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KRAS G12D , the most frequent KRAS oncogenic mutation, is a promising target for cancer therapy. Herein, we report the design, synthesis, and biological evaluation of a series of KRAS G12D PROTACs by connecting the analogues of MRTX1133 and the VHL ligand. Structural modifications of the linker moiety and KRAS inhibitor part suggested a critical role of membrane permeability in the degradation activity of the KRAS G12D PROTACs. Mechanism studies with the representative compound 8o demonstrated that the potent, rapid, and selective degradation of KRAS G12D induced by 8o was via a VHL- and proteasome-dependent manner. This compound selectively and potently suppressed the growth of multiple KRAS G12D mutant cancer cells, displayed favorable pharmacokinetic and pharmacodynamic properties in mice, and showed significant antitumor efficacy in the AsPC-1 xenograft mouse model. Further optimization of 8o appears to be promising for the development of a new chemotherapy for KRAS G12D -driven cancers as the complementary therapeutic strategy to KRAS inhibition.

Tropomyosin receptor kinase (TRK) fusion, an oncogenic form of kinase with pan-tumor occurrence, is a clinically validated important antitumor target. In this study, we screened our in-house kinase inhibitor library against TRK and identified a promising hit compound 4 with a novel pyridin-2(1 H )-one scaffold. Through a combination of structure-based drug design and structure-activity relationship (SAR) study, compound 14q was identified as a potent TRK inhibitor with good kinase selectivity. It also blocked cellular TRK signaling, thereby inhibiting TRK-dependent cell viability. Additionally, 14q displayed acceptable pharmacokinetic properties with 37.8% oral bioavailability in mice. Strong in vivo tumor growth inhibition of 14q was observed in subcutaneous M091 and KM12 tumor xenograft models with TRK fusion, causing significant tumor inhibition or even complete tumor regression.

The use of small agonists to target stimulators of interferon genes (STING) has been demonstrated to be a promising strategy for the treatment of various cancers and infectious diseases. Herein, we discovered a series of 1 H -pyrrole-3-carbonitrile derivatives as potential STING agonists. On this basis, the structure-activity relationship of this scaffold was studied by introducing various substituents on the aniline ring system. Representative compounds 7F , 7P , and 7R all displayed comparable activities to the reported STING agonist SR-717 in binding various hSTING alleles and induced reporter signal in human THP1 cell lines. Model compound 7F induced phosphorylation of TBK1, IRF3, p65, and STAT3 in a STING-dependent fashion and stimulated the expression of target genes IFNB1 , CXCL10 , and IL6 in a time-dependent manner in human THP1 cells. Our findings afforded a series of novel STING agonists with promising potential., Competing Interests: The authors declare no competing financial interest., (© 2023 American Chemical Society.)

The use of small molecular modulators to target the guanine nucleotide exchange factor SOS1 has been demonstrated to be a promising strategy for the treatment of various KRAS-driven cancers. In the present study, we designed and synthesized a series of new SOS1 inhibitors with the pyrido[2,3- d ]pyrimidin-7-one scaffold. One representative compound 8u showed comparable activities to the reported SOS1 inhibitor BI-3406 in both the biochemical assay and the 3-D cell growth inhibition assay. Compound 8u obtained good cellular activities against a panel of KRAS G12-mutated cancer cell lines and inhibited downstream ERK and AKT activation in MIA PaCa-2 and AsPC-1 cells. In addition, it displayed synergistic antiproliferative effects when used in combination with KRAS G12C or G12D inhibitors. Further modifications of the new compounds may give us a promising SOS1 inhibitor with favorable druglike properties for use in the treatment of KRAS-mutated patients., Competing Interests: The authors declare no competing financial interest., (© 2023 American Chemical Society.)

Alterations of discoidin domain receptor1 (DDR1) may lead to increased production of inflammatory cytokines, making DDR1 an attractive target for inflammatory bowel disease (IBD) therapy. A scaffold-based molecular design workflow was established and performed by integrating a deep generative model, kinase selectivity screening and molecular docking, leading to a novel DDR1 inhibitor compound 2 , which showed potent DDR1 inhibition profile (IC 50 = 10.6 ± 1.9 nM) and excellent selectivity against a panel of 430 kinases ( S (10) = 0.002 at 0.1 μM). Compound 2 potently inhibited the expression of pro-inflammatory cytokines and DDR1 autophosphorylation in cells, and it also demonstrated promising oral therapeutic effect in a dextran sulfate sodium (DSS)-induced mouse colitis model.

The success of artificial intelligence (AI) models has been limited by the requirement of large amounts of high-quality training data, which is just the opposite of the situation in most drug discovery pipelines. Active learning (AL) is a subfield of AI that focuses on algorithms that select the data they need to improve their models. Here, we propose a two-phase AL pipeline and apply it to the prediction of drug oral plasma exposure. In phase I, the AL-based model demonstrated a remarkable capability to sample informative data from a noisy data set, which used only 30% of the training data to yield a prediction capability with an accuracy of 0.856 on an independent test set. In phase II, the AL-based model explored a large diverse chemical space (855K samples) for experimental testing and feedback. Improved accuracy and new highly confident predictions (50K samples) were observed, which suggest that the model's applicability domain has been significantly expanded.

Artificial intelligence (AI) is booming. Among various AI approaches, generative models have received much attention in recent years. Inspired by these successes, researchers are now applying generative model techniques to de novo drug design, which has been considered as the "holy grail" of drug discovery. In this Perspective, we first focus on describing models such as recurrent neural network, autoencoder, generative adversarial network, transformer, and hybrid models with reinforcement learning. Next, we summarize the applications of generative models to drug design, including generating various compounds to expand the compound library and designing compounds with specific properties, and we also list a few publicly available molecular design tools based on generative models which can be used directly to generate molecules. In addition, we also introduce current benchmarks and metrics frequently used for generative models. Finally, we discuss the challenges and prospects of using generative models to aid drug design.

Aldehyde oxidase (AOX) is a drug metabolizing molybdo-flavoenzyme that has gained increasing attention because of contribution to the biotransformation in phase I metabolism of xenobiotics. Unfortunately, the intra- and interspecies variations in AOX activity and lack of reliable and predictive animal models make evaluation of AOX-catalyzed metabolism prone to be misleading. In this study, we developed an improved computational model integrating both atom-level and molecule-level features to predict whether a drug-like molecule is a potential human AOX (hAOX) substrate and to identify the corresponding sites of metabolism. Additionally, we combined the proposed computational strategy and in vitro experiments for evaluating the metabolic property of a series of epigenetic-related drug candidates still in the early stage of development. In summary, this study provides an improved strategy to evaluate the liability of molecules toward hAOX and offers useful information for accelerating the drug design and optimization stage.

p300 and CREB-binding protein (CBP) are ubiquitously expressed pleiotropic lysine acetyltransferases and play a key role as transcriptional co-activators that are essential for a multitude of cellular processes. Despite great importance, there is a lack of highly selective, potent, druglike p300/CBP inhibitors. Through the artificial-intelligence-assisted drug discovery pipeline and further optimization, we reported the discovery of novel, highly selective, potent small-molecule inhibitors of p300/CBP histone acetyltransferases (HAT) with desired druglike properties, exemplified by B026 . Our data demonstrated that B026 , with half maximal inhibitory concentration (IC 50 ) values of 1.8 nM to p300 and 9.5 nM to CBP enzyme inhibitory activity, is the most potent, selective p300/CBP HAT inhibitor. Moreover, B026 achieves significant and dose-dependent tumor growth inhibition in an animal model of human cancer, suggesting that B026 is a highly promising p300/CBP HAT inhibitor and warrants extensive preclinical investigation as a potential clinical development candidate.

Alterations of fibroblast growth factor receptors (FGFRs) play key roles in numerous cancer progression and development, which makes FGFRs attractive targets in the cancer therapy. In the present study, based on a newly devised FGFR target-specific scoring function, a novel FGFR inhibitor hit was identified through virtual screening. Hit-to-lead optimization was then performed by integrating molecular docking and site-of-metabolism predictions with an array of in vitro evaluations and X-ray cocrystal structure determination, leading to a covalent FGFR inhibitor 15 , which showed a highly selective and potent FGFR inhibition profile. Pharmacokinetic assessment, protein kinase profiling, and hERG inhibition evaluation were also conducted, and they confirmed the value of 15 as a lead for further investigation. Overall, this study exemplifies the importance of the integrative use of computational methods and experimental techniques in drug discovery.

A novel series of pyridin-3-amine derivatives were designed, synthesized, and evaluated as multitargeted protein kinase inhibitors for the treatment of non-small cell lung cancer (NSCLC). Hit 1 was first disclosed by in silico screening against fibroblast growth factor receptors (FGFR), which was subsequently validated by in vitro experiments. The structure-activity relationship (SAR) of its analogues was then explored to afford novel FGFR inhibitors 2a-2p and 3a-3q. Among them, 3m showed potent inhibition against FGFR1, 2, and 3. Interestingly, compound 3m not only inhibited various phosphorylation and downstream signaling across different oncogenic forms in FGFR-overactivated cancer cells but also showed nanomolar level inhibition against several other NSCLC-related oncogene kinases, including RET, EGFR, EGFR/T790M/L858R, DDR2, and ALK. Finally, in vivo pharmacology evaluations of 3m showed significant antitumor activity (TGI = 66.1%) in NCI-H1581 NSCLC xenografts with a good pharmacokinetic profile.

Bromodomain-containing protein 4 (BRD4) is implicated in the pathogenesis of a number of different cancers, inflammatory diseases and heart failure. Much effort has been dedicated toward discovering novel scaffold BRD4 inhibitors (BRD4is) with different selectivity profiles and potential antiresistance properties. Structure-based drug design (SBDD) and virtual screening (VS) are the most frequently used approaches. Here, we demonstrate a novel, structure-based VS approach that uses machine-learning algorithms trained on the priori structure and activity knowledge to predict the likelihood that a compound is a BRD4i based on its binding pattern with BRD4. In addition to positive experimental data, such as X-ray structures of BRD4-ligand complexes and BRD4 inhibitory potencies, negative data such as false positives (FPs) identified from our earlier ligand screening results were incorporated into our knowledge base. We used the resulting data to train a machine-learning model named BRD4LGR to predict the BRD4i-likeness of a compound. BRD4LGR achieved a 20-30% higher AUC-ROC than that of Glide using the same test set. When conducting in vitro experiments against a library of previously untested, commercially available organic compounds, the second round of VS using BRD4LGR generated 15 new BRD4is. Moreover, inverting the machine-learning model provided easy access to structure-activity relationship (SAR) interpretation for hit-to-lead optimization.

Aldehyde oxidase (AOX) is an important drug-metabolizing enzyme. However, the current in vitro models for evaluating AOX metabolism are sometimes misleading, and preclinical animal models generally fail to predict human AOX-mediated metabolism. In this study, we report a combined computational and experimental investigation of drug-like molecules that are potential aldehyde oxidase substrates, of which multiple sites of metabolism (SOMs) mediated by AOX and their preferences for the reaction can be unambiguously identified. In addition, the proposed strategy was used to evaluate the metabolism of newly designed c-Met inhibitors, and a success switch-off of AOX metabolism was observed. Overall, this study provide useful information to guide lead optimization and drug discovery based on AOX-mediated metabolism.

The disruptor of telomeric silencing 1-like (DOT1L) protein is a histone H3K79 methyltransferase that plays a key role in transcriptional elongation and cell cycle regulation and is required for the development and maintenance of MLL-rearranged mixed lineage leukemia. Much effort has been dedicated toward discovering novel scaffold DOT1L inhibitors using different strategies. Here, we report the development and application of a target-specific scoring function, the SAM score, for (S)-adenosyl-l-methionine (SAM)-dependent methyltransferases, for the discovery of novel DOT1L inhibitors. On the basis of the SAM score, we successfully identified a novel class of DOT1L inhibitors with a scaffold of [1,2,4]-triazolo-[3,4-b][1,3,4]-thiadiazole, in which compound 6 exhibits an IC 50 value of 8.3 μM with selectivity versus other tested SAM-dependent methyltransferases. In cellular studies, 6 selectively targets DOT1L, blocks the proliferation of mixed lineage leukemia cell lines, and causes cell cycle arrest and apoptosis. Moreover, we analyzed the putative binding modes of 6 and its analogues obtained by molecular docking, which may assist with the future development of DOT1L inhibitors with improved potency and selectivity profiles.

Disrupting the interaction between mixed lineage leukemia (MLL) fusion protein and menin provides a therapeutic approach for MLL-mediated leukemia. Here, we aim to discover novel inhibitors targeting the menin-MLL interface with virtual screening. Both structure-based molecular docking and ligand-based pharmacophore models were established, and the models used for compound screening show a remarkable ability to retrieve known active ligands from decoy molecules. Verified by a fluorescence polarization assay, five hits with novel scaffolds were identified. Among them, DCZ_M123 exhibited potent inhibitory activity with an IC50 of 4.71 ± 0.12 μM and a KD of 14.70 ± 2.13 μM, and it can effectively inhibit the human MLL-rearranged leukemia cells MV4;11 and KOPN8 with GI50 values of 0.84 μM and 0.54 μM, respectively.

Histone methyltransferases are involved in many important biological processes, and abnormalities in these enzymes are associated with tumorigenesis and progression. Disruptor of telomeric silencing 1-like (DOT1L), a key hub in histone lysine methyltransferases, has been reported to play an important role in the processes of mixed-lineage leukemia (MLL)-rearranged leukemias and validated to be a potential therapeutic target. In this study, we identified a novel DOT1L inhibitor, DC_L115 (CAS no. 1163729-79-0), by combining structure-based virtual screening with biochemical analyses. This potent inhibitor DC_L115 shows high inhibitory activity toward DOT1L (IC50 = 1.5 μM). Through a process of surface plasmon resonance-based binding assays, DC_L115 was founded to bind to DOT1L with a binding affinity of 0.6 μM in vitro. Moreover, this compound selectively inhibits MLL-rearranged cell proliferation with an IC50 value of 37.1 μM. We further predicted the binding modes of DC_L115 through molecular docking analysis and found that the inhibitor competitively occupies the binding site of S-adenosylmethionine. Overall, this study demonstrates the development of potent DOT1L inhibitors with novel scaffolds.

Histone methyltransferases are involved in various biological functions, and these methylation regulating enzymes' abnormal expression or activity has been noted in several human cancers. Within this context, SET domain-containing (lysine methyltransferase) 7 (SET7, also called KMT7, SETD7, SET9) is of increasing significance due to its diverse roles in biological functions and diseases, such as diabetes, cancers, alopecia areata, atherosclerotic vascular disease, HIV, and HCV. In this study, DC-S100, which was discovered by pharmacophore- and docking-based virtual screening, was identified as the hit compound of SET7 inhibitor. Structure-activity relationship (SAR) analysis was performed on analogs of DC-S100 and according to the putative binding mode of DC-S100, structure modifications were made to improve its activity. Of note, compounds DC-S238 and DC-S239, with IC50 values of 4.88 and 4.59 μM, respectively, displayed selectivity for DNMT1, DOT1L, EZH2, NSD1, SETD8, and G9a. Taken together, DC-S238 and DC-S239 can serve as leads for further investigation as SET7 inhibitors and the chemical toolkits for functional biology studies of SET7.

Polycomb Repressive Complex 2 (PRC2) modulates the chromatin structure and transcriptional repression by trimethylation lysine 27 of histone H3 (H3K27me3), a process that necessitates the protein-protein interaction (PPI) between the catalytic subunit EZH2 and EED. Deregulated PRC2 is intimately involved in tumorigenesis and progression, making it an invaluable target for epigenetic cancer therapy. However, until now, there have been no reported small molecule compounds targeting the EZH2-EED interactions. In the present study, we identified astemizole, an FDA-approved drug, as a small molecule inhibitor of the EZH2-EED interaction of PRC2. The disruption of the EZH2-EED interaction by astemizole destabilizes the PRC2 complex and inhibits its methyltransferase activity in cancer cells. Multiple lines of evidence have demonstrated that astemizole arrests the proliferation of PRC2-driven lymphomas primarily by disabling the PRC2 complex. Our findings demonstrate the chemical tractability of the difficult PPI target by a small molecule compound, highlighting the therapeutic promise for PRC2-driven human cancers via targeted destruction of the EZH2-EED complex.

The DNA methyltransferases (DNMTs) found in mammals include DNMT1, DNMT3A, and DNMT3B and are attractive targets in cancer chemotherapy. DNMT1 was the first among the DNMTs to be characterized, and it is responsible for maintaining DNA methylation patterns. A number of DNMT inhibitors have been reported, but most of them are nucleoside analogs that can lead to toxic side effects and lack specificity. By combining docking-based virtual screening with biochemical analyses, we identified a novel compound, DC_05. DC_05 is a non-nucleoside DNMT1 inhibitor with low micromolar IC50 values and significant selectivity toward other AdoMet-dependent protein methyltransferases. Through a process of similarity-based analog searching, compounds DC_501 and DC_517 were found to be more potent than DC_05. These three potent compounds significantly inhibited cancer cell proliferation. The structure-activity relationship (SAR) and binding modes of these inhibitors were also analyzed to assist in the future development of more potent and more specific DNMT1 inhibitors.

The C-terminal domain of the bacterial transcription antiterminator RfaH undergoes a dramatic all-α-helix to all-β-barrel transition when released from its N-terminal domain. These two distinct folding patterns correspond to different functions: the all-α state acts as an essential regulator of transcription to ensure RNA polymerase binding, whereas the all-β state operates as an activator of translation by interacting with the ribosomal protein S10 and recruits ribosomal mRNA. Accordingly, this drastic conformational change enables RfaH to physically couple the transcription and translation processes in gene expression. To understand the mechanism behind this extraordinary functionally relevant structural transition, we constructed Markov state models using an adaptive seeding method. The constructed models highlight several parallel folding pathways with heterogeneous molecular mechanisms, which reveal the folding kinetics and atomic details of the conformational transition.

A library of privileged-substructure-based, heterocyclic compounds was constructed by a sequence of Ugi four-component reactions incorporating the indole motif and microwave-assisted cyclizations in branched pathways. Cheminformatic analysis confirmed that the library exhibited a high degree of structural diversity and good drug-likeness.

The transcriptional coactivator and histone acetyltransferase (HAT) p300 acetylates the four core histones and other transcription factors to regulate a plethora of fundamental biological processes including cell growth, development, oncogenesis and apoptosis. Recent structural and biochemical studies on the p300 HAT domain revealed a Theorell-Chance, or "hit-and-run", catalytic mechanism. Nonetheless, the chemical mechanism of the entire reaction process including the proton transfer (PT) scheme and consequent acetylation reaction route remains unclear. In this study, a combined computational strategy consisting of molecular modeling, molecular dynamic (MD) simulation, and quantum mechanics/molecular mechanics (QM/MM) simulation was applied to elucidate these important issues. An initial p300/H3/Ac-CoA complex structure was modeled and optimized using a 100 ns MD simulation. Residues that play important roles in substrate binding and the acetylation reaction were comprehensively investigated. For the first time, these studies reveal a plausible PT scheme consisting of Y1394, D1507, and a conserved crystallographic water molecule, with all components of the scheme being stable during the MD simulation and the energy barrier low for PT to occur. The two-dimensional potential energy surface for the nucleophilic attack process was also calculated. The comparison of potential energies for two possible elimination half-reaction mechanisms revealed that Y1467 reprotonates the coenzyme-A leaving group to form product. This study provides new insights into the detailed catalytic mechanism of p300 and has important implications for the discovery of novel small molecule regulators for p300.

Organic cation transporter 2 (OCT2) is responsible for the entry step of many drugs in renal elimination, of which the changing activity may cause unwanted drug-drug interactions (DDIs). To develop drugs with favorable safety profile and provide instruction for rational clinical drug administration, it is of great interest to investigate the multiple mechanisms of OCT2 inhibition. In this study, we designed a combinatorial scheme to screen the optimum combination of pharmacophores from a pool of hypotheses established based on 162 OCT2 inhibitors. Among them, one single pharmacophore hypothesis represents a potential binding mode that may account for one unique inhibitory mechanism, and the obtained pharmacophore combination describes the multimechanisms of OCT2 inhibition. The final model consists of four individual pharmacophores, i.e., DHPR18, APR2, PRR5 and HHR4. Given a query ligand, it is considered as an inhibitor if it matches at least one of the hypotheses, or a noninhibitor if it fails to match any of four hypotheses. Our combinatorial pharmacophore model performs reasonably well to discriminate inhibitors and noninhibitors, yielding an overall accuracy around 0.70 for a test set containing 81 OCT2 inhibitors and 218 noninhibitors. Intriguingly, we found that the number of matched hypotheses was positively correlated with inhibition rate, which coincides with the pharmacophore modeling result of P-gp substrate binding. Further analysis suggested that the hypothesis PRR5 was responsible for competitive inhibition of OCT2, and other hypotheses were important for interaction between the inhibitor and OCT2. In light of the results, a hypothetical model for inhibiting transporting mediated by OCT2 was proposed.

The aberrant function of c-Met kinase signaling pathway is ubiquitously involved in a broad spectrum of human cancers; thus, a strong rationale exists for targeting the kinase pathway in cancer therapy. Via integration of computational and experimental studies, anthraquinone derivatives were identified for the first time as potent c-Met kinase inhibitors in this research. The aberrant activation of the c-Met kinase pathway results from (TPR)-Met, MET gene mutation, or amplification and a hepatocyte growth factor (HGF)/scatter factor-dependent autocrine or paracrine mechanism. However, anthraquinone derivatives exclusively suppressed c-Met phosphorylation stimulated by HGF in A549 cells, indicating that the compounds possess the ability to block the extracellular HGF-dependent pathway. A surface plasmon resonance assay revealed that the most potent compound, 2a, shows a high binding affinity for HGF with an equilibrium dissociation constant of 1.95 μM. The dual roles of compound 2a demonstrate the potency of anthraquinone derivatives and provide a new design solution for the c-Met kinase signaling pathway.

In order to exploit the 430-cavity in the active sites of neuraminidases, 22 zanamivir analogs with C-1 and C-4 modification were synthesized, and their inhibitory activities against both group-1 (H5N1, H1N1) and group-2 neuraminidases (H3N2) were determined. Compound 9f exerts the most potency, with IC(50) value of 0.013, 0.001, and 0.09 μM against H3N2, H5N1, and H1N1, which is similar to that of zanamivir (H3N2 IC(50) = 0.0014 μM, H5N1 IC(50) = 0.012 μM, H1N1 IC(50) = 0.001 μM). Pharmacokinetic studies of compound 9f in rats showed a much longer plasma half-life (t(1/2)) than that of zanamivir following administration (po dose). Molecular modeling provided information about the binding model between the new inhibitors and neuraminidase, with the elongated groups at the C-1-position being projected toward the 430-loop region. This study may represent a novel starting point for the future development of improved antiflu agents.