

Human immunodeficiency virus type 1 (HIV-1) stimulates innate immune responses upon infection, including cyclic GMP-AMP synthase (cGAS) signaling that results in type I interferon production. HIV-1-induced activation of cGAS requires the host cell factor polyglutamine binding protein 1 (PQBP1), an intrinsically disordered protein that bridges capsid recognition and cGAS recruitment. However, the molecular details of PQBP1 interactions with the HIV-1 capsid and their functional implications remain poorly understood. Here, we show that PQBP1 binds to HIV-1 capsids through charge complementing contacts between acidic residues in the N-terminal region of PQBP1 and an arginine ring in the central channel of the HIV-1 CA hexamer that makes up the viral capsid. These studies reveal the molecular details of PQBP1's primary interaction with the HIV-1 capsid and suggest that additional elements are likely to contribute to stable capsid binding.

Decoding dissociation of sequence-specific protein-DNA complexes with non-equilibrium simulations.

Sequence-specific protein-DNA interactions are crucial in processes such as DNA organization, gene regulation and DNA replication. Obtaining detailed insights into the recognition mechanisms of protein-DNA complexes through experiments is hampered by a lack of resolution in both space and time. Here, we present a molecular simulation approach to quantify the sequence specificity of protein-DNA complexes, that yields results fast, and is generally applicable to any protein-DNA complex. The approach is based on molecular dynamics simulations in combination with a sophisticated steering potential and results in an estimate of the free energy difference of dissociation. We provide predictions of the nucleotide specific binding affinity of the minor groove binding Histone-like Nucleoid Structuring (H-NS) protein, that are in agreement with experimental data. Furthermore, our approach offers mechanistic insight into the process of dissociation. Applying our approach to the major groove binding ETS domain in complex with three different nucleotide sequences identified the high affinity consensus sequence, quantitatively in agreement with experiments. Our protocol facilitates quantitative prediction of protein-DNA complex stability, while also providing high resolution insights into recognition mechanisms. As such, our simulation approach has the potential to yield detailed and quantitative insights into biological processes involving sequence-specific protein-DNA interactions.

Stochastic nucleosome disassembly mediated by remodelers and histone fragmentation.

We construct and analyze monomeric and multimeric models of the stochastic disassembly of a single nucleosome. Our monomeric model predicts the time needed for a number of histone-DNA contacts to spontaneously break, leading to dissociation of a non-fragmented histone from DNA. The dissociation process can be facilitated by DNA binding proteins or processing molecular motors that compete with histones for histone-DNA contact sites. Eigenvalue analysis of the corresponding master equation allows us to evaluate histone detachment times under both spontaneous detachment and protein-facilitated processes. We find that competitive DNA binding of remodeling proteins can significantly reduce the typical detachment time but only if these remodelers have DNA-binding affinities comparable to those of histone-DNA contact sites. In the presence of processive motors, the histone detachment rate is shown to be proportional to the product of the histone single-bond dissociation constant and the speed of motor protein procession. Our simple intact-histone model is then extended to allow for multimeric nucleosome kinetics that reveal additional pathways of disassembly. In addition to a dependence of complete disassembly times on subunit-DNA contact energies, we show how histone subunit concentrations in bulk solutions can mediate the disassembly process by rescuing partially disassembled nucleosomes. Moreover, our kinetic model predicts that remodeler binding can also bias certain pathways of nucleosome disassembly, with higher remodeler binding rates favoring intact-histone detachment.