Abstract: Osteoarthritis (OA) and major depression (MD) are two debilitating disorders that frequently co-occur and affect millions of the elderly each year. Despite the greater symptom severity, poorer clinical outcomes, and increased mortality of the comorbid conditions, we have a limited understanding of their etiologic relationships. In this study, we conducted the first cross-disorder investigations of OA and MD, using genome-wide association data representing over 247K cases and 475K controls. Along with significant positive genome-wide genetic correlations (r g = 0.299 +/- 0.026, p = 9.10 x 10(-31)), Mendelian randomization (MR) analysis identified a bidirectional causal effect between OA and MD (betaOA --> MD = 0.09, SE = 0.02, z-score p-value < 1.02 x 10(-5); betaMD --> OA = 0.19, SE = 0.026, p < 2.67 x 10(-13)), indicating genetic variants affecting OA risk are, in part, shared with those influencing MD risk. Cross-disorder meta-analysis of OA and MD identified 56 genomic risk loci (P meta = 5 x 10(-8)), which show heightened expression of the associated genes in the brain and pituitary. Gene-set enrichment analysis highlighted "mechanosensory behavior" genes (GO:0007638; P gene_set = 2.45 x 10(-8)) as potential biological mechanisms that simultaneously increase susceptibility to these mental and physical health conditions. Taken together, these findings show that OA and MD share common genetic risk mechanisms, one of which centers on the neural response to the sensation of mechanical stimulus. Further investigation is warranted to elaborate the etiologic mechanisms of the pleiotropic risk genes, as well as to develop early intervention and integrative clinical care of these serious conditions that disproportionally affect the aging population.

Abstract: The novel coronavirus pneumonia COVID-19 infected by SARS-CoV-2 has attracted worldwide attention. It is urgent to find effective therapeutic strategies for stopping COVID-19. In this study, a Bounded Nuclear Norm Regularization (BNNR) method is developed to predict anti-SARS-CoV-2 drug candidates. First, three virus-drug association datasets are compiled. Second, a heterogeneous virus-drug network is constructed. Third, complete genomic sequences and Gaussian association profiles are integrated to compute virus similarities; chemical structures and Gaussian association profiles are integrated to calculate drug similarities. Fourth, a BNNR model based on kernel similarity (VDA-GBNNR) is proposed to predict possible anti-SARS-CoV-2 drugs. VDA-GBNNR is compared with four existing advanced methods under fivefold cross-validation. The results show that VDA-GBNNR computes better AUCs of 0.8965, 0.8562, and 0.8803 on the three datasets, respectively. There are 6 anti-SARS-CoV-2 drugs overlapping in any two datasets, that is, remdesivir, favipiravir, ribavirin, mycophenolic acid, niclosamide, and mizoribine. Molecular dockings are conducted for the 6 small molecules and the junction of SARS-CoV-2 spike protein and human angiotensin-converting enzyme 2. In particular, niclosamide and mizoribine show higher binding energy of -8.06 and -7.06 kcal/mol with the junction, respectively. G496 and K353 may be potential key residues between anti-SARS-CoV-2 drugs and the interface junction. We hope that the predicted results can contribute to the treatment of COVID-19.

Abstract: Influenza viruses cause respiratory tract infections and substantial health concerns. Infection may result in mild to severe respiratory disease associated with morbidity and some mortality. Several anti-influenza drugs are available, but these agents target viral components and are susceptible to drug resistance. There is a need for new antiviral drug strategies that include repurposing of clinically approved drugs. Drugs that target cellular machinery necessary for influenza virus replication can provide a means for inhibiting influenza virus replication. We used RNA interference screening to identify key host cell genes required for influenza replication, and then FDA-approved drugs that could be repurposed for targeting host genes. We examined the effects of Clopidogrel and Triamterene to inhibit A/WSN/33 (EC50 5.84 uM and 31.48 uM, respectively), A/CA/04/09 (EC50 6.432 uM and 3.32 uM, respectively), and B/Yamagata/16/1988 (EC50 0.28 uM and 0.11 uM, respectively) replication. Clopidogrel and Triamterene provide a druggable approach to influenza treatment across multiple strains and subtypes.

Abstract: Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging tick-borne virus that causes severe infection in humans characterized by an acute febrile illness with thrombocytopenia and hemorrhagic complications, and a mortality rate of up to 30%. Understanding on virus-host protein interactions may facilitate the identification of druggable antiviral targets. Herein, we utilized liquid chromatography-tandem mass spectrometry to characterize the SFTSV interactome in human embryonic kidney-derived permanent culture (HEK-293T) cells. We identified 445 host proteins that co-precipitated with the viral glycoprotein N, glycoprotein C, nucleoprotein, or nonstructural protein. A network of SFTSV-host protein interactions based on reduced viral fitness affected upon host factor down-regulation was then generated. Screening of the DrugBank database revealed numerous drug compounds that inhibited the prioritized host factors in this SFTSV interactome. Among these drug compounds, the clinically approved artenimol (an antimalarial) and omacetaxine mepesuccinate (a cephalotaxine) were found to exhibit anti-SFTSV activity in vitro. The higher selectivity of artenimol (71.83) than omacetaxine mepesuccinate (8.00) highlights artenimol's potential for further antiviral development. Mechanistic evaluation showed that artenimol interfered with the interaction between the SFTSV nucleoprotein and the host glucose-6-phosphate isomerase (GPI), and that omacetaxine mepesuccinate interfered with the interaction between the viral nucleoprotein with the host ribosomal protein L3 (RPL3). In summary, the novel interactomic data in this study revealed the virus-host protein interactions in SFTSV infection and facilitated the discovery of potential anti-SFTSV treatments.

Abstract: Atopic Dermatitis (AD) is a chronic and relapsing skin disease. The medications for treating AD are still limited, most of them are topical corticosteroid creams or antibiotics. The current study attempted to discover potential AD treatments by integrating a gene network and genomic analytic approaches. Herein, the Single Nucleotide Polymorphism (SNPs) associated with AD were extracted from the GWAS catalog. We identified 70 AD-associated loci, and then 94 AD risk genes were found by extending to proximal SNPs based on r(2) > 0.8 in Asian populations using HaploReg v4.1. Next, we prioritized the AD risk genes using in silico pipelines of bioinformatic analysis based on six functional annotations to identify biological AD risk genes. Finally, we expanded them according to the molecular interactions using the STRING database to find the drug target genes. Our analysis showed 27 biological AD risk genes, and they were mapped to 76 drug target genes. According to DrugBank and Therapeutic Target Database, 25 drug target genes overlapping with 53 drugs were identified. Importantly, dupilumab, which is approved for AD, was successfully identified in this bioinformatic analysis. Furthermore, ten drugs were found to be potentially useful for AD with clinical or preclinical evidence. In particular, we identified filgotinub and fedratinib, targeting gene JAK1, as potential drugs for AD. Furthermore, four monoclonal antibody drugs (lebrikizumab, tralokinumab, tocilizumab, and canakinumab) were successfully identified as promising for AD repurposing. In sum, the results showed the feasibility of gene networking and genomic information as a potential drug discovery resource.

Abstract: Background: Parkinson's disease (PD) is a common neurodegenerative disease in middle-aged and elderly people. Liuwei Dihuang (LWDH) pills have a good effect on PD, but its mechanism remains unclear. Network pharmacology is the result of integrating basic theories and research methods of medicine, biology, computer science, bioinformatics, and other disciplines, which can systematically and comprehensively reflect the mechanism of drug intervention in disease networks. Methods: The main components and targets of herbs in LWDH pills were obtained through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Its active components were screened based on absorption, distribution, metabolism, and excretion (ADME); the PD-related targets were obtained from the Genecards, OMIM, TTD, and DRUGBANK databases. We used R to take the intersection of LWDH- and PD-related targets and Cytoscape software to construct the drug-component-target network. Moreover, STRING and Cytoscape software was used to analyze protein-protein interactions (PPI), construct a PPI network, and explore potential protein functional modules in the network. The Metascape platform was used to perform KEGG pathway and GO function enrichment analyses. Finally, molecular docking was performed to verify whether the compound and target have good binding activity. Results: After screening and deduplication, 210 effective active ingredients, 204 drug targets, 4333 disease targets, and 162 drug-disease targets were obtained. We consequently constructed a drug-component-targets network and a PPI-drug-disease-targets network. The results showed that the hub components of LWDH pills were quercetin, stigmasterol, kaempferol, and beta-sitosterol; the hub targets were AKT1, VEGFA, and IL6. GO and KEGG enrichment analyses showed that these targets are involved in neuronal death, G protein-coupled amine receptor activity, reactive oxygen species metabolic processes, membrane rafts, MAPK signaling pathways, cellular senescence, and other biological processes. Molecular docking showed that the hub components were in good agreement with the hub targets. Conclusion: LWDH pills have implications for the treatment of PD since they contain several active components, target multiple ligands, and activate various pathways. The hub components possibly include quercetin, stigmasterol, kaempferol, and beta-sitosterol and act through pairing with hub targets, such as AKT1, VEGFA, and IL6, to regulate neuronal death, G protein-coupled amine receptor activity, reactive oxygen species metabolic process, membrane raft, MAPK signaling pathway, and cellular senescence for the treatment of PD.

Abstract: Objectives: To estimate the frequency of manipulations of all tablets and capsules prescribed for children in a teaching and tertiary children's hospital in China over the course of 1 month. Moreover, hypothetical reduction of manipulation according to the availability of low-strength tablets/capsules licensed by the Chinese National Medical Products Administration (CNMPA) was evaluated. Methods: Information on all tablets and capsules prescribed in the hospital from March 17 to April 16, 2019 was collected. It was assumed that tablets or capsules were manipulated if the prescribed dose would have required only a proportion of the intact dose form. Manipulation typically includes splitting or crushing tablets, opening capsules and dispersing in water, or combinations of these method. Moreover, we defined an "avoidable manipulation," when the dose could be rounded and/or when alternative products with a reduced strength or in liquid formulation were available in the hospital, and a "inappropriate manipulation," which involved manipulated medications with a direct contraindication for any manipulation, such as those with a narrow therapeutic index or hazardous ingredients, or modified release dosage-forms. The frequencies of total, avoidable, and inappropriate manipulation were estimated, along with the hypothetical reduction of manipulation according to the availability of CNMPA-approved drug doses. Results: A total of 17,123 prescriptions for 142 medications were identified to have required a manipulation among 78,366 prescriptions administered during the study period, with 43 different proportions of subdivisions, ranging from a 19/20 to 1/180 product strength reduction. Half, quarter, and trisection were the most common subdivisions administered. Overall, 19% of the manipulated prescriptions were determined to be avoidable, and 19% of the manipulations involved medications with a clear recommendation to not manipulate. In addition, 21% of the manipulated prescriptions could have been potentially avoided if all of the approved preparations with the lowest strength would have been available at the hospital. Any manipulations undertaken were carried out by pharmacists and family care givers. Conclusions: More than 20% of tablets and capsules prescriptions need manipulated, included a high incidence of avoidable and inappropriate manipulation.

Abstract: The emergence of drug resistance against the known hookworm drugs namely albendazole and mebendazole and their reduced efficacies necessitate the need for new drugs. Chemically diverse natural products present plausible templates to augment hookworm drug discovery. The present work utilized pharmacoinformatics techniques to predict African natural compounds ZINC95486082, ZINC95486052 and euphohelionon as potential inhibitory molecules of the hookworm Necator americanus beta tubulin gene. A library of 3390 compounds was screened against a homology-modelled structure of beta tubulin. The docking results obtained from AutoDock Vina was validated with an acceptable area under the curve (AUC) of 0.714 computed from the receiver operating characteristic (ROC) curve. The three selected compounds had favourable binding affinities and were predicted to form no interactions with the resistance-associated mutations Phe167, Glu198 and Phe200. The compounds were predicted as anthelmintics using a Bayesian-based technique and were pharmacologically profiled to be druglike. Further molecular dynamics simulations and MM-PBSA calculations showed the compounds as promising anthelmintic drug leads. Novel critical residues comprising Leu246, Asn247 and Asn256 were also predicted for binding. Euphohelionon was selected as a template for the de novo fragment-based design of five compounds labelled A1, A2, A3, A4 and A5; with four of them having SAscore values below 6, denoting easy synthesis. All the five de novo molecules docked firmly in the binding pocket of the beta tubulin with no binding interactions with the three known resistance mutation residues. Binding energies of -8.2, -7.6, -7.3, -7.2 and -6.8 kcal/mol were obtained for A1, A2, A3, A4 and A5, respectively. The identified compounds can serve as treasure troves from which future potent anthelmintics can be designed. The current study strives to assuage the hookworm disease burden, especially making available molecules with the potential to circumvent the chemoresistance.

Abstract: Methods: Individualized treatment of traditional Chinese medicine (TCM) provides a theoretical basis for the study of the personalized classification of complex diseases. Utilizing the TCM clinical electronic medical records (EMRs) of 7170 in patients with IS, a patient similarity network (PSN) with shared symptoms was constructed. Next, patient subgroups were identified using community detection methods and enrichment analyses were performed. Finally, genetic data of symptoms, herbs, and drugs were used for pathway and GO analysis to explore the characteristics of pathways of subgroups and to compare the similarities and differences in genetic pathways of herbs and drugs from the perspective of molecular pathways of symptoms. Results: We identified 34 patient modules from the PSN, of which 7 modules include 98.48% of the whole cases. The 7 patient subgroups have their own characteristics of risk factors, complications, and comorbidities and the underlying genetic pathways of symptoms, drugs, and herbs. Each subgroup has the largest number of herb pathways. For specific symptom pathways, the number of herb pathways is more than that of drugs. Conclusion: The research of disease classification based on community detection of symptom-shared patient networks is practical; the common molecular pathway of symptoms and herbs reflects the rationality of TCM herbs on symptoms and the wide range of therapeutic targets.

Abstract: Objectives: Our ex vivo study was designed to determine the sequestration of teicoplanin, tigecycline, micafungin, meropenem, polymyxin B, caspofungin, cefoperazone sulbactam, and voriconazole in extracorporeal membrane oxygenation (ECMO) circuits. Methods: Simulated closed-loop ECMO circuits were prepared using 2 types of blood-primed ECMO. After the circulation was stabilized, the study drugs were injected into the circuit. Blood samples were collected at 2, 5, 15, 30 min, 1, 3, 6, 12, and 24 h after injection. Drug concentrations were measured by high-performance liquid chromatography-tandem mass spectrometry. Control groups were stored at 4 degrees C after 3, 6, 12, and 24 h immersing in a water bath at 37 degrees C to observe spontaneous drug degradation. Results: Twenty-six samples were analyzed. The average drug recoveries from the ECMO circuits and control groups at 24 h relative to baseline were 67 and 89% for teicoplanin, 100 and 145% for tigecycline, 67 and 99% for micafungin, 45 and 75% for meropenem, 62 and 60% for polymyxin B, 83 and 85% for caspofungin, 79 and 98% for cefoperazone, 75 and 87% for sulbactam, and 60 and 101% for voriconazole, respectively. Simple linear regression showed no significant correlation between lipophilicity (r (2) = 0.008, P = 0.225) or the protein binding rate (r (2) = 0.168, P = 0.479) of drugs and the extent of drug loss in the ECMO circuits. Conclusions: In the two ECMO circuits, meropenem and voriconazole were significantly lost, cefoperazone was slightly lost, while tigecycline and caspofungin were not lost. Drugs with high lipophilicity were lost more in the Maquet circuit than in the Sorin circuit. This study needs more in vivo studies with larger samples for further confirmation, and it suggests that therapeutic drug concentration monitoring should be strongly considered during ECMO.