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.

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.

Structure-Based Virtual Screening for Methyltransferase Inhibitors of SARS-CoV-2 nsp14 and nsp16.

The ongoing COVID-19 pandemic still threatens human health around the world. The methyltransferases (MTases) of SARS-CoV-2, specifically nsp14 and nsp16, play crucial roles in the methylation of the N7 and 2'-O positions of viral RNA, making them promising targets for the development of antiviral drugs. In this work, we performed structure-based virtual screening for nsp14 and nsp16 using the screening workflow (HTVS, SP, XP) of Schrödinger 2019 software, and we carried out biochemical assays and molecular dynamics simulation for the identification of potential MTase inhibitors. For nsp14, we screened 239,000 molecules, leading to the identification of three hits A1-A3 showing N7-MTase inhibition rates greater than 60% under a concentration of 50 µM. For the SAM binding and nsp10-16 interface sites of nsp16, the screening of 210,000 and 237,000 molecules, respectively, from ZINC15 led to the discovery of three hit compounds B1-B3 exhibiting more than 45% of 2'-O-MTase inhibition under 50 µM. These six compounds with moderate MTase inhibitory activities could be used as novel candidates for the further development of anti-SARS-CoV-2 drugs.

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.

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.

Two symmetric arginine residues play distinct roles in Thermus thermophilus Argonaute DNA guide strand-mediated DNA target cleavage.

Bacterium Thermus thermophilus Argonaute (Ago; TtAgo) is a prokaryotic Ago (pAgo) that acts as the host defense against the uptake and propagation of foreign DNA by catalyzing the DNA cleavage reaction. The TtAgo active site consists of a plugged-in glutamate finger with two arginine residues (R545 and R486) located symmetrically around it. An interesting challenge is to understand how they can collaboratively facilitate enzymatic catalysis. In Kluyveromyces polysporus Ago, a eukaryotic Ago, the evolutionarily symmetrical residues are arginine and histidine, both of which function to stabilize the plugged-in catalytic tetrad conformation. Surprisingly, our simulation results indicated that, in TtAgo, only R545 is involved in the cleavage reaction by serving as a critical structural anchor to stabilize the catalytic tetrad Asp-Glu-Asp-Asp that is completed by the insertion of the glutamate finger, whereas R486 is not involved in target cleavage. The TtAgo-mediated target DNA cleavage occurs in a substrate-assisted mechanism, in which the pro-Rp (Rp, a tetrahedral phosphorus center with "R-type" chirality) oxygen of scissile phosphate acts as a general base to activate the nucleophilic water. Our unexpected theoretical findings on distinct roles played by R545 and R486 in TtAgo catalysis have been validated by single-point site-mutagenesis experiments, wherein the target cleavage is abolished for all mutants of R545. In sharp contrast, the cleavage activity is maintained for all mutants of R486. Our work provides mechanistic insights on the catalytic specificity of Ago proteins and could facilitate the design of new gene-editing tools in the long term.

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.

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.

Blue Light-Promoted Formal [4+1]-Annulation of Diazoacetates with o-Aminoacetophenones: Synthesis of Polysubstituted Indolines and Computational Study.

A blue light-promoted formal [4+1]-annulation of diazoacetates with o-aminoacetophenones has been reported, which provides an environmentally friendly method for the synthesis of polysubstituted indoline derivatives in moderate to good yields with excellent diastereoselectivities. Detailed mechanistic studies through density functional theory calculations reveal that the (E)-enol species is the key intermediate in this transformation, and the excellent diastereoselectivity is enabled via H-bonding in the intramolecular Aldol-type addition.

Multifunctional AuI -based AIEgens: Manipulating Molecular Structures and Boosting Specific Cancer Cell Imaging and Theranostics.

Gold(I) N-heterocyclic carbene (AuI -NHC) complexes have emerged as potential anticancer agents owing to their high cytotoxicity and stability. Integration of their above unique functions with customized aggregation-induced emission (AIE) luminogens to achieve specific bioimaging and efficient theranostics to cancer is highly desirable but is rarely studied. Now, a series of novel AuI -NHC compounds were developed with AIE characteristics. A complex with a PPh3 ligand was selected out as it could achieve both prominent specific imaging of various cancer cells and efficient inhibition of their growth with negligible toxic effects on normal cells due to the targeting binding and strong inhibition towards thioredoxin reductase. This complex could also act as a powerful radiosensitizer to boost the anticancer efficacy with performance superior to that of popularly used auranofin. It holds great potential as a specific and effective theranostic drug in cancer diagnosis and precise therapy.

Crystallographic Snapshots of Class A ß-Lactamase Catalysis Reveal Structural Changes That Facilitate ß-Lactam Hydrolysis.

ß-Lactamases confer resistance to ß-lactam-based antibiotics. There is great interest in understanding their mechanisms to enable the development of ß-lactamase-specific inhibitors. The mechanism of class A ß-lactamases has been studied extensively, revealing Lys-73 and Glu-166 as general bases that assist the catalytic residue Ser-70. However, the specific roles of these two residues within the catalytic cycle remain not fully understood. To help resolve this, we first identified an E166H mutant that is functional but is kinetically slow. We then carried out time-resolved crystallographic study of a full cycle of the catalytic reaction. We obtained structures that represent apo, ES*-acylation, and ES*-deacylation states and analyzed the conformational changes of His-166. The "in" conformation in the apo structure allows His-166 to form a hydrogen bond with Lys-73. The unexpected "flipped-out" conformation of His-166 in the ES*-acylation structure was further examined by molecular dynamics simulations, which suggested deprotonated Lys-73 serving as the general base for acylation. The "revert-in" conformation in the ES*-deacylation structure aligns His-166 toward the water molecule that hydrolyzes the acyl adduct. Finally, when the acyl adduct is fully hydrolyzed, His-166 rotates back to the "in" conformation of the apo-state, restoring the Lys-73/His-166 interaction. Using His-166 as surrogate, our study identifies distinct conformational changes within the active site during catalysis. We suggest that the native Glu-166 executes similar changes in a less constricted way. Taken together, this structural series improves our understanding of ß-lactam hydrolysis in this important class of enzymes.

The association of HTR3A mRNA expression and craving in Han Chinese alcohol-dependent patients: a preliminary study.

BACKGROUND: 5-Hydroxytryptamine (5-HT) 3 receptor plays a crucial role in craving of alcohol dependence. Recent evidence shows that chronic alcohol exposure causes changes in gene expression and induces behavioral changes. However, the relationship between gene expression of 5-HT3 receptor and craving in alcohol-dependent patients is not fully understood. OBJECTIVES: The aim of this preliminary study was to investigate the relationship between gene expression of the 5-HT3 receptor and craving in alcohol-dependent patients and the epigenetic mechanism. METHODS: We recruited 50 male Han Chinese alcohol-dependent patients and 46 male Han Chinese healthy controls. We investigated the changes of HTR3A mRNA, which encodes the 5-HT3 receptor A subunit, and H3K9 acetylation in HTR3A promoter region. Obsessive Compulsive Drinking Scale (OCDS) was used to assess the craving of alcohol-dependent patients relative to controls. RESULTS: HTR3A mRNA expression levels and acetylation levels of H3K9 in the HTR3A promoter region were significantly higher in the alcohol-dependent patients. HTR3A mRNA expression levels were positively correlated with OCDS scores. Moreover, HTR3A mRNA expression levels were positively correlated with acetylation levels of H3K9 in HTR3A promoter region. CONCLUSION: The current findings suggest that HTR3A mRNA expression levels were positively correlated with craving in Han Chinese alcohol-dependent patients. The regulation of H3K9 histone acetylation in HTR3A promoter region may offer a target for the treatment of alcohol dependence.

[Studies of Male Fertility with Raman Spectroscopy].

Raman spectroscopy which belongs to scattering spectroscopy obtained molecular vibrational and rotational information to achieve detection and analysis of molecular structure and corresponding changes through recording the frequency shift when light interacted with materials. Compared with routine biochemical analysis, Raman spectroscopy has the advantage of non-invasive, label-free and no sample requirement. Raman spectroscopy has been widely applied in biomedical field such as human tissue, organs, cells and human body fluids for disease diagnosis. This article mainly focuses on recent research advances of Raman spectroscopy in human semen. Firstly, Raman spectroscopy(including surface-enhanced Raman spectroscopy, SERS) employed in forensic science for semen analysis, and some related data processing methods were introduced, then Raman spectroscopy involved investigations of male fertility was highlighted, more specifically, the Raman-based qualitative and quantitative analysis which assist the objective detection and evaluation of male fertility. Furthermore, studies of single sperm cell based on micro-Raman system to characterize and evaluate sperm quality and the preliminarily obtained Raman biomarkers which indicate high-quality sperm cell were introduced. Finally, the potential development of Raman spectroscopy involved in reproduction and fertility field was also discussed.

Mechanistic insights into a classic wonder drug--aspirin.

Aspirin, one of the oldest and most common anti-inflammatory agents, has recently been shown to reduce cancer risks. The principal pharmacological effects of aspirin are known to arise from its covalent modification of cyclooxygenase-2 (COX-2) through acetylation of Ser530, but the detailed mechanism of its biochemical action and specificity remains to be elucidated. In this work, we have filled this gap by employing a state-of-the-art computational approach, Born-Oppenheimer molecular dynamics simulations with ab initio quantum mechanical/molecular mechanical potential and umbrella sampling. Our studies have characterized a substrate-assisted inhibition mechanism for aspirin acetylating COX: it proceeds in two successive stages with a metastable tetrahedral intermediate, in which the carboxyl group of aspirin serves as the general base. The computational results confirmed that aspirin would be 10-100 times more potent against COX-1 than against COX-2, and revealed that this inhibition specificity between the two COX isoforms can be attributed mainly to the difference in kinetics rate of the covalent inhibition reaction, not the aspirin-binding step. The structural origin of this differential inhibition of the COX enzymes by aspirin has also been elucidated.

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.

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.