Small molecules, big targets: drug discovery faces the protein–protein interaction challenge

Reciprocal Regulation of Hippo and WBP2 Signalling-Implications in Cancer Therapy

Cancer is a global health problem. The delineation of molecular mechanisms pertinent to cancer initiation and development has spurred cancer therapy in the form of precision medicine. The Hippo signalling pathway is a tumour suppressor pathway implicated in a multitude of cancers. Elucidation of the Hippo pathway has revealed an increasing number of regulators that are implicated, some being potential therapeutic targets for cancer interventions. WW domain-binding protein 2 (WBP2) is an oncogenic transcriptional co-factor that interacts, amongst others, with two other transcriptional co-activators, YAP and TAZ, in the Hippo pathway. WBP2 was recently discovered to modulate the upstream Hippo signalling components by associating with LATS2 and WWC3. Exacerbating the complexity of the WBP2/Hippo network, WBP2 itself is reciprocally regulated by Hippo-mediated microRNA biogenesis, contributing to a positive feedback loop that further drives carcinogenesis. Here, we summarise the biological mechanisms of WBP2/Hippo reciprocal regulation and propose therapeutic strategies to overcome Hippo defects in cancers through targeting WBP2.

Targeting small GTPases and their downstream pathways with intracellular macromolecule binders to define alternative therapeutic strategies in cancer

The RAS superfamily of small GTPases regulates major physiological cellular processes. Mutation or deregulation of these small GTPases, their regulators and/or their effectors are associated with many diseases including cancer. Hence, targeting these classes of proteins is an important therapeutic strategy in cancer. This has been recently achieved with the approval of the first KRASG12C covalent inhibitors for the clinic. However, many other mutants and small GTPases are still considered as 'undruggable' with small molecule inhibitors because of a lack of well-defined pocket(s) at their surface. Therefore, alternative therapeutic strategies have been developed to target these proteins. In this review, we discuss the use of intracellular antibodies and derivatives - reagents that bind their antigen inside the cells - for the discovery of novel inhibitory mechanisms, targetable features and therapeutic strategies to inhibit small GTPases and their downstream pathways. These reagents are also versatile tools used to better understand the biological mechanisms regulated by small GTPases and to accelerate the drug discovery process.

RNA aptamers for AMPA receptors

RNA aptamers are single-stranded RNA molecules, and they are selected against a target of interest so that they can bind to and modulate the activity of the target, such as inhibiting the target activity, with high potency and selectivity. Antagonists, such as RNA aptamers, acting on AMPA receptors, a major subtype of ionotropic glutamate receptors, are potential drug candidates for treatment of a number of CNS diseases that involve excessive receptor activation and/or elevated receptor expression. Here we review the approach to discover RNA aptamers targeting AMPA receptors from a random sequence library (∼10¹⁴ sequences) through a process called systematic evolution of ligands by exponential enrichment (SELEX). As compared with small-molecule compounds, RNA aptamers are a new class of regulatory agents with interesting and desirable pharmacological properties. Some AMPA receptor aptamers we have developed are presented in this review. The promises and challenges of translating RNA aptamers into potential drugs and treatment options are also discussed. This article is part of the special Issue on 'Glutamate Receptors - AMPA receptors'.

Identification and optimization of molecular glue compounds that inhibit a noncovalent E2 enzyme-ubiquitin complex

Pharmacological control of the ubiquitin-proteasome system (UPS) is of intense interest in drug discovery. Here, we report the development of chemical inhibitors of the ubiquitin-conjugating (E2) enzyme CDC34A (also known as UBE2R1), which donates activated ubiquitin to the cullin-RING ligase (CRL) family of ubiquitin ligase (E3) enzymes. A FRET-based interaction assay was used to screen for novel compounds that stabilize the noncovalent complex between CDC34A and ubiquitin, and thereby inhibit the CDC34A catalytic cycle. An isonipecotamide hit compound was elaborated into analogs with ~1000-fold increased potency in stabilizing the CDC34A-ubiquitin complex. These analogs specifically inhibited CDC34A-dependent ubiquitination in vitro and stabilized an E2~ubiquitin thioester reaction intermediate in cells. The x-ray crystal structure of a CDC34A-ubiquitin-inhibitor complex uncovered the basis for analog structure-activity relationships. The development of chemical stabilizers of the CDC34A-ubiquitin complex illustrates a general strategy for de novo discovery of molecular glue compounds that stabilize weak protein interactions.

Thrombopoietin receptor-based protein-protein interaction screening (THROPPIS)

As protein-protein interactions (PPIs) are involved in many cellular events, development of mammalian cytosolic PPI detection systems is important for drug discovery as well as understanding biological phenomena. We have previously reported a c-kit-based PPI screening (KIPPIS) system, in which proteins of interest were fused with a receptor tyrosine kinase c-kit, leading to intracellular PPI-dependent cell growth. However, it has not been investigated whether PPI can be detected using other receptors. In this study, we employed a thrombopoietin receptor, which belongs to the Type I cytokine receptor family, to develop a thrombopoietin receptor-based PPI screening (THROPPIS) system. To improve the sensitivity of THROPPIS, we examined two strategies of (i) localization of the chimeric receptors on the cell membrane, and (ii) addition of a helper module to the chimeric receptors. Intriguingly, the nonlocalized chimeric receptor showed the best performance of THROPPIS. Furthermore, the addition of the helper module dramatically improved the detection sensitivity. In total, 5 peptide-domain interactions were detected successfully, demonstrating the versatility of THROPPIS. In addition, a peptide-domain interaction was detected even when insulin receptor or epidermal growth factor receptor was used as a signaling domain, demonstrating that this PPI detection system can be extended to other receptors.

Establishment of high-throughput screening HTRF assay for identification small molecule inhibitors of Skp2-Cks1

S-phase kinase associated protein 2 (Skp2), a member of the F-box family that constitute the largest known class of ubiquitin E3 specificity components, is responsible for recognizing and recruiting cyclin-dependent kinase inhibitor p27 for its ubiquitination in the presence of the small accessory protein cyclin-dependent kinase regulatory subunit 1(Cks1). Skp2 is overexpressed in esophageal carcinoma tissues and closely related with tumor poor prognosis, and perturbation of the Skp2-Cks1 interaction by inhibitors or RNAi could inhibit the proliferation and metastasis of tumor cells. Therefore, inhibition of Skp2 function by small-molecule compounds targeting Skp2-Cks1 interaction is emerging as a promising and novel anti-cancer strategy. In this study, we establish an improved high-throughput screening platform to screen Skp2 inhibitors targeting Skp2-Cks1interaction, which may provide a new therapeutic approach for the clinic.

Mapping, Structure and Modulation of PPI

Because of the key relevance of protein–protein interactions (PPI) in diseases, the modulation of protein-protein complexes is of relevant clinical significance. The successful design of binding compounds modulating PPI requires a detailed knowledge of the involved protein-protein system at molecular level, and investigation of the structural motifs that drive the association of the proteins at the recognition interface. These elements represent hot spots of the protein binding free energy, define the complex lifetime and possible modulation strategies. Here, we review the advanced technologies used to map the PPI involved in human diseases, to investigate the structure-function features of protein complexes, and to discover effective ligands that modulate the PPI for therapeutic intervention.

Quantitative FRET (qFRET) Technology for the Determination of Protein-Protein Interaction Affinity in Solution

Protein-protein interactions play pivotal roles in life, and the protein interaction affinity confers specific protein interaction events in physiology or pathology. Förster resonance energy transfer (FRET) has been widely used in biological and biomedical research to detect molecular interactions in vitro and in vivo. The FRET assay provides very high sensitivity and efficiency. Several attempts have been made to develop the FRET assay into a quantitative measurement for protein-protein interaction affinity in the past. However, the progress has been slow due to complicated procedures or because of challenges in differentiating the FRET signal from other direct emission signals from donor and receptor. This review focuses on recent developments of the quantitative FRET analysis and its application in the determination of protein-protein interaction affinity (K_D), either through FRET acceptor emission or donor quenching methods. This paper mainly reviews novel theatrical developments and experimental procedures rather than specific experimental results. The FRET-based approach for protein interaction affinity determination provides several advantages, including high sensitivity, high accuracy, low cost, and high-throughput assay. The FRET-based methodology holds excellent potential for those difficult-to-be expressed proteins and for protein interactions in living cells.

Design and synthesis of a DNA-encoded combinatorial library of bicyclic peptoids

Here we describe the design and synthesis of a DNA-encoded library of bicyclic peptoids. We show that our solid-phase strategy is facile and DNA-compatible, yielding a structurally diverse combinatorial library of bicyclic peptoids of various ring sizes. We also demonstrate that affinity-based screening of a DNA-encoded library of bicyclic peptoids enables to efficiently identify high-affinity ligands for a target protein. Given their highly constraint structures, as well as increased cell permeability and proteolytic stability relative to native peptides, bicyclic peptoids could be an excellent source of protein capture agents. As such, our DNA-encoded library of bicyclic peptoids will serve as versatile tools that facilitate the generation of potent ligands against many challenging targets, such as intracellular protein-protein interactions.

Towards optimizing peptide-based inhibitors of protein-protein interactions: predictive saturation variation scanning (PreSaVS)

A simple-to-implement and experimentally validated computational workflow for sequence modification of peptide inhibitors of protein–protein interactions (PPIs) is described.

An experimentally validated approach for in silico modification of peptide based protein–protein interaction inhibitors is described.

Tailored Biosensors for Drug Screening, Efficacy Assessment, and Toxicity Evaluation

Biosensors have been flourishing in the field of drug discovery with pronounced developments in the past few years. They facilitate the screening and discovery of innovative drugs. However, there is still a lack of critical reviews that compare the merits and shortcomings of these biosensors from a pharmaceutical point of view. This contribution presents a critical and up-to-date overview on the recent progress of tailored biosensors, including surface plasmon resonance, fluorescent, photoelectrochemical, and electrochemical systems with emphasis on their mechanisms and applications in drug screening, efficacy assessment, and toxicity evaluation. Multiple functional nanomaterials have also been incorporated into the biosensors. Representative examples of each type of biosensors are discussed in terms of design strategy, response mechanism, and potential applications. In the end, we also compare the results and summarize the major insights gained from the works, demonstrating the challenges and prospects of biosensors-assisted drug discovery.

Design and synthesis of a new orthogonally protected glutamic acid analog and its use in the preparation of high affinity polo-like kinase 1 polo-box domain - binding peptide macrocycles

Targeting protein - protein interactions (PPIs) has emerged as an important area of discovery for anticancer therapeutic development. In the case of phospho-dependent PPIs, such as the polo-like kinase 1 (Plk1) polo-box domain (PBD), a phosphorylated protein residue can provide high-affinity recognition and binding to target protein hot spots. Developing antagonists of the Plk1 PBD can be particularly challenging if one relies solely on interactions within and proximal to the phospho-binding pocket. Fortunately, the affinity of phospho-dependent PPI antagonists can be significantly enhanced by taking advantage of interactions in both the phospho-binding site and hidden "cryptic" pockets that may be revealed on ligand binding. In our current paper, we describe the design and synthesis of macrocyclic peptide mimetics directed against the Plk1 PBD, which are characterized by a new glutamic acid analog that simultaneously serves as a ring-closing junction that provides accesses to a cryptic binding pocket, while at the same time achieving proper orientation of a phosphothreonine (pT) residue for optimal interaction in the signature phospho-binding pocket. Macrocycles prepared with this new amino acid analog introduce additional hydrogen-bonding interactions not found in the open-chain linear parent peptide. It is noteworthy that this new glutamic acid-based amino acid analog represents the first example of extremely high affinity ligands where access to the cryptic pocket from the pT-2 position is made possible with a residue that is not based on histidine. The concepts employed in the design and synthesis of these new macrocyclic peptide mimetics should be useful for further studies directed against the Plk1 PBD and potentially for ligands directed against other PPI targets.

Nanotechnology-Assisted RNA Delivery: From Nucleic Acid Therapeutics to COVID-19 Vaccines

In recent years, the main quest of science has been the pioneering of the groundbreaking biomedical strategies needed for achieving a personalized medicine. Ribonucleic acids (RNAs) are outstanding bioactive macromolecules identified as pivotal actors in regulating a wide range of biochemical pathways. The ability to intimately control the cell fate and tissue activities makes RNA-based drugs the most fascinating family of bioactive agents. However, achieving a widespread application of RNA therapeutics in humans is still a challenging feat, due to both the instability of naked RNA and the presence of biological barriers aimed at hindering the entrance of RNA into cells. Recently, material scientists' enormous efforts have led to the development of various classes of nanostructured carriers customized to overcome these limitations. This work systematically reviews the current advances in developing the next generation of drugs based on nanotechnology-assisted RNA delivery. The features of the most used RNA molecules are presented, together with the development strategies and properties of nanostructured vehicles. Also provided is an in-depth overview of various therapeutic applications of the presented systems, including coronavirus disease vaccines and the newest trends in the field. Lastly, emerging challenges and future perspectives for nanotechnology-mediated RNA therapies are discussed.

Regulation of cadherin dimerization by chemical fragments as a trigger to inhibit cell adhesion

Many cadherin family proteins are associated with diseases such as cancer. Since cell adhesion requires homodimerization of cadherin molecules, a small-molecule regulator of dimerization would have therapeutic potential. Herein, we describe identification of a P-cadherin-specific chemical fragment that inhibits P-cadherin-mediated cell adhesion. Although the identified molecule is a fragment compound, it binds to a cavity of P-cadherin that has not previously been targeted, indirectly prevents formation of hydrogen bonds necessary for formation of an intermediate called the X dimer and thus modulates the process of X dimerization. Our findings will impact on a strategy for regulation of protein-protein interactions and stepwise assembly of protein complexes using small molecules.

Supramolecular Enhancement of a Natural 14-3-3 Protein Ligand

Rational design of protein-protein interaction (PPI) inhibitors is challenging. Connecting a general supramolecular protein binder with a specific peptidic ligand provides a novel conceptual approach. Thus, lysine-specific molecular tweezers were conjugated to a peptide-based 14-3-3 ligand and produced a strong PPI inhibitor with 100-fold elevated protein affinity. X-ray crystal structure elucidation of this supramolecular directed assembly provides unique molecular insight into the binding mode and fully aligns with Molecular Dynamics (MD) simulations. This new supramolecular chemical biology concept opens the path to novel chemical tools for studying PPIs.

MYC protein interactors in gene transcription and cancer

The transcription factor and oncoprotein MYC is a potent driver of many human cancers and can regulate numerous biological activities that contribute to tumorigenesis. How a single transcription factor can regulate such a diverse set of biological programmes is central to the understanding of MYC function in cancer. In this Perspective, we highlight how multiple proteins that interact with MYC enable MYC to regulate several central control points of gene transcription. These include promoter binding, epigenetic modifications, initiation, elongation and post-transcriptional processes. Evidence shows that a combination of multiple protein interactions enables MYC to function as a potent oncoprotein, working together in a 'coalition model', as presented here. Moreover, as MYC depends on its protein interactome for function, we discuss recent research that emphasizes an unprecedented opportunity to target protein interactors to directly impede MYC oncogenesis.

Protein-Small Molecule Interactions in Native Mass Spectrometry

Small molecule drug discovery has been propelled by the continual development of novel scientific methodologies to occasion therapeutic advances. Although established biophysical methods can be used to obtain information regarding the molecular mechanisms underlying drug action, these approaches are often inefficient, low throughput, and ineffective in the analysis of heterogeneous systems including dynamic oligomeric assemblies and proteins that have undergone extensive post-translational modification. Native mass spectrometry can be used to probe protein-small molecule interactions with unprecedented speed and sensitivity, providing unique insights into polydisperse biomolecular systems that are commonly encountered during the drug discovery process. In this review, we describe potential and proven applications of native MS in the study of interactions between small, drug-like molecules and proteins, including large multiprotein complexes and membrane proteins. Approaches to quantify the thermodynamic and kinetic properties of ligand binding are discussed, alongside a summary of gas-phase ion activation techniques that have been used to interrogate the structure of protein-small molecule complexes. We additionally highlight some of the key areas in modern drug design for which native mass spectrometry has elicited significant advances. Future developments and applications of native mass spectrometry in drug discovery workflows are identified, including potential pathways toward studying protein-small molecule interactions on a whole-proteome scale.

A System for the Evolution of Protein-Protein Interaction Inducers

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

Structural and molecular bases to IRE1 activity modulation

The Unfolded Protein response is an adaptive pathway triggered upon alteration of endoplasmic reticulum (ER) homeostasis. It is transduced by three major ER stress sensors, among which the Inositol Requiring Enzyme 1 (IRE1) is the most evolutionarily conserved. IRE1 is an ER-resident type I transmembrane protein exhibiting an ER luminal domain that senses the protein folding status and a catalytic kinase and RNase cytosolic domain. In recent years, IRE1 has emerged as a relevant therapeutic target in various diseases including degenerative, inflammatory and metabolic pathologies and cancer. As such several drugs altering IRE1 activity were developed that target either catalytic activity and showed some efficacy in preclinical pathological mouse models. In this review, we describe the different drugs identified to target IRE1 activity as well as their mode of action from a structural perspective, thereby identifying common and different modes of action. Based on this information we discuss on how new IRE1-targeting drugs could be developed that outperform the currently available molecules.

Can We Pharmacologically Target Dishevelled: The Key Signal Transducer in the Wnt Pathways?

Dishevelled (DVL) is the central signal transducer in both Wnt/β-catenin-dependent and independent signalling pathways. DVL is required to connect receptor complexes and downstream effectors. Since proximal Wnt pathway components and DVL itself are upregulated in many types of cancer, DVL represents an attractive therapeutic target in the Wnt-addicted cancers and other disorders caused by aberrant Wnt signalling. Here, we discuss progress in several approaches for the modulation of DVL function and hence inhibition of the Wnt signalling. Namely, we sum up the potential of modulation of enzymes that control post-translational modification of DVL - such as inhibition of DVL kinases or promotion of DVL ubiquitination and degradation. In addition, we discuss research directions that can take advantage of direct interaction with the protein domains essential for DVL function: the inhibition of DIX- and DEP-domain mediated polymerization and interaction of DVL PDZ domain with its ligands.

Rotavirus viroplasm biogenesis involves microtubule-based dynein transport mediated by an interaction between NSP2 and dynein intermediate chain

Rotaviruses are the causative agents of severe and dehydrating gastroenteritis in children, piglets, and many other young animals. They replicate their genomes and assemble double-layered particles in cytoplasmic electron-dense inclusion bodies called 'viroplasms'. The formation of viroplasms is reportedly associated with the stability of microtubules. Although material transport is an important function of microtubules, whether and how microtubule-based transport influences the formation of viroplasms is still unclear. Here, we demonstrate that the small viroplasms move and fuse in living cells. We show that microtubule-based dynein transport affects rotavirus infection, viroplasm formation, and the assembly of transient enveloped particles (TEPs) and triple-layered particles (TLPs). The dynein intermediate chain (DIC) is shown to localize in the viroplasm and to interact directly with non-structural protein 2 (NSP2), indicating that DIC is responsible for connecting the viroplasm to dynein. The WD40 repeat domain of DIC regulates the interaction between DIC and NSP2, and the knockdown of DIC inhibited rotaviral infection, viroplasm formation, and the assembly of TEPs and TLPs. Our findings show that rotavirus viroplasms hijack dynein transport for fusion events, required for maximal assembly of infectious viral progeny. This study provides novel insights into the intracellular transport of viroplasms, which is involved in their biogenesis. Importance Because the viroplasm is the viral factory for rotavirus replication, viroplasm formation undoubtedly determines the effective production of progeny rotavirus. Therefore, understanding the virus-host interactions involved in the biogenesis of the viroplasm is critical for the future development of prophylactic and therapeutic strategies. Previous studies have reported that the formation of viroplasms is associated with the stability of microtubules, whereas little is known about its specific mechanism. Here, we demonstrate that rotavirus viroplasm formation takes advantage of microtubule-based dynein transport mediated by an interaction between NSP2 and DIC. These findings provide new insight into the intracellular transport of viroplasms.

Machine Learning in Drug Discovery: A Review

This review provides the feasible literature on drug discovery through ML tools and techniques that are enforced in every phase of drug development to accelerate the research process and deduce the risk and expenditure in clinical trials. Machine learning techniques improve the decision-making in pharmaceutical data across various applications like QSAR analysis, hit discoveries, de novo drug architectures to retrieve accurate outcomes. Target validation, prognostic biomarkers, digital pathology are considered under problem statements in this review. ML challenges must be applicable for the main cause of inadequacy in interpretability outcomes that may restrict the applications in drug discovery. In clinical trials, absolute and methodological data must be generated to tackle many puzzles in validating ML techniques, improving decision-making, promoting awareness in ML approaches, and deducing risk failures in drug discovery.

Bioactive recombinant human oncostatin M for NMR-based screening in drug discovery

Oncostatin M (OSM) is a pleiotropic, interleukin-6 family inflammatory cytokine that plays an important role in inflammatory diseases, including inflammatory bowel disease, rheumatoid arthritis, and cancer progression and metastasis. Recently, elevated OSM levels have been found in the serum of COVID-19 patients in intensive care units. Multiple anti-OSM therapeutics have been investigated, but to date no OSM small molecule inhibitors are clinically available. To pursue a high-throughput screening and structure-based drug discovery strategy to design a small molecule inhibitor of OSM, milligram quantities of highly pure, bioactive OSM are required. Here, we developed a reliable protocol to produce highly pure unlabeled and isotope enriched OSM from E. coli for biochemical and NMR studies. High yields (ca. 10 mg/L culture) were obtained in rich and minimal defined media cultures. Purified OSM was characterized by mass spectrometry and circular dichroism. The bioactivity was confirmed by induction of OSM/OSM receptor signaling through STAT3 phosphorylation in human breast cancer cells. Optimized buffer conditions yielded ¹H, ¹⁵N HSQC NMR spectra with intense, well-dispersed peaks. Titration of ¹⁵N OSM with a small molecule inhibitor showed chemical shift perturbations for several key residues with a binding affinity of 12.2 ± 3.9 μM. These results demonstrate the value of bioactive recombinant human OSM for NMR-based small molecule screening.

Synthetic Peptides That Antagonize the Angiotensin-Converting Enzyme-2 (ACE-2) Interaction with SARS-CoV-2 Receptor Binding Spike Protein

The SARS-CoV-2 viral spike protein S receptor-binding domain (S-RBD) binds ACE2 on host cells to initiate molecular events, resulting in intracellular release of the viral genome. Therefore, antagonists of this interaction could allow a modality for therapeutic intervention. Peptides can inhibit the S-RBD:ACE2 interaction by interacting with the protein–protein interface. In this study, protein contact atlas data and molecular dynamics simulations were used to locate interaction hotspots on the secondary structure elements α1, α2, α3, β3, and β4 of ACE2. We designed a library of discontinuous peptides based upon a combination of the hotspot interactions, which were synthesized and screened in a bioluminescence-based assay. The peptides demonstrated high efficacy in antagonizing the SARS-CoV-2 S-RBD:ACE2 interaction and were validated by microscale thermophoresis which demonstrated strong binding affinity (∼10 nM) of these peptides to S-RBD. We anticipate that such discontinuous peptides may hold the potential for an efficient therapeutic treatment for COVID-19.

TopDomain: Exhaustive Protein Domain Boundary Metaprediction Combining Multisource Information and Deep Learning

Protein domains are independent, functional, and stable structural units of proteins. Accurate protein domain boundary prediction plays an important role in understanding protein structure and evolution, as well as for protein structure prediction. Current domain boundary prediction methods differ in terms of boundary definition, methodology, and training databases resulting in disparate performance for different proteins. We developed TopDomain, an exhaustive metapredictor, that uses deep neural networks to combine multisource information from sequence- and homology-based features of over 50 primary predictors. For this purpose, we developed a new domain boundary data set termed the TopDomain data set, in which the true annotations are informed by SCOPe annotations, structural domain parsers, human inspection, and deep learning. We benchmark TopDomain against 2484 targets with 3354 boundaries from the TopDomain test set and achieve F1 scores of 78.4% and 73.8% for multidomain boundary prediction within ±20 residues and ±10 residues of the true boundary, respectively. When examined on targets from CASP11-13 competitions, TopDomain achieves F1 scores of 47.5% and 42.8% for multidomain proteins. TopDomain significantly outperforms 15 widely used, state-of-the-art ab initio and homology-based domain boundary predictors. Finally, we implemented TopDomain_TMC, which accurately predicts whether domain parsing is necessary for the target protein.

Hepatotoxic evaluation of toosendanin via biomarker quantification and pathway mapping of large-scale chemical proteomics

Drug-induced liver injury (DILI) is a major side effect, sometimes can't be exactly evaluated by current approaches partly as the covalent modification of drug or its reactive metabolites (RMs) with proteins is a possible reason. In this study, we developed a rapid, sensitive, and specific analytical method to assess the hepatotoxicity induced by drug covalently modified proteins based on the quantification of the modified amino acids using toosendanin (TSN), a hepatotoxic chemical, as an example. TSN RM-protein adducts both in rat liver and blood showed good correlation with the severity of hepatotoxicity. Thus, TSN RM-protein adducts in serum can potentially serve as minimally invasive biomarkers of hepatotoxicity. Meanwhile, large-scale chemical proteomics analysis showed that at least 84 proteins were modified by TSN RMs in rat liver, and the bioinformatics analysis revealed that TSN might induce hepatotoxicity through multi-target protein-protein interaction especially involved in energy metabolism. These findings suggest that our approach may serve as a valuable tool to evaluate DILI and investigate the possible mechanism, especially for complex compounds.

Structural and evolutionary exploration of the IL-3 family and its alpha subunit receptors

Interleukin-3 (IL-3) is a cytokine belonging to the family of common β (βc) and is involved in various biological systems. Its activity is mediated by the interaction with its receptor (IL-3R), a heterodimer composed of two distinct subunits: IL-3Rα and βc. IL-3 and its receptor, especially IL-3Rα, play a crucial role in pathologies like inflammatory diseases and therefore are interesting therapeutic targets. Here, we have performed an analysis of these proteins and their interaction based on structural and evolutionary information. We highlighted that IL-3 and IL-3Rα structural architectures are conserved across evolution and shared with other proteins belonging to the same βc family interleukin-5 (IL-5) and granulocyte-macrophage colony-stimulating factor (GM-CSF). The IL-3Rα/IL-3 interaction is mediated by a large interface in which most residues are surprisingly not conserved during evolution and across family members. In spite of this high variability, we suggested small regions constituted by few residues conserved during the evolution in both proteins that could be important for the binding affinity.

Identifying hydrophobic protein patches to inform protein interaction interfaces

Interactions between proteins lie at the heart of numerous biological processes and are essential for the proper functioning of the cell. Although the importance of hydrophobic residues in driving protein interactions is universally accepted, a characterization of protein hydrophobicity, which informs its interactions, has remained elusive. The challenge lies in capturing the collective response of the protein hydration waters to the nanoscale chemical and topographical protein patterns, which determine protein hydrophobicity. To address this challenge, here, we employ specialized molecular simulations wherein water molecules are systematically displaced from the protein hydration shell; by identifying protein regions that relinquish their waters more readily than others, we are then able to uncover the most hydrophobic protein patches. Surprisingly, such patches contain a large fraction of polar/charged atoms and have chemical compositions that are similar to the more hydrophilic protein patches. Importantly, we also find a striking correspondence between the most hydrophobic protein patches and regions that mediate protein interactions. Our work thus establishes a computational framework for characterizing the emergent hydrophobicity of amphiphilic solutes, such as proteins, which display nanoscale heterogeneity, and for uncovering their interaction interfaces.

Asymmetric organocatalysis: an enabling technology for medicinal chemistry

The efficacy and synthetic versatility of asymmetric organocatalysis have contributed enormously to the field of organic synthesis since the early 2000s. As asymmetric organocatalytic methods mature, they have extended beyond the academia and undergone scale-up for the production of chiral drugs, natural products, and enantiomerically enriched bioactive molecules. This review provides a comprehensive overview of the applications of asymmetric organocatalysis in medicinal chemistry. A general picture of asymmetric organocatalytic strategies in medicinal chemistry is firstly presented, and the specific applications of these strategies in pharmaceutical synthesis are systematically described, with a focus on the preparation of antiviral, anticancer, neuroprotective, cardiovascular, antibacterial, and antiparasitic agents, as well as several miscellaneous bioactive agents. The review concludes with a discussion of the challenges, limitations and future prospects for organocatalytic asymmetric synthesis of medicinally valuable compounds.

Bicyclic β-Sheet Mimetics that Target the Transcriptional Coactivator β-Catenin and Inhibit Wnt Signaling

Protein complexes are defined by the three-dimensional structure of participating binding partners. Knowledge about these structures can facilitate the design of peptidomimetics which have been applied for example, as inhibitors of protein-protein interactions (PPIs). Even though β-sheets participate widely in PPIs, they have only rarely served as the basis for peptidomimetic PPI inhibitors, in particular when addressing intracellular targets. Here, we present the structure-based design of β-sheet mimetics targeting the intracellular protein β-catenin, a central component of the Wnt signaling pathway. Based on a protein binding partner of β-catenin, a macrocyclic peptide was designed and its crystal structure in complex with β-catenin obtained. Using this structure, we designed a library of bicyclic β-sheet mimetics employing a late-stage diversification strategy. Several mimetics were identified that compete with transcription factor binding to β-catenin and inhibit Wnt signaling in cells. The presented design strategy can support the development of inhibitors for other β-sheet-mediated PPIs.

Small-Molecule Inhibitors of the Coronavirus Spike: ACE2 Protein-Protein Interaction as Blockers of Viral Attachment and Entry for SARS-CoV-2

Inhibitors of the protein-protein interaction (PPI) between the SARS-CoV-2 spike protein and human ACE2 (hACE2), which acts as a ligand-receptor pair that initiates the viral attachment and cellular entry of this coronavirus causing the ongoing COVID-19 pandemic, are of considerable interest as potential antiviral agents. While blockade of such PPIs with small molecules is more challenging than that with antibodies, small-molecule inhibitors (SMIs) might offer alternatives that are less strain- and mutation-sensitive, suitable for oral or inhaled administration, and more controllable/less immunogenic. Here, we report the identification of SMIs of this PPI by screening our compound library focused around the chemical space of organic dyes. Among promising candidates identified, several dyes (Congo red, direct violet 1, Evans blue) and novel druglike compounds (DRI-C23041, DRI-C91005) inhibited the interaction of hACE2 with the spike proteins of SARS-CoV-2 as well as SARS-CoV with low micromolar activity in our cell-free ELISA-type assays (IC50's of 0.2-3.0 μM), whereas control compounds, such as sunset yellow FCF, chloroquine, and suramin, showed no activity. Protein thermal shift assays indicated that the SMIs of interest identified here bind SARS-CoV-2-S and not hACE2. While dyes seemed to be promiscuous inhibitors, DRI-C23041 showed some selectivity and inhibited the entry of two different SARS-CoV-2-S expressing pseudoviruses into hACE2-expressing cells in a concentration-dependent manner with low micromolar IC50's (6-7 μM). This provides proof-of-principle evidence for the feasibility of small-molecule inhibition of PPIs critical for SARS-CoV-2 attachment/entry and serves as a first guide in the search for SMI-based alternative antiviral therapies for the prevention and treatment of diseases caused by coronaviruses in general and COVID-19 in particular.

TRP Channels Interactome as a Novel Therapeutic Target in Breast Cancer

Breast cancer is one of the most frequent cancer types worldwide and the first cause of cancer-related deaths in women. Although significant therapeutic advances have been achieved with drugs such as tamoxifen and trastuzumab, breast cancer still caused 627,000 deaths in 2018. Since cancer is a multifactorial disease, it has become necessary to develop new molecular therapies that can target several relevant cellular processes at once. Ion channels are versatile regulators of several physiological- and pathophysiological-related mechanisms, including cancer-relevant processes such as tumor progression, apoptosis inhibition, proliferation, migration, invasion, and chemoresistance. Ion channels are the main regulators of cellular functions, conducting ions selectively through a pore-forming structure located in the plasma membrane, protein–protein interactions one of their main regulatory mechanisms. Among the different ion channel families, the Transient Receptor Potential (TRP) family stands out in the context of breast cancer since several members have been proposed as prognostic markers in this pathology. However, only a few approaches exist to block their specific activity during tumoral progress. In this article, we describe several TRP channels that have been involved in breast cancer progress with a particular focus on their binding partners that have also been described as drivers of breast cancer progression. Here, we propose disrupting these interactions as attractive and potential new therapeutic targets for treating this neoplastic disease.

Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review

Artificial intelligence (AI) renders cutting-edge applications in diverse sectors of society. Due to substantial progress in high-performance computing, the development of superior algorithms, and the accumulation of huge biological and chemical data, computer-assisted drug design technology is playing a key role in drug discovery with its advantages of high efficiency, fast speed, and low cost. Over recent years, due to continuous progress in machine learning (ML) algorithms, AI has been extensively employed in various drug discovery stages. Very recently, drug design and discovery have entered the big data era. ML algorithms have progressively developed into a deep learning technique with potent generalization capability and more effectual big data handling, which further promotes the integration of AI technology and computer-assisted drug discovery technology, hence accelerating the design and discovery of the newest drugs. This review mainly summarizes the application progression of AI technology in the drug discovery process, and explores and compares its advantages over conventional methods. The challenges and limitations of AI in drug design and discovery have also been discussed.

Progress in the therapeutic inhibition of Cdc42 signalling

Cdc42 is a member of the Rho family of small GTPases and a key regulator of the actin cytoskeleton, controlling cell motility, polarity and cell cycle progression. It signals downstream of the master regulator Ras and is essential for cell transformation by this potent oncogene. Overexpression of Cdc42 is observed in several cancers, where it is linked to poor prognosis. As a regulator of both cell architecture and motility, deregulation of Cdc42 is also linked to tumour metastasis. Like Ras, Cdc42 and other components of the signalling pathways it controls represent important potential targets for cancer therapeutics. In this review, we consider the progress that has been made targeting Cdc42, its regulators and effectors, including new modalities and new approaches to inhibition. Strategies under consideration include inhibition of lipid modification, modulation of Cdc42-GEF, Cdc42-GDI and Cdc42-effector interactions, and direct inhibition of downstream effectors.

Druggable binding sites in the multicomponent assemblies that characterise DNA double-strand-break repair through non-homologous end joining

Non-homologous end joining (NHEJ) is one of the two principal damage repair pathways for DNA double-strand breaks in cells. In this review, we give a brief overview of the system including a discussion of the effects of deregulation of NHEJ components in carcinogenesis and resistance to cancer therapy. We then discuss the relevance of targeting NHEJ components pharmacologically as a potential cancer therapy and review previous approaches to orthosteric regulation of NHEJ factors. Given the limited success of previous investigations to develop inhibitors against individual components, we give a brief discussion of the recent advances in computational and structural biology that allow us to explore different targets, with a particular focus on modulating protein-protein interaction interfaces. We illustrate this discussion with three examples showcasing some current approaches to developing protein-protein interaction inhibitors to modulate the assembly of NHEJ multiprotein complexes in space and time.

Structure-based molecular hybridization design of Keap1-Nrf2 inhibitors as novel protective agents of acute lung injury

Blocking the Kelch-like epichlorohydrin-related protein 1 (Keap1)-nuclear factor-erythroid 2 related factor 2 (Nrf2) pathway represents as a promising strategy to reduce oxidative stress and related-inflammation, including acute lung injury (ALI). NXPZ-2, a naphthalensulfonamide derivative, was previously reported to effectively inhibit the Keap1-Nrf2 protein-protein interaction (PPI) by our group. In the present work, a series of novel isothiocyanate-containing naphthalensulfonamides with the thioether, sulfoxide and sulfone moieties were designed by a structure-based molecular hybridization strategy using NXPZ-2 and the Nrf2 activator sulforaphane. They possessed good Keap1-Nrf2 PPI inhibitory activity and low cytotoxicity. The molecular docking study was performed to further explain the different activity of the thioether-, sulfoxide- and sulfone-containing naphthalensulfonamides. Among these new derivatives, 2-((N-(4-((N-(2-amino-2-oxoethyl)-4-((3-isothiocyanatopropyl)sulfinyl)phenyl)sulfonamido) naphthalen-1-yl)-4-methoxyphenyl)sulfonamido)acetamide (SCN-16) showed a good K_D2 value of 0.455 μM to disrupt the PPI. In an LPS-induced peritoneal macrophage cell model, this compound could cause a significant increase in the nuclear Nrf2 protein, decrease in the cytosolic Nrf2 protein, and further elevate the downstream protective enzymes HO-1 and NQO-1, which were better than the lead compound NXPZ-2 and sulforaphane. What's more, the production of ROS and NO and the expression of pro-inflammatory cytokine TNF-α were also suppressed. In the LPS-induced ALI model, SCN-16 could significantly reduce LPS-induced inflammations and alleviate lung injuries by triggering Nrf2 nuclear translocation. Collectively, our results suggested that SCN-16 could be a novel lead compound targeting Keap1-Nrf2 protective pathway for clinical treatment of ALI.

An Exploration of Chemical Properties Required for Cooperative Stabilization of the 14-3-3 Interaction with NF-κB-Utilizing a Reversible Covalent Tethering Approach

Protein–protein modulation has emerged as a proven approach to drug discovery. While significant progress has been gained in developing protein–protein interaction (PPI) inhibitors, the orthogonal approach of PPI stabilization lacks established methodologies for drug design. Here, we report the systematic ″bottom-up″ development of a reversible covalent PPI stabilizer. An imine bond was employed to anchor the stabilizer at the interface of the 14-3-3/p65 complex, leading to a molecular glue that elicited an 81-fold increase in complex stabilization. Utilizing protein crystallography and biophysical assays, we deconvoluted how chemical properties of a stabilizer translate to structural changes in the ternary 14-3-3/p65/molecular glue complex. Furthermore, we explore how this leads to high cooperativity and increased stability of the complex.

A Multipronged Screening Approach Targeting Inhibition of ETV6 PNT Domain Polymerization

ETV6 is an ETS family transcriptional repressor for which head-to-tail polymerization of its PNT domain facilitates cooperative binding to DNA by its ETS domain. Chromosomal translocations frequently fuse the ETV6 PNT domain to one of several protein tyrosine kinases. The resulting chimeric oncoproteins undergo ligand-independent self-association, autophosphorylation, and aberrant stimulation of downstream signaling pathways, leading to a variety of cancers. Currently, no small-molecule inhibitors of ETV6 PNT domain polymerization are known and no assays targeting PNT domain polymerization have been described. In this study, we developed complementary experimental and computational approaches for identifying such inhibitory compounds. One mammalian cellular approach utilized a mutant PNT domain heterodimer system covalently attached to split Gaussia luciferase fragments. In this protein-fragment complementation assay, inhibition of PNT domain heterodimerization reduces luminescence. A yeast assay took advantage of activation of the reporter HIS3 gene upon heterodimerization of mutant PNT domains fused to DNA-binding and transactivation domains. In this two-hybrid screen, inhibition of PNT domain heterodimerization prevents cell growth in medium lacking histidine. The Bristol University Docking Engine (BUDE) was used to identify virtual ligands from the ZINC8 library predicted to bind the PNT domain polymerization interfaces. More than 75 hits from these three assays were tested by nuclear magnetic resonance spectroscopy for binding to the purified ETV6 PNT domain. Although none were found to bind, the lessons learned from this study may facilitate future approaches for developing therapeutics that act against ETV6 oncoproteins by disrupting PNT domain polymerization.

Protein-protein interaction and in silico mutagenesis studies on IL17A and its peptide inhibitor

Protein-protein interactions of Interleukin-17 (IL17) play vital role in the autoimmune and inflammatory diseases, such as rheumatoid arthritis, multiple sclerosis, and psoriasis. Potent therapeutics for these diseases could be developed by blocking or modulating these interactions through biologics, peptide inhibitors and small molecule inhibitors. Unlike biologics, peptide inhibitors are cost effective and can be orally available. Peptide inhibitors do not require a binding groove as that of small molecules either. Therefore, crystal structure of IL17A in complex with a high affinity peptide inhibitor (HAP) (1-IHVTIPADLWDWIN-14) is investigated with an aim to find hot spots that could improve its potency. An in silico mutagenesis strategy was implemented using FoldX PSSM to scan for positions tolerant to amino acid substitution. Three positions T4, A7, and N14 showed improved stability when mutated with 'F/M/Y', 'P' and 'F/M/Y', respectively. A set of 31 mutant peptides are designed through combinations of these tolerant mutations using Build Model application of FoldX. Binding affinity and interactions of 31 peptides are assessed through protein-peptide docking and binding free energy calculations. Two peptides namely, P1 ("1-IHVTIPPDLWDWIY-14") and P2 ("1-IHVMIPPDLWDWIF-14") showed better binding affinity to IL17A dimerization site compared to HAP. Interactions of P1, P2 and HAP are also analyzed through 100 ns molecular dynamics simulations using GROMACS v5.0. The results revealed that the P2 peptide likely to offer better potency compared to HAP and P1. Therefore, the P2 peptide can be synthesized to develop oral therapies for autoimmune and inflammatory diseases with further experimental evaluations.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-02856-y.

Generalized-ensemble method study: A helix-mimetic compound inhibits protein-protein interaction by long-range and short-range intermolecular interactions

A heterocyclic compound mS-11 is a helix-mimetic designed to inhibit binding of an intrinsic disordered protein neural restrictive silence factor/repressor element 1 silencing factor (NRSF/REST) to a receptor protein mSin3B. We apply a generalized ensemble method, multi-dimensional virtual-system coupled molecular dynamics developed by ourselves recently, to a system consisting of mS-11 and mSin3B, and obtain a thermally equilibrated distribution, which is comprised of the bound and unbound states extensively. The lowest free-energy position of mS-11 coincides with the NRSF/REST position in the experimentally-determined NRSF/REST-mSin3B complex. Importantly, the molecular orientation of mS-11 is ordering in a wide region around mSin3B. The resultant binding scenario is: When mS-11 is distant from the binding site of mSin3B, mS-11 descends the free-energy slope toward the binding site maintaining the molecular orientation to be advantageous for binding. Then, finally a long and flexible hydrophobic sidechain of mS-11 fits into the binding site, which is the lowest-free-energy complex structure inhibiting NRSF/REST binding to mSin3B.

The Synergistic Effects of 5-Aminosalicylic Acid and Vorinostat in the Treatment of Ulcerative Colitis

Background: The drug 5-aminosalicylic acid (5-ASA) is the first-line therapy for the treatment of patients with mild-to-moderate ulcerative colitis (UC). However, in some cases, 5-ASA cannot achieve the desired therapeutic effects. Therefore, patients have to undergo therapies that include corticosteroids, monoclonal antibodies or immunosuppressants, which are expensive and may be accompanied by significant side effects. Synergistic drug combinations can achieve greater therapeutic effects than individual drugs while contributing to combating drug resistance and lessening toxic side effects. Thus, in this study, we sought to identify synergistic drugs that can act synergistically with 5-ASA. Methods: We started our study with protein-metabolite analysis based on peroxisome proliferator-activated receptor gamma (PPARG), the therapeutic target of 5-ASA, to identify more additional potential drug targets. Then, we further evaluated the possibility of their synergy with PPARG by integrating Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis, pathway-pathway interaction analysis, and semantic similarity analysis. Finally, we validated the synergistic effects with in vitro and in vivo experiments. Results: The combination of 5-ASA and vorinostat (SAHA) showed lower toxicity and mRNA expression of p65 in human colonic epithelial cell lines (Caco-2 and HCT-116), and more efficiently alleviated the symptoms of dextran sulfate sodium (DSS)-induced colitis than treatment with 5-ASA and SAHA alone. Conclusion: SAHA can exert effective synergistic effects with 5-ASA in the treatment of UC. One possible mechanism of synergism may be synergistic inhibition of the nuclear factor kappa B (NF-kB) signaling pathway. Moreover, the metabolite-butyric acid may be involved.

Affinity Selections of DNA-Encoded Chemical Libraries on Carbonic Anhydrase IX-Expressing Tumor Cells Reveal a Dependence on Ligand Valence

DNA-encoded chemical libraries are typically screened against purified protein targets. Recently, cell-based selections with encoded chemical libraries have been described, commonly revealing suboptimal performance due to insufficient recovery of binding molecules. We used carbonic anhydrase IX (CAIX)-expressing tumor cells as a model system to optimize selection procedures with code-specific quantitative polymerase chain reaction (qPCR) as selection readout. Salt concentration and performing PCR on cell suspension had the biggest impact on selection performance, leading to 15-fold enrichment factors for high-affinity monovalent CAIX binders (acetazolamide; K_D =8.7 nM). Surprisingly, the homobivalent display of acetazolamide at the extremities of both complementary DNA strands led to a substantial improvement of both ligand recovery and enrichment factors (above 100-fold). The optimized procedures were used for selections with a DNA-encoded chemical library comprising 1 million members against tumor cell lines expressing CAIX, leading to a preferential recovery of known and new ligands against this validated tumor-associated target. This work may facilitate future affinity selections on cells against target proteins which might be difficult to express otherwise.

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.

Rational Design of Peptide-Based Inhibitors Disrupting Protein-Protein Interactions

Protein-protein interactions (PPIs) are well-established as a class of promising drug targets for their implications in a wide range of biological processes. However, drug development toward PPIs is inevitably hampered by their flat and wide interfaces, which generally lack suitable pockets for ligand binding, rendering most PPI systems "undruggable." Here, we summarized drug design strategies for developing peptide-based PPI inhibitors. Importantly, several quintessential examples toward well-established PPI targets such as Bcl-2 family members, p53-MDM2, as well as APC-Asef are presented to illustrate the detailed schemes for peptide-based PPI inhibitor development and optimizations. This review supplies a comprehensive overview of recent progresses in drug discovery targeting PPIs through peptides or peptidomimetics, and will shed light on future therapeutic agent development toward the historically "intractable" PPI systems.

Identification of hot regions in hub protein-protein interactions by clustering and PPRA optimization

Background

Protein–protein interactions (PPIs) are the core of protein function, which provide an effective means to understand the function at cell level. Identification of PPIs is the crucial foundation of predicting drug-target interactions. Although traditional biological experiments of identifying PPIs are becoming available, these experiments remain to be extremely time-consuming and expensive. Therefore, various computational models have been introduced to identify PPIs. In protein-protein interaction network (PPIN), Hub protein, as a highly connected node, can coordinate PPIs and play biological functions. Detecting hot regions on Hub protein interaction interfaces is an issue worthy of discussing.

Methods

Two clustering methods, LCSD and RCNOIK are used to detect the hot regions on Hub protein interaction interfaces in this paper. In order to improve the efficiency of K-means clustering algorithm, the best k value is selected by calculating the distance square sum and the average silhouette coefficients. Then, the optimization of residue coordination number strategy is used to calculate the average coordination number. In addition, the pair potentials and relative ASA (PPRA) strategy is also used to optimize the predicted results.

Results

DataHub dataset and PartyHub dataset were used to train two clustering models respectively. Experiments show that LCSD and RCNOIK have the same coverage with Hub protein datasets, and RCNOIK is slightly higher than LCSD in Precision. The predicted hot regions are closer to the standard hot regions.

Conclusions

This paper optimizes two clustering methods based on PPRA strategy. Compared our methods for hot regions prediction against the well-known approaches, our improved methods have the higher reliability and are effective for predicting hot regions on Hub protein interaction interfaces.

How do you mend inactive tumor suppressor mutants? You glue them!

SMAD4 mutations that disrupt its interaction with SMAD3 and attenuate tumor suppression by TGF-β are major oncogenic drivers. Tang et al. (2020) report the discovery of small molecules that restore the SMAD4:SMAD3 complex and its cytostatic activity, exemplifying the therapeutic potential of fixing tumor suppressor mutants using molecular glues.

Antibody-based cancer therapy

Over the past 25 years, antibody therapeutics have emerged as clinically and commercially successful pharmaceuticals, rapidly approaching 100 Food and Drug Administration approvals with combined annual global sales exceeding $100 billion. Nearly half of the marketed antibody therapeutics are used in oncology. These antibody-based cancer therapies can be broken down into three categories based on their different mechanisms of action, i.e., (i) natural properties, (ii) engagement of cytotoxic T cells, and (iii) delivery of cytotoxic payloads. Both natural and engineered properties of the antibody molecule are founded on its highly stable and modular architecture. In this review we provide an overview and outlook of the rapidly evolving landscape of antibody-based cancer therapy.

Multistage signal-interactive nanoparticles improve tumor targeting through efficient nanoparticle-cell communications

Communication between biological components is critical for homeostasis maintenance among the convergence of complicated bio-signals. For therapeutic nanoparticles (NPs), the general lack of effective communication mechanisms with the external cellular environment causes loss of homeostasis, resulting in deprived autonomy, severe macrophage-mediated clearance, and limited tumor accumulation. Here, we develop a multistage signal-interactive system on porous silicon particles through integrating the Self-peptide and Tyr-Ile-Gly-Ser-Arg (YIGSR) peptide into a hierarchical chimeric signaling interface with “don’t eat me” and “eat me” signals. This biochemical transceiver can act as both the signal receiver for amantadine to achieve NP transformation and signal conversion as well as the signal source to present different signals sequentially by reversible self-mimicking. Compared with the non-interactive controls, these signal-interactive NPs loaded with AS1411 and tanespimycin (17-AAG) as anticancer drugs improve tumor targeting 2.8-fold and tumor suppression 6.5-fold and showed only 51% accumulation in the liver with restricted hepatic injury.

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Constructing a signal-interactive NP system improves NP-cell communication efficiency

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Functional chimeric peptide design enables orderly integrating of multiple signal modules

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Signal-interactive NPs reduce liver accumulation and promote tumor targeting