Oncogenic protein interfaces: small molecules, big challenges

Megalin-related mechanism of hemolysis-induced acute kidney injury and the therapeutic strategy

Hemolysis-induced acute kidney injury (AKI) is attributed to heme-mediated proximal tubule epithelial cell (PTEC) injury and tubular cast formation due to intratubular protein condensation. Megalin is a multiligand endocytic receptor for proteins, peptides, and drugs in PTECs and mediates the uptake of free hemoglobin and the heme-scavenging protein α1-microglobulin. However, understanding of how megalin is involved in the development of hemolysis-induced AKI remains elusive. Here, we investigated the megalin-related pathogenesis of hemolysis-induced AKI and a therapeutic strategy using cilastatin, a megalin blocker. A phenylhydrazine-induced hemolysis model developed in kidney-specific mosaic megalin knockout (MegKO) mice confirmed megalin-dependent PTEC injury revealed by the co-expression of kidney injury molecule-1 (KIM-1). In the hemolysis model in kidney-specific conditional MegKO mice, the uptake of hemoglobin and α1-microglobulin as well as KIM-1 expression in PTECs was suppressed, but tubular cast formation was augmented, likely due to the nonselective inhibition of protein reabsorption in PTECs. Quartz crystal microbalance analysis revealed that cilastatin suppressed the binding of megalin with hemoglobin and α1-microglobulin. Cilastatin also inhibited the specific uptake of fluorescent hemoglobin by megalin-expressing rat yolk sac tumor-derived L2 cells. In a mouse model of hemolysis-induced AKI, repeated cilastatin administration suppressed PTEC injury by inhibiting the uptake of hemoglobin and α1-microglobulin and also prevented cast formation. Hemopexin, another heme-scavenging protein, was also found to be a novel ligand of megalin, and its binding to megalin and uptake by PTECs in the hemolysis model were suppressed by cilastatin. Mass spectrometry-based semiquantitative analysis of urinary proteins in cilastatin-treated C57BL/6J mice indicated that cilastatin suppressed the reabsorption of a limited number of megalin ligands in PTECs, including α1-microglobulin and hemopexin. Collectively, cilastatin-mediated selective megalin blockade is an effective therapeutic strategy to prevent both heme-mediated PTEC injury and cast formation in hemolysis-induced AKI. © 2024 The Pathological Society of Great Britain and Ireland.

Microscale measurements of protein complexes from single cells

Proteins execute numerous cell functions in concert with one another in protein-protein interactions (PPI). While essential in each cell, such interactions are not identical from cell to cell. Instead, PPI heterogeneity contributes to cellular phenotypic heterogeneity in health and diseases such as cancer. Understanding cellular phenotypic heterogeneity thus requires measurements of properties of PPIs such as abundance, stoichiometry, and kinetics at the single-cell level. Here, we review recent, exciting progress in single-cell PPI measurements. Novel technology in this area is enabled by microscale and microfluidic approaches that control analyte concentration in timescales needed to outpace PPI disassembly kinetics. We describe microscale innovations, needed technical capabilities, and methods poised to be adapted for single-cell analysis in the near future.

Identification of WNK1 as a therapeutic target to suppress IgH/MYC expression in multiple myeloma

Multiple myeloma (MM) remains an incurable hematological malignancy demanding innovative therapeutic strategies. Targeting MYC, the notorious yet traditionally undruggable oncogene, presents an appealing avenue. Here, using a genome-scale CRISPR-Cas9 screen, we identify the WNK lysine-deficient protein kinase 1 (WNK1) as a regulator of MYC expression in MM cells. Genetic and pharmacological inhibition of WNK1 reduces MYC expression and, further, disrupts the MYC-dependent transcriptional program. Mechanistically, WNK1 inhibition attenuates the activity of the immunoglobulin heavy chain (IgH) enhancer, thus reducing MYC transcription when this locus is translocated near the MYC locus. WNK1 inhibition profoundly impacts MM cell behaviors, leading to growth inhibition, cell-cycle arrest, senescence, and apoptosis. Importantly, the WNK inhibitor WNK463 inhibits MM growth in primary patient samples as well as xenograft mouse models and exhibits synergistic effects with various anti-MM compounds. Collectively, our study uncovers WNK1 as a potential therapeutic target in MM.

SWISH-X, an Expanded Approach to Detect Cryptic Pockets in Proteins and at Protein-Protein Interfaces

Protein-protein interactions mediate most molecular processes in the cell, offering a significant opportunity to expand the set of known druggable targets. Unfortunately, targeting these interactions can be challenging due to their typically flat and featureless interaction surfaces, which often change as the complex forms. Such surface changes may reveal hidden (cryptic) druggable pockets. Here, we analyze a set of well-characterized protein-protein interactions harboring cryptic pockets and investigate the predictive power of current computational methods. Based on our observations, we developed a new computational strategy, SWISH-X (SWISH Expanded), which combines the established cryptic pocket identification capabilities of SWISH with the rapid temperature range exploration of OPES MultiThermal. SWISH-X is able to reliably identify cryptic pockets at protein-protein interfaces while retaining its predictive power for revealing cryptic pockets in isolated proteins, such as TEM-1 β-lactamase.

Validation of Core Ingredients and Molecular Mechanism of Cinobufotalin Injection Against Liver Cancer

Purpose

Cinobufotalin injection has obvious curative effects on liver cancer patients with less toxicity and fewer side effects than other therapeutic approaches. However, the core ingredients and mechanism underlying these anti-liver cancer effects have not been fully clarified due to its complex composition.

Methods

Multidimensional network analysis was used to screen the core ingredients, key targets and pathways underlying the therapeutic effects of cinobufotalin injection on liver cancer, and in vitro and in vivo experiments were performed to confirm the findings.

Results

By construction of ingredient networks and integrated analysis, eight core ingredients and ten key targets were finally identified in cinobufotalin injection, and all of the core ingredients are tightly linked with the key targets, and these key targets are highly associated with the cell cycle-related pathways, supporting that both cinobufotalin injection and its core ingredients exert anti-liver cancer roles by blocking cell cycle-related pathways. Moreover, in vitro and in vivo experiments confirmed that either cinobufotalin injection or one of its core ingredients, cinobufagin, significantly inhibited cell proliferation, colony formation, cell cycle progression and xenograft tumor growth, and the key target molecules involved in the cell cycle pathway such as CDK1, CDK4, CCNB1, CHEK1 and CCNE1, exhibit consistent changes in expression after treatment with cinobufotalin injection or cinobufagin. Interestingly, some key targets CDK1, CDK4, PLK1, CHEK1, TTK were predicted to bind with multiple of core ingredients of cinobufotalin injection, and the affinity between one of the critical ingredients cinobufagin and key target CDK1 was further confirmed by SPR assay.

Conclusion

Cinobufotalin injection was confirmed to includes eight core ingredients, and they play therapeutic effects in liver cancer by blocking cell cycle-related pathways, which provides important insights for the mechanism of cinobufotalin injection antagonizing liver cancer and the development of novel small molecule anti-cancer drugs.

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

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

In-Bridge Stereochemistry: A Determinant of Stapled Peptide Conformation and Activity

Peptide side chain stapling has been proven to be an effective strategy for fine-tuning peptide properties. This innovative approach leads to the creation of stapled peptides characterized by stabilized α-helical conformations, enhanced protein-binding affinity, improved cell permeability, superior enzymatic stability, and numerous other advantages. Extensive research has explored the impact of various stapling bridges on the properties of these peptides, with limited investigation into the influence of bridge chirality, until very recently. In this concise review, we provide a brief overview of the current state of knowledge regarding the stereochemistry within the bridges of stapled peptides, offering insights into the potential applications of chiral bridges in the design and development of stapled peptides.

Physical-Chemical Features Selection Reveals That Differences in Dipeptide Compositions Correlate Most with Protein-Protein Interactions

The ability to accurately predict protein-protein interactions is critically important for our understanding of major cellular processes. However, current experimental and computational approaches for identifying them are technically very challenging and still have limited success. We propose a new computational method for predicting protein-protein interactions using only primary sequence information. It utilizes a concept of physical-chemical similarity to determine which interactions will most probably occur. In our approach, the physical-chemical features of protein are extracted using bioinformatics tools for different organisms, and then they are utilized in a machine-learning method to identify successful protein-protein interactions via correlation analysis. It is found that the most important property that correlates most with the protein-protein interactions for all studied organisms is dipeptide amino acid compositions. The analysis is specifically applied to the bacterial two-component system that includes histidine kinase and transcriptional response regulators. Our theoretical approach provides a simple and robust method for quantifying the important details of complex mechanisms of biological processes.

Selection of collagen IV fragments forming the outer sphere of the native protein: Assessment of biological activity for regenerative medicine

The aim of this research was to select the fragments that make up the outer layer of the collagen IV (COL4A6) protein and to assess their potential usefulness for regenerative medicine. It was expected that because protein-protein interactions take place via contact between external domains, the set of peptides forming the outer sphere of collagen IV will determine its interaction with other proteins. Cellulose-immobilized protein fragment libraries treated with polyclonal anti-collagen IV antibodies were used to select the peptides forming the outer sphere of collagen IV. In the first test, 33 peptides that strongly interacted with the polyclonal anti-collagen IV antibodies were selected from a library of non-overlapping fragments of collagen IV. The selected fragments of collagen IV (cleaved from the cellulose matrix) were tested for their cytotoxicity, their effects on cell viability and proliferation, and their impact on the formation of reactive oxygen species (ROS). The studies used RAW 264.7 mouse macrophage cells and Hs 680.Tr human fibroblasts. PrestoBlue, ToxiLight™, and ToxiLight 100% Lysis Control assays were conducted. The viability of fibroblasts cultured with the addition of increasing concentrations of the peptide mix did not show statistically significant differences from the control. Fragments 161-170, 221-230, 721-730, 1331-1340, 1521-1530, and 1661-1670 of COL4A6 were examined for cytotoxicity against BJ normal human foreskin fibroblasts. None of the collagen fragments were found to be cytotoxic. Further research is underway on the potential uses of collagen IV fragments in regenerative medicine.

Class-specific recognition and monitoring of environmental steroid estrogens in real water systems utilizing aptamer base substitution mutagenesis approach

The same class of environmental steroid estrogens (SEs) with the highest estrogenic activity share the same chemical core structure and are often found together in the environment, posing significant risks to organismal health and environmental safety due to toxicity accumulation. In this study, a novel method for constructing the group-targeting aptasensor was developed to comprehensively analyze SEs. Through artificial intervention base substitution mutagenesis of adjacent bases T13 and C20 of the aptamer-binding domain recognizing 17β-estradiol, combined with docking calculations, the group-targeting SEs-aptamer for class-specific recognition SEs, such as estrone, estradiol, estriol, and ethinylestradiol were obtained. The binding constant of the SEs-aptamer to the SEs was 108 M-1. The established group-targeting SEs aptasensor exhibited high sensitivity within a concentration range from 0.1 to 10 nM and demonstrated strong interference resistance, as well as high stability and wide pH water applicability. It was further applied to analyze real water samples and monitor changes in SEs concentrations during the removal process by Chlorella pyrenoidosa. These successful applications have demonstrated the excellent ability of this aptasensor to monitor SE in the environment. The method offered a new approach and idea for recognizing and detecting the same class of environmental pollutants in complex systems.

Target-based drug discovery: Applications of fluorescence techniques in high throughput and fragment-based screening

Target-based discovery of first-in-class therapeutics demands an in-depth understanding of the molecular mechanisms underlying human diseases. Precise measurements of cellular and biochemical activities are critical to gain mechanistic knowledge of biomolecules and their altered function in disease conditions. Such measurements enable the development of intervention strategies for preventing or treating diseases by modulation of desired molecular processes. Fluorescence-based techniques are routinely employed for accurate and robust measurements of in-vitro activity of molecular targets and for discovering novel chemical molecules that modulate the activity of molecular targets. In the current review, the authors focus on the applications of fluorescence-based high throughput screening (HTS) and fragment-based ligand discovery (FBLD) techniques such as fluorescence polarization (FP), Förster resonance energy transfer (FRET), fluorescence thermal shift assay (FTSA) and microscale thermophoresis (MST) for the discovery of chemical probe to exploring target's role in disease biology and ultimately, serve as a foundation for drug discovery. Some recent advancements in these techniques for compound library screening against important classes of drug targets, such as G-protein-coupled receptors (GPCRs) and GTPases, as well as phosphorylation- and acetylation-mediated protein-protein interactions, are discussed. Overall, this review presents a landscape of how these techniques paved the way for the discovery of small-molecule modulators and biologics against these targets for therapeutic benefits.

Current trends and future prospects of drug repositioning in gastrointestinal oncology

Gastrointestinal (GI) cancers comprise a significant number of cancer cases worldwide and contribute to a high percentage of cancer-related deaths. To improve survival rates of GI cancer patients, it is important to find and implement more effective therapeutic strategies with better prognoses and fewer side effects. The development of new drugs can be a lengthy and expensive process, often involving clinical trials that may fail in the early stages. One strategy to address these challenges is drug repurposing (DR). Drug repurposing is a developmental strategy that involves using existing drugs approved for other diseases and leveraging their safety and pharmacological data to explore their potential use in treating different diseases. In this paper, we outline the existing therapeutic strategies and challenges associated with GI cancers and explore DR as a promising alternative approach. We have presented an extensive review of different DR methodologies, research efforts and examples of repurposed drugs within various GI cancer types, such as colorectal, pancreatic and liver cancers. Our aim is to provide a comprehensive overview of employing the DR approach in GI cancers to inform future research endeavors and clinical trials in this field.

Stabilized cyclic peptides as modulators of protein-protein interactions: promising strategies and biological evaluation

Protein-protein interactions (PPIs) control many essential biological pathways which are often misregulated in disease. As such, selective PPI modulators are desirable to unravel complex functions of PPIs and thus expand the repertoire of therapeutic targets. However, the large size and relative flatness of PPI interfaces make them challenging molecular targets for conventional drug modalities, rendering most PPIs "undruggable". Therefore, there is a growing need to discover innovative molecules that are able to modulate crucial PPIs. Peptides are ideal candidates to deliver such therapeutics attributed to their ability to closely mimic structural features of protein interfaces. However, their inherently poor proteolysis resistance and cell permeability inevitably hamper their biomedical applications. The introduction of a constraint (i.e., peptide cyclization) to stabilize peptides' secondary structure is a promising strategy to address this problem as witnessed by the rapid development of cyclic peptide drugs in the past two decades. Here, we comprehensively review the recent progress on stabilized cyclic peptides in targeting challenging PPIs. Technological advancements and emerging chemical approaches for stabilizing active peptide conformations are categorized in terms of α-helix stapling, β-hairpin mimetics and macrocyclization. To discover potent and selective ligands, cyclic peptide library technologies were updated based on genetic, biochemical or synthetic methodologies. Moreover, several advances to improve the permeability and oral bioavailability of biologically active cyclic peptides enable the de novo development of cyclic peptide ligands with pharmacological properties. In summary, the development of cyclic peptide-based PPI modulators carries tremendous promise for the next generation of therapeutic agents to target historically "intractable" PPI systems.

Computational Modeling of Stapled Coiled-Coil Inhibitors Against Bcr-Abl: Toward a Treatment Strategy for CML

The chimeric oncoprotein Bcr-Abl is the causative agent of virtually all chronic myeloid leukemias (CML) and a subset of acute lymphoblastic leukemias (ALL). As a result of the so-called Philadelphia Chromosome translocation t(9;22), Bcr-Abl manifests as a constitutively active tyrosine kinase which promotes leukemogenesis by activation of cell cycle signaling pathways. Constitutive and oncogenic activation is mediated by an N-terminal coiled-coil oligomerization domain in Bcr (Bcr-CC), presenting a therapeutic target for inhibition of Bcr-Abl activity toward the treatment of Bcr-Abl+ leukemias. Previously, we demonstrated that a rationally designed Bcr-CC mutant, CCmut3, exerts a dominant negative effect upon Bcr-Abl activity by preferential oligomerization with Bcr-CC. Moreover, we have shown conjugation to a leukemia-specific cell-penetrating peptide (CPP-CCmut3) improves intracellular delivery and activity. However, our full-length CPP-CCmut3 construct (81 aa) is encumbered by an intrinsically high degree of conformational variability and susceptibility to proteolytic degradation, relative to traditional small molecule therapeutics. Here, we iterate a new generation of our inhibitor against Bcr-CC mediated Bcr-Abl assembly that is designed to address these constraints through incorporation of all-hydrocarbon staples spanning i, i + 7 positions in helix α2 (CPP-CCmut3-st). We utilize computational modeling and biomolecular simulation to design and characterize single and double staple candidates in silico, evaluating binding energetics and building upon our seminal work modeling single hydrocarbon staples when applied to a truncated Bcr-CC sequence. This strategy enables us to efficiently build, characterize, and screen lead single/double stapled CPP-CCmut3-st candidates for experimental studies and validation in vitro and in vivo. In addition to full-length CPP-CCmut, we model a truncated system characterized by deletion of helix α1 and the flexible-loop linker, which are known to impart high conformational variability. To study the impact of the N-terminal cyclic CPP toward model stability and inhibitor activity, we also model the full-length and truncated systems without CPP, with cyclized CPP, and with linear CPP, for a total of six systems which comprise our library. From this library, we present lead stapled peptide candidates to be synthesized and evaluated experimentally as our next-generation inhibitors against Bcr-Abl.

Cyclobutane-bearing restricted anchoring residues enabled geometry-specific hydrocarbon peptide stapling

Stapled peptides are regarded as the promising next-generation therapeutics because of their improved secondary structure, membrane permeability and metabolic stability as compared with the prototype linear peptides. Usually, stapled peptides are obtained by a hydrocarbon stapling technique, anchoring from paired olefin-terminated unnatural amino acids and the consequent ring-closing metathesis (RCM). To investigate the adaptability of the rigid cyclobutane structure in RCM and expand the chemical diversity of hydrocarbon peptide stapling, we herein described the rational design and efficient synthesis of cyclobutane-based conformationally constrained amino acids, termed (E)-1-amino-3-(but-3-en-1-yl)cyclobutane-1-carboxylic acid (E7) and (Z)-1-amino-3-(but-3-en-1-yl)cyclobutane-1-carboxylic acid (Z7). All four combinations including E7-E7, E7-Z7, Z7-Z7 and Z7-E7 were proven to be applicable in RCM-mediated peptide stapling to afford the corresponding geometry-specific stapled peptides. With the aid of the combined quantum and molecular mechanics, the E7-E7 combination was proven to be optimal in both the RCM reaction and helical stabilization. With the spike protein of SARS-CoV-2 as the target, a series of cyclobutane-bearing stapled peptides were obtained. Among them, E7-E7 geometry-specific stapled peptides indeed exhibit higher α-helicity and thus stronger biological activity than canonical hydrocarbon stapled peptides. We believe that this methodology possesses great potential to expand the scope of the existing peptide stapling strategy. These cyclobutane-bearing restricted anchoring residues served as effective supplements for the existing olefin-terminated unnatural amino acids and the resultant geometry-specific hydrocarbon peptide stapling provided more potential for peptide therapeutics.

Phosphorylation-Assisted Luciferase Complementation Assay Designed to Monitor Kinase Activity and Kinase-Domain-Mediated Protein-Protein Binding

Protein kinases are key regulators of cell signaling and have been important therapeutic targets for three decades. ATP-competitive drugs directly inhibit the activity of kinases but these enzymes work as part of complex protein networks in which protein-protein interactions (often referred to as kinase docking) may govern a more complex activation pattern. Kinase docking is indispensable for many signaling disease-relevant Ser/Thr kinases and it is mediated by a dedicated surface groove on the kinase domain which is distinct from the substrate-binding pocket. Thus, interfering with kinase docking provides an alternative strategy to control kinases. We describe activity sensors developed for p90 ribosomal S6 kinase (RSK) and mitogen-activated protein kinases (MAPKs: ERK, p38, and JNK) whose substrate phosphorylation is known to depend on kinase-docking-groove-mediated protein-protein binding. The in vitro assays were based on fragment complementation of the NanoBit luciferase, which is facilitated upon substrate motif phosphorylation. The new phosphorylation-assisted luciferase complementation (PhALC) sensors are highly selective and the PhALC assay is a useful tool for the quantitative analysis of kinase activity or kinase docking, and even for high-throughput screening of academic compound collections.

Controlling the Chameleonic Behavior and Membrane Permeability of Cyclosporine Derivatives via Backbone and Side Chain Modifications

Some macrocycles exhibit enhanced membrane permeability through conformational switching in different environmental polarities, a trait known as chameleonic behavior. In this study, we demonstrate specific backbone and side chain modifications that can control chameleonic behavior and passive membrane permeability using a cyclosporin O (CsO) scaffold. To quantify chameleonic behavior, we used a ratio of the population of the closed conformation obtained in polar solvent and nonpolar solvent for each CsO derivative. We found that β-hydroxylation at position 1 (1 and 3) can encode chameleonicity and improve permeability. However, the conformational stabilization induced by adding an additional transannular H-bond (2 and 5) leads to a much slower rate of membrane permeation. Our CsO scaffold provides a platform for the systematic study of the relationship among conformation, membrane permeability, solubility, and protein binding. This knowledge contributes to the discovery of potent beyond the rule of five (bRo5) macrocycles capable of targeting undruggable targets.

Recent advances in targeting the "undruggable" proteins: from drug discovery to clinical trials

Undruggable proteins are a class of proteins that are often characterized by large, complex structures or functions that are difficult to interfere with using conventional drug design strategies. Targeting such undruggable targets has been considered also a great opportunity for treatment of human diseases and has attracted substantial efforts in the field of medicine. Therefore, in this review, we focus on the recent development of drug discovery targeting "undruggable" proteins and their application in clinic. To make this review well organized, we discuss the design strategies targeting the undruggable proteins, including covalent regulation, allosteric inhibition, protein-protein/DNA interaction inhibition, targeted proteins regulation, nucleic acid-based approach, immunotherapy and others.

Are fibrinaloid microclots a cause of autoimmunity in Long Covid and other post-infection diseases?

It is now well established that the blood-clotting protein fibrinogen can polymerise into an anomalous form of fibrin that is amyloid in character; the resultant clots and microclots entrap many other molecules, stain with fluorogenic amyloid stains, are rather resistant to fibrinolysis, can block up microcapillaries, are implicated in a variety of diseases including Long COVID, and have been referred to as fibrinaloids. A necessary corollary of this anomalous polymerisation is the generation of novel epitopes in proteins that would normally be seen as 'self', and otherwise immunologically silent. The precise conformation of the resulting fibrinaloid clots (that, as with prions and classical amyloid proteins, can adopt multiple, stable conformations) must depend on the existing small molecules and metal ions that the fibrinogen may (and is some cases is known to) have bound before polymerisation. Any such novel epitopes, however, are likely to lead to the generation of autoantibodies. A convergent phenomenology, including distinct conformations and seeding of the anomalous form for initiation and propagation, is emerging to link knowledge in prions, prionoids, amyloids and now fibrinaloids. We here summarise the evidence for the above reasoning, which has substantial implications for our understanding of the genesis of autoimmunity (and the possible prevention thereof) based on the primary process of fibrinaloid formation.

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.

Disrupting the α-synuclein-ESCRT interaction with a peptide inhibitor mitigates neurodegeneration in preclinical models of Parkinson's disease

Accumulation of α-synuclein into toxic oligomers or fibrils is implicated in dopaminergic neurodegeneration in Parkinson's disease. Here we performed a high-throughput, proteome-wide peptide screen to identify protein-protein interaction inhibitors that reduce α-synuclein oligomer levels and their associated cytotoxicity. We find that the most potent peptide inhibitor disrupts the direct interaction between the C-terminal region of α-synuclein and CHarged Multivesicular body Protein 2B (CHMP2B), a component of the Endosomal Sorting Complex Required for Transport-III (ESCRT-III). We show that α-synuclein impedes endolysosomal activity via this interaction, thereby inhibiting its own degradation. Conversely, the peptide inhibitor restores endolysosomal function and thereby decreases α-synuclein levels in multiple models, including female and male human cells harboring disease-causing α-synuclein mutations. Furthermore, the peptide inhibitor protects dopaminergic neurons from α-synuclein-mediated degeneration in hermaphroditic C. elegans and preclinical Parkinson's disease models using female rats. Thus, the α-synuclein-CHMP2B interaction is a potential therapeutic target for neurodegenerative disorders.

PRPF19 facilitates colorectal cancer liver metastasis through activation of the Src-YAP1 pathway via K63-linked ubiquitination of MYL9

Distant metastasis is one of the leading causes of cancer-related mortality of colorectal cancer (CRC). Dysregulation of E3 ubiquitin ligases has been implicated in acting vital roles in multiple cancers. In this study, we found that the E3 ubiquitin ligase, PRPF19 was positively correlated with liver metastasis, and predicted a worse clinical outcome in CRC. However, the biological effects and the underlying molecular mechanisms of PRPF19 in CRC remain elusive thus far. We illustrated that PRPF19 promoted the migration and invasion capability of CRC cells in both gain- and loss- of function assays. Mechanistically, we uncovered that myosin light chain 9 (MYL9) was the downstream substrate of PRPF19. PRPF19 enhanced the stability of MYL9 via K63-linked ubiquitination, and promoted the migration and invasion capability of CRC cells in an MYL9-mediated manner. Furthermore, the Src-YAP1 cascade was identified as the downstream effector mechanism by which the PRPF19/MYL9 axis promoted metastasis in CRC. Taken together, our findings highlighted that the PRPF19/MYL9 axis served as a novel mechanism in CRC metastasis, which provided an attractive therapeutic strategy for CRC treatment.

Lnc-ing epigenetic mechanisms with autophagy and cancer drug resistance

Long noncoding RNAs (lncRNAs) comprise a diverse class of RNA molecules that regulate various physiological processes and have been reported to be involved in several human pathologies ranging from neurodegenerative disease to cancer. Therapeutic resistance is a major hurdle for cancer treatment. Over the past decade, several studies has emerged on the role of lncRNAs in cancer drug resistance and many trials have been conducted employing them. LncRNAs also regulate different cell death pathways thereby maintaining a fine balance of cell survival and death. Autophagy is a complex cell-killing mechanism that has both cytoprotective and cytotoxic roles. Similarly, autophagy can lead to the induction of both chemosensitization and chemoresistance in cancer cells upon therapeutic intervention. Recently the role of lncRNAs in the regulation of autophagy has also surfaced. Thus, lncRNAs can be used in cancer therapeutics to alleviate the challenges of chemoresistance by targeting the autophagosomal axis. In this chapter, we discuss about the role of lncRNAs in autophagy-mediated cancer drug resistance and its implication in targeted cancer therapy.

Inhibitors of the Oncogenic PA2G4-MYCN Protein-Protein Interface

MYCN is a major oncogenic driver for neuroblastoma tumorigenesis, yet there are no direct MYCN inhibitors. We have previously identified PA2G4 as a direct protein-binding partner of MYCN and drive neuroblastoma tumorigenesis. A small molecule known to bind PA2G4, WS6, significantly decreased tumorigenicity in TH-MYCN neuroblastoma mice, along with the inhibition of PA2G4 and MYCN interactions. Here, we identified a number of novel WS6 analogues, with 80% structural similarity, and used surface plasmon resonance assays to determine their binding affinity. Analogues #5333 and #5338 showed direct binding towards human recombinant PA2G4. Importantly, #5333 and #5338 demonstrated a 70-fold lower toxicity for normal human myofibroblasts compared to WS6. Structure-activity relationship analysis showed that a 2,3 dimethylphenol was the most suitable substituent at the R1 position. Replacing the trifluoromethyl group on the phenyl ring at the R2 position, with a bromine or hydrogen atom, increased the difference between efficacy against neuroblastoma cells and normal myofibroblast toxicity. The WS6 analogues inhibited neuroblastoma cell phenotype in vitro, in part through effects on apoptosis, while their anti-cancer effects required both PA2G4 and MYCN expression. Collectively, chemical inhibition of PA2G4-MYCN binding by WS6 analogues represents a first-in-class drug discovery which may have implications for other MYCN-driven cancers.

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

BACKGROUND

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

AREAS COVERED

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

EXPERT OPINION

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

Cell-free Biosynthesis of Peptidomimetics

A wide variety of peptidomimetics (peptide analogs) possessing innovative biological functions have been brought forth as therapeutic candidates through cell-free protein synthesis (CFPS) systems. A key feature of these peptidomimetic drugs is the use of non-canonical amino acid building blocks with diverse biochemical properties that expand functional diversity. Here, we summarize recent technologies leveraging CFPS platforms to expand the reach of peptidomimetics drugs. We also offer perspectives on engineering the translational machinery that may open new opportunities for expanding genetically encoded chemistry to transform drug discovery practice beyond traditional boundaries.

Inhibition of Amyloid Protein Aggregation Using Selected Peptidomimetics

Aberrant protein aggregation leads to the formation of amyloid fibrils. This phenomenon is linked to the development of more than 40 irremediable diseases such as Alzheimer's disease, Parkinson's disease, type 2 diabetes, and cancer. Plenty of research efforts have been given to understanding the underlying mechanism of protein aggregation, associated toxicity, and the development of amyloid inhibitors. Recently, the peptidomimetic approach has emerged as a potential tool to modulate several protein-protein interactions (PPIs). In this review, we discussed selected peptidomimetic-based approaches for the modulation of important amyloid proteins (Islet Amyloid Polypeptide, Amyloid Beta, α-synuclein, mutant p53, and insulin) aggregation. This approach holds a powerful platform for creating an essential stepping stone for the vital development of anti-amyloid therapeutic agents.

A knowledge-based protein-protein interaction inhibition (KPI) pipeline: an insight from drug repositioning for COVID-19 inhibition

The inhibition of protein-protein interactions (PPIs) by small molecules is an exciting drug discovery strategy. Here, we aimed to develop a pipeline to identify candidate small molecules to inhibit PPIs. Therefore, KPI, a Knowledge-based Protein-Protein Interaction Inhibition pipeline, was introduced to improve the discovery of PPI inhibitors. Then, phytochemicals from a collection of known Middle Eastern antiviral herbs were screened to identify potential inhibitors of key PPIs involved in COVID-19. Here, the following investigations were sequenced: 1) Finding the binding partner and the interface of the proteins in PPIs, 2) Performing the blind ligand-protein inhibition (LPI) simulations, 3) Performing the local LPI simulations, 4) Simulating the interactions of the proteins and their binding partner in the presence and absence of the ligands, and 5) Performing the molecular dynamics simulations. The pharmacophore groups involved in the LPI were also characterized. Aloin, Genistein, Neoglucobrassicin, and Rutin are our new pipeline candidates for inhibiting PPIs involved in COVID-19. We also propose KPI for drug repositioning studies.Communicated by Ramaswamy H. Sarma.

Atomic-level thermodynamics analysis of the binding free energy of SARS-CoV-2 neutralizing antibodies

Understanding how protein-protein binding affinity is determined from molecular interactions at the interface is essential in developing protein therapeutics such as antibodies, but this has not yet been fully achieved. Among the major difficulties are the facts that it is generally difficult to decompose thermodynamic quantities into contributions from individual molecular interactions and that the solvent effect-dehydration penalty-must also be taken into consideration for every contact formation at the binding interface. Here, we present an atomic-level thermodynamics analysis that overcomes these difficulties and illustrate its utility through application to SARS-CoV-2 neutralizing antibodies. Our analysis is based on the direct interaction energy computed from simulated antibody-protein complex structures and on the decomposition of solvation free energy change upon complex formation. We find that the formation of a single contact such as a hydrogen bond at the interface barely contributes to binding free energy due to the dehydration penalty. On the other hand, the simultaneous formation of multiple contacts between two interface residues favorably contributes to binding affinity. This is because the dehydration penalty is significantly alleviated: the total penalty for multiple contacts is smaller than a sum of what would be expected for individual dehydrations of those contacts. Our results thus provide a new perspective for designing protein therapeutics of improved binding affinity.

An overview of PROTACs: a promising drug discovery paradigm

Proteolysis targeting chimeras (PROTACs) technology has emerged as a novel therapeutic paradigm in recent years. PROTACs are heterobifunctional molecules that degrade target proteins by hijacking the ubiquitin-proteasome system. Currently, about 20-25% of all protein targets are being studied, and most works focus on their enzymatic functions. Unlike small molecules, PROTACs inhibit the whole biological function of the target protein by binding to the target protein and inducing subsequent proteasomal degradation. PROTACs compensate for limitations that transcription factors, nuclear proteins, and other scaffolding proteins are difficult to handle with traditional small-molecule inhibitors. Currently, PROTACs have successfully degraded diverse proteins, such as BTK, BRD4, AR, ER, STAT3, IRAK4, tau, etc. And ARV-110 and ARV-471 exhibited excellent efficacy in clinical II trials. However, what targets are appropriate for PROTAC technology to achieve better benefits than small-molecule inhibitors are not fully understood. And how to rationally design an efficient PROTACs and optimize it to be orally effective poses big challenges for researchers. In this review, we summarize the features of PROTAC technology, analyze the detail of general principles for designing efficient PROTACs, and discuss the typical application of PROTACs targeting different protein categories. In addition, we also introduce the progress of relevant clinical trial results of representative PROTACs and assess the challenges and limitations that PROTACs may face. Collectively, our studies provide references for further application of PROTACs.

Designing a Nitro-Induced Sutured Biomacromolecule to Engineer Electroconductive Adhesive Hydrogels

Nitro-functionality, with a large deficit of negative charge, embraces biological importance and has proven its therapeutic essence even in chemotherapy. Functionally, with its strong electron-withdrawing capability, nitro can manipulate the electron density of organic moieties and regulates cellular-biochemical reactions. However, the chemistry of nitro-functionality to introduce physiologically relevant macroscopic properties from the molecular skeleton is unknown. Therefore, herein, a neurotransmitter moiety, dopamine, was chemically modified with a nitro-group to explore its influence on synthesizing a multifunctional biomaterial for therapeutic applications. Chemically, while the nitro-group perturbed the aromatic electron density of nitrocatecholic domain, it facilitated the suturing of nitrocatechol moieties to regain its aromaticity through a radical transfer mechanism, forming a novel macromolecular structure. Incorporation of the sutured-nitrocatecholic strand (S-nCAT) in a gelatin-based hydrogel introduced an electroconductive microenvironment through the delocalization of π-electrons in S-nCAT, while maintaining its catechol-mediated adhesive property for tissue repairing/sealing. Meanwhile, the engineered hydrogel enriched with noncovalent interactions, demonstrated excellent mechano-physical properties to support tissue functions. Cytocompatibility of the bioadhesive was assessed with in vitro and in vivo studies, confirming its potential usage for biomedical applications. In conclusion, this novel chemical approach enabled designing a multifunctional biomaterial by manipulating the electronic properties of small bioactive molecules for various biomedical applications.

Large-Scale Crystallographic Fragment Screening Expedites Compound Optimization and Identifies Putative Protein-Protein Interaction Sites

The identification of starting points for compound development is one of the key steps in early-stage drug discovery. Information-rich techniques such as crystallographic fragment screening can potentially increase the efficiency of this step by providing the structural information of the binding mode of the ligands in addition to the mere binding information. Here, we present the crystallographic screening of our 1000-plus-compound F2X-Universal Library against the complex of the yeast spliceosomal Prp8 RNaseH-like domain and the snRNP assembly factor Aar2. The observed 269 hits are distributed over 10 distinct binding sites on the surface of the protein-protein complex. Our work shows that hit clusters from large-scale crystallographic fragment screening campaigns identify known interaction sites with other proteins and suggest putative additional interaction sites. Furthermore, the inherent binding pose validation within the hit clusters may accelerate downstream compound optimization.

Targeted Protein Degradation to Overcome Resistance in Cancer Therapies: PROTAC and N-Degron Pathway

Extensive progress in understanding the molecular mechanisms of cancer growth and proliferation has led to the remarkable development of drugs that target cancer-driving molecules. Most target molecules are proteins such as kinases and kinase-associated receptors, which have enzymatic activities needed for the signaling cascades of cells. The small molecule inhibitors for these target molecules greatly improved therapeutic efficacy and lowered the systemic toxicity in cancer therapies. However, long-term and high-dosage treatment of small inhibitors for cancer has produced other obstacles, such as resistance to inhibitors. Among recent approaches to overcoming drug resistance to cancers, targeted protein degradation (TPD) such as proteolysis-targeting chimera (PROTAC) technology adopts a distinct mechanism of action by which a target protein is destroyed through the cellular proteolytic system, such as the ubiquitin–proteasome system or autophagy. Here, we review the currently developed PROTACs as the representative TPD molecules for cancer therapy and the N-degrons of the N-degron pathways as the potential TPD ligands.

Application of nanopore sensors for biomolecular interactions and drug discovery

Biomolecular interactions, including protein-protein, protein-nucleic acid, and protein/nucleic acid-ligand interactions, play crucial roles in various cellular signaling and biological processes, and offer attractive therapeutic targets in numerous human diseases. Currently, drug discovery is limited by the low efficiency and high cost of conventional ensemble-averaging-based techniques for biomolecular interaction analysis and high-throughput drug screening. Nanopores are an emerging technology for single-molecule sensing of biomolecules. Owing to the robust advantages of single-molecule sensing, nanopore sensors have contributed tremendously to nucleic acid sequencing and disease diagnostics. In this minireview, we summarize the recent developments and outlooks in single-molecule sensing of various biomolecular interactions for drug discovery applications using biological and solid-state nanopore sensors.

DTSyn: a dual-transformer-based neural network to predict synergistic drug combinations

Drug combination therapies are superior to monotherapy for cancer treatment in many ways. Identifying novel drug combinations by screening is challenging for the wet-lab experiments due to the time-consuming process of the enormous search space of possible drug pairs. Thus, computational methods have been developed to predict drug pairs with potential synergistic functions. Notwithstanding the success of current models, understanding the mechanism of drug synergy from a chemical-gene-tissue interaction perspective lacks study, hindering current algorithms from drug mechanism study. Here, we proposed a deep neural network model termed DTSyn (Dual Transformer encoder model for drug pair Synergy prediction) based on a multi-head attention mechanism to identify novel drug combinations. We designed a fine-granularity transformer encoder to capture chemical substructure-gene and gene-gene associations and a coarse-granularity transformer encoder to extract chemical-chemical and chemical-cell line interactions. DTSyn achieved the highest receiver operating characteristic area under the curve of 0.73, 0.78. 0.82 and 0.81 on four different cross-validation tasks, outperforming all competing methods. Further, DTSyn achieved the best True Positive Rate (TPR) over five independent data sets. The ablation study showed that both transformer encoder blocks contributed to the performance of DTSyn. In addition, DTSyn can extract interactions among chemicals and cell lines, representing the potential mechanisms of drug action. By leveraging the attention mechanism and pretrained gene embeddings, DTSyn shows improved interpretability ability. Thus, we envision our model as a valuable tool to prioritize synergistic drug pairs with chemical and cell line gene expression profile.

Microscale Thermophoresis as a Tool to Study Protein Interactions and Their Implication in Human Diseases

The review highlights how protein–protein interactions (PPIs) have determining roles in most life processes and how interactions between protein partners are involved in various human diseases. The study of PPIs and binding interactions as well as their understanding, quantification and pharmacological regulation are crucial for therapeutic purposes. Diverse computational and analytical methods, combined with high-throughput screening (HTS), have been extensively used to characterize multiple types of PPIs, but these procedures are generally laborious, long and expensive. Rapid, robust and efficient alternative methods are proposed, including the use of Microscale Thermophoresis (MST), which has emerged as the technology of choice in drug discovery programs in recent years. This review summarizes selected case studies pertaining to the use of MST to detect therapeutically pertinent proteins and highlights the biological importance of binding interactions, implicated in various human diseases. The benefits and limitations of MST to study PPIs and to identify regulators are discussed.

Development of VPC-70619, a Small-Molecule N-Myc Inhibitor as a Potential Therapy for Neuroendocrine Prostate Cancer

The Myc family of transcription factors are involved in the development and progression of numerous cancers, including prostate cancer (PCa). Under the pressure of androgen receptor (AR)-directed therapies resistance can occur, leading to the lethal form of PCa known as neuroendocrine prostate cancer (NEPC), characterized among other features by N-Myc overexpression. There are no clinically approved treatments for NEPC, translating into poor patient prognosis and survival. Therefore, there is a pressing need to develop novel therapeutic avenues to treat NEPC patients. In this study, we investigate the N-Myc-Max DNA binding domain (DBD) as a potential target for small molecule inhibitors and utilize computer-aided drug design (CADD) approaches to discover prospective hits. Through further exploration and optimization, a compound, VPC-70619, was identified with notable anti-N-Myc potency and strong antiproliferative activity against numerous N-Myc expressing cell lines, including those representing NEPC.

PPI-HotspotDB: Database of Protein-Protein Interaction Hot Spots

Single-point mutations of certain residues (so-called hot spots) impair/disrupt protein-protein interactions (PPIs), leading to pathogenesis and drug resistance. Conventionally, a PPI-hot spot is identified when its replacement decreased the binding free energy significantly, generally by ≥2 kcal/mol. The relatively few mutations with such a significant binding free energy drop limited the number of distinct PPI-hot spots. By defining PPI-hot spots based on mutations that have been manually curated in UniProtKB to significantly impair/disrupt PPIs in addition to binding free energy changes, we have greatly expanded the number of distinct PPI-hot spots by an order of magnitude. These experimentally determined PPI-hot spots along with available structures have been collected in a database called PPI-Hotspot^DB. We have applied the PPI-Hotspot^DB to create a nonredundant benchmark, PPI-Hotspot+PDB^BM, for assessing methods to predict PPI-hot spots using the free structure as input. PPI-Hotspot^DB will benefit the design of mutagenesis experiments and development of PPI-hot spot prediction methods. The database and benchmark are freely available at https://ppihotspot.limlab.dnsalias.org.

Mapping oncogenic protein interactions for precision medicine

Normal protein‐protein interactions (normPPIs) occur with high fidelity to regulate almost every physiological process. In cancer, this highly organised and precisely regulated network is disrupted, hijacked or reprogrammed resulting in oncogenic protein‐protein interactions (oncoPPIs). OncoPPIs, which can result from genomic alterations, are a hallmark of many types of cancers. Recent technological advances in the field of mass spectrometry (MS)‐based interactomics, structural biology and drug discovery have prompted scientists to identify and characterise oncoPPIs. Disruption of oncoPPI interfaces has become a major focus of drug discovery programs and has resulted in the use of PPI‐specific drugs clinically. However, due to several technical hurdles, studies to build a reference oncoPPI map for various cancer types have not been undertaken. Therefore, there is an urgent need for experimental workflows to overcome the existing challenges in studying oncoPPIs in various cancers and to build comprehensive reference maps. Here, we discuss the important hurdles for characterising oncoPPIs and propose a three‐phase multidisciplinary workflow to identify and characterise oncoPPIs. Systematic identification of cancer‐type‐specific oncogenic interactions will spur new opportunities for PPI‐focused drug discovery projects and precision medicine.

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.

Small-molecule inhibitors that disrupt the MTDH-SND1 complex suppress breast cancer progression and metastasis

Metastatic breast cancer is a leading health burden worldwide. Previous studies have shown that metadherin (MTDH) promotes breast cancer initiation, metastasis and therapy resistance; however, the therapeutic potential of targeting MTDH remains largely unexplored. Here, we used genetically modified mice and demonstrate that genetic ablation of Mtdh inhibits breast cancer development through disrupting the interaction with staphylococcal nuclease domain-containing 1 (SND1), which is required to sustain breast cancer progression in established tumors. We performed a small-molecule compound screening to identify a class of specific inhibitors that disrupts the protein-protein interaction (PPI) between MTDH and SND1 and show that our lead candidate compounds C26-A2 and C26-A6 suppressed tumor growth and metastasis and enhanced chemotherapy sensitivity in preclinical models of triple-negative breast cancer (TNBC). Our results demonstrate a significant therapeutic potential in targeting the MTDH-SND1 complex and identify a new class of therapeutic agents for metastatic breast cancer.

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.

Discovery of Novel Small Molecule Inhibitors Disrupting the PCSK9-LDLR Interaction

Proprotein convertase subtilisin kexin 9 (PCSK9) has been identified as a reliable therapeutic target for hypercholesterolemia and coronary artery heart diseases since the monoclonal antibodies of PCSK9 have launched. Disrupting the protein-protein interaction (PPI) between PCSK9 and the low-density lipoprotein receptor (LDLR) has been considered as a promising approach for developing PCSK9 inhibitors. However, PPIs have been traditionally considered difficult to target by small molecules since the PPI surface is usually large, flat, featureless, and without a "pocket" or "groove" for ligand binding. The PCSK9-LDLR PPI interface is such a typical case. In this study, a potential binding pocket was generated on the PCSK9-LDLR PPI surface of PCSK9 through induced-fit docking. On the basis of this induced binding pocket, virtual screening, molecular dynamics (MD) simulation, and biological evaluations have been applied for the identification of novel small molecule inhibitors of PCSK9-LDLR PPI. Among the selected compounds, compound 13 exhibited certain PCSK9-LDLR PPI inhibitory activity (IC₅₀: 7.57 ± 1.40 μM). The direct binding affinity between 13 and PCSK9 was determined with a K_D value of 2.50 ± 0.73 μM. The LDLR uptake function could be also restored to a certain extent by 13 in HepG2 cells. This well-characterized hit compound will facilitate the further development of novel small molecule inhibitors of PCSK9-LDLR PPI.

Systematic characterization of the absorbed components of Ligustri Lucidi Fructus and their metabolic pathways in rat plasma by ultra-high-performance liquid chromatography-Q-Exactive Orbitrap tandem mass spectrometry combined with network pharmacology

Ligustri Lucidi Fructus is a dried and mature fruit of Ligustrum lucidum Ait., which has the effects of nourishing liver and kidney. Herein, an accurate and sensitive method was established for the separation and identification of the absorbed constituents and metabolites of Ligustri Lucidi Fructus in rat plasma based on ultra-high-performance liquid chromatography-Q-Exactive Orbitrap tandem mass spectrometry. A total of 73 prototype constituents and 148 metabolites were identified or characterized in administered plasma, and the possible metabolic pathways of constituents mainly involved hydroxylation, sulfation, demethylation, and glucuronidation. Besides, the network pharmacology was further investigated to illuminate its potential mechanism of treatment for liver injury by the biological targets regulating related pathways. Network pharmacological analysis showed that target components through 399 targets regulate 220 pathways. The docking results showed that 36 key target components were closely related to liver injury. Overall, the study clearly presented the metabolic processes of Ligustri Lucidi Fructus and gave a comprehensive metabolic profile of Ligustri Lucidi Fructus in vivo first. Combining with network pharmacology and molecular docking discovered potential drug targets and disclose the biological processes of Ligustri Lucidi Fructus, which will be a viable step toward uncovering the secret mask of study for traditional Chinese medicine.

Analysis of physicochemical properties of protein-protein interaction modulators suggests stronger alignment with the "rule of five"

Despite the important roles played by protein-protein interactions (PPIs) in disease, they have been long considered as 'undruggable'. However, recent advances have suggested that PPIs are druggable but may not follow conventional rules of 'drug ability'. Here we explore which physicochemical parameters are essential for a PPI modulator to be a clinical drug by analysing the physicochemical properties of small-molecule PPI modulators in the market, in clinical trials, and published. Our analysis reveals that those compounds currently on the market have a larger range of values for most of the physicochemical parameters, whereas those in clinical trials fit much more stringently to standard drug-like parameters. This observation was particularly true for molecular weight, clog P and topological polar surface area, where aside from a few outliers, most of the compounds in clinical trials fit within standard drug-like parameters. This implies that the newer PPI modulators are more drug-like than those currently on the market, suggesting that designing new PPI-specific screening libraries should remain within standard drug-like parameters in order to obtain a clinical candidate. Taken together, our analysis has important implications for designing future drug discovery campaigns aimed at targeting PPIs.

Lights, Camera, Interaction: Studying Protein-Protein Interactions of the ER Protein Translocase in Living Cells

Various landmark studies have revealed structures and functions of the Sec61/SecY complex in all domains of live demonstrating the conserved nature of this ancestral protein translocase. While the bacterial homolog of the Sec61 complex resides in the plasma membrane, the eukaryotic counterpart manages the transfer of precursor proteins into or across the membrane of the endoplasmic reticulum (ER). Sec61 complexes are accompanied by a set of dynamically recruited auxiliary proteins assisting the transport of certain precursor polypeptides. TRAP and Sec62/Sec63 are two auxiliary protein complexes in mammalian cells that have been characterized by structural and biochemical methods. Using these ER membrane protein complexes for our proof-of-concept study, we aimed to detect interactions of membrane proteins in living mammalian cells under physiological conditions. Bimolecular luminescence complementation and competition was used to demonstrate multiple protein-protein interactions of different topological layouts. In addition to the interaction of the soluble catalytic and regulatory subunits of the cytosolic protein kinase A, we detected interactions of ER membrane proteins that either belong to the same multimeric protein complex (intra-complex interactions: Sec61α-Sec61β, TRAPα-TRAPβ) or protein complexes in juxtaposition (inter-complex interactions: Sec61α-TRAPα, Sec61α-Sec63, and Sec61β-Sec63). In the process, we established further control elements like synthetic peptide complementation for expression profiling of fusion constructs and protease-mediated reporter degradation demonstrating the cytosolic localization of a reporter complementation. Ease of use and flexibility of the approach presented here will spur further research regarding the dynamics of protein-protein interactions in response to changing cellular conditions in living cells.

Allosteric Inhibition of the Tumor-Promoting Interaction between AIMP2-DX2 and HSP70

Although protein-protein interactions (PPIs) have emerged as an attractive therapeutic target space, the identification of chemicals that effectively inhibit PPIs remains challenging. Here, we identified through library screening a chemical probe, compound 1 that can inhibit the tumor-promoting interaction between the oncogenic factor AIMP2-DX2 and HSP70. We found that compound 1 binds to the N-terminal subdomain of glutathione S transferase (GST-N) of AIMP2-DX2, causing a direct steric clash with HSP70 and an intramolecular interaction between the N-terminal flexible region (NFR) and the GST-N of AIMP2-DX2, which induces masking of the HSP70 binding region during molecular dynamics and mutation studies. Compound 1 thus interferes with the AIMP2-DX2 and HSP70 interaction and suppresses the growth of cancer cells that express high levels of AIMP2-DX2 in vitro and in preliminary in vivo experiment. This work provides an example showing that allosteric conformational changes induced by chemicals can be a way to control pathologic PPIs. Significance Statement Compound 1 is a promising protein-protein interaction inhibitor between AIMP2-DX2 and HSP70 for cancer therapy by the mechanism with allosteric modulation as well as competitive binding. It seems to induce allosteric conformational change of AIMP2-DX2 proteins and direct binding clash between AIMP2-DX2 and HSP70. The compound reduced the level of AIMP2-DX2 in ubiquitin-dependent manner via suppression of binding between AIMP2-DX2 and HSP70, and suppressed the growth of cancer cells highly expressing AIMP2-DX2 in vitro and in preliminary in vivo experiment.

Peptide-Based Inhibitors for SARS-CoV-2 and SARS-CoV

The COVID‐19 (coronavirus disease) global pandemic, caused by the spread of the SARS‐CoV‐2 (severe acute respiratory syndrome coronavirus 2) virus, currently has limited treatment options which include vaccines, anti‐virals, and repurposed therapeutics. With their high specificity, tunability, and biocompatibility, small molecules like peptides are positioned to act as key players in combating SARS‐CoV‐2, and can be readily modified to match viral mutation rate. A recent expansion of the understanding of the viral structure and entry mechanisms has led to the proliferation of therapeutic viral entry inhibitors. In this comprehensive review, inhibitors of SARS and SARS‐CoV‐2 are investigated and discussed based on therapeutic design, inhibitory mechanistic approaches, and common targets. Peptide therapeutics are highlighted, which have demonstrated in vitro or in vivo efficacy, discuss advantages of peptide therapeutics, and common strategies in identifying targets for viral inhibition.

Peptide Based Inhibitors of Protein Binding to the Mitogen-Activated Protein Kinase Docking Groove

Mitogen-activated protein kinases (MAPK) are important regulatory units in cells and they take part in the regulation of many cellular functions such as cell division, differentiation or apoptosis. All MAPKs have a shallow docking groove that interacts with linear binding motifs of their substrate proteins and their regulatory proteins such as kinases, phosphatases, scaffolds. Inhibition of these protein–protein interactions may reduce or abolish the activity of the targeted kinase. Based on the wide range of their biological activity, this kind of inhibition can be useful in the treatment of many disorders like tumors, inflammation or undesired cell apoptosis. In this study a linear binding motif from the RHDF1 protein—a 15 amino acids long peptide—was selected for optimization to increase its cellular uptake but retaining its low micromolar binding affinity. First, we synthesized an octaarginine conjugate that showed efficient cellular uptake. Next, we set out to reduce the size of this construct. We were able to decrease the length of the original peptide, and to increase its cellular uptake with specific chemical modifications. These new constructs bound better to ERK2 and p38 kinases than the original peptide and they showed markedly increased cellular uptake. The new octaarginine conjugate and one of the minimized bicyclic derivatives could inhibit the phosphorylation of intracellular ERK or p38. However, the modulation of MAPK phosphorylation levels by these cell-penetrating peptides were complex, despite that in biochemical assays they all inhibited MAPK-substrate binding as well as phosphorylation. The optimized peptides depending on the applied concentration caused an expected decrease, but also some unexpected increase in MAPK phosphorylation patterns in the cell. This possibly reflects the complexity of MAPK docking groove mediated protein–protein interactions including bone fide MAPK clients such activator kinases, deactivating phosphatases or regulatory scaffolds. Thus, our findings with optimized cell-penetrating “inhibitory” peptides highlight the opportunities but also the pitfalls of docking peptide based MAPK activity regulation and call for a better quantitative understanding of MAPK mediated protein–protein interactions in cells.