Novel STAT3 oligonucleotide compounds suppress tumor growth and overcome the acquired resistance to sorafenib in hepatocellular carcinoma.

Signal transducer and activator of transcription 3 (STAT3) plays an important role in the occurrence and progression of tumors, leading to resistance and poor prognosis. Activation of STAT3 signaling is frequently detected in hepatocellular carcinoma (HCC), but potent and less toxic STAT3 inhibitors have not been discovered. Here, based on antisense technology, we designed a series of stabilized modified antisense oligonucleotides targeting STAT3 mRNA (STAT3 ASOs). Treatment with STAT3 ASOs decreased the STAT3 mRNA and protein levels in HCC cells. STAT3 ASOs significantly inhibited the proliferation, survival, migration, and invasion of cancer cells by specifically perturbing STAT3 signaling. Treatment with STAT3 ASOs decreased the tumor burden in an HCC xenograft model. Moreover, aberrant STAT3 signaling activation is one of multiple signaling pathways involved in sorafenib resistance in HCC. STAT3 ASOs effectively sensitized resistant HCC cell lines to sorafenib in vitro and improved the inhibitory potency of sorafenib in a resistant HCC xenograft model. The developed STAT3 ASOs enrich the tools capable of targeting STAT3 and modulating STAT3 activity, serve as a promising strategy for treating HCC and other STAT3-addicted tumors, and alleviate the acquired resistance to sorafenib in HCC patients. A series of novel STAT3 antisense oligonucleotide were designed and showed potent anti-cancer efficacy in hepatocellular carcinoma in vitro and in vivo by targeting STAT3 signaling. Moreover, the selected STAT3 ASOs enhance sorafenib sensitivity in resistant cell model and xenograft model.

Discovery of the small molecular inhibitors against sclerostin loop3 as potential anti-osteoporosis agents by structural based virtual screening and molecular design.

Sclerostin is a secreted glycoprotein that expresses predominantly in osteocytes and inhibits bone formation by antagonizing the Wnt/ß-catenin signaling pathway, and the loop3 region of sclerostin has recently discovered as a novel therapeutic target for bone anabolic treatment without increasing cardiovascular risk. Herein, we used a structural based virtual screening to search for small molecular inhibitors selectively targeting sclerostin loop3. A novel natural product hit ZINC4228235 (THFA) was identified as the sclerostin loop3-selective inhibitor with a Kd value of 42.43 nM against sclerostin loop3. The simplification and derivation of THFA using molecular modeling-guided modification allowed the discovery of an effective and loop3-selective small molecular inhibitor, compound (4-(3-acetamidoprop-1-yn-1-yl)benzoyl)glycine (AACA), with improved binding affinity (Kd = 15.4 nM) compared to the hit THFA. Further in-vitro experiment revealed that compound AACA could attenuate the suppressive effect of transfected sclerostin on Wnt signaling and bone formation. These results make AACA as a potential candidate for development of anti-osteoporosis agents without increasing cardiovascular risk.

DiffDec: Structure-Aware Scaffold Decoration with an End-to-End Diffusion Model.

In molecular optimization, one popular way is R-group decoration on molecular scaffolds, and many efforts have been made to generate R-groups based on deep generative models. However, these methods mostly use information on known binding ligands, without fully utilizing target structure information. In this study, we proposed a new method, DiffDec, to involve 3D pocket constraints by a modified diffusion technique for optimizing molecules through molecular scaffold decoration. For end-to-end generation of R-groups with different sizes, we designed a novel fake atom mechanism. DiffDec was shown to be able to generate structure-aware R-groups with realistic geometric substructures by the analysis of bond angles and dihedral angles and simultaneously generate multiple R-groups for one scaffold on different growth anchors. The growth anchors could be provided by users or automatically determined by our model. DiffDec achieved R-group recovery rates of 69.67% and 45.34% in the single and multiple R-group decoration tasks, respectively, and these values were significantly higher than competing methods (37.33% and 26.85%). According to the molecular docking study, our decorated molecules obtained a better average binding affinity than baseline methods. The docking pose analysis revealed that DiffDec could decorate scaffolds with R-groups that exhibited improved binding affinities and more favorable interactions with the pocket. These results demonstrated the potential and applicability of DiffDec in real-world scaffold decoration for molecular optimization.

GRELinker: A Graph-Based Generative Model for Molecular Linker Design with Reinforcement and Curriculum Learning.

Fragment-based drug discovery (FBDD) is widely used in drug design. One useful strategy in FBDD is designing linkers for linking fragments to optimize their molecular properties. In the current study, we present a novel generative fragment linking model, GRELinker, which utilizes a gated-graph neural network combined with reinforcement and curriculum learning to generate molecules with desirable attributes. The model has been shown to be efficient in multiple tasks, including controlling log P, optimizing synthesizability or predicted bioactivity of compounds, and generating molecules with high 3D similarity but low 2D similarity to the lead compound. Specifically, our model outperforms the previously reported reinforcement learning (RL) built-in method DRlinker on these benchmark tasks. Moreover, GRELinker has been successfully used in an actual FBDD case to generate optimized molecules with enhanced affinities by employing the docking score as the scoring function in RL. Besides, the implementation of curriculum learning in our framework enables the generation of structurally complex linkers more efficiently. These results demonstrate the benefits and feasibility of GRELinker in linker design for molecular optimization and drug discovery.

Deep learning-based design and screening of benzimidazole-pyrazine derivatives as adenosine A2B receptor antagonists.

The Adenosine A2B receptor (A2BAR) is considered a novel potential target for the immunotherapy of cancer, and A2BAR antagonists have an inhibitory effect on tumor growth, proliferation, and metastasis. In our previous studies, we identified a class of benzimidazole-pyrazine scaffolds whose derivatives exhibited the antagonistic effect but lacked subtype selectivity towards A2BAR. In this work, we developed a scaffold-based protocol that incorporates a deep generative model and multilayer virtual screening to design benzimidazole-pyrazine derivatives as potential selective A2BAR antagonists. By utilizing a generative model with reported A2BAR antagonists as the training set, we built up a scaffold-focused library of benzimidazole-pyrazine derivatives and processed a virtual screening protocol to discover potential A2BAR antagonists. Finally, five molecules with different Bemis-Murcko scaffolds were identified and exhibited higher binding free energies than the reference molecule 12o. Further computational analysis revealed that the 3-benzyl derivative ABA-1266 presented high selectivity toward A2BAR and showed preferred draggability, providing future potent development of selective A2BAR antagonists.Communicated by Ramaswamy H. Sarma.

A novel PPARß/FFA1 dual agonist Y8 promotes diabetic wound healing.

BACKGROUND: Diabetes ulcer is one of the leading causes of disability and death in diabetics. Y8 [(2-(2-fluoro-4-((4-methyl-2-(4-(trifluoromethyl)phenyl)thiazol-5-yl)methoxy) phenoxy)acetic acid)], a dual agonist of peroxisome proliferation activated receptorß (PPARß) and free fatty acid receptor 1 (FFA1/FFAR1/GPR40), a new compound molecule with the potential for diabetes ulcer treatment. OBJECTIVE: To research the effect of the dual target agonist Y8 and its mechanism of action in the treatment of diabetic ulcers. METHODS: We have established a wound model in diabetic mice. After treatment with Y8, wound healing was evaluated by tissue pathology, reactive oxygen species (ROS) levels, and gene expression testing. Under high sugar conditions, the mechanism of Y8 affecting fibroblasts' proliferation and keratinocytes' migration is further studied. RESULTS: We found that Y8 accelerated wound healing and shortened healing time in diabetic mice. Granulation tissue generation and extracellular matrix (ECM) deposition were significantly increased in Y8-treated mice. Mechanistically, Y8 promotes keratinocyte proliferation by activating PPARß and migration of keratinocytes by triggering FFA1 in vitro. In addition, Y8 also decreased ROS levels in fibroblasts in vitro and in vivo by activating PPARß, reducing their release of superoxide anions. CONCLUSION: Our results suggest that PPARß/FFA1 dual agonist Y8 has the effect of promoting the healing of diabetic ulcer wounds in vivo and in vitro, and its therapeutic effect is better than that of single-target agonists.

Discovery and Design of Novel Cyclic Peptides as Specific Inhibitors Targeting CCN2 and Disrupting CCN2/EGFR Interaction for Kidney Fibrosis Treatment.

Kidney fibrosis is a serious consequence of chronic kidney disease (CKD), and currently, there is no effective pharmacological treatment available. Cellular communication network-2 (CCN2/CTGF) is an extracellular matrix (ECM) protein that regulates the fibrotic process by activating the epidermal growth factor receptor (EGFR) signaling pathway. We herein present the discovery and structure-activity relationship study of novel peptides targeting CCN2 to develop potent and stable specific inhibitors of the CCN2/EGFR interaction. Remarkably, the 7-mer cyclic peptide OK2 exhibited potent activities to inhibit CCN2/EGFR-induced STAT3 phosphorylation and cellular ECM protein synthesis. Subsequent in vivo studies demonstrated that OK2 significantly alleviated renal fibrosis in a unilateral ureteral obstruction (UUO) mouse model. Moreover, this study first revealed that the peptide candidate could efficiently block CCN2/EGFR interaction through binding to the CT domain of CCN2, providing a new alternative strategy for peptide-based targeting of CCN2 and modulating CCN2/EGFR-mediated biological functions in kidney fibrosis.

Synthesis of dihydrofuran-3-one and 9,10-phenanthrenequinone hybrid molecules and biological evaluation against colon cancer cells as selective Akt kinase inhibitors.

A series of dihydrofuran-3-one and 9,10-phenanthrenequinone hybrid compounds were synthetized through a one-pot gold-catalyzed oxidative cyclization and Aldol-type addition cascade reaction of homopropargylic alcohols with 9,10-phenanthrenequinone. The cytotoxicity of newly synthesized compounds was evaluated in CCK8 assay against different human cancer cells, showing significantly antiproliferative activity against tested tumor cell lines with a lowest IC50 value of 0.92 µM over HCT-116. Further investigation revealed that the treatment of HCT-116 cell line with the promising compound 4c induced cell death as a selective Akt inhibitor. In addition, controlled experiments and molecular docking study suggested that the significant antitumor activity might be attributed to the unique hybrid structure, which implied the promising potential of this dual heterocycle hybrid method in the discovery of novel bioactive molecules with structural diversity.

DRlinker: Deep Reinforcement Learning for Optimization in Fragment Linking Design.

Fragment-based drug discovery is a widely used strategy for drug design in both academic and pharmaceutical industries. Although fragments can be linked to generate candidate compounds by the latest deep generative models, generating linkers with specified attributes remains underdeveloped. In this study, we presented a novel framework, DRlinker, to control fragment linking toward compounds with given attributes through reinforcement learning. The method has been shown to be effective for many tasks from controlling the linker length and log P, optimizing predicted bioactivity of compounds, to various multiobjective tasks. Specifically, our model successfully generated 91.0% and 93.9% of compounds complying with the desired linker length and log P and improved the 7.5 pChEMBL value in bioactivity optimization. Finally, a quasi-scaffold-hopping study revealed that DRlinker could generate nearly 30% molecules with high 3D similarity but low 2D similarity to the lead inhibitor, demonstrating the benefits and applicability of DRlinker in actual fragment-based drug design.

Surface urban heat island and its relationship with land cover change in five urban agglomerations in China based on GEE.

The development of urbanization has changed the original land cover and exacerbated the urban heat island effect, seriously affecting the sustainable development of the ecological environment. Research on urban heat island characteristics and land cover changes in five major urban agglomerations in China to provide a reference for preventing thermal environmental risks and urban agglomeration construction planning. This paper estimates the surface urban heat island intensity (SUHII) of the five major urban agglomerations in China from 2003 to 2019 based on Google Earth Engine (GEE) through the urban-rural dichotomy, analyzes their trends through the Sen + M-K trend analysis method, and combines the detrending rate matrix to analyze the impact of land cover type shift on urban heat island change. Research shows that (1) the land cover types of the five major urban agglomerations in China have changed considerably from 2003 to 2019, and all five major urban agglomerations in China experienced varying degrees of urban expansion. (2) The annual average value of SUHII decreases in Beijing-Tianjin-Hebei, Yangtze River Delta, and middle reaches of the urban agglomerations, while the annual average value of SUHII increases in Chengdu-Chongqing and Pearl River Delta urban agglomerations. (3) The spatial composition of land cover types in the five major urban agglomerations in China is highly spatially correlated with urban heat islands, with urban land and bare land urban heat islands being the most pronounced. (4) The land cover type shift has the most significant heat island impact on Beijing-Tianjin-Hebei, Yangtze River Delta, and Chengdu-Chongqing urban agglomerations. (5) The land cover change (LCC) with an increasing trend in SUHII is mainly bare land converted to arable land, and water bodies, grassland, forest land, and arable land converted to urban land.

Discovery of Novel Benzo[4,5]imidazo[1,2-a]pyrazin-1-amine-3-amide-one Derivatives as Anticancer Human A2A Adenosine Receptor Antagonists.

The blockade of A2A adenosine receptor (A2AAR) activates immunostimulatory response through regulating signaling in tumor microenvironment. Thus, A2AAR has been proposed as a promising target for cancer immunotherapy. In this work, we designed a new series of benzo[4,5]imidazo[1,2-a]pyrazin-1-amine derivatives bearing an amide substitution at 3-position to obtain potent antitumor antagonist in vivo. The structure-activity relationship studies were performed by molecular modeling and radioactive assay. The in vitro anticancer activities were evaluated by 3',5'-cyclic adenosine monophosphate (cAMP) functional and T cell activation assay. The most potent compound 12o·2HCl showed much higher affinity toward A2AAR (Ki = 0.08 nM) and exhibited more significant in vitro immunostimulatory anticancer activity than clinical antagonist AZD4635. More importantly, 12o·2HCl significantly inhibited the growth of triple-negative breast cancer by reversing immunosuppressive tumor microenvironment in the xenograft mouse model without severe toxicity at the testing dose. These results make 12o·2HCl a promising immunotherapy anticancer drug candidate.

Targeting autophagy peptidase ATG4B with a novel natural product inhibitor Azalomycin F4a for advanced gastric cancer.

Advanced gastric cancer (GCa) remains highly lethal due to the lack of effective therapies. Identifying promising therapeutic targets and developing effective treatment against GCa are urgently needed. Through mRNA and protein analysis of GCa clinical tumor samples, we found that autophagy-related gene 4B (ATG4B) was overexpressed in GCa tumors and that its high expression was associated with patients' poor prognosis. Knockdown of ATG4B significantly inhibited GCa cell survival and tumor growth. To further probe the role of ATG4B in GCa by pharmacological means, we screened an in-house marine natural compound library against ATG4B and identified Azalomycin F4a (Am-F4a) as a novel and potent ATG4B inhibitor. Am-F4a directly bound to ATG4B with high affinity and effectively suppressed GCa cell autophagy via inhibition of ATG4B both in vitro and in vivo. Moreover, Am-F4a or ATG4B knockdown significantly suppressed tumor growth as well as GCa cell migration and invasion. Am-F4a effectively blocked the metastatic progression of primary GCa and sensitized tumors to chemotherapy. Taken together, our findings indicate that ATG4B is a potential therapeutic target against GCa and the natural product Am-F4a is a novel ATG4B inhibitor that can be further developed for the treatment of GCa.

The novel indomethacin derivative CZ-212-3 exerts antitumor effects on castration-resistant prostate cancer by degrading androgen receptor and its variants.

Androgen receptor (AR) serves as a main therapeutic target for prostate cancer (PCa). However, resistance to anti-androgen therapy (SAT) inevitably occurs. Indomethacin is a nonsteroidal anti-inflammatory drug that exhibits activity against prostate cancer. Recently, we designed and synthesized a series of new indomethacin derivatives (CZ compounds) via Pd (II)-catalyzed synthesis of substituted N-benzoylindole. In this study, we evaluated the antitumor effect of these novel indomethacin derivatives in castration-resistant prostate cancer (CRPC). Upon employing CCK-8 cell viability assays and colony formation assays, we found that these derivatives had high efficacy against CRPC tumor growth in vitro. Among these derivatives, CZ-212-3 exhibited the most potent efficacy against CRPC cell survival and on apoptosis induction. Mechanistically, CZ-212-3 significantly suppressed the expression of AR target gene networks by degrading AR and its variants. Consistently, CZ-212-3 significantly inhibited tumor growth in CRPC cell line-based xenograft and PDX models in vivo. Taken together, the data show that the indomethacin derivative CZ-212-3 significantly inhibited CRPC tumor growth by degrading AR and its variants and could be a promising agent for CRPC therapy.

3D Conformational Generative Models for Biological Structures Using Graph Information-Embedded Relative Coordinates.

Developing molecular generative models for directly generating 3D conformation has recently become a hot research area. Here, an autoencoder based generative model was proposed for molecular conformation generation. A unique feature of our method is that the graph information embedded relative coordinate (GIE-RC), satisfying translation and rotation invariance, was proposed as a novel way for encoding molecular three-dimensional structure. Compared with commonly used Cartesian coordinate and internal coordinate, GIE-RC is less sensitive on errors when decoding latent variables to 3D coordinates. By using this method, a complex 3D generation task can be turned into a graph node feature generation problem. Examples were shown that the GIE-RC based autoencoder model can be used for both ligand and peptide conformation generation. Additionally, this model was used as an efficient conformation sampling method to augment conformation data needed in the construction of neural network-based force field.

Ilicicolin A Exerts Antitumor Effect in Castration-Resistant Prostate Cancer Via Suppressing EZH2 Signaling Pathway.

The Polycomb protein enhancer of zeste homolog 2 (EZH2) has critical roles in prostate cancer (PCa) progression and drug-resistance, which remains an obstacle for PCa treatment. Enzalutamide (ENZ) is a second-generation androgen receptor antagonist employed for treatment of metastatic castration-resistant prostate cancer A considerable proportion of tumors eventually develop resistance during treatment. Thus, agents that can overcome resistance to PCa are needed urgently. Ilicicolin A (Ili-A), an ascochlorin derivative isolated from the coral-derived fungus Acremonium sclerotigenum GXIMD 02501, shows antiproliferative activity in human PCa cells, but its mechanism of action against Castration-resistant prostate cancer is not known. Herein, RNA-sequencing showed the EZH2 pathway to be involved in PCa proliferation. Ili-A at low doses reduced the protein level of EZH2, leading to transcriptional change. Interestingly, Ili-A suppressed the binding of EZH2 to promoter regions in AR/serine/threonine polo-like kinase-1/aurora kinase A. Moreover, Ili-A could enhance the anticancer activity of enzalutamide in CRPC cancer models. These data suggest that Ili-A could be used in combination with enzalutamide to treat CRPC.

Prediction of Spatiotemporal Invasive Risk of the Red Import Fire Ant, Solenopsis invicta (Hymenoptera: Formicidae), in China.

The red imported fire ant, Solenopsis invicta (Hymenoptera: Formicidae), is an invasive pest, and it has spread rapidly all over the world. Predicting the suitable area of S. invicta growth in China will provide a reference that will allow for its invasion to be curbed. In this study, based on the 354 geographical distribution records of S. invicta, combined with 24 environmental factors, the suitable areas of S. invicta growth in China under current (2000s) and future (2030s and 2050s) climate scenarios (SSPs1-2.5s, SSPs2-3.5s and SSPs5-8.5s) were predicted by using the optimized MaxEnt model and geo-detector model. An iterative algorithm and knife-cut test were used to evaluate the important environmental factors that restrict the suitable area under the current climatic conditions. This study also used the response curve to determine the appropriate value of environmental factors to further predict the change and the center of gravity transfer of the suitable area under climate change. The optimized MaxEnt model has high prediction accuracy, and the working curve area (AUC) of the subjects is 0.974. Under climatic conditions, the suitable area is 81.37 × 104 km2 in size and is mainly located in the south and southeast of China. The main environmental factors affecting the suitable area are temperature (Bio1, Bio6, and Bio9), precipitation (Bio12 and Bio14) and NDVI. In future climate change scenarios, the total suitable area will spread to higher latitudes. This distribution will provide an important theoretical basis for relevant departments to rapidly prevent and control the invasion of S. invicta.

Exploring Marine-Derived Ascochlorins as Novel Human Dihydroorotate Dehydrogenase Inhibitors for Treatment of Triple-Negative Breast Cancer.

Human dihydroorotate dehydrogenase (hDHODH) is an attractive tumor target essential to de novo pyrimidine biosynthesis. Novel potent hDHODH inhibitors with low toxicity are urgently needed. Herein, we demonstrate the isolation of 25 ascochlorin (ASC) derivatives, including 13 new ones, from the coral-derived fungus Acremonium sclerotigenum, and several of them showed pronounced inhibitions against hDHODH and triple-negative breast cancer (TNBC) cell lines, MDA-MB-231/-468. Interestingly, we found that hDHODH is required for proliferation and survival of TNBC cells, and several ASCs significantly inhibited TNBC cell growth and induced their apoptosis via hDHODH inhibition. Furthermore, the novel and potent hDHODH inhibitors (1 and 21) efficiently suppressed tumor growth in patient-derived TNBC xenograft models without obvious body weight loss or overt toxicity in mice. Collectively, our findings offered a novel lead scaffold as the hDHODH inhibitor for further development of potent anticancer agents and a potential therapeutic strategy for TNBC.

Microsecond timescale MD simulations at the transition state of PmHMGR predict remote allosteric residues.

Understanding the mechanisms of enzymatic catalysis requires a detailed understanding of the complex interplay of structure and dynamics of large systems that is a challenge for both experimental and computational approaches. More importantly, the computational demands of QM/MM simulations mean that the dynamics of the reaction can only be considered on a timescale of nanoseconds even though the conformational changes needed to reach the catalytically active state happen on a much slower timescale. Here we demonstrate an alternative approach that uses transition state force fields (TSFFs) derived by the quantum-guided molecular mechanics (Q2MM) method that provides a consistent treatment of the entire system at the classical molecular mechanics level and allows simulations at the microsecond timescale. Application of this approach to the second hydride transfer transition state of HMG-CoA reductase from Pseudomonas mevalonii (PmHMGR) identified three remote residues, R396, E399 and L407, (15-27 Å away from the active site) that have a remote dynamic effect on enzyme activity. The predictions were subsequently validated experimentally via site-directed mutagenesis. These results show that microsecond timescale MD simulations of transition states are possible and can predict rather than just rationalize remote allosteric residues.

Strain-Induced Nucleophilic Ring Opening of Donor-Acceptor Cyclopropenes for Synthesis of Monosubstituted Succinic Acid Derivatives.

1,2,3-Trisubstituted donor-acceptor cyclopropenes (DACPs) generated in situ from enoldiazo compounds react with nucleophiles to form α-substituted succinic acid derivatives in high yields. Initial dirhodium(II) carboxylate catalysis rapidly converts enoldiazo-acetates or -acetamides to DACPs that undergo catalyst-free Favorskii ring opening with amines, and also with anilines, alcohols, and thiols, when facilitated by catalytic amounts of 4-dimethylaminopyridine (DMAP). This methodology provides easy access to mixed esters and amides of monosubstituted succinic acids, including derivatives of naturally occurring compounds. It also affords dihydrazide, dihydroxamic acid, and diamide derivatives, as well as α-substituted tetrahydropyridazine-3,6-diones in high yields. Attempts to generate optically enriched DACPs were not successful because their populations having the R and S configurations formed with a chiral dirhodium catalyst are quite similar, and the loss of enantiocontrol likely originates from the DACP ring forming step which is reversible with its intermediate metal carbene.

Design, synthesis and biological evaluation of novel scaffold benzo[4,5]imidazo [1,2-a]pyrazin-1-amine: Towards adenosine A2A receptor (A2A AR) antagonist.

Antagonists of adenosine receptor are under exploration as potential drug candidates for treatment of neurological disorders, depression, certain cancers and potentially used as a cancer immunotherapy. Herein, we describe design and synthesis of novel scaffold benzo[4,5]imidazo [1,2-a]pyrazin-1-amine (6) derivatives. All the compounds were evaluated for A2A AR antagonist activity and displayed encouraging results (IC50 9-300 nM) of A2A AR antagonist binding affinity in biochemical assay. Compound 27 exhibits good activity in A2A AR antagonist cAMP functional assay (IC50 31 nM) and further this compound shows T-cell activation at the IL-2 production assay (EC50 165 nM). Molecular docking studies were carried out to rationalize the observed binding affinity of compound 27.