Between a rock and a hard place?

New approaches for challenging therapeutic targets

Despite successes with new drug approvals over the past two decades through conventional drug development approaches, many human diseases remain intractable to current therapeutic interventions. Possible barriers may be that the complexity of the target, and disease biology, are impervious to such conventional drug development approaches. The US National Institutes of Health hosted a workshop with the goal of identifying challenges and opportunities with alternative modalities for developing treatments across diseases associated with historically undruggable targets. This report highlights key issues discussed during the workshop that, if addressed, could expand the pool of therapeutic approaches for treating various diseases.

A one-two punch targeting reactive oxygen species and fibril for rescuing Alzheimer's disease

Toxic amyloid-beta (Aβ) plaque and harmful inflammation are two leading symptoms of Alzheimer's disease (AD). However, precise AD therapy is unrealizable due to the lack of dual-targeting therapy function, poor BBB penetration, and low imaging sensitivity. Here, we design a near-infrared-II aggregation-induced emission (AIE) nanotheranostic for precise AD therapy. The anti-quenching emission at 1350 nm accurately monitors the in vivo BBB penetration and specifically binding of nanotheranostic with plaques. Triggered by reactive oxygen species (ROS), two encapsulated therapeutic-type AIE molecules are controllably released to activate a self-enhanced therapy program. One specifically inhibits the Aβ fibrils formation, degrades Aβ fibrils, and prevents the reaggregation via multi-competitive interactions that are verified by computational analysis, which further alleviates the inflammation. Another effectively scavenges ROS and inflammation to remodel the cerebral redox balance and enhances the therapy effect, together reversing the neurotoxicity and achieving effective behavioral and cognitive improvements in the female AD mice model.

Expression of Lanthipeptides in Human Cells

Cyclic peptides represent a burgeoning area of interest in therapeutic and biotechnological research. In opposition to their linear counterparts, cyclic peptides, such as certain ribosomally synthesized and post-translationally modified peptides (RiPPs), are more conformationally constrained and less susceptible to proteolytic degradation. The lanthipeptide RiPP cytolysin L forms a covalently enforced helical structure that may be used to disrupt helical interactions at protein-protein interfaces. Herein, an expression system is reported to produce lanthipeptides and structurally diverse cytolysin L derivatives in mammalian cells. Successful targeting of lanthipeptides to the nucleus is demonstrated. In vivo expression and targeting of such peptides in mammalian cells may allow for screening of lanthipeptide inhibitors of native protein-protein interactions.

Targeting Protein-Protein Interfaces with Peptides: The Contribution of Chemical Combinatorial Peptide Library Approaches

Protein-protein interfaces play fundamental roles in the molecular mechanisms underlying pathophysiological pathways and are important targets for the design of compounds of therapeutic interest. However, the identification of binding sites on protein surfaces and the development of modulators of protein-protein interactions still represent a major challenge due to their highly dynamic and extensive interfacial areas. Over the years, multiple strategies including structural, computational, and combinatorial approaches have been developed to characterize PPI and to date, several successful examples of small molecules, antibodies, peptides, and aptamers able to modulate these interfaces have been determined. Notably, peptides are a particularly useful tool for inhibiting PPIs due to their exquisite potency, specificity, and selectivity. Here, after an overview of PPIs and of the commonly used approaches to identify and characterize them, we describe and evaluate the impact of chemical peptide libraries in medicinal chemistry with a special focus on the results achieved through recent applications of this methodology. Finally, we also discuss the role that this methodology can have in the framework of the opportunities, and challenges that the application of new predictive approaches based on artificial intelligence is generating in structural biology.

Near-Infrared Aggregation-Induced Emission Luminogens for In Vivo Theranostics of Alzheimer's Disease

Optimized theranostic strategies for Alzheimer's disease (AD) remain almost absent from bench to clinic. Current probes and drugs attempting to prevent β-amyloid (Aβ) fibrosis encounter failures due to the blood-brain barrier (BBB) penetration challenge and blind intervention time window. Herein, we design a near-infrared (NIR) aggregation-induced emission (AIE) probe, DNTPH, via balanced hydrophobicity-hydrophilicity strategy. DNTPH binds selectively to Aβ fibrils with a high signal-to-noise ratio. In vivo imaging revealed its excellent BBB permeability and long-term tracking ability with high-performance AD diagnosis. Remarkably, DNTPH exhibits a strong inhibitory effect on Aβ fibrosis and promotes fibril disassembly, thereby attenuating Aβ-induced neurotoxicity. DNTPH treatment significantly reduced Aβ plaques and rescued learning deficits in AD mice. Thus, DNTPH serves as the first AIE in vivo theranostic agent for real-time NIR imaging of Aβ plaques and AD therapy simultaneously.

Short Linear Motifs in Colorectal Cancer Interactome and Tumorigenesis

Colorectal tumorigenesis is driven by alterations in genes and proteins responsible for cancer initiation, progression, and invasion. This multistage process is based on a dense network of protein-protein interactions (PPIs) that become dysregulated as a result of changes in various cell signaling effectors. PPIs in signaling and regulatory networks are known to be mediated by short linear motifs (SLiMs), which are conserved contiguous regions of 3-10 amino acids within interacting protein domains. SLiMs are the minimum sequences required for modulating cellular PPI networks. Thus, several in silico approaches have been developed to predict and analyze SLiM-mediated PPIs. In this review, we focus on emerging evidence supporting a crucial role for SLiMs in driver pathways that are disrupted in colorectal cancer (CRC) tumorigenesis and related PPI network alterations. As a result, SLiMs, along with short peptides, are attracting the interest of researchers to devise small molecules amenable to be used as novel anti-CRC targeted therapies. Overall, the characterization of SLiMs mediating crucial PPIs in CRC may foster the development of more specific combined pharmacological approaches.

A Hybrid Docking and Machine Learning Approach to Enhance the Performance of Virtual Screening Carried out on Protein-Protein Interfaces

The modulation of protein-protein interactions (PPIs) by small chemical compounds is challenging. PPIs play a critical role in most cellular processes and are involved in numerous disease pathways. As such, novel strategies that assist the design of PPI inhibitors are of major importance. We previously reported that the knowledge-based DLIGAND2 scoring tool was the best-rescoring function for improving receptor-based virtual screening (VS) performed with the Surflex docking engine applied to several PPI targets with experimentally known active and inactive compounds. Here, we extend our investigation by assessing the vs. potential of other types of scoring functions with an emphasis on docking-pose derived solvent accessible surface area (SASA) descriptors, with or without the use of machine learning (ML) classifiers. First, we explored rescoring strategies of Surflex-generated docking poses with five GOLD scoring functions (GoldScore, ChemScore, ASP, ChemPLP, ChemScore with Receptor Depth Scaling) and with consensus scoring. The top-ranked poses were post-processed to derive a set of protein and ligand SASA descriptors in the bound and unbound states, which were combined to derive descriptors of the docked protein-ligand complexes. Further, eight ML models (tree, bagged forest, random forest, Bayesian, support vector machine, logistic regression, neural network, and neural network with bagging) were trained using the derivatized SASA descriptors and validated on test sets. The results show that many SASA descriptors are better than Surflex and GOLD scoring functions in terms of overall performance and early recovery success on the used dataset. The ML models were superior to all scoring functions and rescoring approaches for most targets yielding up to a seven-fold increase in enrichment factors at 1% of the screened collections. In particular, the neural networks and random forest-based ML emerged as the best techniques for this PPI dataset, making them robust and attractive vs. tools for hit-finding efforts. The presented results suggest that exploring further docking-pose derived SASA descriptors could be valuable for structure-based virtual screening projects, and in the present case, to assist the rational design of small-molecule PPI inhibitors.

Synaptic Secretion and Beyond: Targeting Synapse and Neurotransmitters to Treat Neurodegenerative Diseases

The nervous system is important, because it regulates the physiological function of the body. Neurons are the most basic structural and functional unit of the nervous system. The synapse is an asymmetric structure that is important for neuronal function. The chemical transmission mode of the synapse is realized through neurotransmitters and electrical processes. Based on vesicle transport, the abnormal information transmission process in the synapse can lead to a series of neurorelated diseases. Numerous proteins and complexes that regulate the process of vesicle transport, such as SNARE proteins, Munc18-1, and Synaptotagmin-1, have been identified. Their regulation of synaptic vesicle secretion is complicated and delicate, and their defects can lead to a series of neurodegenerative diseases. This review will discuss the structure and functions of vesicle-based synapses and their roles in neurons. Furthermore, we will analyze neurotransmitter and synaptic functions in neurodegenerative diseases and discuss the potential of using related drugs in their treatment.

Hidden allosteric sites and De-Novo drug design

INTRODUCTION

Hidden allosteric sites are not visible in apo-crystal structures, but they may be visible in holo-structures when a certain ligand binds and maintains the ligand intended conformation. Several computational and experimental techniques have been used to investigate these hidden sites but identifying them remains a challenge.

AREAS COVERED

This review provides a summary of the many theoretical approaches for predicting hidden allosteric sites in disease-related proteins. Furthermore, promising cases have been thoroughly examined to reveal the hidden allosteric site and its modulator.

EXPERT OPINION

In the recent past, with the development in scientific techniques and bioinformatics tools, the number of drug targets for complex human diseases has significantly increased but unfortunately most of these targets are undruggable due to several reasons. Alternative strategies such as finding cryptic (hidden) allosteric sites are an attractive approach for exploitation of the discovery of new targets. These hidden sites are difficult to recognize compared to allosteric sites, mainly due to a lack of visibility in the crystal structure. In our opinion, after many years of development, MD simulations are finally becoming successful for obtaining a detailed molecular description of drug-target interaction.

Pharmacologically Targeting the Fibroblast Growth Factor 14 Interaction Site on the Voltage-Gated Na+ Channel 1.6 Enables Isoform-Selective Modulation

Voltage-gated Na⁺ (Na_v) channels are the primary molecular determinant of the action potential. Among the nine isoforms of the Na_v channel α subunit that have been described (Na_v1.1-Na_v1.9), Na_v1.1, Na_v1.2, and Na_v1.6 are the primary isoforms expressed in the central nervous system (CNS). Crucially, these three CNS Na_v channel isoforms display differential expression across neuronal cell types and diverge with respect to their subcellular distributions. Considering these differences in terms of their localization, the CNS Na_v channel isoforms could represent promising targets for the development of targeted neuromodulators. However, current therapeutics that target Na_v channels lack selectivity, which results in deleterious side effects due to modulation of off-target Na_v channel isoforms. Among the structural components of the Na_v channel α subunit that could be pharmacologically targeted to achieve isoform selectivity, the C-terminal domains (CTD) of Na_v channels represent promising candidates on account of displaying appreciable amino acid sequence divergence that enables functionally unique protein–protein interactions (PPIs) with Na_v channel auxiliary proteins. In medium spiny neurons (MSNs) of the nucleus accumbens (NAc), a critical brain region of the mesocorticolimbic circuit, the PPI between the CTD of the Na_v1.6 channel and its auxiliary protein fibroblast growth factor 14 (FGF14) is central to the generation of electrical outputs, underscoring its potential value as a site for targeted neuromodulation. Focusing on this PPI, we previously developed a peptidomimetic derived from residues of FGF14 that have an interaction site on the CTD of the Na_v1.6 channel. In this work, we show that whereas the compound displays dose-dependent effects on the activity of Na_v1.6 channels in heterologous cells, the compound does not affect Na_v1.1 or Na_v1.2 channels at comparable concentrations. In addition, we show that the compound correspondingly modulates the action potential discharge and the transient Na+ of MSNs of the NAc. Overall, these results demonstrate that pharmacologically targeting the FGF14 interaction site on the CTD of the Na_v1.6 channel is a strategy to achieve isoform-selective modulation, and, more broadly, that sites on the CTDs of Na_v channels interacted with by auxiliary proteins could represent candidates for the development of targeted therapeutics.

pdCSM-PPI: Using Graph-Based Signatures to Identify Protein-Protein Interaction Inhibitors

Protein-protein interactions are promising sites for development of selective drugs; however, they have generally been viewed as challenging targets. Molecules targeting protein-protein interactions tend to be larger and more lipophilic than other drug-like molecules, mimicking the properties of interacting interfaces. Here, we propose a machine learning approach that uses a graph-based representation of small molecules to guide identification of inhibitors modulating protein-protein interactions, pdCSM-PPI. This approach was applied to 21 different PPI targets. We developed interaction-specific models that were able to accurately identify active compounds achieving MCC and F1 scores up to 1, and Pearson's correlations up to 0.87, outperforming previous approaches. Using insights from these individual models, we developed a generic protein-protein interaction modulator predictive model, which accurately predicted IC50 with a Pearson's correlation of 0.64 on a low redundancy blind test. Importantly, we were able to accurately identify active from inactive compounds, achieving an AUC of 0.77 and sensitivity and specificity of 76% and 78%, respectively. We believe pdCSM-PPI will be an important tool to help guide more efficient screening of new PPI inhibitors; it is freely available as an easy-to-use web server and API at http://biosig.unimelb.edu.au/pdcsm_ppi.

Improving Docking Power for Short Peptides Using Random Forest

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

Development of Allosteric Modulators of Voltage-Gated Na+ Channels: A Novel Approach for an Old Target

Given their primacy in governing the action potential (AP) of excitable cells, voltage-gated Na+ (Nav) channels are important pharmacological targets of therapeutics for a diverse array of clinical indications. Despite historically being a traditional drug target, therapeutics targeting Nav channels lack isoform selectivity, giving rise to off-target side effects. To develop isoform-selective modulators of Nav channels with improved target-specificity, the identification and pharmacological targeting of allosteric sites that display structural divergence among Nav channel isoforms represents an attractive approach. Despite the high homology among Nav channel α subunit isoforms (Nav1.1-Nav1.9), there is considerable amino acid sequence divergence among their constituent C-terminal domains (CTD), which enables structurally and functionally specific protein: protein interactions (PPI) with auxiliary proteins. Although pharmacological targeting of such PPI interfaces between the CTDs of Nav channels and auxiliary proteins represents an innovate approach for developing isoform-selective modulators of Nav channels, appreciable modulation of PPIs using small molecules has conventionally been difficult to achieve. After briefly discussing the challenges of modulating PPIs using small molecules, this current frontier review that follows subsequently expounds on approaches for circumventing such difficulties in the context of developing small molecule modulators of PPIs between transmembrane ion channels and their auxiliary proteins. In addition to broadly discussing such approaches, the implementation of such approaches is specifically discussed in the context of developing small molecule modulators between the CTD of Nav channels and auxiliary proteins. Developing allosteric modulators of ion channels by targeting their PPI interfaces with auxiliary proteins represents an innovative and promising strategy in ion channel drug discovery that could expand the "druggable genome" and usher in first-in-class PPI-targeting therapeutics for a multitude of channelopathies.

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.

Chalcone and its analogs: Therapeutic and diagnostic applications in Alzheimer's disease

Chalcone [(E)-1,3-diphenyl-2-propene-1-one], a small molecule with α, β unsaturated carbonyl group is a precursor or component of many natural flavonoids and isoflavonoids. It is one of the privileged structures in medicinal chemistry. It possesses a wide range of biological activities encouraging many medicinal chemists to study this scaffold for its usefulness to oncology, infectious diseases, virology and neurodegenerative diseases including Alzheimer's disease (AD). Small molecular size, convenient and cost-effective synthesis, and flexibility for modifications to modulate lipophilicity suitable for blood brain barrier (BBB) permeability make chalcones a preferred candidate for their therapeutic and diagnostic potential in AD. This review summarizes and highlights the importance of chalcone and its analogs as single target small therapeutic agents, multi-target directed ligands (MTDLs) as well as molecular imaging agents for AD. The information summarized here will guide many medicinal chemist and researchers involved in drug discovery to consider chalcone as a potential scaffold for the development of anti-AD agents including theranostics.

Fast Rescoring Protocols to Improve the Performance of Structure-Based Virtual Screening Performed on Protein-Protein Interfaces

Protein-protein interactions (PPIs) are attractive targets for drug design because of their essential role in numerous cellular processes and disease pathways. However, in general, PPIs display exposed binding pockets at the interface, and as such, have been largely unexploited for therapeutic interventions with low-molecular weight compounds. Here, we used docking and various rescoring strategies in an attempt to recover PPI inhibitors from a set of active and inactive molecules for 11 targets collected in ChEMBL and PubChem. Our focus is on the screening power of the various developed protocols and on using fast approaches so as to be able to apply such a strategy to the screening of ultralarge libraries in the future. First, we docked compounds into each target using the fast "pscreen" mode of the structure-based virtual screening (VS) package Surflex. Subsequently, the docking poses were postprocessed to derive a set of 3D topological descriptors: (i) shape similarity and (ii) interaction fingerprint similarity with a co-crystallized inhibitor, (iii) solvent-accessible surface area, and (iv) extent of deviation from the geometric center of a reference inhibitor. The derivatized descriptors, together with descriptor-scaled scoring functions, were utilized to investigate possible impacts on VS performance metrics. Moreover, four standalone scoring functions, RF-Score-VS (machine-learning), DLIGAND2 (knowledge-based), Vinardo (empirical), and X-SCORE (empirical), were employed to rescore the PPI compounds. Collectively, the results indicate that the topological scoring algorithms could be valuable both at a global level, with up to 79% increase in areas under the receiver operating characteristic curve for some targets, and in early stages, with up to a 4-fold increase in enrichment factors at 1% of the screened collections. Outstandingly, DLIGAND2 emerged as the best scoring function on this data set, outperforming all rescoring techniques in terms of VS metrics. The described methodology could help in the rational design of small-molecule PPI inhibitors and has direct applications in many therapeutic areas, including cancer, CNS, and infectious diseases such as COVID-19.

Anticancer drug discovery by targeting cullin neddylation

Protein neddylation is a post-translational modification which transfers the ubiquitin-like protein NEDD8 to a lysine residue of the target substrate through a three-step enzymatic cascade. The best-known substrates of neddylation are cullin family proteins, which are the core component of Cullin–RING E3 ubiquitin ligases (CRLs). Given that cullin neddylation is required for CRL activity, and CRLs control the turn-over of a variety of key signal proteins and are often abnormally activated in cancers, targeting neddylation becomes a promising approach for discovery of novel anti-cancer therapeutics. In the past decade, we have witnessed significant progress in the field of protein neddylation from preclinical target validation, to drug screening, then to the clinical trials of neddylation inhibitors. In this review, we first briefly introduced the nature of protein neddylation and the regulation of neddylation cascade, followed by a summary of all reported chemical inhibitors of neddylation enzymes. We then discussed the structure-based targeting of protein–protein interaction in neddylation cascade, and finally the available approaches for the discovery of new neddylation inhibitors. This review will provide a focused, up-to-date and yet comprehensive overview on the discovery effort of neddylation inhibitors.

Toward Development of the Male Pill: A Decade of Potential Non-hormonal Contraceptive Targets

With the continued steep rise of the global human population, and the paucity of safe and practical contraceptive options available to men, the need for development of effective and reversible non-hormonal methods of male fertility control is widely recognized. Currently there are several contraceptive options available to men, however, none of the non-hormonal alternatives have been clinically approved. To advance progress in the development of a safe and reversible contraceptive for men, further identification of novel reproductive tract-specific druggable protein targets is required. Here we provide an overview of genes/proteins identified in the last decade as specific or highly expressed in the male reproductive tract, with deletion phenotypes leading to complete male infertility in mice. These phenotypes include arrest of spermatogenesis and/or spermiogenesis, abnormal spermiation, abnormal spermatid morphology, abnormal sperm motility, azoospermia, globozoospermia, asthenozoospermia, and/or teratozoospermia, which are all desirable outcomes for a novel male contraceptive. We also consider other associated deletion phenotypes that could impact the desirability of a potential contraceptive. We further discuss novel contraceptive targets underscoring promising leads with the objective of presenting data for potential druggability and whether collateral effects may exist from paralogs with close sequence similarity.

Interaction Energetics and Druggability of the Protein-Protein Interaction between Kelch-like ECH-Associated Protein 1 (KEAP1) and Nuclear Factor Erythroid 2 Like 2 (Nrf2)

Development of small molecule inhibitors of protein-protein interactions (PPIs) is hampered by our poor understanding of the druggability of PPI target sites. Here, we describe the combined application of alanine-scanning mutagenesis, fragment screening, and FTMap computational hot spot mapping to evaluate the energetics and druggability of the highly charged PPI interface between Kelch-like ECH-associated protein 1 (KEAP1) and nuclear factor erythroid 2 like 2 (Nrf2), an important drug target. FTMap identifies four binding energy hot spots at the active site. Only two of these are exploited by Nrf2, which alanine scanning of both proteins shows to bind primarily through E79 and E82 interacting with KEAP1 residues S363, R380, R415, R483, and S508. We identify fragment hits and obtain X-ray complex structures for three fragments via crystal soaking using a new crystal form of KEAP1. Combining these results provides a comprehensive and quantitative picture of the origins of binding energy at the interface. Our findings additionally reveal non-native interactions that might be exploited in the design of uncharged synthetic ligands to occupy the same site on KEAP1 that has evolved to bind the highly charged DEETGE binding loop of Nrf2. These include π-stacking with KEAP1 Y525 and interactions at an FTMap-identified hot spot deep in the binding site. Finally, we discuss how the complementary information provided by alanine-scanning mutagenesis, fragment screening, and computational hot spot mapping can be integrated to more comprehensively evaluate PPI druggability.

Organoplatinum-Substituted Polyoxometalate Inhibits β-amyloid Aggregation for Alzheimer's Therapy

Aggregated β-amyloid (Aβ) is widely considered as a key factor in triggering progressive loss of neuronal function in Alzheimer's disease (AD), so targeting and inhibiting Aβ aggregation has been broadly recognized as an efficient therapeutic strategy for curing AD. Herein, we designed and prepared an organic platinum-substituted polyoxometalate, (Me₄ N)₃ [PW₁₁ O₄₀ (SiC₃ H₆ NH₂ )₂ PtCl₂ ] (abbreviated as Pt^II -PW₁₁ ) for inhibiting Aβ₄₂ aggregation. The mechanism of inhibition on Aβ₄₂ aggregation by Pt^II -PW₁₁ was attributed to the multiple interactions of Pt^II -PW₁₁ with Aβ₄₂ including coordination interaction of Pt²⁺ in Pt^II -PW₁₁ with amino group in Aβ₄₂ , electrostatic attraction, hydrogen bonding and van der Waals force. In cell-based assay, Pt^II -PW₁₁ displayed remarkable neuroprotective effect for Aβ₄₂ aggregation-induced cytotoxicity, leading to increase of cell viability from 49 % to 67 % at a dosage of 8 μm. More importantly, the Pt^II -PW₁₁ greatly reduced Aβ deposition and rescued memory loss in APP/PS1 transgenic AD model mice without noticeable cytotoxicity, demonstrating its potential as drugs for AD treatment.

Modelling the binding mode of macrocycles: Docking and conformational sampling

Drug discovery is increasingly tackling challenging protein binding sites regarding molecular recognition and druggability, including shallow and solvent-exposed protein-protein interaction interfaces. Macrocycles are emerging as promising chemotypes to modulate such sites. Despite their chemical complexity, macrocycles comprise important drugs and offer advantages compared to non-cyclic analogs, hence the recent impetus in the medicinal chemistry of macrocycles. Elaboration of macrocycles, or constituent fragments, can strongly benefit from knowledge of their binding mode to a target. When such information from X-ray crystallography is elusive, computational docking can provide working models. However, few studies have explored docking protocols for macrocycles, since conventional docking methods struggle with the conformational complexity of macrocycles, and also potentially with the shallower topology of their binding sites. Indeed, macrocycle binding mode prediction with the mainstream docking software GOLD has hardly been explored. Here, we present an in-depth study of macrocycle docking with GOLD and the ChemPLP scores. First, we summarize the thorough curation of a test set of 41 protein-macrocycle X-ray structures, raising the issue of lattice contacts with such systems. Rigid docking of the known bioactive conformers was successful (three top ranked poses) for 92.7% of the systems, in absence of crystallographic waters. Thus, without conformational search issues, scoring performed well. However, docking success dropped to 29.3% with the GOLD built-in conformational search. Yet, the success rate doubled to 58.5% when GOLD was supplied with extensive conformer ensembles docked rigidly. The reasons for failure, sampling or scoring, were analyzed, exemplified with particular cases. Overall, binding mode prediction of macrocycles remains challenging, but can be much improved with tailored protocols. The analysis of the interplay between conformational sampling and docking will be relevant to the prospective modelling of macrocycles in general.

Allosteric Modulators of Protein-Protein Interactions (PPIs)

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

Computational Opportunities and Challenges in Finding Cyclic Peptide Modulators of Protein-Protein Interactions

Peptide cyclization can improve stability, conformational constraint, and compactness. However, apart from beta-turn structures, which are well incorporated into cyclic peptides (CPs), many primary peptide structures and functions are markedly altered by cyclization. Accordingly, to mimic linear peptide interfaces with cyclic peptides, it can be beneficial to screen combinatorial cyclic peptide libraries. Computational methods have been developed to screen CPs, but face a number of challenges. Here, we review methods to develop in silico computational libraries, and the potential for screening naturally occurring libraries of CPs. The simplest and most rapid computational pharmacophore methods that estimate peptide three-dimensional structures to be screened versus targets are relatively easy to implement, and while the constraint on structure imposed by cyclization makes them more effective than the same approaches with linear peptides, there are a large number of limiting assumptions. In contrast, full molecular dynamics simulations of cyclic peptide structures not only are costly to implement, but also require careful attention to interpretation, so that not only is the computation time rate limiting, but the interpretation time is also rate limiting due to the analysis of the typically complex underlying conformational space of CPs. A challenge for the field of computational cyclic peptide screening is to bridge this gap effectively. Natural compound libraries of short cyclic peptides, and short cyclized regions of proteins, encoded in the genomes of many organisms present a potential treasure trove of novel functionality which may be screened via combined computational and experimental screening approaches.

Protein-Protein Interactions: Emerging Oncotargets in the RAS-ERK Pathway

Given the implication of aberrant RAS-extracellular signal-regulated kinase (ERK) signaling in the development of a large number of tumor types, this route is under intense scrutiny to identify new anticancer drugs. Most avenues in that direction have been primarily focused on the inhibition of the catalytic activity of the kinases that participate in this pathway. Although promising, the efficacy of these therapies is short lived due to undesired toxicity and/or drug resistance problems. As an alternative path, new efforts are now being devoted to the targeting of protein-protein interactions (PPIs) involved in the flow of RAS-ERK signals. Many of these efforts have shown promising results in preclinical models. In this review, we summarize recent progress made in this area.

ERK1/2 inhibitors: New weapons to inhibit the RAS-regulated RAF-MEK1/2-ERK1/2 pathway

The RAS-regulated RAF-MEK1/2-ERK1/2 signalling pathway is de-regulated in a variety of cancers due to mutations in receptor tyrosine kinases (RTKs), negative regulators of RAS (such as NF1) and core pathway components themselves (RAS, BRAF, CRAF, MEK1 or MEK2). This has driven the development of a variety of pharmaceutical agents to inhibit RAF-MEK1/2-ERK1/2 signalling in cancer and both RAF and MEK inhibitors are now approved and used in the clinic. There is now much interest in targeting at the level of ERK1/2 for a variety of reasons. First, since the pathway is linear from RAF-to-MEK-to-ERK then ERK1/2 are validated as targets per se. Second, innate resistance to RAF or MEK inhibitors involves relief of negative feedback and pathway re-activation with all signalling going through ERK1/2, validating the use of ERK inhibitors with RAF or MEK inhibitors as an up-front combination. Third, long-term acquired resistance to RAF or MEK inhibitors involves a variety of mechanisms (KRAS or BRAF amplification, MEK mutation, etc.) which re-instate ERK activity, validating the use of ERK inhibitors to forestall acquired resistance to RAF or MEK inhibitors. The first potent highly selective ERK1/2 inhibitors have now been developed and are entering clinical trials. They have one of three discrete mechanisms of action - catalytic, "dual mechanism" or covalent - which could have profound consequences for how cells respond and adapt. In this review we describe the validation of ERK1/2 as anti-cancer drug targets, consider the mechanism of action of new ERK1/2 inhibitors and how this may impact on their efficacy, anticipate factors that will determine how tumour cells respond and adapt to ERK1/2 inhibitors and consider ERK1/2 inhibitor drug combinations.

Structural insights into pharmacophore-assisted in silico identification of protein-protein interaction inhibitors for inhibition of human toll-like receptor 4 - myeloid differentiation factor-2 (hTLR4-MD-2) complex

Toll-like receptor 4 (TLR4) is a member of Toll-Like Receptors (TLRs) family that serves as a receptor for bacterial lipopolysaccharide (LPS). TLR4 alone cannot recognize LPS without aid of co-receptor myeloid differentiation factor-2 (MD-2). Binding of LPS with TLR4 forms a LPS-TLR4-MD-2 complex and directs downstream signaling for activation of immune response, inflammation and NF-κB activation. Activation of TLR4 signaling is associated with various pathophysiological consequences. Therefore, targeting protein-protein interaction (PPI) in TLR4-MD-2 complex formation could be an attractive therapeutic approach for targeting inflammatory disorders. The aim of present study was directed to identify small molecule PPI inhibitors (SMPPIIs) using pharmacophore mapping-based approach of computational drug discovery. Here, we had retrieved the information about the hot spot residues and their pharmacophoric features at both primary (TLR4-MD-2) and dimerization (MD-2-TLR4*) protein-protein interaction interfaces in TLR4-MD-2 homo-dimer complex using in silico methods. Promising candidates were identified after virtual screening, which may restrict TLR4-MD-2 protein-protein interaction. In silico off-target profiling over the virtually screened compounds revealed other possible molecular targets. Two of the virtually screened compounds (C11 and C15) were predicted to have an inhibitory concentration in μM range after HYDE assessment. Molecular dynamics simulation study performed for these two compounds in complex with target protein confirms the stability of the complex. After virtual high throughput screening we found selective hTLR4-MD-2 inhibitors, which may have therapeutic potential to target chronic inflammatory diseases.

Cryptic binding sites on proteins: definition, detection, and druggability

Many proteins in their unbound structures lack surface pockets appropriately sized for drug binding. Hence, a variety of experimental and computational tools have been developed for the identification of cryptic sites that are not evident in the unbound protein but form upon ligand binding, and can provide tractable drug target sites. The goal of this review is to discuss the definition, detection, and druggability of such sites, and their potential value for drug discovery. Novel methods based on molecular dynamics simulations are particularly promising and yield a large number of transient pockets, but it has been shown that only a minority of such sites are generally capable of binding ligands with substantial affinity. Based on recent studies, current methodology can be improved by combining molecular dynamics with fragment docking and machine learning approaches.

Exploring the structural origins of cryptic sites on proteins

Molecular dynamics (MD) simulations of proteins reveal the existence of many transient surface pockets; however, the factors determining what small subset of these represent druggable or functionally relevant ligand binding sites, called "cryptic sites," are not understood. Here, we examine multiple X-ray structures for a set of proteins with validated cryptic sites, using the computational hot spot identification tool FTMap. The results show that cryptic sites in ligand-free structures generally have a strong binding energy hot spot very close by. As expected, regions around cryptic sites exhibit above-average flexibility, and close to 50% of the proteins studied here have unbound structures that could accommodate the ligand without clashes. Nevertheless, the strong hot spot neighboring each cryptic site is almost always exploited by the bound ligand, suggesting that binding may frequently involve an induced fit component. We additionally evaluated the structural basis for cryptic site formation, by comparing unbound to bound structures. Cryptic sites are most frequently occluded in the unbound structure by intrusion of loops (22.5%), side chains (19.4%), or in some cases entire helices (5.4%), but motions that create sites that are too open can also eliminate pockets (19.4%). The flexibility of cryptic sites frequently leads to missing side chains or loops (12%) that are particularly evident in low resolution crystal structures. An interesting observation is that cryptic sites formed solely by the movement of side chains, or of backbone segments with fewer than five residues, result only in low affinity binding sites with limited use for drug discovery.

Progress towards the broad use of non-peptide synthetic macrocycles in drug discovery

We discuss progress towards addressing three key questions pertaining to the design of screening libraries of synthetic non-peptidic macrocycles (MCs) for drug discovery: What structural and physicochemical properties of MCs maximize the likelihood of achieving strong and specific binding to protein targets? What features render a protein target suitable for binding MCs, and can this information be used to identify suitable targets for inhibition by MCs? What properties of synthetic MCs confer good pharmaceutical properties, and particularly good aqueous solubility coupled with passive membrane permeability? We additionally discuss how the criteria that define a meaningful MC screening hit are linked to the size of the screening library and the synthetic methodology employed in its preparation.

Differential Protein Dynamics of Regulators of G-Protein Signaling: Role in Specificity of Small-Molecule Inhibitors

Small-molecule inhibitor selectivity may be influenced by variation in dynamics among members of a protein family. Regulator of G-protein Signaling (RGS) proteins are a family that plays a key role in G-Protein Coupled Receptor (GPCR) signaling by binding to active Gα subunits and accelerating GTP hydrolysis, thereby terminating activity. Thiadiazolidinones (TDZDs) inhibit the RGS-Gα interaction by covalent modification of cysteine residues in RGS proteins. Some differences in specificity may be explained by differences in the complement of cysteines among RGS proteins. However, key cysteines shared by RGS proteins inhibited by TDZDs are not exposed on the protein surface, and differences in potency exist among RGS proteins containing only buried cysteines. We hypothesize that differential exposure of buried cysteine residues among RGS proteins partially drives TDZD selectivity. Hydrogen-deuterium exchange (HDX) studies and molecular dynamics (MD) simulations were used to probe the dynamics of RGS4, RGS8, and RGS19, three RGS proteins inhibited at a range of potencies by TDZDs. When these proteins were mutated to contain a single, shared cysteine, RGS19 was found to be most potently inhibited. HDX studies revealed differences in α4 and α6 helix flexibility among RGS isoforms, with particularly high flexibility in RGS19. This could cause differences in cysteine exposure and lead to differences in potency of TDZD inhibition. MD simulations of RGS proteins revealed motions that correspond to solvent exposure observed in HDX, providing further evidence for a role of protein dynamics in TDZD selectivity.

Toward Small-Molecule Inhibition of Protein-Protein Interactions: General Aspects and Recent Progress in Targeting Costimulatory and Coinhibitory (Immune Checkpoint) Interactions

Protein-Protein Interactions (PPIs) that are part of the costimulatory and coinhibitory (immune checkpoint) signaling are critical for adequate T cell response and are important therapeutic targets for immunomodulation. Biologics targeting them have already achieved considerable clinical success in the treatment of autoimmune diseases or transplant recipients (e.g., abatacept, belatacept, and belimumab) as well as cancer (e.g., ipilimumab, nivolumab, pembrolizumab, atezolizumab, durvalumab, and avelumab). In view of such progress, there have been only relatively limited efforts toward developing small-molecule PPI inhibitors (SMPPIIs) targeting these cosignaling interactions, possibly because they, as all other PPIs, are difficult to target by small molecules and were not considered druggable. Nevertheless, substantial progress has been achieved during the last decade. SMPPIIs proving the feasibility of such approaches have been identified through various strategies for a number of cosignaling interactions including CD40-CD40L, OX40-OX40L, BAFFR-BAFF, CD80-CD28, and PD-1-PD-L1s. Here, after an overview of the general aspects and challenges of SMPPII-focused drug discovery, we review them briefly together with relevant structural, immune-signaling, physicochemical, and medicinal chemistry aspects. While so far only a few of these SMPPIIs have shown activity in animal models (DRI-C21045 for CD40-D40L, KR33426 for BAFFR-BAFF) or reached clinical development (RhuDex for CD80-CD28, CA-170 for PD-1-PD-L1), there is proof-of-principle evidence for the feasibility of such approaches in immunomodulation. They can result in products that are easier to develop/ manufacture and are less likely to be immunogenic or encounter postmarket safety events than corresponding biologics, and, contrary to them, can even become orally bioavailable.

Small-Molecule Inhibitors of the CD40-CD40L Costimulatory Protein-Protein Interaction

Costimulatory interactions are required for T cell activation and development of an effective immune response; hence, they are valuable therapeutic targets for immunomodulation. However, they, as all other protein-protein interactions, are difficult to target by small molecules. Here, we report the identification of novel small-molecule inhibitors of the CD40-CD40L interaction designed starting from the chemical space of organic dyes. For the most promising compounds such as DRI-C21045, activity (IC50) in the low micromolar range has been confirmed in cell assays including inhibition of CD40L-induced activation in NF-κB sensor cells, THP-1 myeloid cells, and primary human B cells as well as in murine allogeneic skin transplant and alloantigen-induced T cell expansion in draining lymph node experiments. Specificity versus other TNF-superfamily interactions (TNF-R1-TNF-α) and lack of cytotoxicity have also been confirmed at these concentrations. These novel compounds provide proof-of-principle evidence for the possibility of small-molecule inhibition of costimulatory protein-protein interactions, establish the structural requirements needed for efficient CD40-CD40L inhibition, and serve to guide the search for such immune therapeutics.

A yeast two-hybrid system for the screening and characterization of small-molecule inhibitors of protein-protein interactions identifies a novel putative Mdm2-binding site in p53

BACKGROUND

Protein-protein interactions (PPIs) are fundamental to the growth and survival of cells and serve as excellent targets to develop inhibitors of biological processes such as host-pathogen interactions and cancer cell proliferation. However, isolation of PPI inhibitors is extremely challenging. While several in vitro assays to screen for PPI inhibitors are available, they are often expensive, cumbersome, and require large amounts of purified protein. In contrast, limited in vivo assays are available to screen for small-molecule inhibitors of PPI.

METHODS

We have engineered a yeast strain that is suitable for screening of small-molecule inhibitors of protein-protein interaction using the Yeast 2-hybrid Assay. We have optimised and validated the assay using inhibitors of the p53-Mdm2 interaction and identified a hitherto unreported putative Mdm2-binding domain in p53.

RESULTS

We report a significantly improved and thoroughly validated yeast two-hybrid (Y2H) assay that can be used in a high throughput manner to screen for small-molecule PPI inhibitors. Using the p53-Mdm2 interaction to optimize the assay, we show that the p53-Mdm2 inhibitor nutlin-3 is a substrate for the yeast ATP-binding cassette (ABC) transporter Pdr5. By deleting nine ABC transporter-related genes, we generated a ABC9Δ yeast strain that is highly permeable to small molecules. In the ABC9Δ strain, p53-Mdm2 interaction inhibitors, like AMG232 and MI-773, completely inhibited the p53-Mdm2 interaction at nanomolar concentrations in the Y2H assay. In addition, we identified a conserved segment in the core DNA-binding domain of p53 that facilitates stable interaction with Mdm2 in yeast cells and in vitro.

CONCLUSION

The Y2H assay can be utilized for high-throughput screening of small-molecule inhibitors of PPIs and to identify domains that stabilize PPIs.

Development of proteolytically stable N-methylated peptide inhibitors of aggregation of the amylin peptide implicated in type 2 diabetes

Islet amyloid polypeptide, also known as amylin, is the main component of the amyloid deposits present in approximately 90% of people with type 2 diabetes mellitus (T2DM). In this disease, amylin aggregates into multimeric β-pleated sheet structures which cause damage to pancreatic islet β-cells. Inhibitors of early-stage amylin aggregation could therefore provide a disease-modifying treatment for T2DM. In this study, overlapping peptides were designed to target the 'binding' region (RLANFLVHSS, residues 11-20) of human amylin, and their effects on amyloid fibril formation were determined by thioflavin-T assay. The first generation peptides showed less than 50% inhibition of aggregation, but a second generation peptide (H₂N-RGANFLVHGR-CONH₂) showed strong inhibitory effects on amylin aggregation, and this was confirmed by negative stain electron microscopy. Cytotoxicity studies revealed that this peptide protected human pancreatic 1.4E7 (ECACC 10070102) insulin-secreting cells from the toxic effects of human amylin. Unlike the retro-inverso version of this peptide, which stimulated aggregation, two N-methylated peptides (H₂N-RGAmNFmLVmHGR-CONH₂ and H₂N-RGANmFLmVHmR-CONH₂) gave very clear dose-dependent inhibition of fibril formation. These two peptides were also stable against a range of different proteolytic enzymes, and in human plasma. These N-methylated peptides could provide a novel treatment for slowing progression of T2DM.

Advances in the synthesis of glycosidic macrolides: clavosolides A-D and cyanolide A

Covering: 2005 to 2016Clavosolides A-D and cyanolide A are glycosidic macrolides and represent a new family of marine natural products. They possess a number of unusual structural features and have attracted considerable interest from the synthetic community. This review presents a comprehensive survey of all aspects of the clavosolides A-D and cyanolide A. Specific topics include isolation, structure determination, biological activity, and synthetic approaches.

A diversity oriented synthesis of natural product inspired molecular libraries

Diversity oriented synthesis of natural product inspired compounds from S-tryptophan methyl ester.

Tuning Oligovalent Biomacromolecular Interfaces Using Double-Layered α-Helical Coiled-Coil Nanoassemblies from Lariat-Type Building Blocks

The target affinity and selectivity of many biomacromolecules depend on the three-dimensional (3D) distribution of multiple ligands on their surfaces. Here, we devised a self-assembly strategy to control the target-tailored 3D distribution of multiple α-helical ligands on a coiled-coil core scaffold using novel lariat-type supramolecular building blocks. Depending on the coiled-coil composition and ligand grafting sites in the lariat building blocks, the structural and functional features of the self-assembled peptide nanostructures (SPNs) could be variably fine-tuned. Using oligovalent protein-RNA (Rev-RRE) interactions as a model system, we demonstrate that longer grafting reinforces the helicity of the peptide ligands, whereas shorter grafting strengthens the target binding affinity of the SPNs in both monovalent and oligovalent interactions. This supramolecular approach should be useful in developing precisely controllable multivalent ligands for biomacromolecular interactions.

Tunable Helicity, Stability and DNA-Binding Properties of Short Peptides with Hybrid Metal Coordination Motifs

Given the prevalent role of α-helical motifs on protein surfaces in mediating protein-protein and protein-DNA interactions, there have been significant efforts to develop strategies to induce α-helicity in short, unstructured peptides to interrogate such interactions. Toward this goal, we have recently introduced hybrid metal coordination motifs (HCMs). HCMs combine a natural metal-binding amino acid side chain with a synthetic chelating group that are appropriately positioned in a peptide sequence to stabilize an α-helical conformation upon metal coordination. Here, we present a series of short peptides modified with HCMs consisting of a His and a phenanthroline group at i and i+7 positions that can induce α-helicity in a metal-tunable fashion as well as direct the formation of discrete dimeric architectures for recognition of biological targets. We show that the induction of α-helicity can be further modulated by secondary sphere interactions between amino acids at the i+4 position and the HCM. A frequently cited drawback of the use of peptides as therapeutics is their propensity to be quickly digested by proteases; here, we observe an enhancement of up to ∼100-fold in the half-lifes of the metal-bound HCM-peptides in the presence of trypsin. Finally, we show that an HCM-bearing peptide sequence, which contains the DNA-recognition domain of a bZIP protein but is devoid of the obligate dimerization domain, can dimerize with the proper geometry and in an α-helical conformation to bind a cognate DNA sequence with high affinities (K_d≥ 65 nM), again in a metal-tunable manner.

β-Turn mimetic-based stabilizers of protein-protein interactions for the study of the non-canonical roles of leucyl-tRNA synthetase

For the systematic perturbation of protein–protein interactions, we designed and synthesized tetra-substituted hexahydro-4H-pyrazino[2,1-c][1,2,4]triazine-4,7(6H)-diones as β-turn mimetics. 5c{3,9} stabilizes the direct interaction between LRS and RagD and activates mTORC1 in living cells.

For the systematic perturbation of protein–protein interactions, we designed and synthesized tetra-substituted hexahydro-4H-pyrazino[2,1-c][1,2,4]triazine-4,7(6H)-diones as β-turn mimetics. We then devised a new synthetic route to obtain β-turn mimetic scaffolds via tandem N-acyliminium cyclization and constructed a 162-member library of tetra-substituted pyrazinotriazinediones with an average purity of 90% using a solid-phase parallel synthesis platform. Each library member was subjected to ELISA-based modulator screening for the LRS–RagD interaction, which plays a pivotal role in the nutrient-dependent mTORC1 signalling pathway. Western blot analysis of phosphorylated S6K1 as well as FRET-based imaging confirmed that 5c{3,9} stabilizes the direct interaction between LRS and RagD and activates mTORC1 in live cells under leucine-deprived conditions. Thus, 5c{3,9} can be used as a new research tool for studying the non-canonical role of LRS.

Sequence context and crosslinking mechanism affect the efficiency of in vivo capture of a protein-protein interaction

Protein-protein interactions (PPIs) are essential for implementing cellular processes and thus methods for the discovery and study of PPIs are highly desirable. An emerging method for capturing PPIs in their native cellular environment is in vivo covalent chemical capture, a method that uses nonsense suppression to site specifically incorporate photoactivable unnatural amino acids (UAAs) in living cells. However, in one study we found that this method did not capture a PPI for which there was abundant functional evidence, a complex formed between the transcriptional activator Gal4 and its repressor protein Gal80. Here we describe the factors that influence the success of covalent chemical capture and show that the innate reactivity of the two UAAs utilized, (p-benzoylphenylalanine (pBpa) and p-azidophenylalanine (pAzpa)), plays a profound role in the capture of Gal80 by Gal4. Based upon these data, guidelines are outlined for the successful use of in vivo photo-crosslinking to capture novel PPIs and to characterize the interfaces.

An Intriguing Correlation Based on the Superimposition of Residue Pairs with Inhibitors that Target Protein-Protein Interfaces

Druggable sites on protein-protein interfaces are difficult to predict. To survey inhibitor-binding sites onto which residues are superimposed at protein-protein interfaces, we analyzed publicly available information for 39 inhibitors that target the protein-protein interfaces of 8 drug targets. By focusing on the differences between residues that were superimposed with inhibitors and non-superimposed residues, we observed clear differences in the distances and changes in the solvent-accessible surface areas (∆SASA). Based on the observation that two or more residues were superimposed onto inhibitors in 37 (95%) of 39 protein-inhibitor complexes, we focused on the two-residue relationships. Application of a cross-validation procedure confirmed a linear negative correlation between the absolute value of the dihedral angle and the sum of the ∆SASAs of the residues. Finally, we applied the regression equation of this correlation to four inhibitors that bind to new sites not bound by the 39 inhibitors as well as additional inhibitors of different targets. Our results shed light on the two-residue correlation between the absolute value of the dihedral angle and the sum of the ∆SASA, which may be a useful relationship for identifying the key two-residues as potential targets of protein-protein interfaces.

Targeting protein-protein interactions in hematologic malignancies: still a challenge or a great opportunity for future therapies?

Over the past several years, there has been an increasing research effort focused on inhibition of protein-protein interactions (PPIs) to develop novel therapeutic approaches for cancer, including hematologic malignancies. These efforts have led to development of small molecule inhibitors of PPIs, some of which already advanced to the stage of clinical trials while others are at different stages of preclinical optimization, emphasizing PPIs as an emerging and attractive class of drug targets. Here, we review several examples of recently developed inhibitors of PPIs highly relevant to hematologic cancers. We address the existing skepticism about feasibility of targeting PPIs and emphasize potential therapeutic benefit from blocking PPIs in hematologic malignancies. We then use these examples to discuss the approaches for successful identification of PPI inhibitors and provide analysis of the protein-protein interfaces, with the goal to address 'druggability' of new PPIs relevant to hematology. We discuss lessons learned to improve the success of targeting new PPIs and evaluate prospects and limits of the research in this field. We conclude that not all PPIs are equally tractable for blocking by small molecules, and detailed analysis of PPI interfaces is critical for selection of those with the highest chance of success. Together, our analysis uncovers patterns that should help to advance drug discovery in hematologic malignancies by successful targeting of new PPIs.

New Frontiers in Druggability

A powerful early approach to evaluating the druggability of proteins involved determining the hit rate in NMR-based screening of a library of small compounds. Here, we show that a computational analog of this method, based on mapping proteins using small molecules as probes, can reliably reproduce druggability results from NMR-based screening and can provide a more meaningful assessment in cases where the two approaches disagree. We apply the method to a large set of proteins. The results show that, because the method is based on the biophysics of binding rather than on empirical parametrization, meaningful information can be gained about classes of proteins and classes of compounds beyond those resembling validated targets and conventionally druglike ligands. In particular, the method identifies targets that, while not druggable by druglike compounds, may become druggable using compound classes such as macrocycles or other large molecules beyond the rule-of-five limit.

A Kinase Divided

In this issue of Cancer Cell, Herrero and colleagues identify an anti-tumorigenic small molecule that blocks ERK dimerization, but neither its catalytic activity nor its phosphorylation by MEK. These findings demonstrate that targeting protein dimerization could be a therapeutic avenue for inhibiting kinase signaling pathways associated with lower drug resistance.

AlphaSpace: Fragment-Centric Topographical Mapping To Target Protein-Protein Interaction Interfaces

Inhibition of protein–protein interactions (PPIs) is emerging as a promising therapeutic strategy despite the difficulty in targeting such interfaces with drug-like small molecules. PPIs generally feature large and flat binding surfaces as compared to typical drug targets. These features pose a challenge for structural characterization of the surface using geometry-based pocket-detection methods. An attractive mapping strategy—that builds on the principles of fragment-based drug discovery (FBDD)—is to detect the fragment-centric modularity at the protein surface and then characterize the large PPI interface as a set of localized, fragment-targetable interaction regions. Here, we introduce AlphaSpace, a computational analysis tool designed for fragment-centric topographical mapping (FCTM) of PPI interfaces. Our approach uses the alpha sphere construct, a geometric feature of a protein’s Voronoi diagram, to map out concave interaction space at the protein surface. We introduce two new features—alpha-atom and alpha-space—and the concept of the alpha-atom/alpha-space pair to rank pockets for fragment-targetability and to facilitate the evaluation of pocket/fragment complementarity. The resulting high-resolution interfacial map of targetable pocket space can be used to guide the rational design and optimization of small molecule or biomimetic PPI inhibitors.

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

Targeting protein-protein interactions (PPIs) has emerged as a viable approach in modern drug discovery. However, the identification of small molecules enabling us to effectively interrupt their interactions presents significant challenges. In the recent past, significant advances have been made in the development of new biological and chemical strategies to facilitate the discovery process of small-molecule PPI inhibitors. This review aims to highlight the state-of-the-art technologies and the achievements made recently in this field. The "hot spots" of PPIs have been proved to be critical for small molecules to bind. Three strategies including screening, designing, and synthetic approaches have been explored for discovering PPI inhibitors by targeting the "hot spots". Although the classic high throughput screening approach can be used, fragment screening, fragment-based drug design and newly improved virtual screening are demonstrated to be more effective in the discovery of PPI inhibitors. In addition to screening approaches, design strategies including anchor-based and small molecule mimetics of secondary structures involved in PPIs have become powerful tools as well. Finally, constructing new chemically spaced libraries with high diversity and complexity is becoming an important area of interest for PPI inhibitors. The successful cases from the recent five year studies are used to illustrate how these approaches are implemented to uncover and optimize small molecule PPI inhibitors and notably some of them have become promising therapeutics.

DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites

Protein-protein interactions represent an exciting and challenging target class for therapeutic intervention using small molecules. Protein interaction sites are often devoid of the deep surface pockets presented by "traditional" drug targets, and crystal structures reveal that inhibitors typically engage these sites using very shallow binding modes. As a consequence, modern virtual screening tools developed to identify inhibitors of traditional drug targets do not perform as well when they are instead deployed at protein interaction sites. To address the need for novel inhibitors of important protein interactions, here we introduce an alternate docking strategy specifically designed for this regime. Our method, termed DARC (Docking Approach using Ray-Casting), matches the topography of a surface pocket "observed" from within the protein to the topography "observed" when viewing a potential ligand from the same vantage point. We applied DARC to carry out a virtual screen against the protein interaction site of human antiapoptotic protein Mcl-1 and found that four of the top-scoring 21 compounds showed clear inhibition in a biochemical assay. The Ki values for these compounds ranged from 1.2 to 21 μM, and each had ligand efficiency comparable to promising small-molecule inhibitors of other protein-protein interactions. These hit compounds do not resemble the natural (protein) binding partner of Mcl-1, nor do they resemble any known inhibitors of Mcl-1. Our results thus demonstrate the utility of DARC for identifying novel inhibitors of protein-protein interactions.

Small-molecule modulators of the OX40-OX40 ligand co-stimulatory protein-protein interaction

BACKGROUND AND PURPOSE

The OX40-OX40L protein-protein interaction (PPI) is an important cell-surface signalling co-stimulatory regulator within the TNFR superfamily (TNFRSF) and a promising therapeutic target for immunomodulation. PPIs are difficult to modulate using small-molecules. Here, we describe the identification of a small-molecule OX40 modulator and confirm its partial agonist character.

EXPERIMENTAL APPROACH

Cell-free screening assays were developed and used to identify OX40-OX40L inhibitors. Modified versions of this assay were used to elucidate the binding partner and the binding nature of active compounds. OX40-transfected sensor cells with NF-κB reporters were constructed and used to confirm and characterize activity and specificity. Immunomodulatory activity and partial agonist nature were further confirmed by ex vivo T-cell polarization assays.

KEY RESULTS

Several compounds that concentration-dependently affected OX40-OX40L were identified. Cell assays indicated that they were partial agonists with low micromolar potency and adequate selectivity. Under polarizing conditions based on TGF-β, the most promising compound mimicked the effect of an agonistic anti-OX40 antibody in suppressing regulatory T-cell generation and diverting CD4(+) CD62L(+) Foxp3(-) cells to TH 9 phenotype in vitro.

CONCLUSIONS AND IMPLICATIONS

We identified, to our knowledge, the first small-molecule compounds able to interfere with OX40-OX40L binding and, more importantly, to act as partial agonists of OX40. This is particularly interesting, as small-molecule agonism or activation of PPIs is considered unusually challenging and there are only few known examples. These results provide proof-of-principle evidence for the feasibility of small-molecule modulation of the OX40-OX40L interaction and for the existence of partial agonists for TNFRSF-PPIs.