The G protein database, GproteinDb.

Two-thirds of signaling substances, several sensory stimuli and over one-third of drugs act via receptors coupling to G proteins. Here, we present an online platform for G protein research with reference data and tools for analysis, visualization and design of scientific studies across disciplines and areas. This platform may help translate new pharmacological, structural and genomic data into insights on G protein signaling vital for human physiology and medicine. The G protein database is accessible at https://gproteindb.org.

Massively parallel characterization of CYP2C9 variant enzyme activity and abundance.

CYP2C9 encodes a cytochrome P450 enzyme responsible for metabolizing up to 15% of small molecule drugs, and CYP2C9 variants can alter the safety and efficacy of these therapeutics. In particular, the anti-coagulant warfarin is prescribed to over 15 million people annually and polymorphisms in CYP2C9 can affect individual drug response and lead to an increased risk of hemorrhage. We developed click-seq, a pooled yeast-based activity assay, to test thousands of variants. Using click-seq, we measured the activity of 6,142 missense variants in yeast. We also measured the steady-state cellular abundance of 6,370 missense variants in a human cell line by using variant abundance by massively parallel sequencing (VAMP-seq). These data revealed that almost two-thirds of CYP2C9 variants showed decreased activity and that protein abundance accounted for half of the variation in CYP2C9 function. We also measured activity scores for 319 previously unannotated human variants, many of which may have clinical relevance.

High-content, targeted RNA-seq screening in organoids for drug discovery in colorectal cancer.

Organoids allow the recapitulation of intestinal homeostasis and cancerogenesis in vitro; however, RNA sequencing (RNA-seq)-based methods for drug screens are missing. We develop targeted organoid sequencing (TORNADO-seq), a high-throughput, high-content drug discovery platform that uses targeted RNA-seq to monitor the expression of large gene signatures for the detailed evaluation of cellular phenotypes in organoids. TORNADO-seq is a fast, highly reproducible time- and cost-effective ($5 per sample) method that can probe cell mixtures and their differentiation state in the intestinal system. We apply this method to isolate drugs that enrich for differentiated cell phenotypes and show that these drugs are highly efficacious against cancer compared to wild-type organoids. Furthermore, TORNADO-seq facilitates in-depth insight into the mode of action of these drugs. Our technology can easily be adapted to many other systems and will allow for more systematic, large-scale, and quantitative approaches to study the biology of complex cellular systems.

Development of a High-Throughput Screening Assay to Identify Inhibitors of the SARS-CoV-2 Guanine-N7-Methyltransferase Using RapidFire Mass Spectrometry.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) represents a significant threat to human health. Despite its similarity to related coronaviruses, there are currently no specific treatments for COVID-19 infection, and therefore there is an urgent need to develop therapies for this and future coronavirus outbreaks. Formation of the cap at the 5' end of viral RNA has been shown to help coronaviruses evade host defenses. Nonstructural protein 14 (nsp14) is responsible for N7-methylation of the cap guanosine in coronaviruses. This enzyme is highly conserved among coronaviruses and is a bifunctional protein with both N7-methyltransferase and 3'-5' exonuclease activities that distinguish nsp14 from its human equivalent. Mutational analysis of SARS-CoV nsp14 highlighted its role in viral replication and translation efficiency of the viral genome. In this paper, we describe the characterization and development of a high-throughput assay for nsp14 utilizing RapidFire technology. The assay has been used to screen a library of 1771 Food and Drug Administration (FDA)-approved drugs. From this, we have validated nitazoxanide as a selective inhibitor of the methyltransferase activity of nsp14. Although modestly active, this compound could serve as a starting point for further optimization.

Machine learning identifies candidates for drug repurposing in Alzheimer's disease.

Clinical trials of novel therapeutics for Alzheimer's Disease (AD) have consumed a large amount of time and resources with largely negative results. Repurposing drugs already approved by the Food and Drug Administration (FDA) for another indication is a more rapid and less expensive option. We present DRIAD (Drug Repurposing In AD), a machine learning framework that quantifies potential associations between the pathology of AD severity (the Braak stage) and molecular mechanisms as encoded in lists of gene names. DRIAD is applied to lists of genes arising from perturbations in differentiated human neural cell cultures by 80 FDA-approved and clinically tested drugs, producing a ranked list of possible repurposing candidates. Top-scoring drugs are inspected for common trends among their targets. We propose that the DRIAD method can be used to nominate drugs that, after additional validation and identification of relevant pharmacodynamic biomarker(s), could be readily evaluated in a clinical trial.

[Relationship between the number of prescribed medications and oral dysfunction in elderly individuals].

Objective　Polypharmacy in elderly individuals may cause reduced flow of saliva and xerostomia. A dry mouth can lead to poor oral function; however, there are no reports on the relationship between polypharmacy and subjective or objective oral dysfunction. The purpose of this study was to clarify the relationship between the number of prescribed medications and subjective and objective oral dysfunction.Methods　The subjects of this study were 215 community-dwelling, elderly individuals, aged 75 years or older, who visited the dental clinic in the Chubu region for a dental health examination from January to February 2019. A medical interview was conducted to assess three items that were related to subjective oral function and record four measurements related to objective oral function. In addition, information was collected on the diseases being treated and prescribed medications. A subject with a decrease in any of the three subjective oral function categories was considered to have subjective oral dysfunction. Objective oral dysfunction was analyzed with respect to two types of oral dysfunction: a decrease in all four objective oral functions and a decrease in two or more of the four objective oral functions. Logistic regression analysis was performed to examine the relationship between subjective and objective oral dysfunction after adjustment for sex, age group, inveterate disease, and the number of prescribed medications.Results　Individuals who had eight or more prescribed medications had lower subjective oral function than those with seven or fewer medications (odds ratio, 95% confidence interval: 2.3, 1.0-5.1; P<0.05). Individuals with eight or more medications had lower scores in all four objective oral functions than those with seven or fewer medications (4.4 : 1.5-12.6, P<0.01). A decrease in two or more of the four objective oral functions was related to 10 or more prescribed medications (4.3 : 1.2-16.2, P<0.05).　In addition, taking eight or more prescribed medications was associated with a decrease in either subjective oral function or all four objective oral functions (8.1 : 2.1-30.8, P<0.01). A decrease in either subjective oral function or two or more objective oral functions was related to taking 10 or more prescribed medications (4.9 : 1.6-15.6, P<0.01).Conclusion　In conclusion, more than eight prescribed pharmaceutical medications in the elderly is associated with subjective or objective oral dysfunction.

Comparative Toxicogenomics Database (CTD): update 2021.

The public Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) is an innovative digital ecosystem that relates toxicological information for chemicals, genes, phenotypes, diseases, and exposures to advance understanding about human health. Literature-based, manually curated interactions are integrated to create a knowledgebase that harmonizes cross-species heterogeneous data for chemical exposures and their biological repercussions. In this biennial update, we report a 20% increase in CTD curated content and now provide 45 million toxicogenomic relationships for over 16 300 chemicals, 51 300 genes, 5500 phenotypes, 7200 diseases and 163 000 exposure events, from 600 comparative species. Furthermore, we increase the functionality of chemical-phenotype content with new data-tabs on CTD Disease pages (to help fill in knowledge gaps for environmental health) and new phenotype search parameters (for Batch Query and Venn analysis tools). As well, we introduce new CTD Anatomy pages that allow users to uniquely explore and analyze chemical-phenotype interactions from an anatomical perspective. Finally, we have enhanced CTD Chemical pages with new literature-based chemical synonyms (to improve querying) and added 1600 amino acid-based compounds (to increase chemical landscape). Together, these updates continue to augment CTD as a powerful resource for generating testable hypotheses about the etiologies and molecular mechanisms underlying environmentally influenced diseases.

CovalentInDB: a comprehensive database facilitating the discovery of covalent inhibitors.

Inhibitors that form covalent bonds with their targets have traditionally been considered highly adventurous due to their potential off-target effects and toxicity concerns. However, with the clinical validation and approval of many covalent inhibitors during the past decade, design and discovery of novel covalent inhibitors have attracted increasing attention. A large amount of scattered experimental data for covalent inhibitors have been reported, but a resource by integrating the experimental information for covalent inhibitor discovery is still lacking. In this study, we presented Covalent Inhibitor Database (CovalentInDB), the largest online database that provides the structural information and experimental data for covalent inhibitors. CovalentInDB contains 4511 covalent inhibitors (including 68 approved drugs) with 57 different reactive warheads for 280 protein targets. The crystal structures of some of the proteins bound with a covalent inhibitor are provided to visualize the protein-ligand interactions around the binding site. Each covalent inhibitor is annotated with the structure, warhead, experimental bioactivity, physicochemical properties, etc. Moreover, CovalentInDB provides the covalent reaction mechanism and the corresponding experimental verification methods for each inhibitor towards its target. High-quality datasets are downloadable for users to evaluate and develop computational methods for covalent drug design. CovalentInDB is freely accessible at http://cadd.zju.edu.cn/cidb/.

Global Substance Registration System: consistent scientific descriptions for substances related to health.

The US Food and Drug Administration (FDA) and the National Center for Advancing Translational Sciences (NCATS) have collaborated to publish rigorous scientific descriptions of substances relevant to regulated products. The FDA has adopted the global ISO 11238 data standard for the identification of substances in medicinal products and has populated a database to organize the agency's regulatory submissions and marketed products data. NCATS has worked with FDA to develop the Global Substance Registration System (GSRS) and produce a non-proprietary version of the database for public benefit. In 2019, more than half of all new drugs in clinical development were proteins, nucleic acid therapeutics, polymer products, structurally diverse natural products or cellular therapies. While multiple databases of small molecule chemical structures are available, this resource is unique in its application of regulatory standards for the identification of medicinal substances and its robust support for other substances in addition to small molecules. This public, manually curated dataset provides unique ingredient identifiers (UNIIs) and detailed descriptions for over 100 000 substances that are particularly relevant to medicine and translational research. The dataset can be accessed and queried at https://gsrs.ncats.nih.gov/app/substances.

Docking Paradigm in Drug Design.

Docking is in demand for the rational computer aided structure based drug design. A review of docking methods and programs is presented. Different types of docking programs are described. They include docking of non-covalent small ligands, protein-protein docking, supercomputer docking, quantum docking, the new generation of docking programs and the application of docking for covalent inhibitors discovery. Taking into account the threat of COVID-19, we present here a short review of docking applications to the discovery of inhibitors of SARS-CoV and SARS-CoV-2 target proteins, including our own result of the search for inhibitors of SARS-CoV-2 main protease using docking and quantum chemical post-processing. The conclusion is made that docking is extremely important in the fight against COVID-19 during the process of development of antivirus drugs having a direct action on SARS-CoV-2 target proteins.

Integration of the Drug-Gene Interaction Database (DGIdb 4.0) with open crowdsource efforts.

The Drug-Gene Interaction Database (DGIdb, www.dgidb.org) is a web resource that provides information on drug-gene interactions and druggable genes from publications, databases, and other web-based sources. Drug, gene, and interaction data are normalized and merged into conceptual groups. The information contained in this resource is available to users through a straightforward search interface, an application programming interface (API), and TSV data downloads. DGIdb 4.0 is the latest major version release of this database. A primary focus of this update was integration with crowdsourced efforts, leveraging the Drug Target Commons for community-contributed interaction data, Wikidata to facilitate term normalization, and export to NDEx for drug-gene interaction network representations. Seven new sources have been added since the last major version release, bringing the total number of sources included to 41. Of the previously aggregated sources, 15 have been updated. DGIdb 4.0 also includes improvements to the process of drug normalization and grouping of imported sources. Other notable updates include the introduction of a more sophisticated Query Score for interaction search results, an updated Interaction Score, the inclusion of interaction directionality, and several additional improvements to search features, data releases, licensing documentation and the application framework.

Inhibition of the ß-carbonic anhydrase from the protozoan pathogen Trichomonas vaginalis with sulphonamides.

Sulphonamides and their isosteres are classical inhibitors of the carbonic anhydrase (CAs, EC 4.2.1.1) metalloenzymes. The protozoan pathogen Trichomonas vaginalis encodes two such enzymes belonging to the ß-class, TvaCA1 and TvaCA2. Here we report the first sulphonamide inhibition study of TvaCA1, with a series of simple aromatic/heterocyclic primary sulphonamides as well as with clinically approved/investigational drugs for a range of pathologies (diuretics, antiglaucoma, antiepileptic, antiobesity, and antitumor drugs). TvaCA1 was effectively inhibited by acetazolamide and ethoxzolamide, with KIs of 391 and 283 nM, respectively, whereas many other simple or clinically used sulphonamides were micromolar inhibitors or did not efficiently inhibit the enzyme. Finding more effective TvaCA1 inhibitors may constitute an innovative approach for fighting trichomoniasis, a sexually transmitted infection, caused by T. vaginalis.

DrugSpaceX: a large screenable and synthetically tractable database extending drug space.

One of the most prominent topics in drug discovery is efficient exploration of the vast drug-like chemical space to find synthesizable and novel chemical structures with desired biological properties. To address this challenge, we created the DrugSpaceX (https://drugspacex.simm.ac.cn/) database based on expert-defined transformations of approved drug molecules. The current version of DrugSpaceX contains >100 million transformed chemical products for virtual screening, with outstanding characteristics in terms of structural novelty, diversity and large three-dimensional chemical space coverage. To illustrate its practical application in drug discovery, we used a case study of discoidin domain receptor 1 (DDR1), a kinase target implicated in fibrosis and other diseases, to show DrugSpaceX performing a quick search of initial hit compounds. Additionally, for ligand identification and optimization purposes, DrugSpaceX also provides several subsets for download, including a 10% diversity subset, an extended drug-like subset, a drug-like subset, a lead-like subset, and a fragment-like subset. In addition to chemical properties and transformation instructions, DrugSpaceX can locate the position of transformation, which will enable medicinal chemists to easily integrate strategy planning and protection design.

ConjuPepDB: a database of peptide-drug conjugates.

Peptide-drug conjugates are organic molecules composed of (i) a small drug molecule, (ii) a peptide and (iii) a linker. The drug molecule is mandatory for the biological action, however, its efficacy can be enhanced by targeted delivery, which often also reduces unwanted side effects. For site-specificity the peptide part is mainly responsible. The linker attaches chemically the drug to the peptide, but it could also be biodegradable which ensures controlled liberation of the small drug. Despite the importance of the field, there is no public comprehensive database on these species. Herein we describe ConjuPepBD, a freely available, fully annotated and manually curated database of peptide drug conjugates. ConjuPepDB contains basic information about the entries, e.g. CAS number. Furthermore, it also implies their biomedical application and the type of chemical conjugation employed. It covers more than 1600 conjugates from ∼230 publications. The web-interface is user-friendly, intuitive, and useable on several devices, e.g. phones, tablets, PCs. The webpage allows the user to search for content using numerous criteria, chemical structure and a help page is also provided. Besides giving quick insight for newcomers, ConjuPepDB is hoped to be also helpful for researchers from various related fields. The database is accessible at: https://conjupepdb.ttk.hu/.

Historical Evolution and Provider Awareness of Inactive Ingredients in Oral Medications.

PURPOSE: A multitude of different versions of the same medication with different inactive ingredients are currently available. It has not been quantified how this has evolved historically. Furthermore, it is unknown whether healthcare professionals consider the inactive ingredient portion when prescribing medications to patients. METHODS: We used data mining to track the number of available formulations for the same medication over time and correlate the number of available versions in 2019 to the number of manufacturers, the years since first approval, and the number of prescriptions. A focused survey among healthcare professionals was conducted to query their consideration of the inactive ingredient portion of a medication when writing prescriptions. RESULTS: The number of available versions of a single medication have dramatically increased in the last 40 years. The number of available, different versions of medications are largely determined by the number of manufacturers producing this medication. Healthcare providers commonly do not consider the inactive ingredient portion when prescribing a medication. CONCLUSIONS: A multitude of available versions of the same medications provides a potentially under-recognized opportunity to prescribe the most suitable formulation to a patient as a step towards personalized medicine and mitigate potential adverse events from inactive ingredients.

Student Pharmacists' Ability to Organize Complex Medication Regimens According to the Universal Medication Schedule.

Objective. To assess student pharmacists' ability to impact the administration of complex prescription regimens using the universal medication schedule in a standardized laboratory exercise. Methods. First and third professional year (P1 and P3) student pharmacists at three colleges of pharmacy completed a required activity to simplify and organize a complex medication regimen. Using a medication box, students planned how and when they would advise a patient to take seven fictitious medications over a 24-hour period. Picture documentation of each students' activity was used for data analysis. Descriptive statistics were used to compare P1 and P3 students' performance, and an independent t test was used to assess the frequency of daily dosing. A chi-square analysis was used to compare differences between P1 and P3 students, and analysis of variance was used to compare differences among individual institutions. Results. Of 842 students invited, 459 P1 and 372 P3 students (98.7%) consented to participate. Student pharmacists recommended 5.1 (SD=1.0; Range=3-11) dosing intervals per 24 hours, with 27% of students successfully reducing the regimen to four total intervals. The P3 students were more effective than the P1 students in planning the number of dosing intervals (4.9 vs 5.4 per 24 hours). Conclusion. Student pharmacists may become more effective at organizing complex medication regimens as they proceed through the pharmacy curriculum and gain experience. Student pharmacists can translate what they learned from this exercise to potentially improve patients' self-organized medication regimens.

Retrospective survey of compounded medications for children in Japan.

Compounding of medications, such as crushing tablets and dispersing the contents of capsules, is a common practice in pharmacies and hospitals worldwide and is often done to provide age-appropriate formulations for oral use in pediatric patients. In the present study, a retrospective, descriptive, questionnaire-based survey was conducted to clarify the current status of drug compounding for pediatric patients in Japan. An electronic questionnaire was distributed to 740 hospitals in Japan with pediatric beds, and 208 (28.1%) of these hospitals responded. The total instances of compounding numbered 14,864 (9.6% of the total pediatric oral prescriptions) and comprised 266 active pharmaceutical ingredients (APIs), one-third of which (98 APIs) were compounded even though flexible dosage forms were available. The three most frequently compounded drugs were dantrolene sodium capsules (1152 prescriptions), ramelteon tablets (726 prescriptions), and hydrocortisone tablets (652 prescriptions), all of which were prescribed and administered in powder form. Although compounding of medications frequently varied by the patients' age, steroids such as prednisolone, dexamethasone, and hydrocortisone were commonly compounded in all age groups. To ensure the quality and safety of these compounded medications, developing a standard protocol for compounding methods is urgently needed in Japan.

Vitamin B12 may inhibit RNA-dependent-RNA polymerase activity of nsp12 from the SARS-CoV-2 virus.

SARS-CoV-2 is the causative agent for the ongoing COVID19 pandemic, and this virus belongs to the Coronaviridae family. Like other members of this family, the virus possesses a positive-sense single-stranded RNA genome. The genome encodes for the nsp12 protein, which houses the RNA-dependent-RNA polymerase (RdRP) activity responsible for the replication of the viral genome. A homology model of nsp12 was prepared using the structure of the SARS nsp12 (6NUR) as a model. The model was used to carry out in silico screening to identify molecules among natural products, or Food and Drug Administration-approved drugs that can potentially inhibit the activity of nsp12. This exercise showed that vitamin B12 (methylcobalamin) may bind to the active site of the nsp12 protein. A model of the nsp12 in complex with substrate RNA and incoming NTP showed that vitamin B12 binding site overlaps with that of the incoming nucleotide. A comparison of the calculated energies of binding for RNA plus NTP and methylcobalamin suggested that the vitamin may bind to the active site of nsp12 with significant affinity. It is, therefore, possible that methylcobalamin binding may prevent association with RNA and NTP and thus inhibit the RdRP activity of nsp12. Overall, our computational studies suggest that methylcobalamin form of vitamin B12 may serve as an effective inhibitor of the nsp12 protein.

A New Data Repository for Pharmacokinetic Natural Product-Drug Interactions: From Chemical Characterization to Clinical Studies.

There are many gaps in scientific knowledge about the clinical significance of pharmacokinetic natural product-drug interactions (NPDIs) in which the natural product (NP) is the precipitant and a conventional drug is the object. The National Center for Complimentary and Integrative Health created the Center of Excellence for NPDI Research (NaPDI Center) (www.napdi.org) to provide leadership and guidance on the study of pharmacokinetic NPDIs. A key contribution of the Center is the first user-friendly online repository that stores and links pharmacokinetic NPDI data across chemical characterization, metabolomics analyses, and pharmacokinetic in vitro and clinical experiments (repo.napdi.org). The design is expected to help researchers more easily arrive at a complete understanding of pharmacokinetic NPDI research on a particular NP. The repository will also facilitate multidisciplinary collaborations, as the repository links all of the experimental data for a given NP across the study types. The current work describes the design of the repository, standard operating procedures used to enter data, and pharmacokinetic NPDI data that have been entered to date. To illustrate the usefulness of the NaPDI Center repository, more details on two high-priority NPs, cannabis and kratom, are provided as case studies. SIGNIFICANCE STATEMENT: The data and knowledge resulting from natural product-drug interaction (NPDI) studies is distributed across a variety of information sources, rendering difficulties to find, access, and reuse. The Center of Excellence for NPDI Research addressed these difficulties by developing the first user-friendly online repository that stores data from in vitro and clinical pharmacokinetic NPDI experiments and links them with study data from chemical characterization and metabolomics analyses of natural products that are also stored in the repository.