A common binding motif in the ET domain of BRD3 forms polymorphic structural interfaces with host and viral proteins

An Overview of Property, Design, and Functionality of Linkers for Fusion Protein Construction

Linkers are naturally occurring short amino acid sequences that are used to separate domains within a protein. The advent of recombinant DNA technology has made it possible to combine two interacting partners by introducing artificial linkers that often, allow for the production of stable and functional proteins. Glycine-rich linkers are useful for transient interactions, especially where the interaction is weak, by covalently linking proteins and forming a stable protein-protein complex. These linkers have also been used to generate covalently stable dimers and to connect two independent domains that create a ligand binding site or recognition sequence. Various structures of covalently linked protein complexes have been described using nuclear magnetic resonance methods, cryo-electron microscopy techniques, and X-ray crystallography; in addition, several structures where linkers have been used to generate stable protein-protein complexes, improve protein solubility, and obtain protein dimers are investigated, and also the design and engineering of the linker in fusion proteins is discussed. Therefore, one of the main factors for linker design and optimization is their flexibility, which can directly contribute to the physical distance between the domains of a fusion protein and describe the tendency of a linker to maintain a stable conformation during expression. We summarize the research on design and bioinformatics can be used to predict the spatial structure of the fusion protein. To perform simulations of spatial structures and drug molecule design, future research will concentrate on various correlation models.

A Minireview on BET Inhibitors: Beyond Bromodomain Targeting

Bromodomain and extra-terminal domain (BET) proteins are epigenetic readers that recognize the histone acetylation code and play a critical role in regulating gene transcription. Dysregulation of BET proteins is associated with a number of pathologies, including cancer, inflammation-related metabolic disorders, etc. BET proteins can also be hijacked by some viruses and mediate latent viral infections, making BET proteins promising targets for therapeutic intervention. Research in this area has mainly focused on bromodomain inhibition, with less attention paid to other domains. Bromodomain inhibitors have great potential as anticancer and anti-inflammatory drug candidates. However, their broad-spectrum impact on transcription and potential cross-reactivity with non-BET bromodomain-containing proteins raise concerns about unforeseen side effects. Non-bromodomain BET inhibitors hold promise for gaining better control over the expression of host and viral genes by targeting different stages of BET-dependent transcriptional regulation. In this review, we discuss recent advances in the development of non-bromodomain BET inhibitors, as well as their potential applications, advantages, and perspectives.

Design of intrinsically disordered region binding proteins

Intrinsically disordered proteins and peptides play key roles in biology, but the lack of defined structures and the high variability in sequence and conformational preferences has made targeting such systems challenging. We describe a general approach for designing proteins that bind intrinsically disordered protein regions in diverse extended conformations with side chains fitting into complementary binding pockets. We used the approach to design binders for 39 highly diverse unstructured targets and obtain designs with pM to 100 nM affinities in 34 cases, testing ∼22 designs per target (including polar targets). The designs function in cells and as detection reagents, and are specific for their intended targets in all-by-all binding experiments. Our approach is a major step towards a general solution to the intrinsically disordered protein and peptide recognition problem.

MELD-Adapt: On-the-Fly Belief Updating in Integrative Molecular Dynamics

Integrative structural biology synergizes experimental data with computational methods to elucidate the structures and interactions within biomolecules, a task that becomes critical in the absence of high-resolution structural data. A challenging step for integrating the data is knowing the expected accuracy or belief in the dataset. We previously showed that the Modeling Employing Limited Data (MELD) approach succeeds at predicting structures and finding the best interpretation of the data when the initial belief is equal to or slightly lower than the real value. However, the initial belief might be unknown to the user, as it depends on both the technique and the system of study. Here we introduce MELD-Adapt, designed to dynamically evaluate and infer the reliability of input data while at the same time finding the best interpretation of the data and the structures compatible with it. We demonstrate the utility of this method across different systems, particularly emphasizing its capability to correct initial assumptions and identify the correct fraction of data to produce reliable structural models. The approach is tested with two benchmark sets: the folding of 12 proteins with coarse physical insights and the binding of peptides with varying affinities to the extraterminal domain using chemical shift perturbation data. We find that subtle differences in data structure (e.g., locally clustered or globally distributed), starting belief, and force field preferences can have an impact on the predictions, limiting the possibility of a transferable protocol across all systems and data types. Nonetheless, we find a wide range of initial setup conditions that will lead to successful sampling and identification of native states, leading to a robust pipeline. Furthermore, disagreements about how much data is enforced and satisfied rapidly serve to identify incorrect setup conditions.

Integrative Modeling of Protein-Polypeptide Complexes by Bayesian Model Selection using AlphaFold and NMR Chemical Shift Perturbation Data

Protein-polypeptide interactions, including those involving intrinsically-disordered peptides and intrinsically-disordered regions of protein binding partners, are crucial for many biological functions. However, experimental structure determination of protein-peptide complexes can be challenging. Computational methods, while promising, generally require experimental data for validation and refinement. Here we present CSP_Rank, an integrated modeling approach to determine the structures of protein-peptide complexes. This method combines AlphaFold2 (AF2) enhanced sampling methods with a Bayesian conformational selection process based on experimental Nuclear Magnetic Resonance (NMR) Chemical Shift Perturbation (CSP) data and AF2 confidence metrics. Using a curated dataset of 108 protein-peptide complexes from the Biological Magnetic Resonance Data Bank (BMRB), we observe that while AF2 typically yields models with excellent consistency with experimental CSP data, applying enhanced sampling followed by data-guided conformational selection routinely results in ensembles of structures with improved agreement with NMR observables. For two systems, we cross-validate the CSP-selected models using independently acquired nuclear Overhauser effect (NOE) NMR data and demonstrate how CSP and NMR can be combined using our Bayesian framework for model selection. CSP_Rank is a novel method for integrative modeling of protein-peptide complexes and has broad implications for studies of protein-peptide interactions and aiding in understanding their biological functions.

A Review of the Bromodomain and Extraterminal Domain Epigenetic Reader Proteins: Function on Virus Infection and Cancer

The BET (bromodomain and extraterminal domain) family of proteins, particularly BRD4 (bromodomain-containing protein 4), plays a crucial role in transcription regulation and epigenetic mechanisms, impacting key cellular processes such as proliferation, differentiation, and the DNA damage response. BRD4, the most studied member of this family, binds to acetylated lysines on both histones and non-histone proteins, thereby regulating gene expression and influencing diverse cellular functions such as the cell cycle, tumorigenesis, and immune responses to viral infections. Given BRD4's involvement in these fundamental processes, it is implicated in various diseases, including cancer and inflammation, making it a promising target for therapeutic development. This review comprehensively explores the roles of the BET family in gene transcription, DNA damage response, and viral infection, discussing the potential of targeted small-molecule compounds and highlighting BET proteins as promising candidates for anticancer therapy.

A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners but often include false positives. Furthermore, they provide no information about what the binding region is (e.g., the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competitive Binding Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment and the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies of AF and AF-CBA to help users identify scenarios where the approach will be most useful. Given the method's speed and accuracy, we anticipate its broad applicability to identify binding epitope regions among potential partners, setting the stage for experimental verification.

Structural studies of intrinsically disordered MLL-fusion protein AF9 in complex with peptidomimetic inhibitors

AF9 (MLLT3) and its paralog ENL(MLLT1) are members of the YEATS family of proteins with important role in transcriptional and epigenetic regulatory complexes. These proteins are two common MLL fusion partners in MLL-rearranged leukemias. The oncofusion proteins MLL-AF9/ENL recruit multiple binding partners, including the histone methyltransferase DOT1L, leading to aberrant transcriptional activation and enhancing the expression of a characteristic set of genes that drive leukemogenesis. The interaction between AF9 and DOT1L is mediated by an intrinsically disordered C-terminal ANC1 homology domain (AHD) in AF9, which undergoes folding upon binding of DOT1L and other partner proteins. We have recently reported peptidomimetics that disrupt the recruitment of DOT1L by AF9 and ENL, providing a proof-of-concept for targeting AHD and assessing its druggability. Intrinsically disordered proteins, such as AF9 AHD, are difficult to study and characterize experimentally on a structural level. In this study, we present a successful protein engineering strategy to facilitate structural investigation of the intrinsically disordered AF9 AHD domain in complex with peptidomimetic inhibitors by using maltose binding protein (MBP) as a crystallization chaperone connected with linkers of varying flexibility and length. The strategic incorporation of disulfide bonds provided diffraction-quality crystals of the two disulfide-bridged MBP-AF9 AHD fusion proteins in complex with the peptidomimetics. These successfully determined first series of 2.1-2.6 Å crystal complex structures provide high-resolution insights into the interactions between AHD and its inhibitors, shedding light on the role of AHD in recruiting various binding partner proteins. We show that the overall complex structures closely resemble the reported NMR structure of AF9 AHD/DOT1L with notable difference in the conformation of the β-hairpin region, stabilized through conserved hydrogen bonds network. These first series of AF9 AHD/peptidomimetics complex structures are providing insights of the protein-inhibitor interactions and will facilitate further development of novel inhibitors targeting the AF9/ENL AHD domain.

Bromodomain and Extraterminal Domain Protein 2 in Multiple Human Diseases

Bromodomain and extraterminal domain protein 2 (BRD2), a member of the bromodomain and extraterminal domain (BET) protein family, is a crucial epigenetic regulator with significant function in various diseases and cellular processes. The central function of BRD2 is modulating gene transcription by binding to acetylated lysine residues on histones and transcription factors. This review highlights key findings on BRD2 in recent years, emphasizing its roles in maintaining genomic stability, influencing chromatin spatial organization, and participating in transcriptional regulation. BRD2's diverse functions are underscored by its involvement in diseases such as malignant tumors, neurologic disorders, inflammatory conditions, metabolic diseases, and virus infection. Notably, the potential role of BRD2 as a diagnostic marker and therapeutic target is discussed in the context of various diseases. Although pan inhibitors targeting the BET family have shown promise in preclinical studies, a critical need exists for the development of highly selective BRD2 inhibitors. In conclusion, this review offers insights into the multifaceted nature of BRD2 and calls for continued research to unravel its intricate mechanisms and harness its therapeutic potential. SIGNIFICANCE STATEMENT: BRD2 is involved in the occurrence and development of diseases through maintaining genomic stability, influencing chromatin spatial organization, and participating in transcriptional regulation. Targeting BRD2 through protein degradation-targeting complexes technology is emerging as a promising therapeutic approach for malignant cancer and inflammatory diseases.

Sifting Through the Noise: A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners, but often include false positives. Furthermore, they provide no information about what the binding region is (e.g. the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competition Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment, along with the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies to AF and AF-CBA, to help users identify scenarios where the approach will be most useful. Given the speed and accuracy of the methodology, we expect it to be generally applicable to facilitate target selection for experimental verification starting from high-throughput protein libraries.

Targeting the epigenetic reader "BET" as a therapeutic strategy for cancer

Bromodomain and extraterminal (BET) proteins have the ability to bind to acetylated lysine residues present in both histones and non-histone proteins. This binding is facilitated by the presence of tandem bromodomains. The regulatory role of BET proteins extends to chromatin dynamics, cellular processes, and disease progression. The BET family comprises of BRD 2, 3, 4 and BRDT. The BET proteins are a class of epigenetic readers that regulate the transcriptional activity of a multitude of genes that are involved in the pathogenesis of cancer. Thus, targeting BET proteins has been identified as a potentially efficacious approach for the treatment of cancer. BET inhibitors (BETis) are known to interfere with the binding of BET proteins to acetylated lysine residues of chromatin, thereby leading to the suppression of transcription of several genes, including oncogenic transcription factors. Here in this review, we focus on role of Bromodomain and extra C-terminal (BET) proteins in cancer progression. Furthermore, numerous small-molecule inhibitors with pan-BET activity have been documented, with certain compounds currently undergoing clinical assessment. However, it is apparent that the clinical effectiveness of the present BET inhibitors is restricted, prompting the exploration of novel technologies to enhance their clinical outcomes and mitigate undesired adverse effects. Thus, strategies like development of selective BET-BD1, & BD2 inhibitors, dual and acting BET are also presented in this review and attempts to cover the chemistry needed for proper establishment of designed molecules into BRD have been made. Moreover, the review attempts to summarize the details of research till date and proposes a space for future development of BET inhibitor with diminished side effects. It can be concluded that discovery of isoform selective BET inhibitors can be a way forward in order to develop BET inhibitors with negligible side effects.

From PROTAC to inhibitor: Structure-guided discovery of potent and orally bioavailable BET inhibitors

An X-ray structure of a CLICK chemistry-based BET PROTAC bound to BRD2(BD2) inspired synthesis of JQ1 derived heterocyclic amides. This effort led to the discovery of potent BET inhibitors displaying overall improved profiles when compared to JQ1 and birabresib. A thiadiazole derived 1q (SJ1461) displayed excellent BRD4 and BRD2 affinity and high potency in the panel of acute leukaemia and medulloblastoma cell lines. A structure of 1q co-crystalised with BRD4-BD1 revealed polar interactions with the AZ/BC loops, in particular with Asn140 and Tyr139, rationalising the observed affinity improvements. In addition, exploration of pharmacokinetic properties of this class of compounds suggest that the heterocyclic amide moiety improves drug-like features. Our study led to the discovery of potent and orally bioavailable BET inhibitor 1q (SJ1461) as a promising candidate for further development.

BET Bromodomain Inhibitors: Novel Design Strategies and Therapeutic Applications

The mammalian bromodomain and extra-terminal domain (BET) family of proteins consists of four conserved members (Brd2, Brd3, Brd4, and Brdt) that regulate numerous cancer-related and immunity-associated genes. They are epigenetic readers of histone acetylation with broad specificity. BET proteins are linked to cancer progression due to their interaction with numerous cellular proteins including chromatin-modifying factors, transcription factors, and histone modification enzymes. The spectacular growth in the clinical development of small-molecule BET inhibitors underscores the interest and importance of this protein family as an anticancer target. Current approaches targeting BET proteins for cancer therapy rely on acetylation mimics to block the bromodomains from binding chromatin. However, bromodomain-targeted agents are suffering from dose-limiting toxicities because of their effects on other bromodomain-containing proteins. In this review, we provided an updated summary about the evolution of small-molecule BET inhibitors. The design of bivalent BET inhibitors, kinase and BET dual inhibitors, BET protein proteolysis-targeting chimeras (PROTACs), and Brd4-selective inhibitors are discussed. The novel strategy of targeting the unique C-terminal extra-terminal (ET) domain of BET proteins and its therapeutic significance will also be highlighted. Apart from single agent treatment alone, BET inhibitors have also been combined with other chemotherapeutic modalities for cancer treatment demonstrating favorable clinical outcomes. The investigation of specific biomarkers for predicting the efficacy and resistance of BET inhibitors is needed to fully realize their therapeutic potential in the clinical setting.

Computational approaches for the design of modulators targeting protein-protein interactions

BACKGROUND

Protein-protein interactions (PPIs) are intriguing targets for designing novel small-molecule inhibitors. The role of PPIs in various infectious and neurodegenerative disorders makes them potential therapeutic targets . Despite being portrayed as undruggable targets, due to their flat surfaces, disorderedness, and lack of grooves. Recent progresses in computational biology have led researchers to reconsider PPIs in drug discovery.

AREAS COVERED

In this review, we introduce in-silico methods used to identify PPI interfaces and present an in-depth overview of various computational methodologies that are successfully applied to annotate the PPIs. We also discuss several successful case studies that use computational tools to understand PPIs modulation and their key roles in various physiological processes.

EXPERT OPINION

Computational methods face challenges due to the inherent flexibility of proteins, which makes them expensive, and result in the use of rigid models. This problem becomes more significant in PPIs due to their flexible and flat interfaces. Computational methods like molecular dynamics (MD) simulation and machine learning can integrate the chemical structure data into biochemical and can be used for target identification and modulation. These computational methodologies have been crucial in understanding the structure of PPIs, designing PPI modulators, discovering new drug targets, and predicting treatment outcomes.

Ranking Peptide Binders by Affinity with AlphaFold

AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides and other proteins. However, for protein-peptide systems, we are also interested in identifying the highest affinity binder among a set of candidate peptides. We present a novel competitive binding assay using AlphaFold to predict structures of the receptor in the presence of two peptides. For systems in which the individual structures of the peptides are well predicted, the assay captures the higher affinity binder in the bound state, and the other peptide in the unbound form with statistical significance. We test the application on six protein receptors for which we have experimental binding affinities to several peptides. We find that the assay is best suited for identifying medium to strong peptide binders that adopt stable secondary structures upon binding.

Towards rational computational peptide design

Peptides are prevalent in biology, mediating as many as 40% of protein-protein interactions, and involved in other cellular functions such as transport and signaling. Their ability to bind with high specificity make them promising therapeutical agents with intermediate properties between small molecules and large biologics. Beyond their biological role, peptides can be programmed to self-assembly, and they are already being used for functions as diverse as oligonuclotide delivery, tissue regeneration or as drugs. However, the transient nature of their interactions has limited the number of structures and knowledge of binding affinities available-and their flexible nature has limited the success of computational pipelines that predict the structures and affinities of these molecules. Fortunately, recent advances in experimental and computational pipelines are creating new opportunities for this field. We are starting to see promising predictions of complex structures, thermodynamic and kinetic properties. We believe in the following years this will lead to robust rational peptide design pipelines with success similar to those applied for small molecule drug discovery.

Catching BETs by viruses

Viruses use diverse tactics to hijack host cellular machineries to evade innate immune responses and maintain their life cycles. Being critical transcriptional regulators, human BET proteins are prominent targets of a growing number of viruses. The BET proteins associate with chromatin through the interaction of their bromodomains with acetylated histones, whereas the carboxy-terminal domains of these proteins contain docking sites for various human co-transcriptional regulators. The same docking sites however can be occupied by viral proteins that exploit the BET proteins to anchor their genome components to chromatin in the infected host cell. In this review we highlight the pathological functions of the BET proteins upon viral infection, focusing on the mechanisms underlying their direct interactions with viral proteins, such as the envelope protein from SARS-CoV-2.

Identification and functional characterization of transcriptional activators in human cells

Transcription is orchestrated by thousands of transcription factors (TFs) and chromatin-associated proteins, but how these are causally connected to transcriptional activation is poorly understood. Here, we conduct an unbiased proteome-scale screen to systematically uncover human proteins that activate transcription in a natural chromatin context. By combining interaction proteomics and chemical inhibitors, we delineate the preference of these transcriptional activators for specific co-activators, highlighting how even closely related TFs can function via distinct cofactors. We also identify potent transactivation domains among the hits and use AlphaFold2 to predict and experimentally validate interaction interfaces of two activation domains with BRD4. Finally, we show that many novel activators are partners in fusion events in tumors and functionally characterize a myofibroma-associated fusion between SRF and C3orf62, a potent p300-dependent activator. Our work provides a functional catalog of potent transactivators in the human proteome and a platform for discovering transcriptional regulators at genome scale.

Structure and function of retroviral integrase

A hallmark of retroviral replication is establishment of the proviral state, wherein a DNA copy of the viral RNA genome is stably incorporated into a host cell chromosome. Integrase is the viral enzyme responsible for the catalytic steps involved in this process, and integrase strand transfer inhibitors are widely used to treat people living with HIV. Over the past decade, a series of X-ray crystallography and cryogenic electron microscopy studies have revealed the structural basis of retroviral DNA integration. A variable number of integrase molecules congregate on viral DNA ends to assemble a conserved intasome core machine that facilitates integration. The structures additionally informed on the modes of integrase inhibitor action and the means by which HIV acquires drug resistance. Recent years have witnessed the development of allosteric integrase inhibitors, a highly promising class of small molecules that antagonize viral morphogenesis. In this Review, we explore recent insights into the organization and mechanism of the retroviral integration machinery and highlight open questions as well as new directions in the field.

Simultaneous Assignment and Structure Determination of Proteins From Sparsely Labeled NMR Datasets

Sparsely labeled NMR samples provide opportunities to study larger biomolecular assemblies than is traditionally done by NMR. This requires new computational tools that can handle the sparsity and ambiguity in the NMR datasets. The MELD (modeling employing limited data) Bayesian approach was assessed to be the best performing in predicting structures from sparsely labeled NMR data in the 13th edition of the Critical Assessment of Structure Prediction (CASP) event—and limitations of the methodology were also noted. In this report, we evaluate the nature and difficulty in modeling unassigned sparsely labeled NMR datasets and report on an improved methodological pipeline leading to higher-accuracy predictions. We benchmark our methodology against the NMR datasets provided by CASP 13.

Oncogenic Truncations of ASXL1 Enhance a Motif for BRD4 ET-Domain Binding

Proper regulation of gene-expression relies on specific protein-protein interactions between a myriad of epigenetic regulators. As such, mutation of genes encoding epigenetic regulators often drive cancer and developmental disorders. Additional sex combs-like protein 1 (ASXL1) is a key example, where mutations frequently drive haematological cancers and can cause developmental disorders. It has been reported that nonsense mutations in ASXL1 promote an interaction with BRD4, another central epigenetic regulator. Here we provide a molecular mechanism for the BRD4-ASXL1 interaction, demonstrating that a motif near to common truncation breakpoints of ASXL1 contains an epitope that binds the ET domain within BRD4. Binding-studies show that this interaction is analogous to common ET-binding modes of BRD4-interactors, and that all three ASX-like protein orthologs (ASXL1-3) contain a functional ET domain-binding epitope. Crucially, we observe that BRD4-ASXL1 binding is markedly increased in the prevalent ASXL1^Y591X truncation that maintains the BRD4-binding epitope, relative to full-length ASXL1 or truncated proteins that delete the epitope. Together, these results show that ASXL1 truncation enhances BRD4 recruitment to transcriptional complexes via its ET domain, which could misdirect regulatory activity of either BRD4 or ASXL1 and may inform potential therapeutic interventions.

A tail goes viral by forming an anchor and a tether

In this issue of Structure, Aiyer et al. (2021) report NMR structures of BET:MLV IN complexes, highlighting a role for the disordered tail domain of MLV IN in viral integration. These studies expand the understanding of molecular recognition polymorphism in BET complexes and offer insight into cancer and antiviral therapeutics.

Computational Modeling as a Tool to Investigate PPI: From Drug Design to Tissue Engineering

Protein-protein interactions (PPIs) mediate a large number of important regulatory pathways. Their modulation represents an important strategy for discovering novel therapeutic agents. However, the features of PPI binding surfaces make the use of structure-based drug discovery methods very challenging. Among the diverse approaches used in the literature to tackle the problem, linear peptides have demonstrated to be a suitable methodology to discover PPI disruptors. Unfortunately, the poor pharmacokinetic properties of linear peptides prevent their direct use as drugs. However, they can be used as models to design enzyme resistant analogs including, cyclic peptides, peptide surrogates or peptidomimetics. Small molecules have a narrower set of targets they can bind to, but the screening technology based on virtual docking is robust and well tested, adding to the computational tools used to disrupt PPI. We review computational approaches used to understand and modulate PPI and highlight applications in a few case studies involved in physiological processes such as cell growth, apoptosis and intercellular communication.