State-of-the-art strategies for targeting protein-protein interactions by small-molecule inhibitors

The future of therapeutic options for hereditary angioedema

Hereditary angioedema (HAE) is a rare genetic condition causing unpredictable and severe episodes of angioedema that are debilitating and life-threatening. Moreover, HAE can be classified into HAE due to C1-esterase inhibitor deficiency (HAE-C1INH) or HAE with normal C1INH. Moreover, HAE-C1INH is subcategorized as types I and II based on deficient or dysfunctional circulating C1INH protein resulting from inherited or spontaneous mutations in the SERPING1 gene leading to uncontrolled factor XII/plasma kallikrein activation and excessive bradykinin production. Bradykinin-2 receptor activation leads to vasodilation, increased vascular permeability, and smooth muscle contractions, resulting in subcutaneous or submucosal fluid extravasation that can affect the face, extremities, airway, and gastrointestinal and genitourinary systems. Furthermore, HAE with normal C1INH is caused by either a known or unknown genetic mutation, and the mechanisms are less well-established but most forms are thought to be related to bradykinin signaling with a similar presentation as HAE-C1INH despite normal levels of C1INH protein and function. Current HAE management strategies include on-demand and prophylactic treatments which replace C1INH, reduce kallikrein activity, or block bradykinin binding to the bradykinin B2 receptor. With the advent of additional small molecule inhibitors, monoclonal antibodies, RNA-targeted therapies, gene therapies, and gene modification approaches, preclinical studies and human clinical trials are underway to further expand therapeutic options in HAE. This review article will briefly summarize current HAE treatments and provide an overview of potential future therapies for HAE.

Production of marine-derived bioactive peptide molecules for industrial applications: A reverse engineering approach

This review examines a wide range of marine microbial-derived bioactive peptide molecules, emphasizing the significance of reverse engineering in their production. The discussion encompasses the advancements in Marine Natural Products (MNPs) bio-manufacturing through the integration of omics-driven microbial engineering and bioinformatics. The distinctive features of non-ribosomally synthesised peptides (NRPs), and ribosomally synthesised precursor peptides (RiPP) biosynthesis is elucidated and presented. Additionally, the article delves into the origins of common peptide modifications. It highlights various genome mining approaches for the targeted identification of Biosynthetic Gene Clusters (BGCs) and novel RiPP and NRPs-derived peptides. The review aims to demonstrate the advancements, prospects, and obstacles in engineering both RiPP and NRP biosynthetic pathways.

Carbene Footprinting Directs Design of Genetically Encoded Proximity-Reactive Protein Binders

Genetically encoding proximal-reactive unnatural amino acids (PrUaas), such as fluorosulfate-l-tyrosine (FSY), into natural proteins of interest (POI) confer the POI with the ability to covalently bind to its interacting proteins (IPs). The PrUaa-incorporated POIs hold promise for blocking undesirable POI-IP interactions. Selecting appropriate PrUaa anchor sites is crucial, but it remains challenging with the current methodology, which heavily relies on crystallography to identify the proximal residues between the POIs and the IPs for the PrUaa anchorage. To address the challenge, here, we propose a footprinting-directed genetically encoded covalent binder (footprinting-GECB) approach. This approach employs carbene footprinting, a structural mass spectrometry (MS) technique that quantifies the extent of labeling of the POI following the addition of its IP, and thus identifies the responsive residues. By genetically encoding PrUaa into these responsive sites, POI variants with covalent bonding ability to its IP can be produced without the need for crystallography. Using the POI-IP model, KRAS/RAF1, we showed that engineering FSY at the footprint-assigned KRAS residue resulted in a KRAS variant that can bind irreversibly to RAF1. Additionally, we inserted FSY at the responsive residue in RAF1 upon footprinting the oncogenic KRASG12D/RAF1, which lacks crystal structure, and generated a covalent binder to KRASG12D. Together, we demonstrated that by adopting carbene footprinting to direct PrUaa anchorage, we can greatly expand the opportunities for designing covalent protein binders for PPIs without relying on crystallography. This holds promise for creating effective PPI inhibitors and supports both fundamental research and biotherapeutics development.

Programming interchangeable and reversible heterooligomeric protein self-assembly using a bifunctional ligand

Protein design for self-assembly allows us to explore the emergence of protein-protein interfaces through various chemical interactions. Heterooligomers, unlike homooligomers, inherently offer a comprehensive range of structural and functional variations. Besides, the macromolecular repertoire and their applications would significantly expand if protein components could be easily interchangeable. This study demonstrates that a rationally designed bifunctional linker containing an enzyme inhibitor and maleimide can guide the formation of diverse protein heterooligomers in an easily applicable and exchangeable manner without extensive sequence optimizations. As proof of concept, we selected four structurally and functionally unrelated proteins, carbonic anhydrase, aldolase, acetyltransferase, and encapsulin, as building block proteins. The combinations of two proteins with the bifunctional linker yielded four two-component heterooligomers with discrete sizes, shapes, and enzyme activities. Besides, the overall size and formation kinetics of the heterooligomers alter upon adding metal chelators, acidic buffer components, and reducing agents, showing the reversibility and tunability in the protein self-assembly. Given that the functional groups of both the linker and protein components are readily interchangeable, our work broadens the scope of protein-assembled architectures and their potential applications as functional biomaterials.

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.

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.

Medicinal Chemistry Insights into the Development of Small-Molecule Kelch-Like ECH-Associated Protein 1-Nuclear Factor Erythroid 2-Related Factor 2 (Keap1-Nrf2) Protein-Protein Interaction Inhibitors

Oxidative stress has been implicated in a wide range of pathological conditions. The transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2) exerts a central role in regulating the cellular defense system against oxidative and electrophilic insults. Nonelectrophilic inhibition of the protein-protein interaction (PPI) between Kelch-like ECH-associated protein 1 (Keap1) and Nrf2 has become a promising approach to activate Nrf2. Recently, multiple drug discovery strategies have facilitated the development of small-molecule Keap1-Nrf2 PPI inhibitors with potent activity and favorable drug-like properties. In this Perspective, we summarize the latest progress of small-molecule Keap1-Nrf2 PPI inhibitors from medicinal chemistry insights and discuss future prospects and challenges in this field.

Selected Approaches to Disrupting Protein-Protein Interactions within the MAPK/RAS Pathway

Within the MAPK/RAS pathway, there exists a plethora of protein-protein interactions (PPIs). For many years, scientists have focused efforts on drugging KRAS and its effectors in hopes to provide much needed therapies for patients with KRAS-mutant driven cancers. In this review, we focus on recent strategies to inhibit RAS-signaling via disrupting PPIs associated with SOS1, RAF, PDEδ, Grb2, and RAS.

Identification of a short ACE2-derived stapled peptide targeting the SARS-CoV-2 spike protein

The design and synthesis of a series of peptide derivatives based on a short ACE2 α-helix 1 epitope and subsequent [i - i+4] stapling of the secondary structure resulted in the identification of a 9-mer peptide capable to compete with recombinant ACE2 towards Spike RBD in the micromolar range. Specifically, SARS-CoV-2 Spike inhibitor screening based on colorimetric ELISA assay and structural studies by circular dichroism showed the ring-closing metathesis cyclization being capable to stabilize the helical structure of the 9-mer ³⁴HEAEDLFYQ⁴² epitope better than the triazole stapling via click chemistry. MD simulations showed the stapled peptide being able not only to bind the Spike RBD, sterically interfering with ACE2, but also showing higher affinity to the target as compared to parent epitope.

Computational design of cyclic peptides to inhibit protein-peptide interactions

Many protein-protein interactions result from the binding of one folded protein with one short peptide segment, such as complexes formed by SH3 or PDZ domains. These transient protein-peptide interactions are notably involved in cellular signaling pathways and generally have low affinities, which opens the possibility to design competitive inhibitors of these complexes. We present and assess here our computational approach, called Des3PI, to design de novo cyclic peptides with potential high affinity for protein surfaces involved in interactions with peptide segments. The results were not conclusive for two receptors, the αVβ3 integrin and the CXCR4 chemokine receptor, but were promising in the case of SH3 and PDZ domains: For the former, Des3PI was able to find at least one cyclic sequence with six hotspots that binds a SH3 domain with a better theoretical affinity to the known proline-rich RLP2 peptide. For the latter, Des3PI could identify at least four cyclic sequences with four or five hotspots that have lower binding free energies computed by the MM-PBSA method than the reference peptide GKAP.

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.

Fragment-based drug discovery supports drugging 'undruggable' protein-protein interactions

Protein-protein interactions (PPIs) have important roles in various cellular processes, but are commonly described as 'undruggable' therapeutic targets due to their large, flat, featureless interfaces. Fragment-based drug discovery (FBDD) has achieved great success in modulating PPIs, with more than ten compounds in clinical trials. Here, we highlight the progress of FBDD in modulating PPIs for therapeutic development. Targeting hot spots that have essential roles in both fragment binding and PPIs provides a shortcut for the development of PPI modulators via FBDD. We highlight successful cases of cracking the 'undruggable' problems of PPIs using fragment-based approaches. We also introduce new technologies and future trends. Thus, we hope that this review will provide useful guidance for drug discovery targeting PPIs.

Advances of Artificial Intelligence in Anti-Cancer Drug Design: A Review of the Past Decade

Anti-cancer drug design has been acknowledged as a complicated, expensive, time-consuming, and challenging task. How to reduce the research costs and speed up the development process of anti-cancer drug designs has become a challenging and urgent question for the pharmaceutical industry. Computer-aided drug design methods have played a major role in the development of cancer treatments for over three decades. Recently, artificial intelligence has emerged as a powerful and promising technology for faster, cheaper, and more effective anti-cancer drug designs. This study is a narrative review that reviews a wide range of applications of artificial intelligence-based methods in anti-cancer drug design. We further clarify the fundamental principles of these methods, along with their advantages and disadvantages. Furthermore, we collate a large number of databases, including the omics database, the epigenomics database, the chemical compound database, and drug databases. Other researchers can consider them and adapt them to their own requirements.

A biocatalytic peptidobiosensing molecular bridge for detecting osteosarcoma marker protein

A biosensing scheme requiring only one-step sample incubation before signal collection, and using a compact "three-in-one" probe of target-binding, signal conversion, and amplification, may greatly simplify the design of biosensors. Therefore, sparing the multi-step addition of enzymes, protein, and nanomaterial, as well as the associated complexity and non-specific interactions. In this work, a peptide probe aimed at such compact features has been designed, based on protein-triggered, conformation-driven, and Cu (II) facilitated side-chain di-tyrosine cyclization. This design can use target-probe recognition to induce discriminated cross-linking and self-cleavage of the probe, resulting in retention or dissociation of a signal amplification motif from the search and consequently quantitative detection performance. The method has also been tested preliminarily in fractioned osteosarcoma clinical samples, showing an acceptable coherence between signal readout and clinical diagnosis. On the basis of these early findings, it is reasonable to assume that the proposed probe will be beneficial for the next development of tumor screening and prognosis sensors.

Medicinal Chemistry Strategies for the Development of Inhibitors Disrupting β-Catenin's Interactions with Its Nuclear Partners

Dysregulation of the Wnt/β-catenin signaling pathway is strongly associated with various aspects of cancer, including tumor initiation, proliferation, and metastasis as well as antitumor immunity, and presents a promising opportunity for cancer therapy. Wnt/β-catenin signaling activation increases nuclear dephosphorylated β-catenin levels, resulting in β-catenin binding to TCF and additional cotranscription factors, such as BCL9, CBP, and p300. Therefore, directly disrupting β-catenin's interactions with these nuclear partners holds promise for the effective and selective suppression of the aberrant activation of Wnt/β-catenin signaling. Herein, we summarize recent advances in biochemical techniques and medicinal chemistry strategies used to identify potent peptide-based and small-molecule inhibitors that directly disrupt β-catenin's interactions with its nuclear binding partners. We discuss the challenges involved in developing drug-like inhibitors that target the interactions of β-catenin and its nuclear binding partner into therapeutic agents.

Design and Synthesis of Novel Helix Mimetics Based on the Covalent H-Bond Replacement and Amide Surrogate

A novel hydrogen bond surrogate-based (HBS) α-helix mimetic was designed by the combination of covalent H-bond replacement and the use of an ether linkage to substitute an amide bond within a short peptide sequence. The new helix template could be placed in position other than the N-terminus of a short peptide, and the CD studies demonstrate that the template adopts stable conformations in aqueous buffer at exceptionally high temperatures.

Integrating Protein Interaction Surface Prediction with a Fragment-Based Drug Design: Automatic Design of New Leads with Fragments on Energy Surfaces

Protein-protein interactions (PPIs) have emerged in the past years as significant pharmacological targets in the development of new therapeutics due to their key roles in determining pathological pathways. Herein, we present fragments on energy surfaces, a simple and general design strategy that integrates the analysis of the dynamic and energetic signatures of proteins to unveil the substructures involved in PPIs, with docking, selection, and combination of drug-like fragments to generate new PPI inhibitor candidates. Specifically, structural representatives of the target protein are used as inputs for the blind physics-based prediction of potential protein interaction surfaces using the matrix of low coupling energy decomposition method. The predicted interaction surfaces are subdivided into overlapping windows that are used as templates to direct the docking and combination of fragments representative of moieties typically found in active drugs. This protocol is then applied and validated using structurally diverse, important PPI targets as test systems. We demonstrate that our approach facilitates the exploration of the molecular diversity space of potential ligands, with no requirement of prior information on the location and properties of interaction surfaces or on the structures of potential lead compounds. Importantly, the hit molecules that emerge from our ab initio design share high chemical similarity with experimentally tested active PPI inhibitors. We propose that the protocol we describe here represents a valuable means of generating initial leads against difficult targets for further development and refinement.

Using the Cyclotide Scaffold for Targeting Biomolecular Interactions in Drug Development

This review provides an overview of the properties of cyclotides and their potential for developing novel peptide-based therapeutics. The selective disruption of protein–protein interactions remains challenging, as the interacting surfaces are relatively large and flat. However, highly constrained polypeptide-based molecular frameworks with cell-permeability properties, such as the cyclotide scaffold, have shown great promise for targeting those biomolecular interactions. The use of molecular techniques, such as epitope grafting and molecular evolution employing the cyclotide scaffold, has shown to be highly effective for selecting bioactive cyclotides.

Small Molecules as Toll-like Receptor 4 Modulators Drug and In-House Computational Repurposing

The innate immunity toll-like receptor 4 (TLR4) system is a receptor of paramount importance as a therapeutic target. Virtual screening following a “computer-aided drug repurposing” approach was applied to the discovery of novel TLR4 modulators with a non-lipopolysaccharide-like structure. We screened almost 29,000 approved drugs and drug-like molecules from commercial, public, and in-house academia chemical libraries and, after biological assays, identified several compounds with TLR4 antagonist activity. Our computational protocol showed to be a robust approach for the identification of hits with drug-like scaffolds as possible inhibitors of the TLR4 innate immune pathways. Our collaborative work broadens the chemical diversity for inspiration of new classes of TLR4 modulators.

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.

Fragment hopping protocol for the design of small-molecule protein-protein interaction inhibitors

Fragment-based ligand discovery (FBLD) is one of the most successful approaches to designing small-molecule protein-protein interaction (PPI) inhibitors. The incorporation of computational tools to FBLD allows the exploration of chemical space in a time- and cost-efficient manner. Herein, a computational protocol for the development of small-molecule PPI inhibitors using fragment hopping, a fragment-based de novo design approach, is described and a case study is presented to illustrate the efficiency of this protocol. Fragment hopping facilitates the design of PPI inhibitors from scratch solely based on key binding features in the PPI complex structure. This approach is an open system that enables the inclusion of different state-of-the-art programs and softwares to improve its performances.

Abiotic Synthetic Antibodies to Target a Specific Protein Domain and Inhibit Its Function

The Bacillus thuringiensis (Bt) Cry proteins are widely used in insect pest control. Despite their economic benefits, remaining concerns over potential ecological and health risks warrant their ongoing surveillance. Affinity reagents, most often antibodies, protein scaffolds, and aptamers, are the traditional tools used for protein binding and detection. We report a synthetic antibody (SA) alternative to traditional biological affinity reagents for binding Bt Cry proteins. Analysis of hotspots of the Bt Cry protein-insect midgut cadherin-like receptor complexes was used for the design of the SA. The SA was selected from a small focused library of hydrogel copolymers containing functional monomers complementary to key exposed hotspots of Bt Cry proteins. A directed chemical evolution identified a SA, APhe-NP23, with affinity and selectivity for Bt Cry1Ab/Ac proteins. The putative intermolecular polymer-protein interfaces were identified by the SA's uptake of Bt Cry1Ac pepsin hydrolysates, binding epitope mutation studies, and protein-protein inhibition studies of the toxin binding to its native insect receptor binding domains. The SA inhibitor binds to the same protein domains as the insect's cadherin-like receptors, Bt-R₁ and SeCad1b. The SA binds rapidly to Bt Cry1Ab/Ac with high capacity, is pH-responsive, and is synthesized reproducibly. We believe that a hotspot-directed approach is general for creation of abiotic protein affinity reagents that target functional protein domains. Affinity ligands are typically high-information content biologicals. Their structure and function are determined from their amino acid or oligo sequence. In contract, the SA described in this work is a statistical copolymer that lacks sequence specificity. These results are an important contribution to the concept that randomness and biospecificity are not mutually exclusive.

Abrogating the Interaction Between p53 and Mortalin (Grp75/HSPA9/mtHsp70) for Cancer Therapy: The Story so far

p53 is a transcription factor that activates the expression of a set of genes that serve as a critical barrier to oncogenesis. Inactivation of p53 is the most common characteristic in sporadic human cancers. Mortalin is a differentially sub-cellularly localized member of the heat shock protein 70 family of chaperones that has essential mitochondrial and extra-mitochondrial functions. Elevated mortalin levels in multiple cancerous tissues and tumor-derived cell lines emphasized its key role in oncogenesis. One of mortalin’s major oncogenic roles is the inactivation of p53. Mortalin binds to p53 sequestering it in the cytoplasm. Hence, p53 cannot freely shuttle to the nucleus to perform its tumor suppressor functions as a transcription factor. This protein-protein interaction was reported to be cancer-specific, hence, a selective druggable target for a rationalistic cancer therapeutic strategy. In this review article, the chronological identification of mortalin-p53 interactions is summarized, the challenges and general strategies for targeting protein-protein interactions are briefly discussed, and information about compounds that have been reported to abrogate mortalin-p53 interaction is provided. Finally, the reasons why the disruption of this druggable interaction has not yet been applied clinically are discussed.

A Bionic-Homodimerization Strategy for Optimizing Modulators of Protein-Protein Interactions: From Statistical Mechanics Theory to Potential Clinical Translation

Emerging protein-protein interaction (PPI) modulators have brought out exciting ability as therapeutics in human diseases, but its clinical translation has been greatly hampered by the limited affinity. Inspired by the homodimerize structure of antibody, the homodimerization contributes hugely to generating the optimized affinity is conjectured. Herein, a statistical-mechanics-theory-guided method is established to quantize the affinity of ligands with different topologies through analyzing the change of enthalpy and the loss of translational and rotational entropies. A peptide modulator for p53-MDM2 termed CPAP is used to homodimerize connecting, and this simple homodimerization can significantly increase the affinity. To realize the cellular internalization and tumor accumulation, Dimer CPAP and Mono CPAP are nanoengineered into gold(I)-CPAP supermolecule by the aurophilic interaction-driven self-assembly. Nano-Dimer CPAP potently suppressed tumor growth in lung cancer allograft model and a patient-derived xenograft model in more action than Nano-Mono CPAP, while keeping a favorable drug safety profile. This work not only presents a physico-mechanical method for calculating the affinity of PPI modulators, but also provides a simple yet robust homodimerization strategy to optimize the affinity of PPI modulators.

Methods for the Discovery and Identification of Small Molecules Targeting Oxidative Stress-Related Protein–Protein Interactions: An Update

The oxidative stress response pathway is one of the hotspots of current pharmaceutical research. Many proteins involved in these pathways work through protein–protein interactions (PPIs). Hence, targeting PPI to develop drugs for an oxidative stress response is a promising strategy. In recent years, small molecules targeting protein–protein interactions (PPIs), which provide efficient methods for drug discovery, are being investigated by an increasing number of studies. However, unlike the enzyme–ligand binding mode, PPIs usually exhibit large and dynamic binding interfaces, which raise additional challenges for the discovery and optimization of small molecules and for the biochemical techniques used to screen compounds and study structure–activity relationships (SARs). Currently, multiple types of PPIs have been clustered into different classes, which make it difficult to design stationary methods for small molecules. Deficient experimental methods are plaguing medicinal chemists and are becoming a major challenge in the discovery of PPI inhibitors. In this review, we present current methods that are specifically used in the discovery and identification of small molecules that target oxidative stress-related PPIs, including proximity-based, affinity-based, competition-based, structure-guided, and function-based methods. Our aim is to introduce feasible methods and their characteristics that are implemented in the discovery of small molecules for different types of PPIs. For each of these methods, we highlight successful examples of PPI inhibitors associated with oxidative stress to illustrate the strategies and provide insights for further design.

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.

Discovery of phenylpyrrolidine derivatives as a novel class of retinol binding protein 4 (RBP4) reducers

Retinol-binding protein 4 (RBP4) is a potential drug target for metabolic and ophthalmologic diseases. A high-throughput screening of our compound library has identified a small-molecule RBP4 reducer 7a, as a hit compound. Aiming to provide a suitable tool for investigating the pharmacological effects of RBP4 reducers, we conducted a structure-activity relationship study of 7a. Exploration of the aryl head, oxazole core, and propanoic acid tail of 7a resulted in the discovery of novel, potent, and orally available phenylpyrrolidine derivatives 43b and 43c. Compound 43b had a potent and long-lasting blood RBP4-level-reducing effect when orally administered to mice at a dose as low as 0.3 mg/kg.

Divergent, C-C Bond Forming Macrocyclizations Using Modular Sulfonylhydrazone and Derived Substrates

A divergent approach to C-C bond forming macrocycle construction is described. Modular sulfonylhydrazone and derived pyridotriazole substrates with three key building blocks have been constructed and cyclized to afford diverse macrocyclic frameworks. Broad substrate scope and functional group tolerance have been demonstrated. In addition, site-selective postfunctionalization allowed for further diversification of macrocyclic cores.

In Silico Identification and Evaluation of Natural Products as Potential Tumor Necrosis Factor Function Inhibitors Using Advanced Enalos Asclepios KNIME Nodes

Tumor necrosis factor (TNF) is a regulator of several chronic inflammatory diseases, such as rheumatoid arthritis. Although anti-TNF biologics have been used in clinic, they render several drawbacks, such as patients' progressive immunodeficiency and loss of response, high cost, and intravenous administration. In order to find new potential anti-TNF small molecule inhibitors, we employed an in silico approach, aiming to find natural products, analogs of Ampelopsin H, a compound that blocks the formation of TNF active trimer. Two out of nine commercially available compounds tested, Nepalensinol B and Miyabenol A, efficiently reduced TNF-induced cytotoxicity in L929 cells and production of chemokines in mice joints' synovial fibroblasts, while Nepalensinol B also abolished TNF-TNFR1 binding in non-toxic concentrations. The binding mode of the compounds was further investigated by molecular dynamics and free energy calculation studies, using and advancing the Enalos Asclepios pipeline. Conclusively, we propose that Nepalensinol B, characterized by the lowest free energy of binding and by a higher number of hydrogen bonds with TNF, qualifies as a potential lead compound for TNF inhibitors' drug development. Finally, the upgraded Enalos Asclepios pipeline can be used for improved identification of new therapeutics against TNF-mediated chronic inflammatory diseases, providing state-of-the-art insight on their binding mode.

Hot Spot Analysis of YAP-TEAD Protein-Protein Interaction Using the Fragment Molecular Orbital Method and Its Application for Inhibitor Discovery

The Hippo pathway is an important signaling pathway modulating growth control and cancer cell proliferation. Dysregulation of the Hippo pathway is a common feature of several types of cancer cells. The modulation of the interaction between yes-associated protein (YAP) and transcriptional enhancer associated domain (TEAD) in the Hippo pathway is considered an attractive target for cancer therapeutic development, although the inhibition of PPI is a challenging task. In order to investigate the hot spots of the YAP and TEAD1 interacting complex, an ab initio Fragment Molecular Orbital (FMO) method was introduced. With the hot spots, pharmacophores for the inhibitor design were constructed, then virtual screening was performed to an in-house library. Next, we performed molecular docking simulations and FMO calculations for screening results to study the binding modes and affinities between PPI inhibitors and TEAD1. As a result of the virtual screening, three compounds were selected as virtual hit compounds. In order to confirm their biological activities, cellular (luciferase activity, proximity ligation assay and wound healing assay in A375 cells, qRT-PCR in HEK 293T cells) and biophysical assays (surface plasmon resonance assays) were performed. Based on the findings of the study, we propose a novel PPI inhibitor BY03 and demonstrate a profitable strategy to analyze YAP-TEAD PPI and discover novel PPI inhibitors.

Synthesis of Three-Dimensional (Di)Azatricyclododecene Scaffold and Its Application to Peptidomimetics

A novel sp³ carbon-rich tricyclic 3D scaffold-based peptide mimetic compound library was constructed to target protein-protein interactions. Tricyclic framework 7 was synthesized from 9-azabicyclo[3,3,1]nonan-3-one (11) via a gold(I)-catalyzed Conia-ene reaction. The electron-donating group on the pendant alkyne of cyclization precursor 12 b-e was the key to forming 6-endo-dig cyclized product 7 with complete regioselectivity. Using the synthetic strategy for regioselective construction of bridged tricyclic framework 7, a diazatricyclododecene 3D-scaffold 8 a, which enables the introduction of substituents into the scaffold to mimic amino acid side chains, was designed and synthesized. The peptide mimetics 21 a-u were synthesized via step-by-step installation of three substituents on diazatricyclododecene scaffold 8 a. Compounds 21 a-h were synthesized as α-helix peptide mimics of hydrophobic ZZxxZ and ZxxZZ sequences (Z=Leu or Phe) and subjected to cell-based assays: antiproliferative activity, HIF-1 transcriptional activity which is considered to affect cancer malignancy, and antiviral activity against rabies virus. Compound 21 a showed the strongest inhibitory activity of HIF-1 transcriptional activity (IC₅₀ =4.1±0.8 μM), whereas compounds 21 a-g showed antiviral activity with IC₅₀ values of 4.2-12.4 μM, suggesting that the 3D-scaffold 8 a has potential as a versatile peptide mimic skeleton.

Exploring the chemical space of protein-protein interaction inhibitors through machine learning

Although protein-protein interactions (PPIs) have emerged as the basis of potential new therapeutic approaches, targeting intracellular PPIs with small molecule inhibitors is conventionally considered highly challenging. Driven by increasing research efforts, success rates have increased significantly in recent years. In this study, we analyze the physicochemical properties of 9351 non-redundant inhibitors present in the iPPI-DB and TIMBAL databases to define a computational model for active compounds acting against PPI targets. Principle component analysis (PCA) and k-means clustering were used to identify plausible PPI targets in regions of interest in the active group in the chemical space between active and inactive iPPI compounds. Notably, the uniquely defined active group exhibited distinct differences in activity compared with other active compounds. These results demonstrate that active compounds with regions of interest in the chemical space may be expected to provide insights into potential PPI inhibitors for particular protein targets.

High-Throughput Screening to Identify Inhibitors of SSB-Protein Interactions

The bacterial single-stranded DNA-binding protein (SSB) uses an acidic C-terminal tail to interact with over a dozen proteins, acting as a genome maintenance hub. These SSB-protein interactions are essential, as mutations to the C-terminal tail that disrupt these interactions are lethal in Escherichia coli. While the roles of individual SSB-protein interactions have been dissected with mutational studies, small-molecule inhibitors of these interactions could serve as valuable research tools and have potential as novel antimicrobial agents. This chapter describes a high-throughput screening campaign used to identify inhibitors of SSB-protein interactions. A screen targeting the PriA-SSB interface from Klebsiella pneumoniae is presented as an example, but the methods may be adapted to target nearly any SSB interaction.

PPI Modulators of E6 as Potential Targeted Therapeutics for Cervical Cancer: Progress and Challenges in Targeting E6

Advanced cervical cancer is primarily managed using cytotoxic therapies, despite evidence of limited efficacy and known toxicity. There is a current lack of alternative therapeutics to treat the disease more effectively. As such, there have been more research endeavors to develop targeted therapies directed at oncogenic host cellular targets over the past 4 decades, but thus far, only marginal gains in survival have been realized. The E6 oncoprotein, a protein of human papillomavirus origin that functionally inactivates various cellular antitumor proteins through protein–protein interactions (PPIs), represents an alternative target and intriguing opportunity to identify novel and potentially effective therapies to treat cervical cancer. Published research has reported a number of peptide and small-molecule modulators targeting the PPIs of E6 in various cell-based models. However, the reported compounds have rarely been well characterized in animal or human subjects. This indicates that while notable progress has been made in targeting E6, more extensive research is needed to accelerate the optimization of leads. In this review, we summarize the current knowledge and understanding of specific E6 PPI inhibition, the progress and challenges being faced, and potential approaches that can be utilized to identify novel and potent PPI inhibitors for cervical cancer treatment.

An affinity prediction approach for the ligand of E3 ligase Cbl-b and an insight into substrate binding pattern

Protein-protein interactions (PPIs) are essentially fundamental to all cellular processes, so that developing small molecule inhibitors of PPIs have great significance despite representing a huge challenge. Studying PPIs with the help of peptide motifs could obtain the structural information and reference significance to reduce the difficulty in the development of small molecules. Computational methods are powerful tools to characterize peptide-protein interactions, especially molecular dynamics simulation and binding free energy calculation. Here, we established an affinity prediction model suitable for Casitas B lymphoma-b (Cbl-b) and phosphorylated motif system. According to the affinity data set of multiple truncated peptides, the force field, solvent model, and internal dielectric constant of molecular mechanics/generalized Born surface area (MM/GBSA) method were optimized. Further, we predicted the affinity of the rationally designed new sequences through this model and obtained a new 6-mer motif with a 7-fold increase in affinity and the comprehensive structure-activity relationship. Moreover, we proposed an insight of unexpected activity of the truncated 5-mer peptide and revealed the possible binding mode of the new highly active 6-mer motif by extended simulation. Our results showed that the activity enhancement of the truncated peptide was caused by the acetyl-mediated conformation change. The side chain of Arg and pTyr in the 6-mer motif co-occupied the site p1 to form numerous hydrogen bond interactions and increased hydrophobic interaction formed with Tyr266, leading to the higher affinity. The present work provided a reference to investigate the PPI of Cbl-b and phosphorylated substrates and guided the development of Cbl-b inhibitors.

Recent advances in β-catenin/BCL9 protein-protein interaction inhibitors

Wnt/β-catenin signaling is crucial both in normal embryonic development and throughout the life of an organism. Moreover, aberrant Wnt signaling has been associated with various diseases, especially cancer and fibrosis. Recent research suggests that direct targeting of the β-catenin/BCL9 protein-protein interaction (PPI) is a promising strategy to block the Wnt pathway. Progress in understanding the cocrystalline complex and mechanism of action of the β-catenin/BCL9 interaction facilitates the discovery process of its inhibitors, but only a few inhibitors have been reported. In this review, the discovery and development of β-catenin/BCL9 PPI inhibitors in the areas of drug design, structure-activity relationships and biological and biochemical properties are summarized. In addition, perspectives for the future development of β-catenin/BCL9 PPI inhibitors are explored.

Scanning Protein Surfaces with DNA-Encoded Libraries

Understanding the ligandability of a target protein, defined as the capability of a protein to bind drug-like compounds on any site, can give important stimuli to drug-development projects. For instance, inhibition of protein-protein interactions usually depends on the identification of protein surface binders. DNA-encoded chemical libraries (DELs) allow scanning of protein surfaces with large chemical space. Encoded library selection screens uncovered several protein-protein interaction inhibitors and compounds binding to the surface of G protein-coupled receptors (GPCRs) and kinases. The protein surface-binding chemotypes from DELs are predominantly chemically modified and cyclized peptides, and functional small-molecule peptidomimetics. Peptoid libraries and structural peptidomimetics have been less studied in the DEL field, hinting at hitherto less populated chemical space and suggesting alternative library designs. Roughly a third of bioactive molecules evolved from smaller, target-focused libraries. They showcase the potential of encoded libraries to identify more potent molecules from weak, for example, fragment-like, starting points.

Modulators of protein-protein interactions as antimicrobial agents

Protein-Protein interactions (PPIs) are involved in a myriad of cellular processes in all living organisms and the modulation of PPIs is already under investigation for the development of new drugs targeting cancers, autoimmune diseases and viruses. PPIs are also involved in the regulation of vital functions in bacteria and, therefore, targeting bacterial PPIs offers an attractive strategy for the development of antibiotics with novel modes of action. The latter are urgently needed to tackle multidrug-resistant and multidrug-tolerant bacteria. In this review, we describe recent developments in the modulation of PPIs in pathogenic bacteria for antibiotic development, including advanced small molecule and peptide inhibitors acting on bacterial PPIs involved in division, replication and transcription, outer membrane protein biogenesis, with an additional focus on toxin-antitoxin systems as upcoming drug targets.

Network Analysis Identifies Drug Targets and Small Molecules to Modulate Apoptosis Resistant Cancers

Programed cell death or apoptosis fails to induce cell death in many recalcitrant cancers. Thus, there is an emerging need to activate the alternate cell death pathways in such cancers. In this study, we analyzed the apoptosis-resistant colon adenocarcinoma, glioblastoma multiforme, and small cell lung cancers transcriptome profiles. We extracted clusters of non-apoptotic cell death genes from each cancer to understand functional networks affected by these genes and their role in the induction of cell death when apoptosis fails. We identified transcription factors regulating cell death genes and protein-protein interaction networks to understand their role in regulating cell death mechanisms. Topological analysis of networks yielded FANCD2 (ferroptosis, negative regulator, down), NCOA4 (ferroptosis, up), IKBKB (alkaliptosis, down), and RHOA (entotic cell death, down) as potential drug targets in colon adenocarcinoma, glioblastoma multiforme, small cell lung cancer phenotypes respectively. We also assessed the miRNA association with the drug targets. We identified tumor growth-related interacting partners based on the pathway information of drug-target interaction networks. The protein-protein interaction binding site between the drug targets and their interacting proteins provided an opportunity to identify small molecules that can modulate the activity of functional cell death interactions in each cancer. Overall, our systematic screening of non-apoptotic cell death-related genes uncovered targets helpful for cancer therapy.

In silico peptide-directed ligand design complements experimental peptide-directed binding for protein-protein interaction modulator discovery

Using the protein-protein interaction of Mcl-1/Noxa, two methods for efficient modulator discovery are directly compared. In silico peptide-directed ligand design is evaluated against experimental peptide-directed binding, allowing for the discovery of two new inhibitors of Mcl-1/Noxa with cellular activity. In silico peptide-directed ligand design demonstrates an in vitro hit rate of 80% (IC50 < 100 μM). The two rapid and efficient methods demonstrate complementary features for protein-protein interaction modulator discovery.

Applications of Solution NMR in Drug Discovery

During the past decades, solution nuclear magnetic resonance (NMR) spectroscopy has demonstrated itself as a promising tool in drug discovery. Especially, fragment-based drug discovery (FBDD) has benefited a lot from the NMR development. Multiple candidate compounds and FDA-approved drugs derived from FBDD have been developed with the assistance of NMR techniques. NMR has broad applications in different stages of the FBDD process, which includes fragment library construction, hit generation and validation, hit-to-lead optimization and working mechanism elucidation, etc. In this manuscript, we reviewed the current progresses of NMR applications in fragment-based drug discovery, which were illustrated by multiple reported cases. Moreover, the NMR applications in protein-protein interaction (PPI) modulators development and the progress of in-cell NMR for drug discovery were also briefly summarized.

Alternative Sigma Factor of Staphylococcus aureus Interacts with the Cognate Antisigma Factor Primarily Using Its Domain 3

σ^B, an alternative sigma factor, is usually employed to tackle the general stress response in Staphylococcus aureus and other Gram-positive bacteria. This protein, involved in S. aureus-mediated pathogenesis, is typically blocked by RsbW, an antisigma factor having serine kinase activity. σ^B, a σ⁷⁰-like sigma factor, harbors three conserved domains designated σ^B2, σ^B3, and σ^B4. To better understand the interaction between RsbW and σ^B or its domains, we have studied their recombinant forms, rRsbW, rσ^B, rσ^B2, rσ^B3, and rσ^B4, using different probes. The results show that none of the rσ^B domains, unlike rσ^B, showed binding to a cognate DNA in the presence of a core RNA polymerase. However, both rσ^B2 and rσ^B3, like rσ^B, interacted with rRsbW, and the order of their rRsbW binding affinity looks like rσ^B > rσ^B3 > rσ^B2. Furthermore, the reaction between rRsbW and rσ^B or rσ^B3 was exothermic and occurred spontaneously. rRsbW and rσ^B3 also associate with each other at a stoichiometry of 2:1, and different types of noncovalent bonds might be responsible for their interaction. A structural model of the RsbW-σ^B3 complex that has supported our experimental results indicated the binding of rσ^B3 at the putative dimeric interface of RsbW. A genetic study shows that the tentative dimer-forming region of RsbW is crucial for preserving its rσ^B binding ability, serine kinase activity, and dimerization ability. Additionally, a urea-induced equilibrium unfolding study indicated a notable thermodynamic stabilization of σ^B3 in the presence of RsbW. Possible implications of the stabilization data in drug discovery were discussed at length.

Targeting Protein Neddylation to Inactivate Cullin-RING Ligases by Gossypol: A Lucky Hit or a New Start?

Cullin-RING E3 ligases (CRLs) are the largest family of E3 ubiquitin ligases, responsible for about 20% of the protein degradation by the ubiquitin-proteasome system (UPS). Given their vital roles in multiple cellular processes, and over-activation in many human cancers, CRLs are validated as promising targets for anti-cancer therapies. Activation of CRLs requires cullin neddylation, a process catalysed by three neddylation enzymes. Recently, our group established an AlphaScreen-based in vitro cullin neddylation assay and employed it for high-throughput screening to search for small-molecule inhibitors targeting cullin neddylation. During our pilot screen, gossypol, a natural product extracted from cottonseeds, was identified as one of the most potent neddylation inhibitors of cullin-1 and cullin-5. We further demonstrated that gossypol blocks cullin neddylation by binding to cullin-1/-5 to inactivate CRL1/5 ligase activity, leading to accumulation of MCL-1 and NOXA, the substrates of CRL1 and CRL5, respectively. The combination of gossypol and an MCL-1 inhibitor synergistically enhanced the anti-proliferative effect in multiple human cancer cell lines. Our study unveiled a rational combination of two previously known inhibitors of the Bcl-2 family for enhanced anti-cancer efficacy and identified a novel activity of gossypol as an inhibitor of CRL1 and CRL5 E3s, thus providing a new possibility in the development of novel CRL inhibitors for anti-cancer therapy.

Aza-heterocyclic frameworks through intramolecular π-system trapping of spiro-N-acyliminiums generated from isoindolinone

Spiro-acetoxylactams, obtained easily by the tandem carbonyl reduction/O-acylation, were submitted to acids giving through π-cationic cyclization aza-heterocyclic systems including amino-acids.

Computational design of small molecular modulators of protein-protein interactions with a novel thermodynamic cycle: Allosteric inhibitors of HIV-1 integrase

Targeting protein-protein interactions for therapeutic development involves designing small molecules to either disrupt or enhance a known PPI. For this purpose, it is necessary to compute reliably the effect of chemical modifications of small molecules on the protein-protein association free energy. Here we present results obtained using a novel thermodynamic free energy cycle, for the rational design of allosteric inhibitors of HIV-1 integrase (ALLINI) that act specifically in the early stage of the infection cycle. The new compounds can serve as molecular probes to dissect the multifunctional mechanisms of ALLINIs to inform the discovery of new allosteric inhibitors. The free energy protocol developed here can be more broadly applied to study quantitatively the effects of small molecules on modulating the strengths of protein-protein interactions.

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

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

The study of EGFR-ligand complex electron property relationship with biological activity

The present investigation grounded on estimation of electron properties of the structures of EGFR proteins-ligand complexes using our laboratory-developed methodology AlteQ approach, which describes the molecular electron density of the complex in space for a certain point in three-dimensional coordinates. Briefly, the system embodies molecular electron density as a sum of Slater's type atomic increments of the molecular system. Further, using this methodology, we calculated different electron characteristics of selected EGFR protein-ligand complexes and established the relationship between different electron properties with their experimental pharmacological activity value (pIC₅₀). The study suggested that EGFR inhibitory activity has higher correlation with intermolecular contacts of H with pi-system of aromatic ring between protein and ligands. Therefore, this created model has impact to identify and design potential ligands against EGFR in anticancer drug discovery.Communicated by Ramaswamy H. Sarma.

Computational methods-guided design of modulators targeting protein-protein interactions (PPIs)

Protein-protein interactions (PPIs) play a pivotal role in extensive biological processes and are thus crucial to human health and the development of disease states. Due to their critical implications, PPIs have been spotlighted as promising drug targets of broad-spectrum therapeutic interests. However, owing to the general properties of PPIs, such as flat surfaces, featureless conformations, difficult topologies, and shallow pockets, previous attempts were faced with serious obstacles when targeting PPIs and almost portrayed them as "intractable" for decades. To date, rapid progress in computational chemistry and structural biology methods has promoted the exploitation of PPIs in drug discovery. These techniques boost their cost-effective and high-throughput traits, and enable the study of dynamic PPI interfaces. Thus, computational methods represent an alternative strategy to target "undruggable" PPI interfaces and have attracted intense pharmaceutical interest in recent years, as exemplified by the accumulating number of successful cases. In this review, we first introduce a diverse set of computational methods used to design PPI modulators. Herein, we focus on the recent progress in computational strategies and provide a comprehensive overview covering various methodologies. Importantly, a list of recently-reported successful examples is highlighted to verify the feasibility of these computational approaches. Finally, we conclude the general role of computational methods in targeting PPIs, and also discuss future perspectives on the development of such aids.