RESUMO
Machine learning (ML) has shown a great promise in predicting toxicity of small molecules. However, the availability of data for such predictions is often limited. Because of the unsatisfactory performance of models trained on a single toxicity endpoint, we collected toxic small molecules with multiple toxicity endpoints from previous study. The dataset comprises 27 toxic endpoints categorized into seven toxicity classes, namely, carcinogenicity and mutagenicity, acute oral toxicity, respiratory toxicity, irritation and corrosion, cardiotoxicity, CYP450, and endocrine disruption. In addition, a binary classification Common-Toxicity task was added based on the aforementioned dataset. To improve the performance of the models, we added marketed drugs as negative samples. This study presents a toxicity predictive model, ToxMPNN, based on the message passing neural network (MPNN) architecture, aiming to predict the toxicity of small molecules. The results demonstrate that ToxMPNN outperforms other models in capturing toxic features within the molecular structure, resulting in more precise predictions with the ROC_AUC testing score of 0.886 for the Toxicity_drug dataset. Furthermore, it was observed that adding marketed drugs as negative samples not only improves the predictive performance of the binary classification Common-Toxicity task but also enhances the stability of the model prediction. It shows that the graph-based deep learning (DL) algorithms in this study can be used as a trustworthy and effective tool to assess small molecule toxicity in the development of new drugs.
Assuntos
Aprendizado Profundo , Redes Neurais de Computação , Testes de Toxicidade/métodos , HumanosRESUMO
USP7, a ubiquitin-specific peptidase (USP), plays an important role in many cellular processes through its catalytic deubiquitination of various substrates. However, its nuclear function that shapes the transcriptional network in mouse embryonic stem cells (mESCs) remains poorly understood. We report that USP7 maintains mESC identity through both catalytic activity-dependent and -independent repression of lineage differentiation genes. Usp7 depletion attenuates SOX2 levels and derepresses lineage differentiation genes thereby compromising mESC pluripotency. Mechanistically, USP7 deubiquitinates and stabilizes SOX2 to repress mesoendodermal (ME) lineage genes. Moreover, USP7 assembles into RYBP-variant Polycomb repressive complex 1 and contributes to Polycomb chromatin-mediated repression of ME lineage genes in a catalytic activity-dependent manner. USP7 deficiency in its deubiquitination function is able to maintain RYBP binding to chromatin for repressing primitive endoderm-associated genes. Our study demonstrates that USP7 harbors both catalytic and noncatalytic activities to repress different lineage differentiation genes, thereby revealing a previously unrecognized role in controlling gene expression for maintaining mESC identity.
Assuntos
Cromatina , Células-Tronco Embrionárias Murinas , Animais , Camundongos , Peptidase 7 Específica de Ubiquitina/genética , Peptidase 7 Específica de Ubiquitina/metabolismo , Diferenciação Celular/genética , Proteínas do Grupo Polycomb/genética , Cromatina/genética , Cromatina/metabolismo , Proteínas Repressoras/metabolismoRESUMO
@#Hepatitis C virus (HCV) infection is known to cause acute and chronic active hepatitis. In addition, HCV also has systemic disorder involvement that links to various extra-hepatic complications. We report a case of a patient which has been diagnosed to have Hepatitis C Genotype 3A who has been started on antiviral. He achieved end treatment response and sustained virologic response. During routine follow up, he experienced acute kidney injury. Renal biopsy showed type III membranoproliferative glomerulonephritis. His proteinuria improved greatly with the addition of angiotensin converting enzyme inhibitor. This case highlights the possibility of appearance of HCV related glomerulonephritis in patient who has sustained virological response.