Stabilization of protein-protein interaction complexes through small molecules

14-3-3 Protein-Protein Interactions: From Mechanistic Understanding to Their Small-Molecule Stabilization

Protein-protein interactions (PPIs) are of utmost importance for maintenance of cellular homeostasis. Herein, a central role can be found for 14-3-3 proteins. These hub-proteins are known to bind hundreds of interaction partners, thereby regulating their activity, localization, and/or stabilization. Due to their ability to bind a large variety of client proteins, studies of 14-3-3 protein complexes flourished over the last decades, aiming to gain greater molecular understanding of these complexes and their role in health and disease. Because of their crucial role within the cell, 14-3-3 protein complexes are recognized as highly interesting therapeutic targets, encouraging the discovery of small molecule modulators of these PPIs. We discuss various examples of 14-3-3-mediated regulation of its binding partners on a mechanistic level, highlighting the versatile and multi-functional role of 14-3-3 within the cell. Furthermore, an overview is given on the development of stabilizers of 14-3-3 protein complexes, from initially used natural products to fragment-based approaches. These studies show the potential of 14-3-3 PPI stabilizers as novel agents in drug discovery and as tool compounds to gain greater molecular understanding of the role of 14-3-3-based protein regulation.

DrugMap: A quantitative pan-cancer analysis of cysteine ligandability

Cysteine-focused chemical proteomic platforms have accelerated the clinical development of covalent inhibitors for a wide range of targets in cancer. However, how different oncogenic contexts influence cysteine targeting remains unknown. To address this question, we have developed "DrugMap," an atlas of cysteine ligandability compiled across 416 cancer cell lines. We unexpectedly find that cysteine ligandability varies across cancer cell lines, and we attribute this to differences in cellular redox states, protein conformational changes, and genetic mutations. Leveraging these findings, we identify actionable cysteines in NF-κB1 and SOX10 and develop corresponding covalent ligands that block the activity of these transcription factors. We demonstrate that the NF-κB1 probe blocks DNA binding, whereas the SOX10 ligand increases SOX10-SOX10 interactions and disrupts melanoma transcriptional signaling. Our findings reveal heterogeneity in cysteine ligandability across cancers, pinpoint cell-intrinsic features driving cysteine targeting, and illustrate the use of covalent probes to disrupt oncogenic transcription-factor activity.

Screening for molecular glues - Challenges and opportunities

Molecular glues are small molecules, typically smaller than PROTACs, and usually with improved physicochemical properties that aim to stabilise the interaction between two proteins. Most often this approach is used to improve or induce an interaction between the target and an E3 ligase, but other interactions which stabilise interactions to increase activity or to inhibit binding to a natural effector have also been demonstrated. This review will describe the effects of induced proximity, discuss current methods used to identify molecular glues and introduce approaches that could be adapted for molecular glue screening.

DrugMap: A quantitative pan-cancer analysis of cysteine ligandability

Cysteine-focused chemical proteomic platforms have accelerated the clinical development of covalent inhibitors of a wide-range of targets in cancer. However, how different oncogenic contexts influence cysteine targeting remains unknown. To address this question, we have developed DrugMap , an atlas of cysteine ligandability compiled across 416 cancer cell lines. We unexpectedly find that cysteine ligandability varies across cancer cell lines, and we attribute this to differences in cellular redox states, protein conformational changes, and genetic mutations. Leveraging these findings, we identify actionable cysteines in NFκB1 and SOX10 and develop corresponding covalent ligands that block the activity of these transcription factors. We demonstrate that the NFκB1 probe blocks DNA binding, whereas the SOX10 ligand increases SOX10-SOX10 interactions and disrupts melanoma transcriptional signaling. Our findings reveal heterogeneity in cysteine ligandability across cancers, pinpoint cell-intrinsic features driving cysteine targeting, and illustrate the use of covalent probes to disrupt oncogenic transcription factor activity.

A model-informed method to retrieve intrinsic from apparent cooperativity and project cellular target occupancy for ternary complex-forming compounds

There is an increasing interest to develop therapeutics that modulate challenging or undruggable target proteins via a mechanism that involves ternary complexes. In general, such compounds can be characterized by their direct affinities to a chaperone and a target protein and by their degree of cooperativity in the formation of the ternary complex. As a trend, smaller compounds have a greater dependency on intrinsic cooperativity to their thermodynamic stability relative to direct target (or chaperone) binding. This highlights the need to consider intrinsic cooperativity of ternary complex-forming compounds early in lead optimization, especially as they provide more control over target selectivity (especially for isoforms) and more insight into the relationship between target occupancy and target response via estimation of ternary complex concentrations. This motivates the need to quantify the natural constant of intrinsic cooperativity (α) which is generally defined as the gain (or loss) in affinity of a compound to its target in pre-bound vs. unbound state. Intrinsic cooperativities can be retrieved via a mathematical binding model from EC₅₀ shifts of binary binding curves of the ternary complex-forming compound with either a target or chaperone relative to the same experiment but in the presence of the counter protein. In this manuscript, we present a mathematical modeling methodology that estimates the intrinsic cooperativity value from experimentally observed apparent cooperativities. This method requires only the two binary binding affinities and the protein concentrations of target and chaperone and is therefore suitable for use in early discovery therapeutic programs. This approach is then extended from biochemical assays to cellular assays (i.e., from a closed system to an open system) by accounting for differences in total ligand vs. free ligand concentrations in the calculations of ternary complex concentrations. Finally, this model is used to translate biochemical potency of ternary complex-forming compounds into expected cellular target occupancy, which could ultimately serve as a way for validation or de-validation of hypothesized biological mechanisms of action.

What Makes a Good Protein-Protein Interaction Stabilizer: Analysis and Application of the Dual-Binding Mechanism

Protein-protein interactions (PPIs) are essential for biological processes including immune reactions and diseases. Inhibition of PPIs by drug-like compounds is a common basis for therapeutic approaches. In many cases the flat interface of PP complexes prevents discovery of specific compound binding to cavities on one partner and PPI inhibition. However, frequently new pockets are formed at the PP interface that allow accommodation of stabilizers which is often as desirable as inhibition but a much less explored alternative strategy. Herein, we employ molecular dynamics simulations and pocket detection to investigate 18 known stabilizers and associated PP complexes. For most cases, we find that a dual-binding mechanism, a similar stabilizer interaction strength with each protein partner, is an important prerequisite for effective stabilization. A few stabilizers follow an allosteric mechanism by stabilizing the protein bound structure and/or increase the PPI indirectly. On 226 protein-protein complexes, we find in >75% of the cases interface cavities suitable for binding of drug-like compounds. We propose a computational compound identification workflow that exploits new PP interface cavities and optimizes the dual-binding mechanism and apply it to 5 PP complexes. Our study demonstrates a great potential for in silico PPI stabilizers discovery with a wide range of therapeutic applications.

Protein-protein interfaces in molecular glue-induced ternary complexes: classification, characterization, and prediction

Molecular glues are a class of small molecules that stabilize the interactions between proteins. Naturally occurring molecular glues are present in many areas of biology where they serve as central regulators of signaling pathways. Importantly, several clinical compounds act as molecular glue degraders that stabilize interactions between E3 ubiquitin ligases and target proteins, leading to their degradation. Molecular glues hold promise as a new generation of therapeutic agents, including those molecular glue degraders that can redirect the protein degradation machinery in a precise way. However, rational discovery of molecular glues is difficult in part due to the lack of understanding of the protein-protein interactions they stabilize. In this review, we summarize the structures of known molecular glue-induced ternary complexes and the interface properties. Detailed analysis shows different mechanisms of ternary structure formation. Additionally, we also review computational approaches for predicting protein-protein interfaces and highlight the promises and challenges. This information will ultimately help inform future approaches for rational molecular glue discovery.

Molecular glues to stabilise protein-protein interactions

Targeting protein-protein interactions (PPIs) has become a common approach to tackle various diseases whose pathobiology is driven by their mis-regulation in important signalling pathways. Modulating PPIs has tremendous untapped therapeutic potential and different approaches can be used to modulate PPIs. Initially, therapeutic effects were mostly sought by inhibiting PPIs. However, by gaining insight in the mode of action of certain therapeutic compounds, it became clear that stabilising (i.e. enhancing) PPIs can also be useful. The latter strategy is recently gaining a lot of attention, as stabilising physiologic, or even inducing novel interactions of a target protein with E3 ubiquitin ligases forms the basis of the targeted protein degradation (TPD) approach. An emerging additional example for drug discovery based on PPI stabilisation are the 14-3-3 proteins, a family of regulatory proteins, which engages in many protein-protein interactions, some of which might become therapeutical targets.

Structure-based assessment and druggability classification of protein-protein interaction sites

The featureless interface formed by protein–protein interactions (PPIs) is notorious for being considered a difficult and poorly druggable target. However, recent advances have shown PPIs to be druggable, with the discovery of potent inhibitors and stabilizers, some of which are currently being clinically tested and approved for medical use. In this study, we assess the druggability of 12 commonly targeted PPIs using the computational tool, SiteMap. After evaluating 320 crystal structures, we find that the PPI binding sites have a wide range of druggability scores. This can be attributed to the unique structural and physiochemical features that influence their ligand binding and concomitantly, their druggability predictions. We then use these features to propose a specific classification system suitable for assessing PPI targets based on their druggability scores and measured binding-affinity. Interestingly, this system was able to distinguish between different PPIs and correctly categorize them into four classes (i.e. very druggable, druggable, moderately druggable, and difficult). We also studied the effects of protein flexibility on the computed druggability scores and found that protein conformational changes accompanying ligand binding in ligand-bound structures result in higher protein druggability scores due to more favorable structural features. Finally, the drug-likeness of many published PPI inhibitors was studied where it was found that the vast majority of the 221 ligands considered here, including orally tested/marketed drugs, violate the currently acceptable limits of compound size and hydrophobicity parameters. This outcome, combined with the lack of correlation observed between druggability and drug-likeness, reinforces the need to redefine drug-likeness for PPI drugs. This work proposes a PPI-specific classification scheme that will assist researchers in assessing the druggability and identifying inhibitors of the PPI interface.

A System for the Evolution of Protein-Protein Interaction Inducers

Molecules that induce interactions between proteins, often referred to as "molecular glues", are increasingly recognized as important therapeutic modalities and as entry points for rewiring cellular signaling networks. Here, we report a new PACE-based method to rapidly select and evolve molecules that mediate interactions between otherwise noninteracting proteins: rapid evolution of protein-protein interaction glues (rePPI-G). By leveraging proximity-dependent split RNA polymerase-based biosensors, we developed E. coli-based detection and selection systems that drive gene expression outputs only when interactions between target proteins are induced. We then validated the system using engineered bivalent molecular glues, showing that rePPI-G robustly selects for molecules that induce the target interaction. Proof-of-concept evolutions demonstrated that rePPI-G reduces the "hook effect" of the engineered molecular glues, due at least in part to tuning the interaction affinities of each individual component of the bifunctional molecule. Altogether, this work validates rePPI-G as a continuous, phage-based evolutionary technology for optimizing molecular glues, providing a strategy for developing molecules that reprogram protein-protein interactions.

Exploration of a 14-3-3 PPI Pocket by Covalent Fragments as Stabilizers

The systematic discovery of functional fragments binding to the composite interface of protein complexes is a first critical step for the development of orthosteric stabilizers of protein–protein interactions (PPIs). We have previously shown that disulfide trapping successfully yielded covalent stabilizers for the PPI of 14-3-3 with the estrogen receptor ERα. Here we provide an assessment of the composite PPI target pocket and the molecular characteristics of various fragments binding to a specific subpocket. Evaluating structure–activity relationships highlights the basic principles for PPI stabilization by these covalent fragments that engage a relatively large and exposed binding pocket at the protein/peptide interface with a “molecular glue” mode of action.

Small-molecule modulation of p53 protein-protein interactions

Small-molecule modulation of protein-protein interactions (PPIs) is a very promising but also challenging area in drug discovery. The tumor suppressor protein p53 is one of the most frequently altered proteins in human cancers, making it an attractive target in oncology. 14-3-3 proteins have been shown to bind to and positively regulate p53 activity by protecting it from MDM2-dependent degradation or activating its DNA binding affinity. PPIs can be modulated by inhibiting or stabilizing specific interactions by small molecules. Whereas inhibition has been widely explored by the pharmaceutical industry and academia, the opposite strategy of stabilizing PPIs still remains relatively underexploited. This is rather interesting considering the number of natural compounds like rapamycin, forskolin and fusicoccin that exert their activity by stabilizing specific PPIs. In this review, we give an overview of 14-3-3 interactions with p53, explain isoform specific stabilization of the tumor suppressor protein, explore the approach of stabilizing the 14-3-3σ-p53 complex and summarize some promising small molecules inhibiting the p53-MDM2 protein-protein interaction.

The iPPI-DB initiative: A Community-centered database of Protein-Protein Interaction modulators

MOTIVATION

One avenue to address the paucity of clinically testable targets is to reinvestigate the druggable genome by tackling complicated types of targets such as Protein-Protein Interactions (PPIs). Given the challenge to target those interfaces with small chemical compounds, it has become clear that learning from successful examples of PPI modulation is a powerful strategy. Freely-accessible databases of PPI modulators that provide the community with tractable chemical and pharmacological data, as well as powerful tools to query them, are therefore essential to stimulate new drug discovery projects on PPI targets.

RESULTS

Here, we present the new version iPPI-DB, our manually curated database of PPI modulators. In this completely redesigned version of the database, we introduce a new web interface relying on crowdsourcing for the maintenance of the database. This interface was created to enable community contributions, whereby external experts can suggest new database entries. Moreover, the data model, the graphical interface, and the tools to query the database have been completely modernized and improved. We added new PPI modulators, new PPI targets, and extended our focus to stabilizers of PPIs as well.

AVAILABILITY AND IMPLEMENTATION

The iPPI-DB server is available at https://ippidb.pasteur.fr The source code for this server is available at https://gitlab.pasteur.fr/ippidb/ippidb-web/ and is distributed under GPL licence (http://www.gnu.org/licences/gpl). Queries can be shared through persistent links according to the FAIR data standards. Data can be downloaded from the website as csv files.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Evolution in non-peptide α-helix mimetics on the road to effective protein-protein interaction modulators

Modulation of interactome networks, essentially protein-protein interactions (PPIs), might represent valuable therapeutic approaches to different pathological conditions. Since a high percentage of PPIs are mediated by α-helical structures at the interacting surface, the development of compounds able to reproduce the amino acid side-chain organization of α-helices (e.g. stabilized α-helix peptides and β-derivatives, proteomimetics, and α-helix small-molecule mimetics) focuses the attention of different research groups. This appraisal describes the recent progress in the non-peptide α-helix mimetics field, which has evolved from single-face to multi-face reproducing compounds and from oligomeric to monomeric scaffolds able to bear different substituents in similar spatial dispositions as the side-chains in canonical helices. Grouped by chemical structures, the review contemplates terphenyl-like molecules, oligobenzamides and heterocyclic analogues, benzamide-amino acid conjugates and non-oligomeric small-molecules mimetics, among others, and their effectiveness to stabilize/disrupt therapeutically relevant PPIs. The X-ray structures of a couple of oligomeric peptidomimetics and of some small-molecules complexed with the MDM2 protein, as well as the state of the art on their development in clinical trials, are also remarked. The discovery of a continuously increasing number of new disease-relevant PPIs could offer future opportunities for these and other forthcoming α-helix mimetics.

Recent advances in the development of protein-protein interactions modulators: mechanisms and clinical trials

Protein-protein interactions (PPIs) have pivotal roles in life processes. The studies showed that aberrant PPIs are associated with various diseases, including cancer, infectious diseases, and neurodegenerative diseases. Therefore, targeting PPIs is a direction in treating diseases and an essential strategy for the development of new drugs. In the past few decades, the modulation of PPIs has been recognized as one of the most challenging drug discovery tasks. In recent years, some PPIs modulators have entered clinical studies, some of which been approved for marketing, indicating that the modulators targeting PPIs have broad prospects. Here, we summarize the recent advances in PPIs modulators, including small molecules, peptides, and antibodies, hoping to provide some guidance to the design of novel drugs targeting PPIs in the future.

Structure-based evolution of a promiscuous inhibitor to a selective stabilizer of protein-protein interactions

The systematic stabilization of protein–protein interactions (PPI) has great potential as innovative drug discovery strategy to target novel and hard-to-drug protein classes. The current lack of chemical starting points and focused screening opportunities limits the identification of small molecule stabilizers that engage two proteins simultaneously. Starting from our previously described virtual screening strategy to identify inhibitors of 14-3-3 proteins, we report a conceptual molecular docking approach providing concrete entries for discovery and rational optimization of stabilizers for the interaction of 14-3-3 with the carbohydrate-response element-binding protein (ChREBP). X-ray crystallography reveals a distinct difference in the binding modes between weak and general inhibitors of 14-3-3 complexes and a specific, potent stabilizer of the 14-3-3/ChREBP complex. Structure-guided stabilizer optimization results in selective, up to 26-fold enhancement of the 14-3-3/ChREBP interaction. This study demonstrates the potential of rational design approaches for the development of selective PPI stabilizers starting from weak, promiscuous PPI inhibitors.

Small molecule stabilizers of protein–protein interactions hold great therapeutic potential. Based on virtual screening and molecular docking, the authors here develop a strategy to evolve weak, promiscuous inhibitors of 14-3-3 interactions into selective stabilizers of the 14-3-3/ChREBP complex.

Revealing hidden information in osteoblast's mechanotransduction through analysis of time patterns of critical events

BACKGROUND

Mechanotransduction in bone cells plays a pivotal role in osteoblast differentiation and bone remodelling. Mechanotransduction provides the link between modulation of the extracellular matrix by mechanical load and intracellular activity. By controlling the balance between the intracellular and extracellular domains, mechanotransduction determines the optimum functionality of skeletal dynamics. Failure of this relationship was suggested to contribute to bone-related diseases such as osteoporosis.

RESULTS

A hybrid mechanical and agent-based model (Mech-ABM), simulating mechanotransduction in a single osteoblast under external mechanical perturbations, was utilised to simulate and examine modulation of the activation dynamics of molecules within mechanotransduction on the cellular response to mechanical stimulation. The number of molecules and their fluctuations have been analysed in terms of recurrences of critical events. A numerical approach has been developed to invert subordination processes and to extract the direction processes from the molecular signals in order to derive the distribution of recurring events. These predict that there are large fluctuations enclosing information hidden in the noise which is beyond the dynamic variations of molecular baselines. Moreover, studying the system under different mechanical load regimes and altered dynamics of feedback loops, illustrate that the waiting time distributions of each molecule are a signature of the system's state.

CONCLUSIONS

The behaviours of the molecular waiting times change with the changing of mechanical load regimes and altered dynamics of feedback loops, presenting the same variation of patterns for similar interacting molecules and identifying specific alterations for key molecules in mechanotransduction. This methodology could be used to provide a new tool to identify potent molecular candidates to modulate mechanotransduction, hence accelerate drug discovery towards therapeutic targets for bone mass upregulation.

Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes

BACKGROUND

The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology.

OBJECTIVE

Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions.

METHODS

We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions.

RESULTS

We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs.

CONCLUSION

PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein-protein complexes for experimental studies.

Exhaustive Repertoire of Druggable Cavities at Protein-Protein Interfaces of Known Three-Dimensional Structure

Protein-protein interactions (PPIs) offer the unique opportunity to tailor ligands aimed at specifically stabilizing or disrupting the corresponding interfaces and providing a safer alternative to conventional ligands targeting monomeric macromolecules. Selecting biologically relevant protein-protein interfaces for either stabilization or disruption by small molecules is usually biology-driven on a case-by-case basis and does not follow a structural rationale that could be applied to an entire interactome. We herewith provide a first step to the latter goal by using a fully automated and structure-based workflow, applicable to any PPI of known three-dimensional (3D) structure, to identify and prioritize druggable cavities at and nearby PPIs of pharmacological interest. When applied to the entire Protein Data Bank, 164 514 druggable cavities were identified and classified in four groups (interfacial, rim, allosteric, orthosteric) according to their properties and spatial locations. Systematic comparison of PPI cavities with pockets deduced from druggable protein-ligand complexes shows almost no overlap in property space, suggesting that even the most druggable PPI cavities are unlikely to be addressed with conventional drug-like compound libraries. The archive is freely accessible at http://drugdesign.unistra.fr/ppiome .

Disease-modifying therapy for proteinopathies: Can the exception become the rule?

Disease-modifying therapies for proteinopathies are urgently needed yet clinical trials for the major neurodegenerative diseases, Alzheimer's and Parkinson's, have been failing at an alarming rate leaving patients and caregivers scrambling for any sign of hope. At the same time, for one family of proteinopathies, the rare TTR amyloidoses, disease-modifying therapy has existed for almost 3 decades and two new types of disease-modifying therapy have become available more recently. In this chapter, I discuss those therapies, examine to what extent they can be generalized for other diseases, and consider what we may learn from their relative success.

New approach to evaluating the effects of a drug on protein complexes with quantitative proteomics, using the SILAC method and bioinformatic approach

Protein-protein interactions (PPIs) lead the formation of protein complexes that perform biochemical reactions that maintain the living state of the living cell. Although therapeutic drugs should influence the formation of protein complexes in addition to PPI network, the methodology analyzing such influences remain to be developed. Here, we demonstrate that a new approach combining HPLC (high performance liquid chromatography) for separating protein complexes, and the SILAC (stable isotope labeling using amino acids in cell culture) method for relative protein quantification, enable us to identify the protein complexes influenced by a drug. We applied this approach to the analysis of thalidomide action on HepG2 cells, assessed the identified proteins by clustering data analyses, and assigned 135 novel protein complexes affected by the drug. We propose that this approach is applicable to elucidating the mechanisms of actions of other therapeutic drugs on the PPI network, and the formation of protein complexes.

Rational modulator design by exploitation of protein-protein complex structures

The horizon of drug discovery is currently expanding to target and modulate protein-protein interactions (PPIs) in globular proteins and intrinsically disordered proteins that are involved in various diseases. To either interrupt or stabilize PPIs, the 3D structure of target protein-protein (or protein-peptide) complexes can be exploited to rationally design PPI modulators (inhibitors or stabilizers) through structure-based molecular design. In this review, we present an overview of experimental and computational methods that can be used to determine 3D structures of protein-protein complexes. Several approaches including rational and in silico methods that can be applied to design peptides, peptidomimetics and small compounds by utilization of determined 3D protein-protein/peptide complexes are summarized and illustrated.

Biochemical characterization of the respiratory syncytial virus N0-P complex in solution

As all the viruses belonging to the Mononegavirales order, the nonsegmented negative-strand RNA genome of respiratory syncytial virus (RSV) is encapsidated by the viral nucleoprotein N. N protein polymerizes along the genomic and anti-genomic RNAs during replication. This requires the maintenance of the neosynthesized N protein in a monomeric and RNA-free form by the viral phosphoprotein P that plays the role of a chaperone protein, forming a soluble N0-P complex. We have previously demonstrated that residues 1-30 of P specifically bind to N0 Here, to isolate a stable N0-P complex suitable for structural studies, we used the N-terminal peptide of P (P40) to purify truncated forms of the N protein. We show that to purify a stable N0-P-like complex, a deletion of the first 30 N-terminal residues of N (NΔ30) is required to impair N oligomerization, whereas the presence of a full-length C-arm of N is required to inhibit RNA binding. We generated structural models of the RSV N0-P with biophysical approaches, including hydrodynamic measurements and small-angle X-ray scattering (SAXS), coupled with biochemical and functional analyses of human RSV (hRSV) NΔ30 mutants. These models suggest a strong structural homology between the hRSV and the human metapneumovirus (hMPV) N0-P complexes. In both complexes, the P40-binding sites on N0 appear to be similar, and the C-arm of N provides a high flexibility and a propensity to interact with the N RNA groove. These findings reveal two potential sites to target on N0-P for the development of RSV antivirals.

Allosteric Modulators of Protein-Protein Interactions (PPIs)

Protein-protein interactions (PPIs) represent promising drug targets of broad-spectrum therapeutic interests due to their critical implications in both health and disease circumstances. Hence, they are widely accepted as the Holy Grail of drug development. Historically, PPIs were rendered "undruggable" for their large, flat, and pocket-less structures. Current attempts to drug these "intractable" targets include orthosteric and allosteric methodologies. Previous efforts employing orthosteric approaches like protein therapeutics and orthosteric small molecules frequently suffered from poor performance caused by the difficulties in directly targeting PPI interfaces. As structural biology progresses rapidly, allosteric modulators, which direct to the allosteric regulatory sites remote to the PPI surfaces, have gradually established as a potential solution. Allosteric pockets are topologically distal from the PPI orthosteric sites, and their ligands do not need to compete with the PPI partners, which helps to improve the physiochemical and pharmacological properties of allosteric PPI modulators. Thus, exploiting allostery to tailor PPIs is regarded as a tempting strategy in future PPI drug discovery. Here, we provide a comprehensive review of our representative achievements along the way we utilize allosteric effects to tame the difficult PPI systems into druggable targets. Importantly, we provide an in-depth mechanistic analysis of this success, which will be instructive to future related lead optimizations and drug design. Finally, we discuss the current challenges in allosteric PPI drug discovery. Their solutions as well as future perspectives are also presented.

NEMO Links Nuclear Factor-κB to Human Diseases

The nuclear factor (NF)-κB essential modulator (NEMO) is a key regulator in NF-κB-mediated signaling. By transmitting extracellular or intracellular signals, NEMO can control NF-κB-regulated genes. NEMO dysfunction is associated with inherited diseases such as incontinentia pigmenti (IP), ectodermal dysplasia, anhidrotic, with immunodeficiency (EDA-ID), and some cancers. We focus on molecular studies, human case reports, and mouse models emphasizing the significance of NEMO molecular interactions and modifications in health and diseases. This knowledge opens new opportunities to engineer suitable drugs that may putatively target precise NEMO functions attributable to various diseases, while leaving other functions intact, and eliminating cytotoxicity. Indeed, with the advent of novel gene editing tools such as clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas)9, treating some inherited diseases may in the long run, become a reality.

Producing irreversible topoisomerase II-mediated DNA breaks by site-specific Pt(II)-methionine coordination chemistry

Human type II topoisomerase (Top2) isoforms, hTop2α and hTop2β, are targeted by some of the most successful anticancer drugs. These drugs induce Top2-mediated DNA cleavage to trigger cell-death pathways. The potency of these drugs correlates positively with their efficacy in stabilizing the enzyme-mediated DNA breaks. Structural analysis of hTop2α and hTop2β revealed the presence of methionine residues in the drug-binding pocket, we therefore tested whether a tighter Top2-drug association may be accomplished by introducing a methionine-reactive Pt²⁺ into a drug to further stabilize the DNA break. Herein, we synthesized an organoplatinum compound, etoplatin-N2β, by replacing the methionine-juxtaposing group of the drug etoposide with a cis-dichlorodiammineplatinum(II) moiety. Compared to etoposide, etoplatin-N2β more potently inhibits both human Top2s. While the DNA breaks arrested by etoposide can be rejoined, those captured by etoplatin-N2β are practically irreversible. Crystallographic analyses of hTop2β complexed with DNA and etoplatin-N2β demonstrate coordinate bond formation between Pt²⁺ and a flanking methionine. Notably, this stable coordinate tether can be loosened by disrupting the structural integrity of drug-binding pocket, suggesting that Pt²⁺ coordination chemistry may allow for the development of potent inhibitors with protein conformation-dependent reversibility. This approach may be exploited to achieve isoform-specific targeting of human Top2s.

Disrupting VEGF-VEGFR1 Interaction: De Novo Designed Linear Helical Peptides to Mimic the VEGF13-25 Fragment

The interaction between vascular endothelial growth factor (VEGF) and its receptors (VEGFR) has important implications in angiogenesis and cancer, which moved us to search for peptide derivatives able to block this protein–protein interaction. In a previous work we had described a collection of linear 13-mer peptides specially designed to adopt helical conformations (Ac-SSEEX⁵ARNX⁹AAX¹²N-NH₂), as well as the evaluation of seven library components for the inhibition of the interaction of VEGF with its Receptor 1 (VEGFR1). This study led to the discovery of some new, quite potent inhibitors of this protein–protein system. The results we found prompted us to extend the study to other peptides of the library. We describe here the evaluation of a new selection of peptides from the initial library that allow us to identify new VEGF-VEGFR1 inhibitors. Among them, the peptide sequence containing F, W, and I residues at the 5, 9, and 12 positions, show a very significant nanomolar IC₅₀ value, competing with VEGF for its receptor 1, VEGFR1 (Flt-1), which could represent a new tool within the therapeutic arsenal for cancer detection and therapy.

The saponin D39 blocks dissociation of non-muscular myosin heavy chain IIA from TNF receptor 2, suppressing tissue factor expression and venous thrombosis

BACKGROUND AND PURPOSE

Non-muscular myosin heavy chain IIA (NMMHC IIA) plays a key role in tissue factor expression and venous thrombosis. Natural products might inhibit thrombosis through effects on NMMHC IIA. Here, we have shown that a natural saponin, D39, from Liriope muscari exerted anti-thrombotic activity in vivo, by targeting NMMHC IIA.

EXPERIMENTAL APPROACH

Expression and activity of tissue factor in endothelial cells were analysed in vitro by Western blot and simplified chromogenic assays. Interactions between D39 and NMMHC IIA were assessed by serial affinity chromatography and molecular docking analysis. D39-dependent interactions between NMMHC IIA and TNF receptor 2 (TNFR2) were measured by immunofluorescence, co-immunoprecipitation and proximity ligation assays. Anti-thrombotic activity of D39 in vivo was evaluated with a model of inferior vena cava ligation injury in mice.

KEY RESULTS

D39 inhibited tissue factor expression and procoagulant activities in HUVECs and decreased thrombus weight in inferior vena cava-ligated mice dose-dependently. Serial affinity chromatography and molecular docking analysis suggested that D39 bound to NMMHC IIA. In HEK293T cells, D39 inhibited tissue factor expression evoked by NMMHC IIA overexpression. This effect was blocked by NMMHC IIA knockdown in HUVECs. D39 inhibited dissociation of NMMHC IIA from TNFR2, which subsequently modulated the Akt/GSK3β-NF-κB signalling pathways.

CONCLUSIONS AND IMPLICATIONS

D39 inhibited tissue factor expression and thrombus formation by modulating the Akt/GSK3β and NF-κB signalling pathways through NMMHC IIA. We identified a new natural product that targeted NMMHC IIA, as a potential treatment for thrombotic disorders and other vasculopathies.

A Novel Assay for Screening Inhibitors Targeting HIV Integrase LEDGF/p75 Interaction Based on Ni(2+) Coated Magnetic Agarose Beads

HIV-1 integrase (IN) plays an essential role in viral replication and thus serves as an important target for chemotherapeutic intervention against HIV-1 infection. However, the current three clinical IN inhibitors, raltegravir, elvitegravir and dolutegravir share the same inhibitory mechanism, resulting in a common clinical resistance profile which have emerged in infected patients receiving treatment. Therefore, it is important to develop small molecule inhibitors that impair IN function with distinct mechanisms of action. In this work, a magnetic-beads based biochemical assay targeting the protein-protein interaction (PPI) between HIV IN and the cellular cofactor LEDGF/p75 was developed for identification of HIV-1 IN inhibitors. Furthermore, a library containing 1000 US. Food and Drug Administration (FDA)-approved drugs currently used for human medication was screened to identify inhibitors targeting the PPI. The assay was proved to be quite robust and with the novel assay we successfully identified dexlansoprazole (IC₅₀ of 4.8 μM), a FDA-approved proton pump inhibitor, as a potential inhibitor for the PPI between IN and LEDGF/p75, which bound to the LEDGF/p75 partner with a kinetic dissociation (Kd) constant of 330 nM ± 2.6 nM.

Systematic Targeting of Protein-Protein Interactions

Over the past decade, protein-protein interactions (PPIs) have gone from being neglected as 'undruggable' to being considered attractive targets for the development of therapeutics. Recent advances in computational analysis, fragment-based screening, and molecular design have revealed promising strategies to address the basic molecular recognition challenge: how to target large protein surfaces with specificity. Several systematic and complementary workflows have been developed to yield successful inhibitors of PPIs. Here we review the major contemporary approaches utilized for the discovery of inhibitors and focus on a structure-based workflow, from the selection of a biological target to design.

Structure-Based Design of Peptidic Inhibitors of the Interaction between CC Chemokine Ligand 5 (CCL5) and Human Neutrophil Peptides 1 (HNP1)

Protein-protein interactions (PPIs) are receiving increasing interest, much sparked by the realization that they represent druggable targets. Recently, we successfully developed a peptidic inhibitor, RRYGTSKYQ ("SKY" peptide), that shows high potential in vitro and in vivo to interrupt a PPI between the platelet-borne chemokine CCL5 and the neutrophil-derived granule protein HNP1. This PPI plays a vital role in monocyte adhesion, representing a key mechanism in acute and chronic inflammatory diseases. Here, we present extensive and detailed computational methods applied to develop the SKY peptide. We combined experimentally determined binding affinities (KD) of several orthologs of CCL5 with HNP1 with in silico studies to identify the most likely heterodimeric CCL5-HNP1 complex which was subsequently used as a starting structure to rationally design peptidic inhibitors. Our method represents a fast and simple approach that can be widely applied to determine other protein-protein complexes and moreover to design inhibitors or stabilizers of protein-protein interaction.