D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer.

As key oncogenic drivers in non-small-cell lung cancer (NSCLC), various mutations in the epidermal growth factor receptor (EGFR) with variable drug sensitivities have been a major obstacle for precision medicine. To achieve clinical-level drug recommendations, a platform for clinical patient case retrieval and reliable drug sensitivity prediction is highly expected. Therefore, we built a database, D3EGFRdb, with the clinicopathologic characteristics and drug responses of 1339 patients with EGFR mutations via literature mining. On the basis of D3EGFRdb, we developed a deep learning-based prediction model, D3EGFRAI, for drug sensitivity prediction of new EGFR mutation-driven NSCLC. Model validations of D3EGFRAI showed a prediction accuracy of 0.81 and 0.85 for patients from D3EGFRdb and our hospitals, respectively. Furthermore, mutation scanning of the crucial residues inside drug-binding pockets, which may occur in the future, was performed to explore their drug sensitivity changes. D3EGFR is the first platform to achieve clinical-level drug response prediction of all approved small molecule drugs for EGFR mutation-driven lung cancer and is freely accessible at https://www.d3pharma.com/D3EGFR/index.php.

Bioactive compounds from Huashi Baidu decoction possess both antiviral and anti-inflammatory effects against COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic is an ongoing global health concern, and effective antiviral reagents are urgently needed. Traditional Chinese medicine theory-driven natural drug research and development (TCMT-NDRD) is a feasible method to address this issue as the traditional Chinese medicine formulae have been shown effective in the treatment of COVID-19. Huashi Baidu decoction (Q-14) is a clinically approved formula for COVID-19 therapy with antiviral and anti-inflammatory effects. Here, an integrative pharmacological strategy was applied to identify the antiviral and anti-inflammatory bioactive compounds from Q-14. Overall, a total of 343 chemical compounds were initially characterized, and 60 prototype compounds in Q-14 were subsequently traced in plasma using ultrahigh-performance liquid chromatography with quadrupole time-of-flight mass spectrometry. Among the 60 compounds, six compounds (magnolol, glycyrrhisoflavone, licoisoflavone A, emodin, echinatin, and quercetin) were identified showing a dose-dependent inhibition effect on the SARS-CoV-2 infection, including two inhibitors (echinatin and quercetin) of the main protease (Mpro), as well as two inhibitors (glycyrrhisoflavone and licoisoflavone A) of the RNA-dependent RNA polymerase (RdRp). Meanwhile, three anti-inflammatory components, including licochalcone B, echinatin, and glycyrrhisoflavone, were identified in a SARS-CoV-2-infected inflammatory cell model. In addition, glycyrrhisoflavone and licoisoflavone A also displayed strong inhibitory activities against cAMP-specific 3',5'-cyclic phosphodiesterase 4 (PDE4). Crystal structures of PDE4 in complex with glycyrrhisoflavone or licoisoflavone A were determined at resolutions of 1.54 Å and 1.65 Å, respectively, and both compounds bind in the active site of PDE4 with similar interactions. These findings will greatly stimulate the study of TCMT-NDRD against COVID-19.

Exploring the immune evasion of SARS-CoV-2 variant harboring E484K by molecular dynamics simulations.

Although the current coronavirus disease 2019 (COVID-19) vaccines have been used worldwide to halt spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the emergence of new SARS-CoV-2 variants with E484K mutation shows significant resistance to the neutralization of vaccine sera. To better understand the resistant mechanism, we calculated the binding affinities of 26 antibodies to wild-type (WT) spike protein and to the protein harboring E484K mutation, respectively. The results showed that most antibodies (~85%) have weaker binding affinities to the E484K mutated spike protein than to the WT, indicating the high risk of immune evasion of the mutated virus from most of current antibodies. Binding free energy decomposition revealed that the residue E484 forms attraction with most antibodies, while the K484 has repulsion from most antibodies, which should be the main reason of the weaker binding affinities of E484K mutant to most antibodies. Impressively, a monoclonal antibody (mAb) combination was found to have much stronger binding affinity with E484K mutant than WT, which may work well against the mutated virus. Based on binding free energy decomposition, we predicted that the mutation of four more residues on receptor-binding domain (RBD) of spike protein, viz., F490, V483, G485 and S494, may have high risk of immune evasion, which we should pay close attention on during the development of new mAb therapeutics.

D3AI-CoV: a deep learning platform for predicting drug targets and for virtual screening against COVID-19.

Target prediction and virtual screening are two powerful tools of computer-aided drug design. Target identification is of great significance for hit discovery, lead optimization, drug repurposing and elucidation of the mechanism. Virtual screening can improve the hit rate of drug screening to shorten the cycle of drug discovery and development. Therefore, target prediction and virtual screening are of great importance for developing highly effective drugs against COVID-19. Here we present D3AI-CoV, a platform for target prediction and virtual screening for the discovery of anti-COVID-19 drugs. The platform is composed of three newly developed deep learning-based models i.e., MultiDTI, MPNNs-CNN and MPNNs-CNN-R models. To compare the predictive performance of D3AI-CoV with other methods, an external test set, named Test-78, was prepared, which consists of 39 newly published independent active compounds and 39 inactive compounds from DrugBank. For target prediction, the areas under the receiver operating characteristic curves (AUCs) of MultiDTI and MPNNs-CNN models are 0.93 and 0.91, respectively, whereas the AUCs of the other reported approaches range from 0.51 to 0.74. For virtual screening, the hit rate of D3AI-CoV is also better than other methods. D3AI-CoV is available for free as a web application at http://www.d3pharma.com/D3Targets-2019-nCoV/D3AI-CoV/index.php, which can serve as a rapid online tool for predicting potential targets for active compounds and for identifying active molecules against a specific target protein for COVID-19 treatment.

Design and synthesis of cantharidin derivative DCZ5418 as a TRIP13 inhibitor with anti-multiple myeloma activity in vitro and in vivo.

Natural product cantharidin can inhibit multiple myeloma cell growth in vitro, while serious adverse effects limited its clinical application. Therefore, the structural modification of cantharidin is needed. Herein, inspired by the structural similarity of the aliphatic endocyclic moiety in cantharidin and TRIP13 inhibitor DCZ0415, we designed and synthesized DCZ5418 and its nineteen derivatives. The molecular docking study indicated that DCZ5418 had a similar binding mode to TRIP13 protein as DCZ0415 while with a stronger docking score. Moreover, the bioassay studies of the MM-cells viability inhibition, TRIP13 protein binding affinity and enzyme inhibiting activity showed that DCZ5418 had good anti-MM activity in vitro and definite interaction with TRIP13 protein. The acute toxicity test of DCZ5418 showed less toxicity in vivo than cantharidin. Furthermore, DCZ5418 showed good anti-MM effects in vivo with a lower dose administration than DCZ0415 (15 mg/kg vs 25 mg/kg) on the tumor xenograft models. Thus, we obtained a new TRIP13 inhibitor DCZ5418 with improved safety and good activity in vivo, which provides a new example of lead optimization by using the structural fragments of natural products.

D3Rings: A Fast and Accurate Method for Ring System Identification and Deep Generation of Drug-Like Cyclic Compounds.

Continuous exploration of the chemical space of molecules to find ligands with high affinity and specificity for specific targets is an important topic in drug discovery. A focus on cyclic compounds, particularly natural compounds with diverse scaffolds, provides important insights into novel molecular structures for drug design. However, the complexity of their ring structures has hindered the applicability of widely accepted methods and software for the systematic identification and classification of cyclic compounds. Herein, we successfully developed a new method, D3Rings, to identify acyclic, monocyclic, spiro ring, fused and bridged ring, and cage ring compounds, as well as macrocyclic compounds. By using D3Rings, we completed the statistics of cyclic compounds in three different databases, e.g., ChEMBL, DrugBank, and COCONUT. The results demonstrated the richness of ring structures in natural products, especially spiro, macrocycles, and fused and bridged rings. Based on this, three deep generative models, namely, VAE, AAE, and CharRNN, were trained and used to construct two data sets similar to DrugBank and COCONUT but 10 times larger than them. The enlarged data sets were then used to explore the molecular chemical space, focusing on complex ring structures, for novel drug discovery and development. Docking experiments with the newly generated COCONUT-like data set against three SARS-CoV-2 target proteins revealed that an expanded compound database improves molecular docking results. Cyclic structures exhibited the best docking scores among the top-ranked docking molecules. These results suggest the importance of exploring the chemical space of structurally novel cyclic compounds and continuous expansion of the library of drug-like compounds to facilitate the discovery of potent ligands with high binding affinity to specific targets. D3Rings is now freely available at http://www.d3pharma.com/D3Rings/.

Discovery and development of novel 10,12-disubstituted aloperine derivatives against HCoV-OC43 by targeting allosteric site of host TMPRSS2.

By inducing steric activation of the 10CH bond with a 12-acyl group to form a key imine oxime intermediate, 20 novel (10S)-10,12-disubstituted aloperine derivatives were successfully synthesized and assessed for their antiviral efficacy against HCoV-OC43. Of them, compound 3i exhibited the moderate activities against HCoV-OC43, as well as against the SARS-CoV-2 variant EG.5.1 with the comparable EC50 values of 4.7 and 4.1 µM. A mechanism study revealed that it inhibited the protease activity of host TMPRSS2 by binding to an allosteric site, rather than the known catalytic center, different from that of camostat. Also, the combination of compound 3i and molnupiravir, as an RdRp inhibitor, showed an additive antiviral effect against HCoV-OC43. The results provide a new binding mode and lead compound for targeting TMPRSS2, with an advantage in combating broad-spectrum coronavirus.

Design, synthesis and triglyceride-lowering activity of tricyclic matrine derivatives for the intervention of non-alcoholic fatty liver disease.

Thirty new tricyclicmatrinic derivatives were successively synthesized and evaluated for their inhibitory activity on the accumulation of triglycerides (TG) in AML12 cells, using 12 N-m-trifluoromethylbenzenesulfonyl matrine (1) as the hit compound. Among the analogues, compound 7n possessing 11-trimethylbutylamine quaternary exerted the highest in vitro TG-lowering potency, as well as a good safety profile. 7n significantly attenuated the hepatic injury and steatosis, and ameliorated dyslipidemia and dysglycemia in the mice with non-alcoholic fatty liver disease (NAFLD) induced by a high-fat diet. Primary mechanism study revealed that upregulation of peroxisome proliferator-activated receptors α (PPARα)-carnitine palmitoyltransferase 1A (CPT1A) pathway mediated the efficacy of 7n. Our study provides powerful information for developing this kind of compound into a new class of anti-NAFLD candidates, and compound 7n is worthy of further investigation as an ideal lead compound.

Laboratory animal ethics education improves medical students' awareness of laboratory animal ethics.

OBJECTIVE: In this study, we added laboratory animal ethics education into both didactic sessions and practical sessions the general surgery laboratory course, with the didactic sessions focus on teaching the fundamental principles of laboratory animal ethics, while the practical sessions emphasize the application of these principles in laboratory classes and have assessed the changes in medical students' perception of laboratory animal ethics following medical students exposure to such education. METHODS: One hundred and eighty-nine third-year medical students from Wuhan University's Second Clinical College completed a laboratory animal ethics awareness questionnaire and a laboratory animal ethics written examination before and after laboratory animal ethics education. RESULTS: After receiving laboratory animal ethics education, the percentage of students who supported euthanasia for the execution of animals and humane treatment of laboratory animals were 95.2% and 98.8%, respectively, which did not differ from the 94.9% and 96.4% observed before the education. Moreover, there was a notable increase in the proportion of students who knew about regulations related to laboratory animals (from 39.9% to 57.1%), welfare issues (from 31.9% to 50.0%), and the 3R principle (from 30.4% to 58.9%) post-education, all statistically significant at P < 0.05. Test scores also showed improvement, with students scoring (93.02 ± 11.65) after education compared to (67.83 ± 8.08) before, a statistically significant difference. CONCLUSIONS: This research helps to provide information for the good practices of laboratory animal ethics education. After receiving laboratory animal ethics education, students are better able to treat laboratory animals in a correct animal ethical manner. Laboratory animal ethics education helps improve students' knowledge of laboratory animal ethics. Students' perception towards how the laboratory animal ethics course should be delivered may vary. Still, new courses or better organized courses on laboratory animal ethics education are required in order to provide students an in-depth understanding.

Ligand-based approach for predicting drug targets and for virtual screening against COVID-19.

Discovering efficient drugs and identifying target proteins are still an unmet but urgent need for curing coronavirus disease 2019 (COVID-19). Protein structure-based docking is a widely applied approach for discovering active compounds against drug targets and for predicting potential targets of active compounds. However, this approach has its inherent deficiency caused by e.g. various different conformations with largely varied binding pockets adopted by proteins, or the lack of true target proteins in the database. This deficiency may result in false negative results. As a complementary approach to the protein structure-based platform for COVID-19, termed as D3Docking in our previous work, we developed in this study a ligand-based method, named D3Similarity, which is based on the molecular similarity evaluation between the submitted molecule(s) and those in an active compound database. The database is constituted by all the reported bioactive molecules against the coronaviruses, viz., severe acute respiratory syndrome coronavirus (SARS), Middle East respiratory syndrome coronavirus (MERS), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), human betacoronavirus 2c EMC/2012 (HCoV-EMC), human CoV 229E (HCoV-229E) and feline infectious peritonitis virus (FIPV), some of which have target or mechanism information but some do not. Based on the two-dimensional (2D) and three-dimensional (3D) similarity evaluation of molecular structures, virtual screening and target prediction could be performed according to similarity ranking results. With two examples, we demonstrated the reliability and efficiency of D3Similarity by using 2D × 3D value as score for drug discovery and target prediction against COVID-19. The database, which will be updated regularly, is available free of charge at https://www.d3pharma.com/D3Targets-2019-nCoV/D3Similarity/index.php.

Preferred microenvironments of halogen bonds and hydrogen bonds revealed using statistics and QM/MM calculation studies.

Hydrogen bonds (HBs) and halogen bonds (XBs) are two essential non-covalent interactions for molecular recognition and drug design. As proteins are heterogeneous in structure, the microenvironments of protein structures should have effects on the formation of HBs and XBs with ligands. However, there are no systematic studies reported on this effect to date. For quantitatively describing protein microenvironments, we defined the local hydrophobicities (LHs) and local dielectric constants (LDCs) in this study. With the defined parameters, we conducted an elaborate database survey on the basis of 22 011 ligand-protein structures to explore the microenvironmental preference of HBs (91 966 in total) and XBs (1436 in total). The statistics show that XBs prefer hydrophobic microenvironments compared to HBs. The polar residues like ASP are more likely to form HBs with ligands, while nonpolar residues such as PHE and MET prefer XBs. Both the LHs and LDCs (10.69 ± 4.36 for HBs; 8.86 ± 4.00 for XBs) demonstrate that XBs are prone to hydrophobic microenvironments compared with HBs with significant differences (p < 0.001), indicating that evaluating their strengths in the corresponding environments should be necessary. Quantum Mechanics-Molecular Mechanics (QM/MM) calculations reveal that in comparison with vacuum environments, the interaction energies of HBs and XBs are decreased to varying degrees given different microenvironments. In addition, the strengths of HBs are impaired more than those of XBs when the local dielectric constant's difference between the XB microenvironments and the HB microenvironments is large.

Exploring the Binding Affinity and Mechanism between ACE2 and the Trimers of Delta and Omicron Spike Proteins by Molecular Dynamics Simulation and Bioassay.

Five major variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged and posed challenges in controlling the pandemic. Among them, the current dominant variant, viz., Omicron, has raised serious concerns about its infectiousness and antibody neutralization. However, few studies pay attention to the effect of the mutations on the dynamic interaction network of Omicron S protein trimers binding to the host angiotensin-converting enzyme 2 (ACE2). In this study, we conducted molecular dynamics (MD) simulations and enzyme linked immunosorbent assay (ELISA) to explore the binding strength and mechanism of wild type (WT), Delta, and Omicron S protein trimers to ACE2. The results showed that the binding capacities of both the two variants' S protein trimers to ACE2 are enhanced in varying degrees, indicating possibly higher cell infectiousness. Energy decomposition and protein-protein interaction network analysis suggested that both the mutational and conserved sites make effects on the increase in the overall affinity through a variety of interactions. The experimentally determined KD values by biolayer interferometry (BLI) and the predicted binding free energies of the RBDs of Delta and Omicron to mAb HLX70 revealed that the two variants may have the high risk of immune evasion from the mAb. These results are not only helpful in understanding the binding strength and mechanism of S protein trimer-ACE2 but also beneficial for drug, especially for antibody development.

Predicting spike protein NTD mutations of SARS-CoV-2 causing immune evasion by molecular dynamics simulations.

The coronavirus disease 2019 (COVID-19) pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Among all the potential targets studied for developing drugs and antibodies, the spike (S) protein is the most striking one, which is on the surface of the virus. In contrast with the intensively investigated immunodominant receptor-binding domain (RBD) of the protein, little is known about the neutralizing antibody binding mechanisms of the N-terminal domain (NTD), let alone the effects of NTD mutations on antibody binding and thereby the risk of immune evasion. Based on 400 ns molecular dynamics simulation for 11 NTD-antibody complexes together with other computational approaches in this study, we investigated critical residues for NTD-antibody binding and their detailed mechanisms. The results show that 36 residues on the NTD including R246, Y144, K147, Y248, L249 and P251 are critically involved in the direct interaction of the NTD with many monoclonal antibodies (mAbs), indicating that the viruses harboring these residue mutations may have a high risk of immune evasion. Binding free energy calculations and an interaction mechanism study reveal that R246I, which is present in the Beta (B.1.351/501Y.V2) variant, may have various impacts on current NTD antibodies through abolishing the hydrogen bonds and electrostatic interaction with the antibodies or affecting other interface residues. Therefore, special attention should be paid to the mutations of these key residues in future antibody and vaccine design and development.

Competitive CatSper Activators of Progesterone from Rhynchosia volubilis.

The root Rhynchosia volubilis was widely used for contraception in folk medicine, although its molecular mechanism on antifertility has not yet been revealed. In human sperm, it was reported that the cation channel of sperm, an indispensable cation channel for the fertilization process, could be regulated by various steroid-like compounds in plants. Interestingly, these nonphysiological ligands would also disturb the activation of the cation channel of sperm induced by progesterone. Therefore, this study aimed to explore whether the compounds in R. volubilis affect the physiological regulation of the cation channel of sperm. The bioguided isolation of the whole herb of R. volubilis has resulted in the novel discovery of five new prenylated isoflavonoids, rhynchones A - E (1:  - 5: ), a new natural product, 5'-O-methylphaseolinisoflavan (6: ) (1H and 13C NMR data, Supporting Information), together with twelve known compounds (7:  - 18: ). Their structures were established by extensive spectroscopic analyses and drawing a comparison with literature data, while their absolute configurations were determined by electronic circular dichroism calculations. The experiments of intracellular Ca2+ signals and patch clamping recordings showed that rhynchone A (1: ) significantly reduced cation channel of sperm activation by competing with progesterone. In conclusion, our findings indicat that rhynchone A might act as a contraceptive compound by impairing the activation of the cation channel of sperm and thus prevent fertilization.

Parthenolide reveals an allosteric mode to inhibit the deISGylation activity of SARS-CoV­2 papain-like protease.

The coronavirus papain-like protease (PLpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for viral polypeptide cleavage and the deISGylation of interferon-stimulated gene 15 (ISG15), which enable it to participate in virus replication and host innate immune pathways. Therefore, PLpro is considered an attractive antiviral drug target. Here, we show that parthenolide, a germacrane sesquiterpene lactone, has SARS-CoV-2 PLpro inhibitory activity. Parthenolide covalently binds to Cys-191 or Cys-194 of the PLpro protein, but not the Cys-111 at the PLpro catalytic site. Mutation of Cys-191 or Cys-194 reduces the activity of PLpro. Molecular docking studies show that parthenolide may also form hydrogen bonds with Lys-192, Thr-193, and Gln-231. Furthermore, parthenolide inhibits the deISGylation but not the deubiquitinating activity of PLpro in vitro. These results reveal that parthenolide inhibits PLpro activity by allosteric regulation.

One step stereoselective synthesis of oxazoline-fused saccharides and their conversion into the corresponding 1,2-cis glycosylamines bearing various protected groups.

Herein we disclosed a straightforward synthesis of oxazoline-fused saccharides (oxazolinoses) from peracetylated saccharides and benzonitriles under acidic conditions with stoichiometric amounts of water. The density functional theory (DFT) calculations have revealed the origin of the stereoselectivity and the key role of water in promoting the departure of the acetyl group at C-2. The resulting oxazolinoses can be concisely converted into the corresponding 1,2-cis glycosylamines bearing various protected groups, allowing the access to schisandrin derivatives.

D3DistalMutation: a Database to Explore the Effect of Distal Mutations on Enzyme Activity.

Enzyme activity is affected by amino acid mutations, particularly mutations near the active site. Increasing evidence has shown that distal mutations more than 10 Å away from the active site may significantly affect enzyme activity. However, it is difficult to study the enzyme regulation mechanism of distal mutations due to the lack of a systematic collection of three-dimensional (3D) structures, highlighting distal mutation site and the corresponding enzyme activity change. Therefore, we constructed a distal mutation database, namely, D3DistalMutation, which relates the distal mutation to enzyme activity. As a result, we observed that approximately 80% of distal mutations could affect enzyme activity and 72.7% of distal mutations would decrease or abolish enzyme activity in D3DistalMutation. Only 6.6% of distal mutations in D3DistalMutation could increase enzyme activity, which have great potential to the industrial field. Among these mutations, the Y to F, S to D, and T to D mutations are most likely to increase enzyme activity, which sheds some light on industrial catalysis. Distal mutations decreasing enzyme activity in the allosteric pocket play an indispensable role in allosteric drug design. In addition, the pockets in the enzyme structures are provided to explore the enzyme regulation mechanism of distal mutations. D3DistalMutation is accessible free of charge at https://www.d3pharma.com/D3DistalMutation/index.php.

Sesquiterpenoid bilobalide inhibits gastric carcinoma cell growth and induces apoptosis both in vitro and in vivo models.

Gastric carcinoma is one of the most aggressive types of cancer that ranks fifth among all cancer incidences and third in cancer mortality. As it exhibits a prolonged asymptomatic condition and high recurrence rate, it is a great challenge to treat gastric cancer. Traditional medicine that utilizes herbal phytochemicals to treat various diseases is a potent alternative for current allopathic treatment. Hence, we evaluated the potency of a phytochemical bilobalide for treating gastric cancer in in vitro and in vivo models. Bilobalide, a sesquiterpenoid, is present in the Ginkgo biloba plant that belongs to the family of Ginkgoaceae. The cytotoxicity effect of bilobalide was evaluated in both gastric cancer (AGS) cells and normal gastric epithelial cells. Apoptosis-inducing property of bilobalide against the AGS cell line was analyzed with different fluorescent staining techniques and terminal deoxynucleotidyl transferase dUTP nick-end labeling assay, and cell cycle analysis was carried out by flow cytometry. The in vivo studies were assessed with N-methyl-N-nitrosourea (MNU)-induced gastric cancer in rats. Serum-specific gastric markers were quantified and histopathological analysis of stomach tissue was performed. The expression of target-signaling molecules was analyzed by a reverse-transcription polymerase chain reaction. The in vitro results proved that bilobalide effectively suppressed the AGS cell growth and induced cell death by nuclear damage and apoptosis induction. The bilobalide treatment effectively arrested the cell cycle of AGS cells via inhibiting the PI3K-signaling pathway. Our in vivo results also confirmed that the bilobalide persuasively inhibited the MNU-induced gastric carcinoma via inhibiting the thioredoxin-fold family proteins and inflammatory markers' expression. Overall, our results authentically prove that bilobalide possesses therapeutic potency to cure gastric carcinoma.

2Ch-2N Square Chalcogen Bonds between Pairs of Radicals: A Case Study of 1,2,3,5-Dichalcogenadiazolyl Derivatives.

Specific 2Ch-2N square interactions between pairs of heterocyclic rings have been the target of many recent crystallographic and computational studies. According to our search of the Cambridge Structural Database (CSD), a number of crystal structures of the derivatives of 1,2,3,5-dichalcogenadiazolyl (DChDA) radicals, which consist of 2Ch-2N square motifs in the dimer units, were extracted. On the basis of the CSD survey results, a set of dimeric complexes of DChDA-based radicals with diverse aryl substituents at the 4-position were selected to model such squares. Similar to that in conventional chalcogen bonds, 2Ch-2N square interactions become stronger as the atomic size of chalcogens increases. Both the orbital term and electrostatics contribute significantly to the attraction of these interactions, while the dispersion contribution is small but unneglectable. Some five-membered aryl substituents, such as imidazole, thiazole, and oxazole, produce markedly enhanced square interactions, leading to a pronounced influence on the distribution of spin populations on DChDA rings.

Structure-activity relationship and biological evaluation of 12 N-substituted aloperine derivatives as PD-L1 down-regulatory agents through proteasome pathway.

Twenty-nine 12 N-substituted aloperine derivatives were synthesized and screened for suppression on PD-L1 expression in H460 cells, as a continuation of our work. Systematic structural modifications led to the identification of compound 6b as the most active PD-L1 modulator. Compound 6b could significantly down-regulate both constitutive and inductive PD-L1 expression in NSCLC cells, and successively enhance the cytotoxicity of co-cultured T cells against tumor cells at the concentration of 20 µM. Also, it exhibited a moderate in vivo anticancer efficacy against Lewis tumor xenograft with a stable PK and safety profile. The mechanism study indicated that 6b mediated the degradation of PD-L1 through a proteasome pathway, rather than a lysosome route. These results provided the powerful information for cancer immunotherapy of aloperine derivatives with unique endocyclic skeleton by targeting PD-L1 to activate immune cells to kill cancer cells.