Small Molecule Binding Sites Research Articles

Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning.

Predicting protein-small molecule binding sites, the initial step in structure-guided drug design, remains challenging for proteins lacking experimentally derived ligand-bound structures. Here, we propose CLAPE-SMB, which integrates a pre-trained protein language model with contrastive learning to provide high accuracy predictions of small molecule binding sites that can accommodate proteins without a published crystal structure. We trained and tested CLAPE-SMB on the SJC dataset, a non-redundant dataset based on sc-PDB, JOINED, and COACH420, and achieved an MCC of 0.529. We also compiled the UniProtSMB dataset, which merges sites from similar proteins based on raw data from UniProtKB database, and achieved an MCC of 0.699 on the test set. In addition, CLAPE-SMB achieved an MCC of 0.815 on our intrinsically disordered protein (IDP) dataset that contains 336 non-redundant sequences. Case studies of DAPK1, RebH, and Nep1 support the potential of this binding site prediction tool to aid in drug design. The code and datasets are freely available at https://github.com/JueWangTHU/CLAPE-SMB . SCIENTIFIC CONTRIBUTION: CLAPE-SMB combines a pre-trained protein language model with contrastive learning to accurately predict protein-small molecule binding sites, especially for proteins without experimental structures, such as IDPs. Trained across various datasets, this model shows strong adaptability, making it a valuable tool for advancing drug design and understanding protein-small molecule interactions.

Potential allosteric pockets identification of glucagon receptor based on molecular dynamics simulations

Glucagon receptor (GCGR) is an important target for the treatment of type 2 diabetes mellitus. Although several small molecules with antagonistic activity have been discovered, so far, only one small molecule binding site has been resolved. To discover more novel allosteric pockets and allosteric molecules, we started with the unique full-length inactive conformation of GCGR and applied all-atom molecular dynamics (MD) simulations to obtain extensive dynamic conformations of the GCGR/glucagon complex. For the first time, MDpocket, FTMove and FTMap were used to detect allosteric pockets in simulation trajectories, selecting 4 stable pockets with a total of 14 structures as templates for virtual screening. From the results of virtual screening, 14 compounds were ultimately selected after a series of filtering steps. The cAMP accumulation assay indicated that compound gs6 has antagonistic activity, and MD simulations further revealed the allosteric mechanism of gs6. We are the first to identify new allosteric pockets and allosteric molecules in simulation trajectories of the GCGR/glucagon complex, providing a reference for research on other G-protein-coupled receptors (GPCR). However, there is still considerable room for improvement, such as using more simulation methods to obtain a richer set of dynamic conformations.

Dynamics of the Pre-Powerstroke Myosin Lever Arm and the Effects of Omecamtiv Mecarbil.

The binding of small molecules to sarcomeric myosin can elicit powerful effects on the chemomechanical cycle, making them effective therapeutics in the clinic and research tools at the benchtop. However, these myotropes can have complex effects that act on different phases of the crossbridge cycle and which depend on structural, dynamic, and environmental variables. While small molecule binding sites have been identified crystallographically and their effects on contraction studied extensively, small molecule-induced dynamic changes that link structure-function are less studied. Here, we use molecular dynamics simulations to explore how omecamtiv mecarbil (OM), a cardiac myosin-specific myotrope, alters the coordinated dynamics of the lever arm and the motor domain in the pre-powerstroke state. We show that the lever arm adopts a range of orientations and find that different lever arm orientations are accompanied by changes in the hydrogen bonding patterns near the converter. We find that the binding of OM to myosin reduces the conformational heterogeneity of the lever arm orientation and also adjusts the average lever arm orientation. Finally, we map out the distinct conformations and ligand-protein interactions adopted by OM. These results uncover some structural factors that govern the motor domain-tail orientations and the mechanisms by which OM primes the pre-powerstroke myosin heads.

Turbocharging protein binding site prediction with geometric attention, inter-resolution transfer learning, and homology-based augmentation

BackgroundLocating small molecule binding sites in target proteins, in the resolution of either pocket or residue, is critical in many drug-discovery scenarios. Since it is not always easy to find such binding sites using conventional methods, different deep learning methods to predict binding sites out of protein structures have been developed in recent years. The existing deep learning based methods have several limitations, including (1) the inefficiency of the CNN-only architecture, (2) loss of information due to excessive post-processing, and (3) the under-utilization of available data sources.MethodsWe present a new model architecture and training method that resolves the aforementioned problems. First, by layering geometric self-attention units on top of residue-level 3D CNN outputs, our model overcomes the problems of CNN-only architectures. Second, by configuring the fundamental units of computation as residues and pockets instead of voxels, our method reduced the information loss from post-processing. Lastly, by employing inter-resolution transfer learning and homology-based augmentation, our method maximizes the utilization of available data sources to a significant extent.ResultsThe proposed method significantly outperformed all state-of-the-art baselines regarding both resolutions—pocket and residue. An ablation study demonstrated the indispensability of our proposed architecture, as well as transfer learning and homology-based augmentation, for achieving optimal performance. We further scrutinized our model’s performance through a case study involving human serum albumin, which demonstrated our model’s superior capability in identifying multiple binding sites of the protein, outperforming the existing methods.ConclusionsWe believe that our contribution to the literature is twofold. Firstly, we introduce a novel computational method for binding site prediction with practical applications, substantiated by its strong performance across diverse benchmarks and case studies. Secondly, the innovative aspects in our method— specifically, the design of the model architecture, inter-resolution transfer learning, and homology-based augmentation—would serve as useful components for future work.

The Inferential Binding Sites of GCGR for Small Molecules Using Protein Dynamic Conformations and Crystal Structures.

Glucagon receptor (GCGR) is a class B1 G-protein-coupled receptor that plays a crucial role in maintaining human blood glucose homeostasis and is a significant target for the treatment of type 2 diabetes mellitus (T2DM). Currently, six small molecules (Bay 27-9955, MK-0893, MK-3577, LY2409021, PF-06291874, and LGD-6972) have been tested or are undergoing clinical trials, but only the binding site of MK-0893 has been resolved. To predict binding sites for other small molecules, we utilized both the crystal structure of the GCGR and MK-0893 complex and dynamic conformations. We docked five small molecules and selected the best conformation based on binding mode, docking score, and binding free energy. We performed MD simulations to verify the binding mode of the selected small molecules. Moreover, when selecting conformations, results of competitive binding were referred to. MD simulation indicated that Bay 27-9955 exhibits moderate binding stability in Pocket 3. MK-3577, LY2409021, and PF-06291874 exhibited highly stable binding to Pocket 2, consistent with experimental results. However, LY2409021 may also bind to Pocket 5. Additionally, LGD-6972 exhibited relatively stable binding in Pocket 5. We also conducted structural modifications of LGD-6972 based on the results of MD simulations and predicted its analogues' bioavailability, providing a reference for the study of GCGR small molecules.

TPCA-1 compound, inhibiting testis-specific serine/threonine protein kinase 3 for potential male sterile in Bombyx mori.

Protein kinases are a type of transferase enzyme that catalyze the phosphorylation of protein substrates, including receptor proteins. Testis-specific serine/threonine kinases (TSSKs) are a highly conserved group of protein kinases found in various organisms. They play an essential role in male reproduction by influencing sperm development and function. In this study, we report on the characterization of BmTSSK3, a TSSK from the silkworm, Bombyx mori. We found that BmTSSK3 is specifically expressed in the testis and localized to the sperm flagella, particularly in the sperm tail cyst. Furthermore, we developed BmTSSK3 inhibitors through molecular docking and binding assays. Small molecules 5-(4-Fluorophenyl)-2-ureidothiophene-3-carboxamide (TPCA-1)and Imidurea were identified to bind to BmTSSK3. Using site-specific mutation technology, we identified amino acid residues R134 and S184 as crucial binding sites for small molecules. RNA interference assay and Western blot analysis showed that knockdown of BmTSSK3 significantly decreased histone 3 phosphorylation. To confirm the inhibitory effect of these small molecules, we treated silkworm testes with TPCA-1 and observed a strong inhibitory effect. TPCA-1 is an inhibitor of BmTSSK3, which raises its potential as a future candidate for male sterility of the silkworm. Thus, this study may offer a novel strategy for sterile silkworms as well as insects. © 2024 Society of Chemical Industry.

Transcriptome-Wide, Unbiased Profiling of Ribonuclease Targeting Chimeras.

Various approaches have been developed to target RNA and modulate its function with modes of action including binding and cleavage. Herein, we explored how small molecule binding is correlated with cleavage induced by heterobifunctional ribonuclease targeting chimeras (RiboTACs), where RNase L is recruited to cleave the bound RNA target, in a transcriptome-wide, unbiased fashion. Only a fraction of bound targets was cleaved by RNase L, induced by RiboTAC binding. Global analysis suggested that (i) cleaved targets generally form a region of stable structure that encompasses the small molecule binding site; (ii) cleaved targets have preferred RNase L cleavage sites nearby small molecule binding sites; (iii) RiboTACs facilitate a cellular interaction between cleaved targets and RNase L; and (iv) the expression level of the target influences the extent of cleavage observed. In one example, we converted a binder of LGALS1 (galectin-1) mRNA into a RiboTAC. In MDA-MB-231 cells, the binder had no effect on galectin-1 protein levels, while the RiboTAC cleaved LGALS1 mRNA, reduced galectin-1 protein abundance, and affected galectin-1-associated oncogenic cellular phenotypes. Using LGALS1, we further assessed additional factors including the length of the linker that tethers the two components of the RiboTAC, cellular uptake, and the RNase L-recruiting module on RiboTAC potency. Collectively, these studies may facilitate triangulation of factors to enable the design of RiboTACs.

Identifying small-molecules binding sites in RNA conformational ensembles with SHAMAN

The rational targeting of RNA with small molecules is hampered by our still limited understanding of RNA structural and dynamic properties. Most in silico tools for binding site identification rely on static structures and therefore cannot face the challenges posed by the dynamic nature of RNA molecules. Here, we present SHAMAN, a computational technique to identify potential small-molecule binding sites in RNA structural ensembles. SHAMAN enables exploring the conformational landscape of RNA with atomistic molecular dynamics simulations and at the same time identifying RNA pockets in an efficient way with the aid of probes and enhanced-sampling techniques. In our benchmark composed of large, structured riboswitches as well as small, flexible viral RNAs, SHAMAN successfully identifies all the experimentally resolved pockets and ranks them among the most favorite probe hotspots. Overall, SHAMAN sets a solid foundation for future drug design efforts targeting RNA with small molecules, effectively addressing the long-standing challenges in the field.

Molecules targeting a novel homotrimer cavity of Spike protein attenuate replication of SARS-CoV-2

The SARS-CoV-2 Spike glycoprotein (S) utilizes a unique trimeric conformation to interact with the ACE2 receptor on host cells, making it a prime target for inhibitors that block viral entry. We have previously identified a novel proteinaceous cavity within the Spike protein homotrimer that could serve as a binding site for small molecules. However, it is not known whether these molecules would inhibit, stimulate, or have no effect on viral replication. To address this, we employed structural-based screening to identify small molecules that dock into the trimer cavity and assessed their impact on viral replication. Our findings show that a cohort of identified small molecules binding to the Spike trimer cavity effectively reduces the replication of various SARS-CoV-2 variants. These molecules exhibited inhibitory effects on B.1 (European original, D614G, EDB2) and B.1.617.2 (δ) variants, while showing moderate activity against the B.1.1.7 (α) variant. We further categorized these molecules into distinct groups based on their structural similarities. Our experiments demonstrated a dose-dependent viral replication inhibitory activity of these compounds, with some, like BCC0040453 exhibiting no adverse effects on cell viability even at high concentrations. Further investigation revealed that pre-incubating virions with compounds like BCC0031216 at different temperatures significantly inhibited viral replication, suggesting their specificity towards the S protein. Overall, our study highlights the inhibitory impact of a diverse set of chemical molecules on the biological activity of the Spike protein. These findings provide valuable insights into the role of the trimer cavity in the viral replication cycle and aid drug discovery programs aimed at targeting the coronavirus family.

An interpretable deep learning model predicts RNA–small molecule binding sites

The intricate interplay between RNA molecules and small ligands plays a pivotal role in regulating biological processes, underscoring the necessity for accurate prediction models of RNA–small molecule binding sites. In this study, we develop CapBind, a novel interpretive deep learning framework utilizing a Capsule Network architecture, to precisely identify RNA–small molecule binding sites. This framework stands out for its multifaceted approach, which leverages both the sequence and structural information of RNA as input features, allowing for a thorough understanding of the complex interactions between RNA and small molecules. Leveraging multi-source bioinformatics data, including the distribution of RNA secondary structures, our model characterizes sequence and structural features with unparalleled depth. Through a unified alignment of these multi-source feature representations, we achieve dimensional homogeneity in the potential feature maps for both types of biological data. The crux of our methodology lies in the deployment of a multi-level Capsule Network, engineered to identify the nuanced interactions of RNA sequences with small molecules. The essence of our approach resides in the implementation of a multi-layered Capsule Network. Utilizing a sophisticated routing mechanism, this network demonstrates unparalleled efficacy in learning and identifying the intricate interactions between RNA sequences and small molecules. This mechanism enables dynamic adjustment of information flow across multiple levels, thereby capturing subtle features and patterns that might elude conventional neural network architectures. The experimental results demonstrate the superior performance of our model, particularly highlighting its progress in evaluation metrics compared to current state-of-the-art models. Case studies further validate the model’s precision in identifying binding sites, offering potential insights into gene expression pathways and novel therapeutic avenues for neurodegenerative diseases. Moreover, an extensive interpretability analysis of our silicon model reveals the internal interaction mechanisms between specific RNA regions and small molecules, contributing valuable perspectives for drug design and molecular biology research. These findings underscore the model’s predictive accuracy and biological applicability, establishing our approach as a significant leap forward in the computational prediction of RNA–small molecule binding sites.

Research Progress on Spike-Dependent SARS-CoV-2 Fusion Inhibitors and Small Molecules Targeting the S2 Subunit of Spike.

Since the beginning of the COVID-19 pandemic, extensive drug repurposing efforts have sought to identify small-molecule antivirals with various mechanisms of action. Here, we aim to review research progress on small-molecule viral entry and fusion inhibitors that directly bind to the SARS-CoV-2 Spike protein. Early in the pandemic, numerous small molecules were identified in drug repurposing screens and reported to be effective in in vitro SARS-CoV-2 viral entry or fusion inhibitors. However, given minimal experimental information regarding the exact location of small-molecule binding sites on Spike, it was unclear what the specific mechanism of action was or where the exact binding sites were on Spike for some inhibitor candidates. The work of countless researchers has yielded great progress, with the identification of many viral entry inhibitors that target elements on the S1 receptor-binding domain (RBD) or N-terminal domain (NTD) and disrupt the S1 receptor-binding function. In this review, we will also focus on highlighting fusion inhibitors that target inhibition of the S2 fusion function, either by disrupting the formation of the postfusion S2 conformation or alternatively by stabilizing structural elements of the prefusion S2 conformation to prevent conformational changes associated with S2 function. We highlight experimentally validated binding sites on the S1/S2 interface and on the S2 subunit. While most substitutions to the Spike protein to date in variants of concern (VOCs) have been localized to the S1 subunit, the S2 subunit sequence is more conserved, with only a few observed substitutions in proximity to S2 binding sites. Several recent small molecules targeting S2 have been shown to have robust activity over recent VOC mutant strains and/or greater broad-spectrum antiviral activity for other more distantly related coronaviruses.

The Dual-Targeted Fusion Inhibitor Clofazimine Binds to the S2 Segment of the SARS-CoV-2 Spike Protein.

Clofazimine and Arbidol have both been reported to be effective in vitro SARS-CoV-2 fusion inhibitors. Both are promising drugs that have been repurposed for the treatment of COVID-19 and have been used in several previous and ongoing clinical trials. Small-molecule bindings to expressed constructs of the trimeric S2 segment of Spike and the full-length SARS-CoV-2 Spike protein were measured using a Surface Plasmon Resonance (SPR) binding assay. We demonstrate that Clofazimine, Toremifene, Arbidol and its derivatives bind to the S2 segment of the Spike protein. Clofazimine provided the most reliable and highest-quality SPR data for binding with S2 over the conditions explored. A molecular docking approach was used to identify the most favorable binding sites on the S2 segment in the prefusion conformation, highlighting two possible small-molecule binding sites for fusion inhibitors. Results related to molecular docking and modeling of the structure-activity relationship (SAR) of a newly reported series of Clofazimine derivatives support the proposed Clofazimine binding site on the S2 segment. When the proposed Clofazimine binding site is superimposed with other experimentally determined coronavirus structures in structure-sequence alignments, the changes in sequence and structure may rationalize the broad-spectrum antiviral activity of Clofazimine in closely related coronaviruses such as SARS-CoV, MERS, hCoV-229E, and hCoV-OC43.

Targeting KRAS in cancer.

RAS family variants-most of which involve KRAS-are the most commonly occurring hotspot mutations in human cancers and are associated with a poor prognosis. For almost four decades, KRAS has been considered undruggable, in part due to its structure, which lacks small-molecule binding sites. But recent developments in bioengineering, organic chemistry and related fields have provided the infrastructure to make direct KRAS targeting possible. The first successes occurred with allele-specific targeting of KRAS p.Gly12Cys (G12C) in non-small cell lung cancer, resulting in regulatory approval of two agents-sotorasib and adagrasib. Inhibitors targeting other variants beyond G12C have shown preliminary antitumor activity in highly refractory malignancies such as pancreatic cancer. Herein, we outline RAS pathobiology with a focus on KRAS, illustrate therapeutic approaches across a variety of malignancies, including emphasis on the 'on' and 'off' switch allele-specific and 'pan' RAS inhibitors, and review immunotherapeutic and other key combination RAS targeting strategies. We summarize mechanistic understanding of de novo and acquired resistance, review combination approaches, emerging technologies and drug development paradigms and outline a blueprint for the future of KRAS therapeutics with anticipated profound clinical impact.

Abstract 3338: Development of a CK2α inhibitor for treatment of wnt-driven colorectal cancer

Abstract A novel, potent and highly selective orally bioavailable small molecule inhibitor of Casein Kinase 2α (CK2α) has been developed and validated in pre-clinical models of wnt-driven colorectal carcinoma; and is poised to enter clinical development.CK2α is considered as a positive regulator of wnt signaling and tumorigenesis. The wnt pathway is known to be sensitive to and amplified by CK2α activity at multiple nodes and can be inhibited by loss of CK2α function. The human genetics of colorectal cancer (CRC) have been well characterized and approximately 80% tumors are identified as being wnt pathway mutation driven. CRC tumors can be further stratified into consensus molecular subtypes (CMS), with iCMS2 representing 37% of CRC patients, being characterized by ongoing wnt pathway upregulation. Development of CK2α inhibitors as a targeted therapy for CRC is therefore mechanistically well aligned to the wnt signaling drive and may serve as a promising therapeutic strategy for this cancer. A novel small molecule binding site on CK2α has been exploited to design and develop an inhibitor with Ki of 95 pM and exquisite selectivity over the kinome. This inhibitor has been comprehensively characterized using in vitro, ex vivo and in vivo pharmacology studies. Cellular mechanism of action studies in CRC cell lines have quantified the potency of target engagement, inhibition of known CK2α phospho-sites, inhibition of tumorigenic wnt pathway activity, and induction of apoptosis. This CK2α inhibitor was also profiled in a high content screen of CRC patient-derived organoids established from various driver mutation backgrounds. Use of these ex vivo models has validated the potent cytotoxic activity of CK2α inhibition in tumor samples with wnt-driven characteristics and highlights the potential therapeutic efficacy of CK2α inhibition in this setting. In vivo CRC xenograft studies have confirmed anti-tumor efficacy and developed the understanding of pharmacokinetic pharmacodynamic relationship between free plasma concentration of drug and inhibition of CK2α-specific biomarker in the tumor. The preclinical data presented establishes the strong rationale for clinical development of a novel CK2α inhibitor for the treatment of locally advanced or metastatic solid tumors, with an emphasis on wnt-driven CRC. Citation Format: Darren Cawkill. Development of a CK2α inhibitor for treatment of wnt-driven colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3338.

Learnt representations of proteins can be used for accurate prediction of small molecule binding sites on experimentally determined and predicted protein structures

Protein-ligand binding site prediction is a useful tool for understanding the functional behaviour and potential drug-target interactions of a novel protein of interest. However, most binding site prediction methods are tested by providing crystallised ligand-bound (holo) structures as input. This testing regime is insufficient to understand the performance on novel protein targets where experimental structures are not available. An alternative option is to provide computationally predicted protein structures, but this is not commonly tested. However, due to the training data used, computationally-predicted protein structures tend to be extremely accurate, and are often biased toward a holo conformation. In this study we describe and benchmark IF-SitePred, a protein-ligand binding site prediction method which is based on the labelling of ESM-IF1 protein language model embeddings combined with point cloud annotation and clustering. We show that not only is IF-SitePred competitive with state-of-the-art methods when predicting binding sites on experimental structures, but it performs better on proxies for novel proteins where low accuracy has been simulated by molecular dynamics. Finally, IF-SitePred outperforms other methods if ensembles of predicted protein structures are generated.

High-resolution RNA tertiary structures in Zika virus stem-loop A for the development of inhibitory small molecules.

Flaviviruses such as Zika (ZIKV) and dengue virus (DENV) are positive-sense RNA viruses belonging to Flaviviridae The flavivirus genome contains a 5' end stem-loop promoter sequence known as stem-loop A (SLA) that is recognized by the flavivirus polymerase NS5 during viral RNA synthesis and 5' guanosine cap methylation. The crystal structures of ZIKV and DENV SLAs show a well-defined fold, consisting of a bottom stem, side loop, and top stem-loop, providing unique interaction sites for small molecule inhibitors to disrupt the promoter function. To facilitate the identification of small molecule binding sites in flavivirus SLA, we determined high-resolution structures of the bottom and top stems of ZIKV SLA, which contain a single U- or G-bulge, respectively. Both bulge nucleotides exhibit multiple orientations, from folded back on the adjacent nucleotide to flipped out of the helix, and are stabilized by stacking or base triple interactions. These structures suggest that even a single unpaired nucleotide can provide flexibility to RNA structures, and its conformation is mainly determined by the stabilizing chemical environment. To facilitate discovery of small molecule inhibitors that interfere with the functions of ZIKV SLA, we screened and identified compounds that bind to the bottom and top stems of ZIKV SLA.

Identification of small-molecule binding sites of a ubiquitin-conjugating enzyme-UBE2T through fragment-based screening.

UBE2T is an attractive target for drug development due to its linkage with several types of cancers. However, the druggability of ubiquitin-conjugating E2 (UBE2T) is low because of the lack of a deep and hydrophobic pocket capable of forming strong binding interactions with drug-like small molecules. Here, we performed fragment screening using 19 F-nuclear magnetic resonance (NMR) and validated the hits with 1 H-15 N-heteronuclear single quantum coherence (HSQC) experiment and X-ray crystallographic studies. The cocrystal structures obtained revealed the binding modes of the hit fragments and allowed for the characterization of the fragment-binding sites. Further screening of structural analogues resulted in the identification of a compound series with inhibitory effect on UBE2T activity. Our current study has identified two new binding pockets in UBE2T, which will be useful for the development of small molecules to regulate the function of this protein. In addition, the compounds identified in this study can serve as chemical starting points for the development of UBE2T modulators.

Enhanced mapping of small-molecule binding sites in cells.

Photoaffinity probes are routinely utilized to identify proteins that interact with small molecules. However, despite this common usage, resolving the specific sites of these interactions remains a challenge. Here we developed a chemoproteomic workflow to determine precise protein binding sites of photoaffinity probes in cells. Deconvolution of features unique to probe-modified peptides, such as their tendency to produce chimeric spectra, facilitated the development of predictive models to confidently determine labeled sites. This yielded an expansive map of small-molecule binding sites on endogenous proteins and enabled the integration with multiplexed quantitation, increasing the throughput and dimensionality of experiments. Finally, using structural information, we characterized diverse binding sites across the proteome, providing direct evidence of their tractability to small molecules. Together, our findings reveal new knowledge for the analysis of photoaffinity probes and provide a robust method for high-resolution mapping of reversible small-molecule interactions en masse in native systems.

Altering the Cleaving Effector in Chimeric Molecules that Target RNA Enhances Cellular Selectivity.

Small molecules that target RNA and effect their cleavage are useful chemical probes and potential lead medicines. In this study, we investigate factors affecting degradation of two cancer-associated RNA targets, the mRNA that encodes the transcription factor JUN (c-Jun) and the hairpin precursor to microRNA-372 (pre-miR-372). The two RNA targets harbor the same small-molecule binding site juxtaposed with different neighboring structures. Specifically, pre-miR-372 has AU pairs and contiguous purines on one strand near the small-molecule binding site, making it an ideal substrate for oxidative cleavage via the direct degrader bleomycin A5. In contrast, while JUN mRNA has a similar number of AU pairs near the small-molecule binding site, it lacks contiguous purine nucleotides. Instead, it contains unpaired pyrimidine nucleotides, which are preferred substrates for RNase L, a ribonuclease that can be recruited to RNA with heterobifunctional ribonuclease targeting chimeras (RiboTACs). We hypothesized that structural features surrounding the binding site could be leveraged to program selective small-molecule degradation by alteration of the cleaving module. Indeed, the bleomycin degrader cleaves pre-miR-372 in gastric cancer cells but not JUN mRNA. Conversely, the RiboTAC cleaves JUN mRNA but not pre-miR-372. Thus, the selection of the appropriate cleaving effector moiety for an RNA-binding small molecule can be leveraged to cleave an RNA selectively in a predictable manner, which could have broad implications.

Unraveling allostery within the angiotensin II type 1 receptor for Gαq and β-arrestin coupling.

G protein-coupled receptors engage both G proteins and β-arrestins, and their coupling can be biased by ligands and mutations. Here, to resolve structural elements and mechanisms underlying effector coupling to the angiotensin II (AngII) type 1 receptor (AT1R), we combined alanine scanning mutagenesis of the entire sequence of the receptor with pharmacological profiling of Gαq and β-arrestin engagement to mutant receptors and molecular dynamics simulations. We showed that Gαq coupling to AT1R involved a large number of residues spread across the receptor, whereas fewer structural regions of the receptor contributed to β-arrestin coupling regulation. Residue stretches in transmembrane domain 4 conferred β-arrestin bias and represented an important structural element in AT1R for functional selectivity. Furthermore, we identified allosteric small-molecule binding sites that were enclosed by communities of residues that produced biased signaling when mutated. Last, we showed that allosteric communication within AT1R emanating from the Gαq coupling site spread beyond the orthosteric AngII-binding site and across different regions of the receptor, including currently unresolved structural regions. Our findings reveal structural elements and mechanisms within AT1R that bias Gαq and β-arrestin coupling and that could be harnessed to design biased receptors for research purposes and to develop allosteric modulators.