Biology subjects

Kurita, K.

Publications and source records attributed to Kurita, K..

3 recordsLinked to original sources

bioRxiv2021

The inhibitory effects of toothpaste and mouthwash ingredients on the interaction between the SARS-CoV-2 spike protein and ACE2, and the protease activity of TMPRSS2, in vitro

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters host cells when the viral spike protein is cleaved by transmembrane protease serine 2 (TMPRSS2) after binding to the host angiotensin-converting enzyme 2 (ACE2). Since ACE2 and TMPRSS2 are expressed in the mucosa of the tongue and gingiva, the oral cavity seems like it is an entry point for SARS-CoV-2. Daily oral care using mouthwash seems to play an important role in preventing SARS-CoV-2 infection. However, the relationship between daily oral care and the mechanisms of virus entry into host cells is unclear. In this study, we evaluated the inhibitory effects of ingredients that are generally contained in toothpaste and mouthwash on the interaction between the spike protein and ACE2 and on the serine protease activity of TMPRSS2 using an enzyme-linked immunosorbent assay and in vitro enzyme assay, respectively. Both assays detected inhibitory effects of sodium tetradecene sulfonate, sodium N-lauroyl-N-methyltaurate, sodium N-lauroylsarcosinate, sodium dodecyl sulfate, and copper gluconate. Molecular docking simulations suggested that these ingredients could bind to the inhibitor-binding site of ACE2. In addition, tranexamic acid and 6-aminohexanoic acid, which act as serine protease inhibitors, exerted inhibitory effects on TMPRSS2 protease activity. Further experimental and clinical studies are needed to further elucidate these mechanisms. Our findings support the possibility that toothpaste and mouthwash contain ingredients that inhibit SARS-CoV-2 infection.

molecular biology↗

bioRxiv2019

The antimalarial natural product salinipostin A identifies essential α/β serine hydrolases involved in lipid metabolism in P. falciparum parasites

Salinipostin A (Sal A) is a potent antimalarial marine natural product with an undefined mechanism of action. Using a Sal A-derived activity-based probe, we identify its targets in the Plasmodium falciparum parasite. All of the identified proteins contain /{beta} serine hydrolase domains, and several are essential for parasite growth. One of the essential targets displays high homology to human monoacylglycerol lipase (MAGL) and is able to process lipid esters including a MAGL acylglyceride substrate. This Sal A target is inhibited by the anti-obesity drug Orlistat, which disrupts lipid metabolism and produces disorganized and stalled schizonts similar to Sal A. Resistance selections yielded parasites that showed only minor reductions in sensitivity and that acquired mutations in a protein linked to drug resistance in Toxoplasma gondii. This inability to evolve efficient resistance mechanisms combined with the non-essentiality of human homologs makes the serine hydrolases identified here promising antimalarial targets.

cell biology↗

bioRxiv2019

High-Throughput Functional Annotation of Natural Products by Integrated Activity Profiling

Determining mechanism of action (MOA) is one of the biggest challenges in natural products discovery. Here, we report a comprehensive platform that uses Similarity Network Fusion (SNF) to improve MOA predictions by integrating data from the cytological profiling high-content imaging platform and the gene expression platform FUSION, and pairs these data with untargeted metabolomics analysis for de novo bioactive compound discovery. The predictive value of the integrative approach was assessed using a library of target-annotated small molecules as benchmarks. Using Kolmogorov-Smirnov (KS) tests to compare in-class to out-of-class similarity, we found that SNF retains the ability to identify significant in-class similarity across a diverse set of target classes, and could also find target classes that were not detectable in either platform alone. This confirmed that integration of expression-based and image-based phenotypes can accurately report on MOA. Furthermore, we integrated untargeted metabolomics of complex natural product fractions with the SNF network to map biological signatures to specific metabolites. Three examples are presented where SNF coupled with metabolomics was used to directly functionally characterize natural products and accelerate identification of bioactive metabolites, including the discovery of the novel azoxy-containing biaryl compounds parkamycins A and B. Our results support SNF integration of multiple phenotypic screening approaches along with untargeted metabolomics as a powerful approach for advancing natural products drug discovery. Significance statementNew data-driven methods to aid in the discovery and biological characterization of natural products are necessary to advance the field. Assigning the mechanism of action (MOA) to novel bioactive compounds is an essential step in drug discovery and a major challenge in chemical biology. Despite technological advances in isolation, synthesis and screening strategies that make many bioactive substances readily available, in most cases their biological targets remain unknown. Additionally, a major bottleneck in natural products discovery efforts is de-replication of the large number of known compounds that predominate in crude extracts and fraction libraries. Advances in metabolomics has provided a better understanding of the constituents present in these libraries, but is not sufficient in itself to drive the discovery of novel biologically active metabolites. Here we describe an unbiased, data-driven strategy which integrates phenotypic screening with metabolomics into a single platform that provides rapid identification and functional annotation of natural products. This approach can be applied to any cohort of uncharacterized chemicals and represents a strategy that could significantly accelerate the process of drug discovery.

pharmacology and toxicology↗