SARS-CoV-2 is a novel coronavirus responsible for the COVID-19 pandemic, in which acute respiratory infections are associated with high socio-economic burden. We applied high-content screening to a ...well-defined collection of 5632 compounds including 3488 that have undergone previous clinical investigations across 600 indications. The compounds were screened by microscopy for their ability to inhibit SARS-CoV-2 cytopathicity in the human epithelial colorectal adenocarcinoma cell line, Caco-2. The primary screen identified 258 hits that inhibited cytopathicity by more than 75%, most of which were not previously known to be active against SARS-CoV-2 in vitro. These compounds were tested in an eight-point dose response screen using the same image-based cytopathicity readout. For the 67 most active molecules, cytotoxicity data were generated to confirm activity against SARS-CoV-2. We verified the ability of known inhibitors camostat, nafamostat, lopinavir, mefloquine, papaverine and cetylpyridinium to reduce the cytopathic effects of SARS-CoV-2, providing confidence in the validity of the assay. The high-content screening data are suitable for reanalysis across numerous drug classes and indications and may yield additional insights into SARS-CoV-2 mechanisms and potential therapeutic strategies.
After almost two years from its first evidence, the COVID-19 pandemic continues to afflict people worldwide, highlighting the need for multiple antiviral strategies. SARS-CoV-2 main protease ...(Mpro/3CLpro) is a recognized promising target for the development of effective drugs. Because single target inhibition might not be sufficient to block SARS-CoV-2 infection and replication, multi enzymatic-based therapies may provide a better strategy. Here we present a structural and biochemical characterization of the binding mode of MG-132 to both the main protease of SARS-CoV-2, and to the human Cathepsin-L, suggesting thus an interesting scaffold for the development of double-inhibitors. X-ray diffraction data show that MG-132 well fits into the Mpro active site, forming a covalent bond with Cys145 independently from reducing agents and crystallization conditions. Docking of MG-132 into Cathepsin-L well-matches with a covalent binding to the catalytic cysteine. Accordingly, MG-132 inhibits Cathepsin-L with nanomolar potency and reversibly inhibits Mpro with micromolar potency, but with a prolonged residency time. We compared the apo and MG-132-inhibited structures of Mpro solved in different space groups and we identified a new apo structure that features several similarities with the inhibited ones, offering interesting perspectives for future drug design and in silico efforts.
Diminished sense of smell impairs the quality of life but olfactorily disabled people are hardly considered in measures of disability inclusion. We aimed to stratify perceptual characteristics and ...odors according to the extent to which they are perceived differently with reduced sense of smell, as a possible basis for creating olfactory experiences that are enjoyed in a similar way by subjects with normal or impaired olfactory function. In 146 subjects with normal or reduced olfactory function, perceptual characteristics (edibility, intensity, irritation, temperature, familiarity, hedonics, painfulness) were tested for four sets of 10 different odors each. Data were analyzed with (i) a projection based on principal component analysis and (ii) the training of a machine-learning algorithm in a 1000-fold cross-validated setting to distinguish between olfactory diagnosis based on odor property ratings. Both analytical approaches identified perceived intensity and familiarity with the odor as discriminating characteristics between olfactory diagnoses, while evoked pain sensation and perceived temperature were not discriminating, followed by edibility. Two disjoint sets of odors were identified, i.e., d = 4 "discriminating odors" with respect to olfactory diagnosis, including cis-3-hexenol, methyl salicylate, 1-butanol and cineole, and d = 7 "non-discriminating odors", including benzyl acetate, heptanal, 4-ethyl-octanoic acid, methional, isobutyric acid, 4-decanolide and p-cresol. Different weightings of the perceptual properties of odors with normal or reduced sense of smell indicate possibilities to create sensory experiences such as food, meals or scents that by emphasizing trigeminal perceptions can be enjoyed by both normosmic and hyposmic individuals.
In June 2022, EU-OS came to the decision to make public a solubility data set of 100+K compounds obtained from several of the EU-OS proprietary screening compound collections. Leveraging on the ...interest of SLAS for screening scientific development it was decided to launch a joint EUOS-SLAS competition within the chemoinformatics and machine learning (ML) communities. The competition was open to real world computation experts, for the best, most predictive, classification model of compound solubility. The aim of the competition was multiple: from a practical side, the winning model should then serve as a cornerstone for future solubility predictions having used the largest training set so far publicly available. From a higher project perspective, the intent was to focus the energies and experiences, even if professionally not precisely coming from Pharma R&D; to address the issue of how to predict compound solubility. Here we report how the competition was ideated and the practical aspects of conducting it within the Kaggle framework, leveraging of the versatility and the open-source nature of this data science platform. Consideration on results and challenges encountered have been also examined.
To improve current methods for the decomposition of molecules into fragments, we compiled a new and more elaborate set of rules for the breaking of retrosynthetically interesting chemical ...substructures (BRICS). We also incorporated further medicinal chemistry concepts and compiled differently sized sets of diverse high‐quality fragments. Relative to existing methods, BRICS performs much better in retrieving compounds from various large and diverse query sets.
Compound repurposing is an important strategy for the identification of effective treatment options against SARS-CoV-2 infection and COVID-19 disease. In this regard, SARS-CoV-2 main protease ...(3CL-Pro), also termed M-Pro, is an attractive drug target as it plays a central role in viral replication by processing the viral polyproteins pp1a and pp1ab at multiple distinct cleavage sites. We here report the results of a repurposing program involving 8.7 K compounds containing marketed drugs, clinical and preclinical candidates, and small molecules regarded as safe in humans. We confirmed previously reported inhibitors of 3CL-Pro and have identified 62 additional compounds with IC50 values below 1 μM and profiled their selectivity toward chymotrypsin and 3CL-Pro from the Middle East respiratory syndrome virus. A subset of eight inhibitors showed anticytopathic effect in a Vero-E6 cell line, and the compounds thioguanosine and MG-132 were analyzed for their predicted binding characteristics to SARS-CoV-2 3CL-Pro. The X-ray crystal structure of the complex of myricetin and SARS-Cov-2 3CL-Pro was solved at a resolution of 1.77 Å, showing that myricetin is covalently bound to the catalytic Cys145 and therefore inhibiting its enzymatic activity.
The Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2) has continuously evolved, resulting in the emergence of several variants of concern (VOCs). To study mechanisms of viral entry ...and potentially identify specific inhibitors, we pseudotyped lentiviral vectors with different SARS-CoV-2 VOC spike variants (D614G, Alpha, Beta, Delta, Omicron/BA.1), responsible for receptor binding and membrane fusion. These SARS-CoV-2 lentiviral pseudoviruses were applied to screen 774 FDA-approved drugs. For the assay we decided to use CaCo2 cells, since they equally allow cell entry through both the direct membrane fusion pathway mediated by TMPRSS2 and the endocytosis pathway mediated by cathepsin-L. The active molecules which showed stronger differences in their potency to inhibit certain SARS-CoV-2 VOCs included antagonists of G-protein coupled receptors, like phenothiazine-derived antipsychotic compounds such as Chlorpromazine, with highest activity against the Omicron pseudovirus. In general, our data showed that the various VOCs differ in their preferences for cell entry, and we were able to identify synergistic combinations of inhibitors. Notably, Omicron singled out by relying primarily on the endocytosis pathway while Delta preferred cell entry via membrane fusion. In conclusion, our data provide new insights into different entry preferences of SARS-CoV-2 VOCs, which might help to identify new drug targets.
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•SARS-CoV-2 lentiviral pseudoviruses were used in a high-throughput drug screening.•Efficient entry inhibitors were identified among 774 FDA-approved drugs.•SARS-CoV-2 VOC Omicron and Delta show different preferences for cell entry pathways.•Inhibitors of the different entry pathways might represent novel drug candidates.
In the pharmaceutical industry, the patent protection of drugs and medicines is accorded importance because of the high costs involved in the development of novel drugs. Over the years, researchers ...have analyzed patent documents to identify freedom-to-operate spaces for novel drug candidates. To assist this, several well-established public patent document data repositories have enabled automated methodologies for extracting information on therapeutic agents. In this study, we delve into one such publicly available patent database, SureChEMBL, which catalogues patent documents related to life sciences. Our exploration begins by identifying patent compounds across public chemical data resources, followed by pinpointing sections in patent documents where the chemical annotations were found. Next, we exhibit the potential of compounds to serve as drug candidates by evaluating their conformity to drug-likeness criteria. Lastly, we examine the drug development stage reported for these compounds to understand their clinical success. In summary, our investigation aims at providing a comprehensive overview of the patent compounds catalogued in SureChEMBL, assessing their relevance to pharmaceutical drug discovery.
Patents play a crucial role in the drug discovery process by providing legal protection for discoveries and incentivising investments in research and development. By identifying patterns within ...patent data resources, researchers can gain insight into the market trends and priorities of the pharmaceutical and biotechnology industries, as well as provide additional perspectives on more fundamental aspects such as the emergence of potential new drug targets. In this paper, we used the patent enrichment tool, PEMT, to extract, integrate, and analyse patent literature for rare diseases (RD) and Alzheimer's disease (AD). This is followed by a systematic review of the underlying patent landscape to decipher trends and applications in patents for these diseases. To do so, we discuss prominent organisations involved in drug discovery research in AD and RD. This allows us to gain an understanding of the importance of AD and RD from specific organisational (pharmaceutical or university) perspectives. Next, we analyse the historical focus of patents in relation to individual therapeutic targets and correlate them with market scenarios allowing the identification of prominent targets for a disease. Lastly, we identified drug repurposing activities within the two diseases with the help of patents. This resulted in identifying existing repurposed drugs and novel potential therapeutic approaches applicable to the indication areas. The study demonstrates the expanded applicability of patent documents from legal to drug discovery, design, and research, thus, providing a valuable resource for future drug discovery efforts. Moreover, this study is an attempt towards understanding the importance of data underlying patent documents and raising the need for preparing the data for machine learning-based applications.
Among the plethora of E3 Ligases, only a few have been utilized for the novel PROTAC technology. However, extensive knowledge of the preparation of E3 ligands and their utilization for PROTACs is ...already present in several databases. Here we provide, together with an analysis of functionalized E3 ligands, a comprehensive list of trained ML models to predict the probability to be an E3 ligase binder. We compared the different algorithms based on the different description schemes used and identified that the pharmacophore-based ML approach was the best. Due to the peculiar pharmacophores present in E3 ligase binders and the presence of an explainable model, we were able to show the capability of our ErG model to filter compound libraries for fast virtual screening or focused library design. A particular focus was also given to target E3 ligase prediction and to find a subset of candidate E3 ligase binders within known public and commercial compound collections.
•Active proximity-based degradative compounds bind E3 ligases.•No ML-based models exist for E3 ligase binding prediction.•Our ErG-based ML model predicts E3 ligase binders in public and commercial compound collections.•The ErG fingerprint's explainability helped rationalize the predictions and findings.•Focused E3 ligase binding compound collections can be thus established in an efficient manner.
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