Benzenesulfonamide derivatives as Vibrio cholerae carbonic anhydrases inhibitors: a computational-aided insight in the structural rigidity-activity relationships.

Vibrio cholerae causes life-threatening infections in low-income countries due to the rise of antibacterial resistance. Innovative pharmacological targets have been investigated and carbonic anhydrases (CAs, EC: 4.2.1.1) encoded by V. cholerae (VchCAs) emerged as a valuable option. Recently, we developed a large library of para- and meta-benzenesulfonamides characterised by moieties with a different flexibility degree as CAs inhibitors. Stopped flow-based enzymatic assays showed strong inhibition of VchαCA for this library, while lower affinity was detected against the other isoforms. In particular, cyclic urea 9c emerged for a nanomolar inhibition of VchαCA (KI = 4.7 nM) and high selectivity with respect to human isoenzymes (SI≥ 90). Computational studies revealed the influence of moiety flexibility on inhibitory activity and isoform selectivity and allowed accurate SARs. However, although VchCAs are involved in the bacterium virulence and not in its survival, we evaluated the antibacterial activity of such compounds, resulting in no direct activity.

Molecular Networking Accelerated Discovery of Biflavonoid Alkaloids from Cephalotaxus sinensis.

Four undescribed biflavonoid alkaloids, sinenbiflavones A-D, were isolated from Cephalotaxus sinensis using a MS/MS-based molecular networking guided strategy. Their structures were elucidated by series of spectroscopic methods (HR-ESI-MS, UV, IR, 1D, and 2D NMR). Sinenbiflavones A-D are the first examples of amentoflavone-type (C-3'-C-8'') biflavonoid alkaloids. Meanwhile, sinenbiflavones B and D are the unique C-6-methylated amentoflavone-type biflavonoid alkaloids. Sinenbiflavone D showed weak SARS-CoV-2 3CLpro inhibitory activity with 43 % inhibition rate at 40 µM.

Standardizing macromolecular structure files: further efforts are needed.

Investigating large datasets of biological information by automatic procedures may offer chances of progress in knowledge. Recently, tremendous improvements in structural biology have allowed the number of structures in the Protein Data Bank (PDB) archive to increase rapidly, in particular those for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-associated proteins. However, their automatic analysis can be hampered by the nonuniform descriptors used by authors in some records of the PDB and PDBx/mmCIF files. In this opinion article we highlight the difficulties encountered in automating the analysis of hundreds of structures, suggesting that further standardization of the description of these molecular entities and of their attributes, generalized to the macromolecular structures contained in the PDB, might generate files more suitable for automatized analyses of a large number of structures.

Extending the Record of Terpenes from Soft Coral Sarcophyton mililatensis.

In the present study, a new polyoxygenated cembranoid named sarcomililatol H (1) as well as six known terpenes 2-7 with different skeletons were isolated from South China Sea soft coral Sarcophyton mililatensis. Based on the comprehensive analyses of 1D and 2D NMR spectroscopic data, the structure of the new compound 1 was established. This new cembranoid was characterized by the presence of the rarely encountered tetrahydropyran ring with the ether linkage across C-2 and C-12. By applying the time-dependent density functional theory electronic circular dichroism (TDDFT ECD) approach, the absolute configuration of sarcomililatol H (1) was determined. All of the isolates were subjected to the anti-inflammatory and anti-tumor bioassays. However, none of them was active in these evaluations. Additionally, the preliminary virtual screening of inhibitory against SARS-CoV-2 by molecular docking showed that diterpene 1 could be regarded as a SARS-CoV-2 main protease (Mpro ) inhibitor (binding energy: -7.63 kcal/mol). The discovery of these terpenes has expanded the chemical diversity and complexity of terpenes from the species S. mililatensis.

Structure-activity relationships of antibacterial peptides.

Antimicrobial peptides play a crucial role in innate immunity, whose components are mainly peptide-based molecules with antibacterial properties. Indeed, the exploration of the immune system over the past 40 years has revealed a number of natural peptides playing a pivotal role in the defence mechanisms of vertebrates and invertebrates, including amphibians, insects, and mammalians. This review provides a discussion regarding the antibacterial mechanisms of peptide-based agents and their structure-activity relationships (SARs) with the aim of describing a topic that is not yet fully explored. Some growing evidence suggests that innate immunity should be strongly considered for the development of novel antibiotic peptide-based libraries. Also, due to the constantly rising concern of antibiotic resistance, the development of new antibiotic drugs is becoming a priority of global importance. Hence, the study and the understanding of defence phenomena occurring in the immune system may inspire the development of novel antibiotic compound libraries and set the stage to overcome drug-resistant pathogens. Here, we provide an overview of the importance of peptide-based antibacterial sources, focusing on accurately selected molecular structures, their SARs including recently introduced modifications, their latest biotechnology applications, and their potential against multi-drug resistant pathogens. Last, we provide cues to describe how antibacterial peptides show a better scope of action selectivity than several anti-infective agents, which are characterized by non-selective activities and non-targeted actions toward pathogens.

Arylnaphthalene Lignans with Anti-SARS-CoV-2 and Antiproliferative Activities from the Underground Organs of Linum austriacum and Linum perenne.

Diphyllin (1) and justicidin B (2) are arylnaphthalene lignans with antiviral and antiproliferative effects. Compound 1 is also known as an effective inhibitor of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). To evaluate the in vitro antiviral and cytotoxic potency of both lignans in SARS-CoV-2 -infected cells and various cancer cell lines, respectively, 1 and 2 were isolated from the underground organs of Linum austriacum and Linum perenne. Two previously undescribed arylnaphthalene lignans, denominated linadiacin A and B (3 and 4), were also isolated and identified. In acidic media, 3 was converted by a two-step reaction into 2 via the intermediate 4. Optimum acid treatment conditions were determined to isolate lignans by one-step preparative high-performance liquid chromatography (HPLC). The results of the conversion, HPLC-tandem mass spectrometry, nuclear magnetic resonance spectroscopy, and molecular modeling studies allowed complete structure analysis. Compounds 1 and 2 were the most effective against SARS-CoV-2 with a 3-log reduction in the viral copy number at a 12.5 µM concentration. Ten human cancer cell lines showed sensitivity to at least one of the isolated lignans.

Eremoxylarins D-J, Antibacterial Eremophilane Sesquiterpenes Discovered from an Endolichenic Strain of Xylaria hypoxylon.

An endolichenic strain of the Ascomycetaceous Xylaria hypoxylon, cultivated alone or in coculture with another endolichenic fungus Dendrothyrium variisporum, produced seven new bioactive eremophilane sesquiterpenes eremoxylarins D-J (1-7). The isolated compounds disclosed a high similarity with the eremophilane core of the bioactive integric acid, and structures were elucidated by 1D and 2D NMR spectra and electronic circular dichroism (ECD) analyses. Eremoxylarins D, F, G, and I showed a selective activity against Gram-positive bacteria such as methicillin-resistant Staphylococcus aureus with minimum inhibitory concentration (MIC) values between 0.39 and 12.5 µg/mL. Eremoxylarin I, the most antibacterial active sesquiterpene, was also active against HCoV-229E at a concentration nontoxic to the hepatoma Huh-7 cell line with an 50% inhibitory concentration (IC50) of 18.1 µM and a 50% cytotoxic concentration (CC50) of 46.6 µM.

Remdesivir Metabolite GS-441524 Effectively Inhibits SARS-CoV-2 Infection in Mouse Models.

The outbreak of coronavirus disease 2019 (COVID-19) has resulted in a global pandemic due to the rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). At the time of this manuscript's publication, remdesivir is the only COVID-19 treatment approved by the United States Food and Drug Administration. However, its effectiveness is still under question due to the results of the large Solidarity Trial conducted by the World Health Organization. Herein, we report that the parent nucleoside of remdesivir, GS-441524, potently inhibits the replication of SARS-CoV-2 in Vero E6 and other cell lines. Challenge studies in both an AAV-hACE2 mouse model of SARS-CoV-2 and in mice infected with murine hepatitis virus, a closely related coronavirus, showed that GS-441524 was highly efficacious in reducing the viral titers in CoV-infected organs without notable toxicity. Our results support that GS-441524 is a promising and inexpensive drug candidate for treating of COVID-19 and other CoV diseases.

A dual graph neural network for drug-drug interactions prediction based on molecular structure and interactions.

Expressive molecular representation plays critical roles in researching drug design, while effective methods are beneficial to learning molecular representations and solving related problems in drug discovery, especially for drug-drug interactions (DDIs) prediction. Recently, a lot of work has been put forward using graph neural networks (GNNs) to forecast DDIs and learn molecular representations. However, under the current GNNs structure, the majority of approaches learn drug molecular representation from one-dimensional string or two-dimensional molecular graph structure, while the interaction information between chemical substructure remains rarely explored, and it is neglected to identify key substructures that contribute significantly to the DDIs prediction. Therefore, we proposed a dual graph neural network named DGNN-DDI to learn drug molecular features by using molecular structure and interactions. Specifically, we first designed a directed message passing neural network with substructure attention mechanism (SA-DMPNN) to adaptively extract substructures. Second, in order to improve the final features, we separated the drug-drug interactions into pairwise interactions between each drug's unique substructures. Then, the features are adopted to predict interaction probability of a DDI tuple. We evaluated DGNN-DDI on real-world dataset. Compared to state-of-the-art methods, the model improved DDIs prediction performance. We also conducted case study on existing drugs aiming to predict drug combinations that may be effective for the novel coronavirus disease 2019 (COVID-19). Moreover, the visual interpretation results proved that the DGNN-DDI was sensitive to the structure information of drugs and able to detect the key substructures for DDIs. These advantages demonstrated that the proposed method enhanced the performance and interpretation capability of DDI prediction modeling.

Integration of LC/MS, NMR and Molecular Docking for Profiling of Bioactive Diterpenes from Euphorbia mauritanica L. with in Vitro Anti-SARS-CoV-2 Activity.

In spite of tremendous efforts exerted in the management of COVID-19, the absence of specific treatments and the prevalence of delayed and long-term complications termed post-COVID syndrome still urged all concerned researchers to develop a potent inhibitor of SARS-Cov-2. The hydromethanolic extracts of different parts of E. mauritanica were in vitro screened for anti-SARS-Cov-2 activity. Then, using an integrated strategy of LC/MS/MS, molecular networking and NMR, the chemical profile of the active extract was determined. To determine the optimum target for these compounds, docking experiments of the active extract's identified compounds were conducted at several viral targets. The leaves extract showed the best inhibitory effect with IC50 8.231±0.04 µg/ml. The jatrophane diterpenes were provisionally annotated as the primary metabolites of the bioactive leaves extract based on multiplex of LC/MS/MS, molecular network, and NMR. In silico studies revealed the potentiality of the compounds in the most active extract to 3CLpro, where compound 20 showed the best binding affinity. Further attention should be paid to the isolation of various jatrophane diterpenes from Euphorbia and evaluating their effects on SARS-Cov-2 and its molecular targets.

Polyoxygenated Terpenoids and Polyketides from the Roots of Flueggea virosa and Their Inhibitory Effect against SARS-CoV-2-Induced Inflammation.

Six new polyoxygenated terpenoids, podovirosanes A-F (1-6), and two known polyketides (7 and 8) were isolated from the roots of F. virosa. Their structures, along with absolute configurations, were deduced using spectroscopic analysis as well as computational calculations, including TDDFT calculation of ECD spectra and GIAO NMR calculations combined with DP4+ probability analysis. Compounds 2, 3, 5, and 8 were found to reduce the phosphorylation levels of NF-κB p65 in SARS-CoV-2 pseudovirus-stimulated PMA-differentiated THP-1 cells.

Instruction of molecular structure similarity and scaffolds of drugs under investigation in ebola virus treatment by atom-pair and graph network: A combination of favipiravir and molnupiravir.

The virus that causes Ebola is fatal. Although many researchers have attempted to contain this deadly infection, the fatality rate remains high. The atom-pair fingerprint technique was used to compare drugs suggested for the treatment of Ebola or those that are currently being tested in clinical settings. Subsequently, using scaffold network graph (SNG) methods, the molecular and structural scaffolds of the drugs chosen based on these similar results were created, and the drug structures were examined. Public databases (PubChem and DrugBank) and literature regarding Ebola treatment were used in the analysis. Graphical representations of the molecular architecture and core structures of the drugs with the highest similarity to Food and Drug Administration (FDA)-approved drugs were produced using the SNG method. The combination of molnupiravir, the first licensed oral medication candidate for COVID-19, and favipiravir, employed in other viral outbreaks, should be further researched for treating Ebola, as observed in our study. We also believe that chemists will benefit from understanding the core structure(s) of medication molecules effective against the Ebola virus, their inhibitors, and the chemical structure similarities of existing pharmaceuticals utilized to build alternative drugs or drug combinations.

Synthesis, Crystal Structure, Theoretical Calculations, Antibacterial Activity, Electrochemical Behavior, and Molecular Docking of Ni(II) and Cu(II) Complexes with Pyridoxal-Semicarbazone.

New Ni (II) and Cu (II) complexes with pyridoxal-semicarbazone were synthesized and their structures were solved by X-ray crystallography. This analysis showed the bis-ligand octahedral structure of [Ni(PLSC-H)2]·H2O and the dimer octahedral structure of [Cu(PLSC)(SO4)(H2O)]2·2H2O. Hirshfeld surface analysis was employed to determine the most important intermolecular interactions in the crystallographic structures. The structures of both complexes were further examined using density functional theory and natural bond orbital analysis. The photocatalytic decomposition of methylene blue in the presence of both compounds was investigated. Both compounds were active toward E. coli and S. aureus, with a minimum inhibition concentration similar to that of chloramphenicol. The obtained complexes led to the formation of free radical species, as was demonstrated in an experiment with dichlorofluorescein-diacetate. It is postulated that this is the mechanistic pathway of the antibacterial and photocatalytic activities. Cyclic voltammograms of the compounds showed the peaks of the reduction of metal ions. A molecular docking study showed that the Ni(II) complex exhibited promising activity towards Janus kinase (JAK), as a potential therapy for inflammatory diseases, cancers, and immunologic disorders.

Prediction of drug-likeness using graph convolutional attention network.

MOTIVATION: The drug-likeness has been widely used as a criterion to distinguish drug-like molecules from non-drugs. Developing reliable computational methods to predict the drug-likeness of compounds is crucial to triage unpromising molecules and accelerate the drug discovery process. RESULTS: In this study, a deep learning method was developed to predict the drug-likeness based on the graph convolutional attention network (D-GCAN) directly from molecular structures. Results showed that the D-GCAN model outperformed other state-of-the-art models for drug-likeness prediction. The combination of graph convolution and attention mechanism made an important contribution to the performance of the model. Specifically, the application of the attention mechanism improved accuracy by 4.0%. The utilization of graph convolution improved the accuracy by 6.1%. Results on the dataset beyond Lipinski's rule of five space and the non-US dataset showed that the model had good versatility. Then, the billion-scale GDB-13 database was used as a case study to screen SARS-CoV-2 3C-like protease inhibitors. Sixty-five drug candidates were screened out, most substructures of which are similar to these of existing oral drugs. Candidates screened from S-GDB13 have higher similarity to existing drugs and better molecular docking performance than those from the rest of GDB-13. The screening speed on S-GDB13 is significantly faster than screening directly on GDB-13. In general, D-GCAN is a promising tool to predict the drug-likeness for selecting potential candidates and accelerating drug discovery by excluding unpromising candidates and avoiding unnecessary biological and clinical testing. AVAILABILITY AND IMPLEMENTATION: The source code, model and tutorials are available at https://github.com/JinYSun/D-GCAN. The S-GDB13 database is available at https://doi.org/10.5281/zenodo.7054367. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Structures, biomimetic synthesis, and anti-SARS-CoV-2 activity of two pairs of enantiomeric phenylpropanoid-conjugated protoberberine alkaloids from the rhizomes of Corydalis decumbens.

(±)-Decumicorine A (1) and (±)-epi-decumicorine A (2), two pairs of enantiomeric isoquinoline alkaloids featuring a novel phenylpropanoid-conjugated protoberberine skeleton, were isolated and purified from the rhizomes of Corydalis decumbens. The separation of (±)-1 and (±)-2 was achieved by chiral HPLC to produce four optically pure enantiomers. The structures and absolute configurations of compounds (-)-1, (+)-1, (-)-2, and (+)-2 were elucidated by spectroscopic analysis, ECD calculations, and X-ray crystallographic analyses. The two racemates were generated from a Diels-Alder [4 + 2] cycloaddition between jatrorrhizine and ferulic acid in the proposed biosynthetic pathways, which were fully verified by a biomimetic synthesis. Moreover, compound (+)-1 exhibited an antiviral entry effect on SARS-CoV-2 pseudovirus by blocking spike binding to the ACE2 receptor on HEK-293T-ACE2h host cells.

Development of spiro-3-indolin-2-one containing compounds of antiproliferative and anti-SARS-CoV-2 properties.

A series of 1″-(alkylsulfonyl)-dispiro[indoline-3,2'-pyrrolidine-3',3″-piperidine]-2,4″-diones 6a‒o has been synthesized through regioselective multi-component azomethine dipolar cycloaddition reaction of 1-(alkylsulfonyl)-3,5-bis(ylidene)-piperidin-4-ones 3a‒h. X-ray diffraction studies (6b‒d,h) confirmed the structures. The majority of the synthesized analogs reveal promising antiproliferation properties against a variety of human cancer cell lines (MCF7, HCT116, A431 and PaCa2) with good selectivity index towards normal cell (RPE1). Some of the synthesized agents exhibit potent inhibitory properties against the tested cell lines with higher efficacies than the standard references (sunitinib and 5-fluorouracil). Compound 6m is the most potent. Multi-targeted inhibitory properties against EGFR and VEGFR-2 have been observed for the synthesized agents. Flow cytometry supports the antiproliferation properties and shows the tested agents as apoptosis and necrosis forming. Vero cell viral infection model demonstrates the anti-SARS-CoV-2 properties of the synthesized agents. Compound 6f is the most promising (about 3.3 and 4.8 times the potency of the standard references, chloroquine and hydroxychloroquine). QSAR models explain and support the observed biological properties.

Computer-Aided and AILDE Approaches to Design Novel 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors.

4-Hydroxyphenylpyruvate dioxygenase (HPPD) is a pivotal enzyme in tocopherol and plastoquinone synthesis and a potential target for novel herbicides. Thirty-five pyridine derivatives were selected to establish a Topomer comparative molecular field analysis (Topomer CoMFA) model to obtain correlation information between HPPD inhibitory activity and the molecular structure. A credible and predictive Topomer CoMFA model was established by "split in two R-groups" cutting methods and fragment combinations (q2 = 0.703, r2 = 0.957, ONC = 6). The established model was used to screen out more active compounds and was optimized through the auto in silico ligand directing evolution (AILDE) platform to obtain potential HPPD inhibitors. Twenty-two new compounds with theoretically good HPPD inhibition were obtained by combining the high-activity contribution substituents in the existing molecules with the R-group search via Topomer search. Molecular docking results revealed that most of the 22 fresh compounds could form stable π-π interactions. The absorption, distribution, metabolism, excretion and toxicity (ADMET) prediction and drug-like properties made 9 compounds potential HPPD inhibitors. Molecular dynamics simulation indicated that Compounds Y12 and Y14 showed good root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values and stability. According to the AILDE online verification, 5 new compounds with potential HPPD inhibition were discovered as HPPD inhibitor candidates. This study provides beneficial insights for subsequent HPPD inhibitor design.

Synthesis of Sugar and Nucleoside Analogs and Evaluation of Their Anticancer and Analgesic Potentials.

Chemical modification of sugars and nucleosides has a long history of producing compounds with improved selectivity and efficacy. In this study, several modified sugars (2-3) and ribonucleoside analogs (4-8) have been synthesized from α-d-glucose in a total of 21 steps. The compounds were tested for peripheral anti-nociceptive characteristics in the acetic acid-induced writhing assay in mice, where compounds 2, 7, and 8 showed a significant reduction in the number of writhes by 56%, 62%, and 63%, respectively. The compounds were also tested for their cytotoxic potential against human HeLa cell line via trypan blue dye exclusion test followed by cell counting kit-8 (CCK-8) assay. Compound 6 demonstrated significant cytotoxic activity with an IC50 value of 54 µg/mL. Molecular docking simulations revealed that compounds 2, 7, and 8 had a comparable binding affinity to cyclooxygenase-1 (COX-1) and cyclooxygenase-2 (COX-2) enzymes. Additionally, the bridged nucleoside analogs 7 and 8 potently inhibited adenosine kinase enzyme as well, which indicates an alternate mechanistic pathway behind their anti-nociceptive action. Cytotoxic compound 6 demonstrated strong docking with cancer drug targets human cytidine deaminase, proto-oncogene tyrosine-protein kinase Src, human thymidine kinase 1, human thymidylate synthase, and human adenosine deaminase 2. This is the first ever reporting of the synthesis and analgesic property of compound 8 and the cytotoxic potential of compound 6.

Novel Thiadiazole-Based Molecules as Promising Inhibitors of Black Fungi and Pathogenic Bacteria: In Vitro Antimicrobial Evaluation and Molecular Docking Studies.

Novel 1,3,4-thiadiazole derivatives were synthesized through the reaction of methyl 2-(4-hydroxy-3-methoxybenzylidene) hydrazine-1-carbodithioate and the appropriate hydrazonoyl halides in the presence of a few drops of diisopropylethylamine. The chemical structure of the newly fabricated compounds was inferred from their microanalytical and spectral data. With the increase in microbial diseases, fungi remain a devastating threat to human health because of the resistance of microorganisms to antifungal drugs. COVID-19-associated pulmonary aspergillosis (CAPA) and COVID-19-associated mucormycosis (CAM) have higher mortality rates in many populations. The present study aimed to find new antifungal agents using the disc diffusion method, and minimal inhibitory concentration (MIC) values were estimated by the microdilution assay. An in vitro experiment of six synthesized chemical compounds exhibited antifungal activity against Rhizopus oryzae; compounds with an imidazole moiety, such as the compound 7, were documented to have energetic antibacterial, antifungal properties. As a result of these findings, this research suggests that the synthesized compounds could be an excellent choice for controlling black fungus diseases. Furthermore, a molecular docking study was achieved on the synthesized compounds, of which compounds 2, 6, and 7 showed the best interactions with the selected protein targets.

Discovery of Dipyridamole Analogues with Enhanced Metabolic Stability for the Treatment of Idiopathic Pulmonary Fibrosis.

Dipyridamole, apart from its well-known antiplatelet and phosphodiesterase inhibitory activities, is a promising old drug for the treatment of pulmonary fibrosis. However, dipyridamole shows poor pharmacokinetic properties with a half-life (T1/2) of 7 min in rat liver microsomes (RLM). To improve the metabolic stability of dipyridamole, a series of pyrimidopyrimidine derivatives have been designed with the assistance of molecular docking. Among all the twenty-four synthesized compounds, compound (S)-4h showed outstanding metabolic stability (T1/2 = 67 min) in RLM, with an IC50 of 332 nM against PDE5. Furthermore, some interesting structure-activity relationships (SAR) were explained with the assistance of molecular docking.