Biology subjects

Kawashima, S.

Publications and source records attributed to Kawashima, S..

8 recordsLinked to original sources

bioRxiv2026

Antiviral activity of anisomycin against chikungunya virus

Chikungunya virus (CHIKV) is a globally prevalent arbovirus transmitted by Aedes mosquitoes, which causes acute fever accompanied by debilitating joint pain that can persist for extended periods. Despite the significant public health impact and an increasing incidence worldwide, antiviral treatment targeting CHIKV has not been clinically approved. In this study, we screened compounds using a newly developed In-Cell ELISA-based assay and CHIKV Indian Ocean Lineage (IOL) and found that an antibiotic derived from Streptomyces bacteria, anisomycin, potentially inhibited CHIKV. The selectivity index of anisomycin was favorable for anti-CHIKV activity, with 50% effective concentration (EC50) of 200 pM and 50% cytotoxic concentration (CC50) of 390 nM in Vero cells. This robust inhibitory activity against CHIKV was confirmed in a human cell line and against a CHIKV East/Central/South African (ECSA) lineage. These effects of anisomycin were apparently independent of its functions as a translation inhibitor and mitogen-activated protein kinase (MAPK) pathway stimulator. These findings, together with the finding that anisomycin suppressed the production of infectious CHIKV virions, suggested that anisomycin inhibits CHIKV via a distinct mechanism. Further mechanistic insights were gained through genetic analyses of anisomycin-resistant mutants, which revealed that a single amino acid substitution (G117R) in the macrodomain of CHIKV nsP3 confers resistance to anisomycin. Importantly, anisomycin reduced footpad swelling and viremia in mice during the early days of CHIKV infection, indicating its therapeutic potential. Given its inhibitory activity against other arboviruses, our study positions anisomycin as a promising lead inhibitor for the future development of broad-spectrum antiviral drugs, including CHIKV. Author summaryChikungunya fever (CHIKF) is a mosquito-borne disease caused by the chikungunya virus (CHIKV) and is characterized by fever, rash, and arthralgia. Although most persons infected with CHIKV recover within days, joint pain and severe complications can persist. However, the management of CHIKF is limited to symptom relief, and specific antiviral treatments are not available. Our study focused on identifying potential inhibitors of CHIKV infection. We found that the natural alkaloid, anisomycin, inhibited CHIKV replication in cultured cells in vitro using a novel screening assay and a chemical compound library. Interestingly, the mechanism by which anisomycin blocks CHIKV infection likely differs from its currently known effects, suggesting a distinct mode of inhibition. We also identified an amino acid change in a nonstructural protein that conferred resistance to anisomycin, providing insights into a viral target of anisomycin. Importantly, anisomycin reduced disease symptoms and viremia in mouse models of CHIKV in vivo. Because anisomycin inhibits other mosquito-borne viruses, our findings suggest that it could serve as a basis for developing broad-acting antiviral drugs.

microbiology↗

bioRxiv2026

BacteReason: A Reasoning Model for Antimicrobial Resistance Prediction

The rapid global spread of antimicrobial resistance (AMR) has placed unprecedented pressure on clinical decision-making. Machine learning predictors of antibiotic susceptibility exist, but their lack of mechanistic grounding limits credibility. We present BO_SCPLOWACTEC_SCPLOWRO_SCPLOWEASONC_SCPLOW, a reasoning large language model (LLM) that predicts bacterial susceptibility to a target antibiotic, together with a mechanistic rationale. BacteReason is obtained by fine-tuning an open-weight LLM on clinical susceptibility data augmented with rationales that explain the molecular mechanisms. These rationales are produced by a proprietary teacher LLM prompted to explain known susceptibility outcomes. The teacher is interfaced via TogoMCP with a collection of biomedical knowledge-graph databases, grounding each reasoning step in retrieved evidence. On an extrapolation benchmark, BO_SCPLOWACTEC_SCPLOWRO_SCPLOWEASONC_SCPLOW achieves a relative improvement of 43% over the untuned baseline and 38% over the same base LLM fine-tuned without rationales, demonstrating that reasoning supervision improves prediction accuracy.

bioinformatics↗

bioRxiv2026

Enzyme activity as an actionable axis for small-molecule precision oncology

Current precision oncology--molecular targeted therapies and immunotherapies--relies on genomic or expressed biomarkers, yet most cancer patients remain ineligible for these treatments. Here, we establish enzyme activity as an actionable and orthogonal axis for precision cancer medicine. Strategic activity-based screening of mouse organs and human clinical specimens with a panel of enzyme-reactive fluorescence probes identified {beta}-galactosidase 1 (GLB1) and {beta}-hexosaminidases (HEX) as broadly elevated tumor-selective biomarkers. Leveraging these activities, we developed 7-ethyl-10-hydroxycamptothecin (SN38)-based GLB1-and HEX-reactive prodrugs. These prodrugs exhibited dramatically reduced systemic toxicities and improved therapeutic windows, compared to a clinically used SN38-based prodrug, irinotecan (CPT-11). Both prodrugs demonstrated activity-dependent therapeutic efficacy, affording a dramatic reduction of tumor volumes across multiple in vivo models, including a subcutaneous patient-derived xenograft (PDX) of lung squamous cell carcinoma that lacked genetic alterations targeted by current precision medicine. Furthermore, this strategy is broadly applicable across various cytotoxic payloads, establishing a generalizable platform for small-molecule precision medicines. Our results define an enzyme-targeting paradigm for precision oncology, in which fluorescence probes serve as companion diagnostic tools to guide development and selection of appropriately targeted prodrugs, which are expected to provide safer and more efficacious treatment options for cancer patients with elevated enzyme activities.

cancer biology↗

bioRxiv2025

Discovery of The Clinical Candidate S-892216: A Second-Generation of SARS-CoV-2 3CL Protease Inhibitor for Treating COVID-19

The coronavirus disease 2019 (COVID-19) pandemic crisis has been mitigated by worldwide efforts to develop vaccines and therapeutic drugs. However, there remains concern regarding public health and an unmet need for therapeutic options. Herein, we report the discovery of S-892216, a second-generation SARS-CoV-2 3C-like protease (3CLpro) inhibitor, to treat COVID-19. S-892216 is a reversible covalent 3CLpro inhibitor with highly potent antiviral activity and an EC50 value of 2.48 nM against SARS-CoV-2 infected cells. Structure-based design of a covalent modifier for compound 1 revealed that introducing a nitrile warhead increased 3CLpro inhibition activity by 180-fold. Subsequent optimization efforts yielded S-892216, which combined a favorable pharmacokinetic profile and high off-target selectivity. S-892216 exhibited antiviral activity against diverse SARS-CoV-2 variants, with no cross-resistance to major mutations reducing antiviral activities of nirmatrelvir and ensitrelvir. In SARS-CoV-2-infected mice, S-892216 inhibited viral replication in the lungs similar to ensitrelvir, although at a 30-fold lower dose.

biochemistry↗

bioRxiv2025

Extraction of biological terms using large language models enhances the usability of metadata in the BioSample database

BioSample is a comprehensive repository of experimental sample metadata, playing a crucial role in providing a comprehensive archive and enabling experiment searches regardless of type. However, the difficulty in comprehensively defining the rules for describing metadata and limited user awareness of best practices for metadata have resulted in substantial variability depending on the submitter. This inconsistency poses significant challenges to the findability and reusability of the data. Given the vast scale of BioSample, which hosts over 40 million records, manual curation is impractical. Rule-based automatic ontology mapping methods have been proposed to address this issue, but their effectiveness is limited by the heterogeneity of BioSample metadata. Recently, large language models (LLMs) have gained attention in natural language processing and have been expected as promising tools for automating metadata curation. In this study, we evaluated the performance of LLMs in extracting cell line names from BioSample descriptions using a gold-standard dataset derived from ChIP-Atlas, a secondary database of epigenomics experiment data, which manually curates samples. Our results demonstrated that LLM-assisted methods outperformed traditional approaches, achieving higher accuracy and coverage. We further extended this approach to extraction of information about experimentally manipulated genes from metadata where manual curation had not yet been applied in ChIP-Atlas. This also yielded successful results for the usage of the database, which facilitates more precise filtering of data and prevents misinterpretation caused by inclusion of unintended data. These findings underscore the potential of LLMs to improve the findability and reusability of experimental data in general, significantly reducing user workload and enabling more effective scientific data management.

bioinformatics↗

bioRxiv2022

Discovery of S-217622, a Non-Covalent Oral SARS-CoV-2 3CL Protease Inhibitor Clinical Candidate for Treating COVID-19

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in millions of deaths and threatens public health and safety. Despite the rapid global spread of COVID-19 vaccines, effective oral antiviral drugs are urgently needed. Here, we describe the discovery of S-217622, the first oral non-covalent, non-peptidic SARS-CoV-2 3CL protease inhibitor clinical candidate. S-217622 was discovered via virtual screening followed by biological screening of an in-house compound library, and optimization of the hit compound using a structure-based drug-design strategy. S-217622 exhibited antiviral activity in vitro against current outbreaking SARS-CoV-2 variants and showed favorable pharmacokinetic profiles in vivo for once-daily oral dosing. Furthermore, S-217622 dose-dependently inhibited intrapulmonary replication of SARS-CoV-2 in mice, indicating that this novel non-covalent inhibitor could be a potential oral agent for treating COVID-19.

biochemistry↗

bioRxiv2020

Visuospatial n-back test for early detection of mild cognitive impairment in patients with Parkinsons Disease : an fMRI study

BackgroundCognitive impairment is a common symptom in the patients with Parkinsons disease (PD). In delineating a therapeutic plan, the early diagnosis of mild cognitive impairment in PD (PD-MCI) is important. Patients with PD-MCI have severe impairment in frontal executive function and/or visuospatial recognition. However, the clinical assessment of these functions is not routinely performed. MethodIn this study, we aimed to clarify the advantage of visuospatial version of the n-back test as a tool for the early detection of neuropsychological change in the patients with PD-MCI. The score of 0-back test reflects visuospatial recognition, and the scores of 1-back and 2-back reflect visuospatial working memory. PD-MCI was classified according to the criteria provided by the Movement Disorder Society Task Force for mild cognitive impairment in PD. We recruited 13 patients with PD-MCI, and 15 patients with cognitive normal PD. Using functional MRI (fMRI), we also aimed to clarify the specific brain regions associated with the impairment of visuospatial working memory. ResultWe demonstrated that the correct answer rate of patients with PD-MCI was lower in the 2-back test than patients with PD-CN. However, we did not find statistical difference in the 0-back test. These results indicate the preservation of visuospatial recognition and the impairment of visuospatial working memory in the patients with PD-MCI. We revealed the reduced activation within the middle frontal gyrus (MFG) and the inferior parietal lobule (IPL) during the 2-back test in the patients with PD-MCI. It may be associated with the severity of cortico-striatal dysfunction in the dopaminergic neural network which is associated with Lewy body pathology. ConclusionThe visuospatial n-back test has advantages for use in rapid and early detection of impaired visual recognition and working memory. The combination of functional neuroimaging and neuropsychological tests may provide markers for the increased risk of dementia before the development of an irreversible disease-specific pathology.

neuroscience↗

bioRxiv2017

Collaborative environmental DNA sampling from petal surfaces of flowering cherry Cerasus ×- yedoensis 'Somei-yoshino' across the Japanese archipelago

Recent studies have shown that environmental DNA is found almost everywhere. Flower petal surfaces are an attractive tissue to use for investigation of the dispersal of environmental DNA in nature as they are isolated from the external environment until the bud opens and only then can the petal surface accumulate environmental DNA. Here, we performed a crowdsourced experiment, the \"Ohanami Project\", to obtain environmental DNA samples from petal surfaces of Cerasus x yedoensis Somei-yoshino across the Japanese archipelago during spring 2015. C. x yedoensis is the most popular garden cherry species in Japan and clones of this cultivar bloom simultaneously every spring. Data collection spanned almost every prefecture and totaled 577 DNA samples from 149 collaborators. Preliminary amplicon-sequencing analysis showed the rapid attachment of environmental DNA onto the petal surfaces. Notably, we found DNA of other common plant species in samples obtained across a wide distribution; this DNA likely originated from pollen of the Japanese cedar. Our analysis supports our belief that petal surfaces after blossoming are a promising target to reveal the dynamics of environmental DNA in nature. The success of our experiment also shows that crowdsourced environmental DNA analyses have considerable value in ecological studies.

microbiology↗