Systematic Targeting of Protein-Protein Interactions

The Druggable Transcriptome Project: From Chemical Probes to Precision Medicines

RNA presents abundant opportunities as a drug target, offering significant potential for small molecule medicine development. The transcriptome, comprising both coding and noncoding RNAs, is a rich area for therapeutic innovation, yet challenges persist in targeting RNA with small molecules. RNA structure can be predicted with or without experimental data, but discrepancies with the actual biological structure can impede progress. Prioritizing RNA targets supported by genetic or evolutionary evidence enhances success. Further, small molecules must demonstrate binding to RNA in cells, not solely in vitro, to validate both the target and compound. Effective small molecule binders modulate functional sites that influence RNA biology, as binding to nonfunctional sites requires recruiting effector mechanisms, for example degradation, to achieve therapeutic outcomes. Addressing these challenges is critical to unlocking RNA's vast potential for small molecule medicines, and a strategic framework is proposed to navigate this promising field, with a focus on targeting human RNAs.

A Brain-Penetrating Foldamer Rescues Aβ Aggregation-Associated Alzheimer's Disease Phenotypes in In Vivo Models

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is the leading cause of dementia, affecting nearly 55 million people across the world. One of the central pathological factors associated with AD is the aggregation of Aβ42, a peptide product cleaved through pathological processes in AD. Under pathological conditions, Aβ42 aggregates into insoluble plaques in the brain and impairs the function of neurons, which contributes to the cognitive decline associated with AD. Therefore, the modulation of Aβ42 aggregation is considered a potential therapeutic intervention for AD. Using an Oligoquinoline-based foldamer library, we have identified a potent foldamer antagonist (SK-131) of Aβ42 aggregation. SK-131 inhibits the aggregation by inducing a α-helical structure in monomeric Aβ42. Here, we demonstrated that SK-131 rescues Aβ42 aggregation-associated phenotypes in AD cellular and multiple Caenorhabditis elegans AD models, including intracellular inhibition of Aβ42 aggregation, rescue of behavioral deficits, and attenuation of reactive oxygen species. It efficiently crosses the blood-brain barrier and demonstrates favorable pharmaceutical properties. It also potently inhibits Zn2+-mediated Aβ42 aggregation by potentially displacing Zn2+ from Aβ42. In summary, we have identified a potent brain-penetrating foldamer that efficiently rescues AD phenotypes in in vivo models. Unlike most of the therapeutic approaches that target Aβ aggregates, we have identified and validated a novel therapeutic pathway by inducing structural change in Aβ and rescuing AD phenotypes in in vivo models. This study will further aid in the quest to identify lead therapeutics to slow or stop the progression of AD.

Recent Developments in 14-3-3 Stabilizers for Regulating Protein-Protein Interactions: An Update

14-3-3 proteins play a crucial role in the regulation of protein-protein interactions, impacting various cellular processes and disease mechanisms. Recent advancements have led to the development of stabilizers that enhance the binding of 14-3-3 proteins to clients, presenting promising therapeutic potentials. This perspective provides an updated overview of the latest developments in the field of 14-3-3 stabilizers, with a focus on their design, synthesis, and biological evaluation. We discuss the structural basis for the interaction between 14-3-3 proteins and their ligands, highlighting key modifications that enhance binding affinity and selectivity. Additionally, we explore the therapeutic applications of 14-3-3 stabilizers across major therapeutic areas such as cancer, metabolic disorders, and neurodegenerative diseases. By summarizing recent research findings and technological advancements, this perspective aims to shed light on the current state of 14-3-3 stabilizer developments and outline future directions for optimizing these compounds as effective therapeutic agents.

Cold plasma reengineers peanut protein isolate: Unveiling changes in functionality, rheology, and structure

This study investigates the effects of cold plasma (CP) treatment on peanut protein isolate (PPI), focusing on functionality, rheology, and structural modifications across various treatment times (0, 90, 180, 270, 360, and 450 s) and voltages (120, 140, and 160 kV). Key findings include a significant increase in solubility from 9.99 mg/mL to 15.98 mg/mL, as well as 161.07 % enhanced water-holding capacity (WHC) and 448.45 % oil-holding capacity (OHC). CP treatment also improved foaming capacity (FC) to 186.46 % and increased emulsion capacity (EC) and emulsion stability (ES) by 185.90 % at 160 kV. Rheological analysis showed shear-thinning behaviour, with viscosity decreasing as the shear rate increased-higher voltages (140 kV and 160 kV) further reduced viscosity, indicating lower resistance to flow. Additionally, CP-treated PPI exhibited viscoelasticity, with increased storage and loss moduli at higher frequencies, indicating greater stiffness. Spectroscopic studies demonstrated shifts in the protein's secondary structure, altering the balance among alpha-helix, beta-sheet, and random coil components, which highlights CP's role in reengineering PPI. FTIR-ATR spectra revealed reductions in the 3200-3400 cm-1 range, suggesting changes in protein backbone vibrations and hydrogen bonding. Particle size analysis showed significant increases, especially at higher voltages and longer treatment times, stabilizing after 270 s. Zeta potential assays indicated a gradual decrease in negative surface charge, suggesting enhanced protein aggregation. Overall, CP treatment significantly improves the functional and rheological properties of PPI while inducing structural changes, making it more suitable for applications in the food and pharmaceutical industries.

Exploring the landscape of post-translational modification in drug discovery

Post-translational modifications (PTMs) play a crucial role in regulating protein function, and their dysregulation is frequently associated with various diseases. The emergence of epigenetic drugs targeting factors such as histone deacetylases (HDACs) and histone methyltransferase enhancers of zeste homolog 2 (EZH2) has led to a significant shift towards precision medicine, offering new possibilities to overcome the limitations of traditional therapeutics. In this review, we aim to systematically explore how small molecules modulate PTMs. We discuss the direct targeting of enzymes involved in PTM pathways, the modulation of substrate proteins, and the disruption of protein-enzyme interactions that govern PTM processes. Additionally, we delve into the emerging strategy of employing multifunctional molecules to precisely regulate the modification levels of proteins of interest (POIs). Furthermore, we examine the specific characteristics of these molecules, evaluating their therapeutic benefits and potential drawbacks. The goal of this review is to provide a comprehensive understanding of PTM-targeting strategies and their potential for personalized medicine, offering a forward-looking perspective on the evolution of precision therapeutics.

Bio-sourced flexible supramolecular glasses for dynamic and full-color phosphorescence

Glass, a diverse family of amorphous materials, has significantly advanced human society across various fields. The demand for flexible ultrathin glass, driven by modern optical displays and portable optoelectronics, presents challenges in energy consumption, fabrication complexity, and recycling. Here, we demonstrate flexibility and full-color luminescence in large-scale ultrathin glasses derived from readily available natural resources, specifically egg albumen (EA) and gelatin (GEL), via an evaporation-driven self-assembly process. The dynamic crosslinked networks formed through hydrogen bonding between EA and GEL impart both high hardness and flexibility to the glasses, with hardness and flexural strength values comparable to state-of-the-art inorganic and organic glasses. Additionally, the EA-GEL-based glasses exhibit excitation-dependent and time-gated chiral ultralong phosphorescence with color from blue and red, and a lifetime of up to 180.4 ms. With their easy processability and full-color emission, these biogenic glasses can be fabricated into anti-counterfeiting patterns and optical information codes.

Short Oligourea Foldamers as N- or C-Caps for Promoting α-Helix Formation in Water

While foldamers have been extensively studied as protein mimics and especially as α-helix mimics, their use as capping motif to enhance α-helix propensity remains comparatively much limited. In this study, we leverage the structural similarities between urea-based helical foldamers and α-helix to investigate the efficacy of oligoureas as N- or C-caps for reinforcing α-helical structures in water. Short oligoureas, comprising 3 to 4 residues, were strategically introduced at the N- or C-terminus of two peptide sequences (S-peptide and an Ala-rich model sequence). The impact of these foldamer insertions on peptide conformation was examined using electronic circular dichroism (ECD) and solution NMR. This research identifies specific foldamer sequences capable of promoting α-helicity when incorporated at either terminus of the peptides. Not only does this work broaden the application scope of foldamers, but it also provides valuable insights into novel strategies for modulating peptide conformation in aqueous environments. The findings presented in this study may have implications for peptide design and the development of bioactive foldamer-based peptide mimics.

Exploring the uncharted territory of the potential protein-protein interactions of cytosolic malate dehydrogenase

In this review, we examine the protein-protein interactions of cytosolic malate dehydrogenase (MDH), an under-studied area in cellular metabolism. We provide a comprehensive overview of MDH involvement in metabolism, especially its interactions with metabolic partners and dynamics of changing metabolism. We present an analysis of the biophysical nature of these interactions and the current methods used to study them. Our review includes an assessment of computational docking studies, which offer initial hypotheses about potential MDH interaction partners. Furthermore, we provide a summary of the sparse yet insightful experimental evidence available, establishing a foundation for future research. By integrating biophysical analysis and methodological advancements, this paper aims to illuminate the intricate network of interactions involving cytosolic MDH and their metabolic implications. This work not only contributes to our understanding of MDH's role in metabolism but also highlights the potential impact of these interactions in metabolic disorders.

The low-entropy hydration shell mediated ice-binding mechanism of antifreeze proteins

Antifreeze proteins (AFPs) can inhibit ice crystal growth. The ice-binding mechanism of AFPs remains unclear, yet the hydration shells of AFPs are thought to play an important role in modulating the binding of AFPs and ice. Here, we performed all-atom molecular dynamics simulations of an AFP from Choristoneura fumiferana (CfAFP) at four different temperatures, with a focus on analysis at 240 and 300 K, to investigate the dynamic and thermodynamic characteristics of hydration shells around ice-binding surfaces (IBS) and non-ice-binding surfaces (NIBS). Our results revealed that the dynamics of CfAFP hydration shells were highly heterogeneous, with its IBS favoring a less dense and more tetrahedral solvation shell, and NIBS hydration shells having opposite features to those of the IBS. The IBS of nine typical hyperactive AFPs were found to be in pure low-entropy hydration shell region, indicating that low-entropy hydration shell region of IBS and the tetrahedral arrangements of water molecules around them mediate the ice-binding mechanism of AFPs. It is because the entropy increase of the low-entropy hydration shell around IBS, while the higher entropy water molecules at NIBS most likely prevent ice crystal growth. These findings provide new mechanistic insights into the ice-binding of AFPs.

Identification of small-molecule ligand-binding sites on and in the ARNT PAS-B domain

Transcription factors are challenging to target with small-molecule inhibitors due to their structural plasticity and lack of catalytic sites. Notable exceptions include naturally ligand-regulated transcription factors, including our prior work with the hypoxia-inducible factor (HIF)-2 transcription factor, showing that small-molecule binding within an internal pocket of the HIF-2α Per-Aryl hydrocarbon Receptor Nuclear Translocator (ARNT)-Sim (PAS)-B domain can disrupt its interactions with its dimerization partner, ARNT. Here, we explore the feasibility of targeting small molecules to the analogous ARNT PAS-B domain itself, potentially opening a promising route to modulate several ARNT-mediated signaling pathways. Using solution NMR fragment screening, we previously identified several compounds that bind ARNT PAS-B and, in certain cases, antagonize ARNT association with the transforming acidic coiled-coil containing protein 3 transcriptional coactivator. However, these ligands have only modest binding affinities, complicating characterization of their binding sites. We address this challenge by combining NMR, molecular dynamics simulations, and ensemble docking to identify ligand-binding "hotspots" on and within the ARNT PAS-B domain. Our data indicate that the two ARNT/transforming acidic coiled-coil containing protein 3 inhibitors, KG-548 and KG-655, bind to a β-sheet surface implicated in both HIF-2 dimerization and coactivator recruitment. Furthermore, while KG-548 binds exclusively to the β-sheet surface, KG-655 can additionally bind within a water-accessible internal cavity in ARNT PAS-B. Finally, KG-279, while not a coactivator inhibitor, exemplifies ligands that preferentially bind only to the internal cavity. All three ligands promoted ARNT PAS-B homodimerization, albeit to varying degrees. Taken together, our findings provide a comprehensive overview of ARNT PAS-B ligand-binding sites and may guide the development of more potent coactivator inhibitors for cellular and functional studies.

TnP and AHR-CYP1A1 Signaling Crosstalk in an Injury-Induced Zebrafish Inflammation Model

Aryl Hydrocarbon Receptor (AHR) signaling is crucial for regulating the biotransformation of xenobiotics and physiological processes like inflammation and immunity. Meanwhile, Thalassophryne nattereri Peptide (TnP), a promising anti-inflammatory candidate from toadfish venom, demonstrates therapeutic effects through immunomodulation. However, its influence on AHR signaling remains unexplored. This study aimed to elucidate TnP's molecular mechanisms on the AHR-cytochrome P450, family 1 (CYP1) pathway upon injury-induced inflammation in wild-type (WT) and Ahr2-knockdown (KD) zebrafish larvae through transcriptomic analysis and Cyp1a reporters. TnP, while unable to directly activate AHR, potentiated AHR activation by the high-affinity ligand 6-Formylindolo [3,2-b]carbazole (FICZ), implying a role as a CYP1A inhibitor, confirmed by in vitro studies. This interplay suggests TnP's ability to modulate the AHR-CYP1 complex, prompting investigations into its influence on biotransformation pathways and injury-induced inflammation. Here, the inflammation model alone resulted in a significant response on the transcriptome, with most differentially expressed genes (DEGs) being upregulated across the groups. Ahr2-KD resulted in an overall greater number of DEGs, as did treatment with the higher dose of TnP in both WT and KD embryos. Genes related to oxidative stress and inflammatory response were the most apparent under inflamed conditions for both WT and KD groups, e.g., Tnfrsf1a, Irf1b, and Mmp9. TnP, specifically, induces the expression of Hspa5, Hsp90aa1.2, Cxcr3.3, and Mpeg1.2. Overall, this study suggests an interplay between TnP and the AHR-CYP1 pathway, stressing the inflammatory modulation through AHR-dependent mechanisms. Altogether, these results may offer new avenues in novel therapeutic strategies, such as based on natural bioactive molecules, harnessing AHR modulation for targeted and sustained drug effects in inflammatory conditions.

Recent advances in Alzheimer's disease: Mechanisms, clinical trials and new drug development strategies

Alzheimer's disease (AD) stands as the predominant form of dementia, presenting significant and escalating global challenges. Its etiology is intricate and diverse, stemming from a combination of factors such as aging, genetics, and environment. Our current understanding of AD pathologies involves various hypotheses, such as the cholinergic, amyloid, tau protein, inflammatory, oxidative stress, metal ion, glutamate excitotoxicity, microbiota-gut-brain axis, and abnormal autophagy. Nonetheless, unraveling the interplay among these pathological aspects and pinpointing the primary initiators of AD require further elucidation and validation. In the past decades, most clinical drugs have been discontinued due to limited effectiveness or adverse effects. Presently, available drugs primarily offer symptomatic relief and often accompanied by undesirable side effects. However, recent approvals of aducanumab (1) and lecanemab (2) by the Food and Drug Administration (FDA) present the potential in disrease-modifying effects. Nevertheless, the long-term efficacy and safety of these drugs need further validation. Consequently, the quest for safer and more effective AD drugs persists as a formidable and pressing task. This review discusses the current understanding of AD pathogenesis, advances in diagnostic biomarkers, the latest updates of clinical trials, and emerging technologies for AD drug development. We highlight recent progress in the discovery of selective inhibitors, dual-target inhibitors, allosteric modulators, covalent inhibitors, proteolysis-targeting chimeras (PROTACs), and protein-protein interaction (PPI) modulators. Our goal is to provide insights into the prospective development and clinical application of novel AD drugs.

Natural triterpenoid-aided identification of the druggable interface of HMGB1 occupied by TLR4

HMGB1 interacts with TLR4 to activate the inflammatory cascade response, contributing to the pathogenesis of endogenous tissue damage and infection. The immense importance of HMGB1-TLR4 interaction in the immune system has made its binding interface an area of significant interest. To map the binding interface of HMGB1 occupied by TLR4, triterpenoids that disrupt the HMGB1-TLR4 interaction and interfere with HMGB1-induced inflammation were developed. Using the unique triterpenoid PT-22 as a probe along with photoaffinity labeling and site-directed mutagenesis, we found that the binding interface of HMGB1 was responsible for the recognition of TLR4 located on the "L" shaped B-box with K114 as a crucial hot-spot residue. Amazingly, this highly conserved interaction surface overlapped with the antigen-recognition epitope of an anti-HMGB1 antibody. Our findings propose a novel strategy for better understanding the druggable interface of HMGB1 that interacts with TLR4 and provide insights for the rational design of HMGB1-TLR4 PPI inhibitors to fine tune immune responses.

Systematic computational strategies for identifying protein targets and lead discovery

Computational algorithms and tools have retrenched the drug discovery and development timeline. The applicability of computational approaches has gained immense relevance owing to the dramatic surge in the structural information of biomacromolecules and their heteromolecular complexes. Computational methods are now extensively used in identifying new protein targets, druggability assessment, pharmacophore mapping, molecular docking, the virtual screening of lead molecules, bioactivity prediction, molecular dynamics of protein-ligand complexes, affinity prediction, and for designing better ligands. Herein, we provide an overview of salient components of recently reported computational drug-discovery workflows that includes algorithms, tools, and databases for protein target identification and optimized ligand selection.

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.

PNSC928, a plant-derived compound, specifically disrupts CtBP2-p300 interaction and reduces inflammation in mice with acute respiratory distress syndrome

BACKGROUND

Prior research has highlighted the involvement of a transcriptional complex comprising C-terminal binding protein 2 (CtBP2), histone acetyltransferase p300, and nuclear factor kappa B (NF-κB) in the transactivation of proinflammatory cytokine genes, contributing to inflammation in mice with acute respiratory distress syndrome (ARDS). Nonetheless, it remains uncertain whether the therapeutic targeting of the CtBP2-p300-NF-κB complex holds potential for ARDS suppression.

METHODS

An ARDS mouse model was established using lipopolysaccharide (LPS) exposure. RNA-Sequencing (RNA-Seq) was performed on ARDS mice and LPS-treated cells with CtBP2, p300, and p65 knockdown. Small molecules inhibiting the CtBP2-p300 interaction were identified through AlphaScreen. Gene and protein expression levels were quantified using RT-qPCR and immunoblots. Tissue damage was assessed via histological staining.

KEY FINDINGS

We elucidated the specific role of the CtBP2-p300-NF-κB complex in proinflammatory gene regulation. RNA-seq analysis in LPS-challenged ARDS mice and LPS-treated CtBP2-knockdown (CtBP2KD), p300KD, and p65KD cells revealed its significant impact on proinflammatory genes with minimal effects on other NF-κB targets. Commercial inhibitors for CtBP2, p300, or NF-κB exhibited moderate cytotoxicity in vitro and in vivo, affecting both proinflammatory genes and other targets. We identified a potent inhibitor, PNSC928, for the CtBP2-p300 interaction using AlphaScreen. PNSC928 treatment hindered the assembly of the CtBP2-p300-NF-κB complex, substantially downregulating proinflammatory cytokine gene expression without observable cytotoxicity in normal cells. In vivo administration of PNSC928 significantly reduced CtBP2-driven proinflammatory gene expression in ARDS mice, alleviating inflammation and lung injury, ultimately improving ARDS prognosis.

CONCLUSION

Our results position PNSC928 as a promising therapeutic candidate to specifically target the CtBP2-p300 interaction and mitigate inflammation in ARDS management.

Identification of Small Molecule Ligand Binding Sites On and In the ARNT PAS-B Domain

Transcription factors are generally challenging to target with small molecule inhibitors due to their structural plasticity and lack of catalytic sites. Notable exceptions include several naturally ligand-regulated transcription factors, including our prior work with the heterodimeric HIF-2 transcription factor which showed that small molecule binding within an internal pocket of the HIF-2α PAS-B domain can disrupt its interactions with its dimerization partner, ARNT. Here, we explore the feasibility of similarly targeting small molecules to the analogous ARNT PAS-B domain itself, potentially opening a promising route to simultaneously modulate several ARNT-mediated signaling pathways. Using solution NMR screening of an in-house fragment library, we previously identified several compounds that bind ARNT PAS-B and, in certain cases, antagonize ARNT association with the TACC3 transcriptional coactivator. However, these ligands have only modest binding affinities, complicating characterization of their binding sites. We address this challenge by combining NMR, MD simulations, and ensemble docking to identify ligand-binding 'hotspots' on and within the ARNT PAS-B domain. Our data indicate that the two ARNT/TACC3 inhibitors, KG-548 and KG-655, bind to a β-sheet surface implicated in both HIF-2 dimerization and coactivator recruitment. Furthermore, while KG-548 binds exclusively to the β-sheet surface, KG-655 can additionally bind within a water-accessible internal cavity in ARNT PAS-B. Finally, KG-279, while not a coactivator inhibitor, exemplifies ligands that preferentially bind only to the internal cavity. All three ligands promoted ARNT PAS-B homodimerization, albeit to varying degrees. Taken together, our findings provide a comprehensive overview of ARNT PAS-B ligand-binding sites and may guide the development of more potent coactivator inhibitors for cellular and functional studies.

Molecular regulation of PPARγ/RXRα signaling by the novel cofactor ZFP407

Cofactors interacting with PPARγ can regulate adipogenesis and adipocyte metabolism by modulating the transcriptional activity and selectivity of PPARγ signaling. ZFP407 was previously demonstrated to regulate PPARγ target genes such as GLUT4, and its overexpression improved glucose homeostasis in mice. Here, using a series of molecular assays, including protein-interaction studies, mutagenesis, and ChIP-seq, ZFP407 was found to interact with the PPARγ/RXRα protein complex in the nucleus of adipocytes. Consistent with this observation, ZFP407 ChIP-seq peaks significantly overlapped with PPARγ ChIP-seq peaks, with more than half of ZFP407 peaks overlapping with PPARγ peaks. Transcription factor binding motifs enriched in these overlapping sites included CTCF, RARα/RXRγ, TP73, and ELK1, which regulate cellular development and function within adipocytes. Site-directed mutagenesis of frequent PPARγ phosphorylation or SUMOylation sites did not prevent its regulation by ZFP407, while mutagenesis of ZFP407 domains potentially necessary for RXR and PPARγ binding abrogated any impact of ZFP407 on PPARγ activity. These data suggest that ZFP407 controls the activity of PPARγ, but does so independently of post-translational modifications, likely by direct binding, establishing ZFP407 as a newly identified PPARγ cofactor. In addition, ZFP407 ChIP-seq analyses identified regions that did not overlap with PPARγ peaks. These non-overlapping peaks were significantly enriched for the transcription factor binding motifs of TBX19, PAX8, HSF4, and ZKSCAN3, which may contribute to the PPARγ-independent functions of ZFP407 in adipocytes and other cell types.

α-Hydrazino Acid Insertion Governs Peptide Organization in Solution by Local Structure Ordering

In this work, we have applied the concept of α-hydrazino acid insertion in a peptide sequence as a means of structurally organizing a potential protein-protein interactions (PPI) inhibitor. Hydrazino peptides characterized by the incorporation of an α-hydrazino acid at specific positions introduce an additional nitrogen atom into their backbone. This modification leads to a change in the electrostatic properties of the peptide and induces the restructuring of its hydrogen bonding network, resulting in conformational changes toward more stable structural motifs. Despite the successful use of synthetic hydrazino oligomers in binding to nucleic acids, the structural changes due to the incorporation of α-hydrazino acid into short natural peptides in solution are still poorly understood. Based on NMR data, we report structural models of p53-derived hydrazino peptides with elements of localized peptide structuring in the form of an α-, β-, or γ-turn as a result of hydrazino modification in the peptide backbone. The modifications could potentially lead to the preorganization of a helical secondary peptide structure in a solution that is favorable for binding to a biological receptor. Spectroscopically, we observed that the ensemble averaged rapidly interconverting conformations, including isomerization of the E-Z hydrazide bond. This further increases the adaptability by expanding the conformational space of hydrazine peptides as potential protein-protein interaction antagonists.

Protein mimetic 2D FAST rescues alpha synuclein aggregation mediated early and post disease Parkinson's phenotypes

Abberent protein-protein interactions potentiate many diseases and one example is the toxic, self-assembly of α-Synuclein in the dopaminergic neurons of patients with Parkinson's disease; therefore, a potential therapeutic strategy is the small molecule modulation of α-Synuclein aggregation. In this work, we develop an Oligopyridylamide based 2-dimensional Fragment-Assisted Structure-based Technique to identify antagonists of α-Synuclein aggregation. The technique utilizes a fragment-based screening of an extensive array of non-proteinogenic side chains in Oligopyridylamides, leading to the identification of NS132 as an antagonist of the multiple facets of α-Synuclein aggregation. We further identify a more cell permeable analog (NS163) without sacrificing activity. Oligopyridylamides rescue α-Synuclein aggregation mediated Parkinson's disease phenotypes in dopaminergic neurons in early and post disease Caenorhabditis elegans models. We forsee tremendous potential in our technique to identify lead therapeutics for Parkinson's disease and other diseases as it is expandable to other oligoamide scaffolds and a larger array of side chains.

An Update on Protein Kinases as Therapeutic Targets-Part II: Peptides as Allosteric Protein Kinase C Modulators Targeting Protein-Protein Interactions

Human protein kinases are highly-sought-after drug targets, historically harnessed for treating cancer, cardiovascular disease, and an increasing number of autoimmune and inflammatory conditions. Most current treatments involve small molecule protein kinase inhibitors that interact orthosterically with the protein kinase ATP-binding pocket. As a result, these compounds are often poorly selective and highly toxic. Part I of this series reviews the role of PKC isoforms in various human diseases, featuring cancer and cardiovascular disease, as well as translational examples of PKC modulation applied to human health and disease. In the present Part II, we discuss alternative allosteric binding mechanisms for targeting PKC, as well as novel drug platforms, such as modified peptides. A major goal is to design protein kinase modulators with enhanced selectivity and improved pharmacological properties. To this end, we use molecular docking analysis to predict the mechanisms of action for inhibitor-kinase interactions that can facilitate the development of next-generation PKC modulators.

In vivo mapping of protein-protein interactions of schizophrenia risk factors generates an interconnected disease network

Genetic analyses of Schizophrenia (SCZ) patients have identified thousands of risk factors. In silico protein-protein interaction (PPI) network analysis has provided strong evidence that disrupted PPI networks underlie SCZ pathogenesis. In this study, we performed in vivo PPI analysis of several SCZ risk factors in the rodent brain. Using endogenous antibody immunoprecipitations coupled to mass spectrometry (MS) analysis, we constructed a SCZ network comprising 1612 unique PPI with a 5% FDR. Over 90% of the PPI were novel, reflecting the lack of previous PPI MS studies in brain tissue. Our SCZ PPI network was enriched with known SCZ risk factors, which supports the hypothesis that an accumulation of disturbances in selected PPI networks underlies SCZ. We used Stable Isotope Labeling in Mammals (SILAM) to quantitate phencyclidine (PCP) perturbations in the SCZ network and found that PCP weakened most PPI but also led to some enhanced or new PPI. These findings demonstrate that quantitating PPI in perturbed biological states can reveal alterations to network biology.

Modular Nanotransporters Delivering Biologically Active Molecules to the Surface of Mitochondria

Treatment of various diseases, in particular cancer, usually requires the targeting of biologically active molecules at a selected subcellular compartment. We modified our previously developed modular nanotransporters (MNTs) for targeting mitochondria. The new MNTs are capable of binding to the protein predominantly localized on the outer mitochondrial membrane, Keap1. These MNTs possessing antiKeap1 monobody co-localize with mitochondria upon addition to the cells. They efficiently interact with Keap1 both in solution and within living cells. A conjugate of the MNT with a photosensitizer, chlorin e6, demonstrated significantly higher photocytotoxicity than chlorin e6 alone. We assume that MNTs of this kind can improve efficiency of therapeutic photosensitizers and radionuclides emitting short-range particles.

Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications

Small molecules have been providing medical breakthroughs for human diseases for more than a century. Recently, identifying small molecule inhibitors that target microRNAs (miRNAs) has gained importance, despite the challenges posed by labour-intensive screening experiments and the significant efforts required for medicinal chemistry optimization. Numerous experimentally-verified cases have demonstrated the potential of miRNA-targeted small molecule inhibitors for disease treatment. This new approach is grounded in their posttranscriptional regulation of the expression of disease-associated genes. Reversing dysregulated gene expression using this mechanism may help control dysfunctional pathways. Furthermore, the ongoing improvement of algorithms has allowed for the integration of computational strategies built on top of laboratory-based data, facilitating a more precise and rational design and discovery of lead compounds. To complement the use of extensive pharmacogenomics data in prioritising potential drugs, our previous work introduced a computational approach based on only molecular sequences. Moreover, various computational tools for predicting molecular interactions in biological networks using similarity-based inference techniques have been accumulated in established studies. However, there are a limited number of comprehensive reviews covering both computational and experimental drug discovery processes. In this review, we outline a cohesive overview of both biological and computational applications in miRNA-targeted drug discovery, along with their disease implications and clinical significance. Finally, utilizing drug-target interaction (DTIs) data from DrugBank, we showcase the effectiveness of deep learning for obtaining the physicochemical characterization of DTIs.

Peptide Stapling Applied to Antimicrobial Peptides

Antimicrobial peptides (AMPs) are considered a promising therapeutic approach against multi-drug resistant microorganisms. Besides their advantages, there are limitations to be overcome so that these molecules can become market competitive. One of the biggest limitations is proteolytic susceptibility, which could be overcome by structural modifications such as cyclization, especially for helix-constraining strategies. Over the years, many helix stabilization techniques have arisen, such as lactam-bridging, triazole-based, N-alkylation and all-hydrocarbon stapling. All-hydrocarbon stapling takes advantage of modified amino acid residues and olefinic cross-linking to constrain peptide helices. Despite being a well-established strategy and presenting efficient stability results, there are different limitations especially related to toxicity. In this review, recent studies on stapled AMPs for antimicrobial usage are explored with the aim of understanding the future of these molecules as putative antimicrobial agents.

Spatial Layouts of Low-Entropy Hydration Shells Guide Protein Binding

Protein-protein binding enables orderly biological self-organization and is therefore considered a miracle of nature. Protein‒protein binding is driven by electrostatic forces, hydrogen bonding, van der Waals force, and hydrophobic interactions. Among these physical forces, only hydrophobic interactions can be considered long-range intermolecular attractions between proteins due to the electrostatic shielding of surrounding water molecules. Low-entropy hydration shells around proteins drive hydrophobic attraction among them that essentially coordinate protein‒protein binding. Here, an innovative method is developed for identifying low-entropy regions of hydration shells of proteins by screening off pseudohydrophilic groups on protein surfaces and revealing that large low-entropy regions of the hydration shells typically cover the binding sites of individual proteins. According to an analysis of determined protein complex structures, shape matching between a large low-entropy hydration shell region of a protein and that of its partner at the binding sites is revealed as a universal law. Protein‒protein binding is thus found to be mainly guided by hydrophobic collapse between the shape-matched low-entropy hydration shells that is verified by bioinformatics analyses of hundreds of structures of protein complexes, which cover four test systems. A simple algorithm is proposed to accurately predict protein binding sites.

"Common-Precursor" Protein Mimetic Approach to Rescue Aβ Aggregation-Mediated Alzheimer's Phenotypes

Abberent protein-protein interactions (aPPIs) are associated with an array of pathological conditions, which make them important therapeutic targets. The aPPIs are mediated via specific chemical interactions that spread over a large and hydrophobic surface. Therefore, ligands that can complement the surface topography and chemical fingerprints could manipulate aPPIs. Oligopyridylamides (OPs) are synthetic protein mimetics that have been shown to manipulate aPPIs. However, the previous OP library used to disrupt these aPPIs was moderate in number (∼30 OPs) with very limited chemical diversity. The onus is on the laborious and time-consuming synthetic pathways with multiple chromatography steps. We have developed a novel chromatography-free technique to synthesize a highly diverse chemical library of OPs using a "common-precursor" approach. We significantly expanded the chemical diversity of OPs using a chromatography-free high-yielding method. To validate our novel approach, we have synthesized an OP with identical chemical diversity to a pre-existing OP-based potent inhibitor of Aβ aggregation, a process central to Alzheimer's disease (AD). The newly synthesized OP ligand (RD242) was very potent in inhibiting Aβ aggregation and rescuing AD phenotypes in an in vivo model. Moreover, RD242 was very effective in rescuing AD phenotypes in a post-disease onset AD model. We envision that our "common-precursor" synthetic approach will have tremendous potential as it is expandable for other oligoamide scaffolds to enhance affinity for disease-relevant targets.

A Systematic Approach to the Discovery of Protein-Protein Interaction Stabilizers

Dysregulation of protein-protein interactions (PPIs) commonly leads to disease. PPI stabilization has only recently been systematically explored for drug discovery despite being a powerful approach to selectively target intrinsically disordered proteins and hub proteins, like 14-3-3, with multiple interaction partners. Disulfide tethering is a site-directed fragment-based drug discovery (FBDD) methodology for identifying reversibly covalent small molecules. We explored the scope of disulfide tethering for the discovery of selective PPI stabilizers (molecular glues) using the hub protein 14-3-3σ. We screened complexes of 14-3-3 with 5 biologically and structurally diverse phosphopeptides derived from the 14-3-3 client proteins ERα, FOXO1, C-RAF, USP8, and SOS1. Stabilizing fragments were found for 4/5 client complexes. Structural elucidation of these complexes revealed the ability of some peptides to conformationally adapt to make productive interactions with the tethered fragments. We validated eight fragment stabilizers, six of which showed selectivity for one phosphopeptide client, and structurally characterized two nonselective hits and four fragments that selectively stabilized C-RAF or FOXO1. The most efficacious fragment increased 14-3-3σ/C-RAF phosphopeptide affinity by 430-fold. Disulfide tethering to the wildtype C38 in 14-3-3σ provided diverse structures for future optimization of 14-3-3/client stabilizers and highlighted a systematic method to discover molecular glues.

Predicting Protein-Peptide Interactions: Benchmarking Deep Learning Techniques and a Comparison with Focused Docking

The accurate prediction of protein structures achieved by deep learning (DL) methods is a significant milestone and has deeply impacted structural biology. Shortly after its release, AlphaFold2 has been evaluated for predicting protein-peptide interactions and shown to significantly outperform RoseTTAfold as well as a conventional blind docking method: PIPER-FlexPepDock. Since then, new AlphaFold2 models, trained specifically to predict multimeric assemblies, have been released and a new ab initio folding model OmegaFold has become available. Here, we assess docking success rates for these new DL folding models and compare their performance with our state-of-the-art, focused peptide-docking software AutoDock CrankPep (ADCP). The evaluation is done using the same dataset and performance metric for all methods. We show that, for a set of 99 nonredundant protein-peptide complexes, the new AlphaFold2 model outperforms other Deep Learning approaches and achieves remarkable docking success rates for peptides. While the docking success rate of ADCP is more modest when considering the top-ranking solution only, it samples correct solutions for around 62% of the complexes. Interestingly, different methods succeed on different complexes, and we describe a consensus docking approach using ADCP and AlphaFold2, which achieves a remarkable 60% for the top-ranking results and 66% for the top 5 results for this set of 99 protein-peptide complexes.

Proteolysis-targeting chimeras in biotherapeutics: Current trends and future applications

The success of inhibitor-based therapeutics is largely constrained by the acquisition of therapeutic resistance, which is partially driven by the undruggable proteome. The emergence of proteolysis targeting chimera (PROTAC) technology, designed for degrading proteins involved in specific biological processes, might provide a novel framework for solving the above constraint. A heterobifunctional PROTAC molecule could structurally connect an E3 ubiquitin ligase ligand with a protein of interest (POI)-binding ligand by chemical linkers. Such technology would result in the degradation of the targeted protein via the ubiquitin-proteasome system (UPS), opening up a novel way of selectively inhibiting undruggable proteins. Herein, we will highlight the advantages of PROTAC technology and summarize the current understanding of the potential mechanisms involved in biotherapeutics, with a particular focus on its application and development where therapeutic benefits over classical small-molecule inhibitors have been achieved. Finally, we discuss how this technology can contribute to developing biotherapeutic drugs, such as antivirals against infectious diseases, for use in clinical practices.

The DarT/DarG Toxin-Antitoxin ADP-Ribosylation System as a Novel Target for a Rational Design of Innovative Antimicrobial Strategies

The chemical modification of cellular macromolecules by the transfer of ADP-ribose unit(s), known as ADP-ribosylation, is an ancient homeostatic and stress response control system. Highly conserved across the evolution, ADP-ribosyltransferases and ADP-ribosylhydrolases control ADP-ribosylation signalling and cellular responses. In addition to proteins, both prokaryotic and eukaryotic transferases can covalently link ADP-ribosylation to different conformations of nucleic acids, thus highlighting the evolutionary conservation of archaic stress response mechanisms. Here, we report several structural and functional aspects of DNA ADP-ribosylation modification controlled by the prototype DarT and DarG pair, which show ADP-ribosyltransferase and hydrolase activity, respectively. DarT/DarG is a toxin-antitoxin system conserved in many bacterial pathogens, for example in Mycobacterium tuberculosis, which regulates two clinically important processes for human health, namely, growth control and the anti-phage response. The chemical modulation of the DarT/DarG system by selective inhibitors may thus represent an exciting strategy to tackle resistance to current antimicrobial therapies.

How to Design Peptides

Novel design of proteins to target receptors for treatment or tissue augmentation has come to the fore owing to advancements in computing power, modeling frameworks, and translational successes. Shorter proteins, or peptides, can offer combinatorial synergies with dendrimer, polymer, or other peptide carriers for enhanced local signaling, which larger proteins may sterically hinder. Here, we present a generalized method for designing a novel peptide. We first show how to create a script protocol that can be used to iteratively optimize and screen novel peptide sequences for binding a target protein. We present a step-by-step introduction to utilizing file repositories, data bases, and the Rosetta software suite. RosettaScripts, an .xml interface that allows for sequential functions to be performed, is used to order the functions for repeatable performance. These strategies may lead to more groups venturing into computational design, which may result in synergies from artificial intelligence/machine learning (AI/ML) to phage display and screening. Importantly, the beginner is expected to be able to design their first peptide ligand and begin their journey in peptide drug discovery. Generally, these peptides potentially could be used to interact with any enzyme or receptor, for example, in the study of chemokines and their interactions with glycosoaminoglycans and their receptors.

Identification of a binding site on soluble RANKL that can be targeted to inhibit soluble RANK-RANKL interactions and treat osteoporosis

One of the major challenges for discovering protein-protein interaction inhibitors is identifying selective and druggable binding sites at the protein surface. Here, we report an approach to identify a small molecular binding site to selectively inhibit the interaction of soluble RANKL and RANK for designing anti-osteoporosis drugs without undesirable immunosuppressive effects. Through molecular dynamic simulations, we discovered a binding site that allows a small molecule to selectively interrupt soluble RANKL-RANK interaction and without interfering with the membrane RANKL-RANK interaction. We describe a highly potent inhibitor, S3-15, and demonstrate its specificity to inhibit the soluble RANKL-RANK interaction with in vitro and in vivo studies. S3-15 exhibits anti-osteoporotic effects without causing immunosuppression. Through in silico and in vitro experiments we further confirm the binding model of S3-15 and soluble RANKL. This work might inspire structure-based drug discovery for targeting protein-protein interactions.

Des3PI: a fragment-based approach to design cyclic peptides targeting protein-protein interactions

Protein-protein interactions (PPIs) play crucial roles in many cellular processes and their deregulation often leads to cellular dysfunctions. One promising way to modulate PPIs is to use peptide derivatives that bind their protein target with high affinity and high specificity. Peptide modulators are often designed using secondary structure mimics. However, fragment-based design is an alternative emergent approach in the PPI field. Most of the reported computational fragment-based libraries targeting PPIs are composed of small molecules or already approved drugs, but, according to our knowledge, no amino acid based library has been reported yet. In this context, we developed a novel fragment-based approach called Des3PI (design of peptides targeting protein-protein interactions) with a library composed of natural amino acids. All the amino acids are docked into the target surface using Autodock Vina. The resulting binding modes are geometrically clustered, and, in each cluster, the most recurrent amino acids are identified and form the hotspots that will compose the designed peptide. This approach was applied on Ras and Mcl-1 proteins, as well as on A[Formula: see text] protofibril. For each target, at least five peptides generated by Des3PI were tested in silico: the peptides were first blindly docked on their target, and then, the stability of the successfully docked complexes was verified using 200 ns MD simulations. Des3PI shows very encouraging results by yielding at least 3 peptides for each protein target that succeeded in passing the two-step assessment.

Targeting the N-Terminus Domain of the Coronavirus Nucleocapsid Protein Induces Abnormal Oligomerization via Allosteric Modulation

Epidemics caused by coronaviruses (CoVs), namely the severe acute respiratory syndrome (SARS) (2003), Middle East respiratory syndrome (MERS) (2012), and coronavirus disease 2019 (COVID-19) (2019), have triggered a global public health emergency. Drug development against CoVs is inherently arduous. The nucleocapsid (N) protein forms an oligomer and facilitates binding with the viral RNA genome, which is critical in the life cycle of the virus. In the current study, we found a potential allosteric site (Site 1) using PARS, an online allosteric site predictor, in the CoV N-N-terminal RNA-binding domain (NTD) to modulate the N protein conformation. We identified 5-hydroxyindole as the lead via molecular docking to target Site 1. We designed and synthesized four 5-hydroxyindole derivatives, named P4-1 to P4-4, based on the pose of 5-hydroxyindole in the docking model complex. Small-angle X-ray scattering (SAXS) data indicate that two 5-hydroxyindole compounds with higher hydrophobic R-groups mediate the binding between N-NTD and N-C-terminal dimerization domain (CTD) and elicit high-order oligomerization of the whole N protein. Furthermore, the crystal structures suggested that these two compounds act on this novel cavity and create a flat surface with higher hydrophobicity, which may mediate the interaction between N-NTD and N-CTD. Taken together, we discovered an allosteric binding pocket targeting small molecules that induces abnormal aggregation of the CoV N protein. These novel concepts will facilitate protein-protein interaction (PPI)-based drug design against various CoVs.

Structure-Activity Relationship of Benzofuran Derivatives with Potential Anticancer Activity

Benzofuran is a heterocyclic compound found naturally in plants and it can also be obtained through synthetic reactions. Multiple physicochemical characteristics and versatile features distinguish benzofuran, and its chemical structure is composed of fused benzene and furan rings. Benzofuran derivatives are essential compounds that hold vital biological activities to design novel therapies with enhanced efficacy compared to conventional treatments. Therefore, medicinal chemists used its core to synthesize new derivatives that can be applied to a variety of disorders. Benzofuran exhibited potential effectiveness in chronic diseases such as hypertension, neurodegenerative and oxidative conditions, and dyslipidemia. In acute infections, benzofuran revealed anti-infective properties against microorganisms like viruses, bacteria, and parasites. In recent years, the complex nature and the number of acquired or resistant cancer cases have been largely increasing. Benzofuran derivatives revealed potential anticancer activity with lower incidence or severity of adverse events normally encountered during chemotherapeutic treatments. This review discusses the structure-activity relationship (SAR) of several benzofuran derivatives in order to elucidate the possible substitution alternatives and structural requirements for a highly potent and selective anticancer activity.

Computational Tools and Strategies to Develop Peptide-Based Inhibitors of Protein-Protein Interactions

Protein-protein interactions play crucial and subtle roles in many biological processes and modifications of their fine mechanisms generally result in severe diseases. Peptide derivatives are very promising therapeutic agents for modulating protein-protein associations with sizes and specificities between those of small compounds and antibodies. For the same reasons, rational design of peptide-based inhibitors naturally borrows and combines computational methods from both protein-ligand and protein-protein research fields. In this chapter, we aim to provide an overview of computational tools and approaches used for identifying and optimizing peptides that target protein-protein interfaces with high affinity and specificity. We hope that this review will help to implement appropriate in silico strategies for peptide-based drug design that builds on available information for the systems of interest.

Deep Sequencing of a Systematic Peptide Library Reveals Conformationally-Constrained Protein Interface Peptides that Disrupt a Protein-Protein Interaction

Disrupting protein-protein interactions is difficult due to the large and flat interaction surfaces of the binding partners. The BLIP and BLIP-II proteins are unrelated in sequence and structure and yet each potently inhibit β-lactamases. High-throughput oligonucleotide synthesis was used to construct a 12,470-member library containing overlapping linear and cyclic peptides ranging in size from 6 to 21 amino acids that scan through the sequences of BLIP and BLIP-II. Phage display affinity selections and deep sequencing revealed that, despite the differences in interaction surfaces with β-lactamases, rapid enrichment of consensus peptide regions originating from both BLIP and BLIP-II contact residues in the binding interface occurred. BLIP and BLIP-II peptides that were enriched by affinity selection were shown to bind β-lactamases and disrupt the BLIP/β-lactamase interaction. The results suggest that peptides that bind at and disrupt PPI interfaces can be identified through systematic peptide library construction, affinity selection, and deep sequencing.

Nanorepairers Rescue Inflammation-Induced Mitochondrial Dysfunction in Mesenchymal Stem Cells

Mitochondrial dysfunction in tissue-specific mesenchymal stem cells (MSCs) plays a critical role in cell fate and the morbidity of chronic inflammation-associated bone diseases, such as periodontitis and osteoarthritis. However, there is still no effective method to cure chronic inflammation-associated bone diseases by physiologically restoring the function of mitochondria and MSCs. Herein, it is first found that chronic inflammation leads to excess Ca2+ transfer from the endoplasmic reticulum to mitochondria, which causes mitochondrial calcium overload and further damage to mitochondria. Furthermore, damaged mitochondria continuously accumulate in MSCs due to the inhibition of mitophagy by activating the Wnt/β-catenin pathway under chronic inflammatory conditions, impairing the differentiation of MSCs. Based on the mechanistic discovery, intracellular microenvironment (esterase and low pH)-responsive nanoparticles are fabricated to capture Ca2+ around mitochondria in MSCs to regulate MSC mitochondrial calcium flux against mitochondrial dysfunction. Furthermore, the same nanoparticles are able to deliver siRNA to MSCs to inhibit the Wnt/β-catenin pathway and regulate mitophagy of the originally dysfunctional mitochondria. These precision-engineered nanoparticles, referred to as "nanorepairers," physiologically restore the function of mitochondria and MSCs, resulting in effective therapy for periodontitis and osteoarthritis. The concept can potentially be expanded to the treatment of other diseases via mitochondrial quality control intervention.

Modeling the MreB-CbtA Interaction to Facilitate the Prediction and Design of Candidate Antibacterial Peptides

Protein-protein interactions (PPIs) have emerged as promising targets for PPI modulators as alternative drugs because they are essential for most biochemical processes in living organisms. In recent years, a spotlight has been put on the development of peptide-based PPI inhibitors as the next-generation therapeutics to combat antimicrobial resistance taking cognizance of protein-based PPI-modulators that interact with target proteins to inhibit function. Although protein-based PPI inhibitors are not effective therapeutic agents because of their high molecular weights, they could serve as sources for peptide-based pharmaceutics if the target-inhibitor complex is accessible and well characterized. The Escherichia coli (E. coli) toxin protein, CbtA, has been identified as a protein-based PPI modulator that binds to the bacterial actin homolog MreB leading to the perturbation of its polymerization dynamics; and consequently has been suggested to have antibacterial properties. Unfortunately, however, the three-dimensional structures of CbtA and the MreB-CbtA complex are currently not available to facilitate the optimization process of the pharmacological properties of CbtA. In this study, computer modeling strategies were used to predict key MreB-CbtA interactions to facilitate the design of antiMreB peptide candidates. A model of the E. coli CbtA was built using the trRosetta software and its stability was assessed through molecular dynamics (MD) simulations. The modeling and simulations data pointed to a model with reasonable quality and stability. Also, the HADDOCK software was used to predict a possible MreB-CbtA complex, which was characterized through MD simulations and compared with MreB-MreB dimmer. The results suggest that CbtA inhibits MreB through the competitive mechanism whereby CbtA competes with MreB monomers for the interprotofilament interface leading to interference with double protofilament formation. Additionally, by using the antiBP software to predict antibacterial peptides in CbtA, and the MreB-CbtA complex as the reference structure to determine important interactions and contacts, candidate antiMreB peptides were suggested. The peptide sequences could be useful in a rational antimicrobial peptide hybridization strategy to design novel antibiotics. All-inclusive, the data reveal the molecular basis of MreB inhibition by CbtA and can be incorporated in the design/development of the next-generation antibacterial peptides targeting MreB.

Peptide Tethering: Pocket-Directed Fragment Screening for Peptidomimetic Inhibitor Discovery

Constrained peptides have proven to be a rich source of ligands for protein surfaces, but are often limited in their binding potency. Deployment of nonnatural side chains that access unoccupied crevices on the receptor surface offers a potential avenue to enhance binding affinity. We recently described a computational approach to create topographic maps of protein surfaces to guide the design of nonnatural side chains [J. Am. Chem. Soc. 2017, 139, 15560]. The computational method, AlphaSpace, was used to predict peptide ligands for the KIX domain of the p300/CBP coactivator. KIX has been the subject of numerous ligand discovery strategies, but potent inhibitors of its interaction with transcription factors remain difficult to access. Although the computational approach provided a significant enhancement in the binding affinity of the peptide, fine-tuning of nonnatural side chains required an experimental screening method. Here we implement a peptide-tethering strategy to screen fragments as nonnatural side chains on conformationally defined peptides. The combined computational-experimental approach offers a general framework for optimizing peptidomimetics as inhibitors of protein-protein interactions.

Rapid de novo discovery of peptidomimetic affinity reagents for human angiotensin converting enzyme 2

Rapid discovery and development of serum-stable, selective, and high affinity peptide-based binders to protein targets are challenging. Angiotensin converting enzyme 2 (ACE2) has recently been identified as a cardiovascular disease biomarker and the primary receptor utilized by the severe acute respiratory syndrome coronavirus 2. In this study, we report the discovery of high affinity peptidomimetic binders to ACE2 via affinity selection-mass spectrometry (AS-MS). Multiple high affinity ACE2-binding peptides (ABP) were identified by selection from canonical and noncanonical peptidomimetic libraries containing 200 million members (dissociation constant, K_D = 19-123 nM). The most potent noncanonical ACE2 peptide binder, ABP N1 (K_D = 19 nM), showed enhanced serum stability in comparison with the most potent canonical binder, ABP C7 (K_D = 26 nM). Picomolar to low nanomolar ACE2 concentrations in human serum were detected selectively using ABP N1 in an enzyme-linked immunosorbent assay. The discovery of serum-stable noncanonical peptidomimetics like ABP N1 from a single-pass selection demonstrates the utility of advanced AS-MS for accelerated development of affinity reagents to protein targets.

Peptides and peptidomimetics as therapeutic agents for Covid-19

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) Covid-19 pandemic has caused high morbidity and mortality rates worldwide. Virus entry into cells can be blocked using several strategies, including inhibition of protein-protein interactions (PPIs) between the viral spike glycoprotein and cellular receptors, as well as blocking of spike protein conformational changes that are required for cleavage/activation and fusogenicity. The spike-mediated viral attachment and entry into cells via fusion of the viral envelope with cellular membranes involve PPIs mediated by short peptide fragments exhibiting particular secondary structures. Thus, peptides that can inhibit these PPIs may be used as potential antiviral agents preventing virus entry and spread. This review is focused on peptides and peptidomimetics as PPI modulators and protease inhibitors against SARS-CoV-2.

Probing GPCR Dimerization Using Peptides

G protein-coupled receptors (GPCRs) are the largest class of membrane proteins and the most common and extensively studied pharmacological target. Numerous studies over the last decade have confirmed that GPCRs do not only exist and function in their monomeric form but in fact, have the ability to form dimers or higher order oligomers with other GPCRs, as well as other classes of receptors. GPCR oligomers have become increasingly attractive to investigate as they have the ability to modulate the pharmacological responses of the receptors which in turn, could have important functional roles in diseases, such as cancer and several neurological & neuropsychiatric disorders. Despite the growing evidence in the field of GPCR oligomerisation, the lack of structural information, as well as targeting the 'undruggable' protein-protein interactions (PPIs) involved in these complexes, has presented difficulties. Outside the field of GPCRs, targeting PPIs has been widely studied, with a variety of techniques being investigated; from small-molecule inhibitors to disrupting peptides. In this review, we will demonstrate several physiologically relevant GPCR dimers and discuss an array of strategies and techniques that can be employed when targeting these complexes, as well as provide ideas for future development.

Targeting ER-Mitochondria Signaling as a Therapeutic Target for Frontotemporal Dementia and Related Amyotrophic Lateral Sclerosis

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are two major neurodegenerative diseases. FTD is the second most common cause of dementia and ALS is the most common form of motor neuron disease. These diseases are now known to be linked. There are no cures or effective treatments for FTD or ALS and so new targets for therapeutic intervention are required but this is hampered by the large number of physiological processes that are damaged in FTD/ALS. Many of these damaged functions are now known to be regulated by signaling between the endoplasmic reticulum (ER) and mitochondria. This signaling is mediated by "tethering" proteins that serve to recruit ER to mitochondria. One tether strongly associated with FTD/ALS involves an interaction between the ER protein VAPB and the mitochondrial protein PTPIP51. Recent studies have shown that ER-mitochondria signaling is damaged in FTD/ALS and that this involves breaking of the VAPB-PTPIP51 tethers. Correcting disrupted tethering may therefore correct many other downstream damaged features of FTD/ALS. Here, we review progress on this topic with particular emphasis on targeting of the VAPB-PTPIP51 tethers as a new drug target.

Split-enzyme immunoassay to monitor EGFR-HER2 heterodimerization on cell surfaces

Over 30,000 protein-protein interactions with pathological implications have been identified; yet, discovering and investigating drugs that target these specific interactions is greatly limited by the inability to monitor native protein-protein interactions (PPIs) efficiently. The two most frequently used tools to monitor PPIs, resonance-energy transfer (RET) assays and protein complementation assays (PCA), face significant limitations. RET assays have a narrow working range of 10 to 50 Å, while PCA require permanent attachment of a reporter probe to a protein of interest by chemical conjugation or genetic engineering. We developed a non-invasive assay platform to measure PPIs without modifications to the proteins of interest and is functional at a greater working range than RET assays. We demonstrate our approach by monitoring the EGFR-HER2 heterodimerization on relevant cell surfaces, utilizing various EGFR- and HER2-specific binders (e.g., Fab, DARPin, and VHH) fused with small fragments of a tri-part split-luciferase derived from NanoLuc®. Following independent binding of the binder fusions to their respective targets, the dimerization of EGFR and HER2 induces complementation of the luciferase fragments into a functional native structure, producing glow-type luminescence. We have confirmed the functionality of the platform to monitor EGFR-HER2 dimerization induction and inhibition. STATEMENT OF SIGNIFICANCE: We describe a platform technology for rapid monitoring of protein-protein interactions (PPIs). Our approach is uses a luciferase split into three parts - two short peptide "tags" and a large third fragment. Each of the short peptides can be fused to antibodies which bind to domains of a target antigens which orients the two tags and facilitates refolding of an active enzyme. To our knowledge this is the first example of a split-enzyme used to monitor PPIs without requiring any modification of the target proteins. We demonstrate our approach on the important PPI of HER2 and EGFR. Significantly, we quantify stimulation and inhibition of these partners, opening the possibility of using our approach to assess potential drugs without engineering cells.

Identification of Secondary Binding Sites on Protein Surfaces for Rational Elaboration of Synthetic Protein Mimics

Minimal mimics of protein conformations provide rationally designed ligands to modulate protein function. The advantage of minimal mimics is that they can be chemically synthesized and coaxed to be proteolytically resistant; a key disadvantage is that minimization of the protein binding epitope may be associated with loss of affinity and specificity. Several approaches to overcome this challenge may be envisioned, including deployment of covalent warheads and use of nonnatural residues to improve contacts with the binding surface. Herein, we describe our computational and experimental efforts to enhance the minimal protein mimics with fragments that can contact undiscovered binding pockets on Mdm2 and MdmX-two well-studied protein partners of p53.

Improving Docking Power for Short Peptides Using Random Forest

In recent years, therapeutic peptides have gained a lot interest as demonstrated by the 60 peptides approved as drugs in major markets and 150+ peptides currently in clinical trials. However, while small molecule docking is routinely used in rational drug design efforts, docking peptides has proven challenging partly because docking scoring functions, developed and calibrated for small molecules, perform poorly for these molecules. Here, we present random forest classifiers trained to discriminate correctly docked peptides. We show that, for a testing set of 47 protein-peptide complexes, structurally dissimilar from the training set and previously used to benchmark AutoDock Vina's ability to dock short peptides, these random forest classifiers improve docking power from ∼25% for AutoDock scoring functions to an average of ∼70%. These results pave the way for peptide-docking success rates comparable to those of small molecule docking. To develop these classifiers, we compiled the ProptPep37_2021 data set, a curated, high-quality set of 322 crystallographic protein-peptides complexes annotated with structural similarity information. The data set also provides a collection of high-quality putative poses with a range of deviations from the crystallographic pose, providing correct and incorrect poses (i.e., decoys) of the peptide for each entry. The ProptPep37_2021 data set as well as the classifiers presented here are freely available.

Structure-based virtual screening of CYP1A1 inhibitors: towards rapid tier-one assessment of potential developmental toxicants

Cytochrome P450 1A1 (CYP1A1) metabolizes estrogens, melatonin, and other key endogenous signaling molecules critical for embryonic/fetal development. The enzyme has increasing expression during pregnancy, and its inhibition or knockout increases embryonic/fetal lethality and/or developmental problems. Here, we present a virtual screening model for CYP1A1 inhibitors based on the orthosteric and predicted allosteric sites of the enzyme. Using 1001 reference compounds with CYP1A1 activity data, we optimized the decision thresholds of our model and classified the training compounds with 68.3% balanced accuracy (91.0% sensitivity and 45.7% specificity). We applied our final model to 11 known CYP1A1 orthosteric binders and related compounds, and found that our ranking of the known orthosteric binders generally agrees with the relative activity of CYP1A1 in metabolizing these compounds. We also applied the model to 22 new test compounds with unknown/unclear CYP1A1 inhibitory activity, and predicted 16 of them are CYP1A1 inhibitors. The CYP1A1 potency and modes of inhibition of these 22 compounds were experimentally determined. We confirmed that most predicted inhibitors, including drugs contraindicated during pregnancy (amiodarone, bicalutamide, cyproterone acetate, ketoconazole, and tamoxifen) and environmental agents suspected to be endocrine disruptors (bisphenol A, diethyl and dibutyl phthalates, and zearalenone), are indeed potent inhibitors of CYP1A1. Our results suggest that virtual screening may be used as a rapid tier-one method to screen for potential CYP1A1 inhibitors, and flag them out for further experimental evaluations.

Cereblon Regulates the Proteotoxicity of Tau by Tuning the Chaperone Activity of DNAJA1

Protein aggregation can induce explicit neurotoxic events that trigger a number of presently untreatable neurodegenerative disorders. Chaperones, on the other hand, play a neuroprotective role because of their ability to unfold and refold abnormal proteins. The progressive nature of neurotoxic events makes it important to discover endogenous factors that affect pathologic and molecular phenotypes of neurodegeneration in animal models. Here, we identified microtubule-associated protein tau, and chaperones Hsp70 (heat shock protein 70) and DNAJA1 (DJ2) as endogenous substrates of cereblon (CRBN), a substrate-recruiting subunit of cullin4-RING-E3-ligase. This recruitment results in ubiquitin-mediated degradation of tau, Hsp70, and DJ2. Knocking out CRBN enhances the chaperone activity of DJ2, resulting in decreased phosphorylation and aggregation of tau, improved association of tau with microtubules, and reduced accumulation of pathologic tau across brain. Functionally abundant DJ2 could prevent tau aggregation induced by various factors like okadaic acid and heparin. Depletion of CRBN also decreases the activity of tau-kinases including GSK3α/β, ERK, and p38. Intriguingly, we found a high expression of CRBN and low levels of DJ2 in neuronal tissues of 5XFAD and APP knock-in male mouse models of Alzheimer's disease. This implies that CRBN-mediated DJ2/Hsp70 pathway may be compromised in neurodegeneration. Being one of the primary pathogenic events, elevated CRBN can be a contributing factor for tauopathies. Our data provide a functional link between CRBN and DJ2/Hsp70 chaperone machinery in abolishing the cytotoxicity of aggregation-prone tau and suggest that Crbn-/- mice serve as an animal model of resistance against tauopathies for further exploration of the molecular mechanisms of neurodegeneration.