Hemophilia

Identification of compounds that repress DUX4 expression in facioscapulohumeral muscular dystrophy

Facioscapulohumeral muscular dystrophy (FSHD) is caused by epigenetic dysregulation of the disease locus, leading to pathogenic misexpression of DUX4 in skeletal muscle. Thus, most FSHD therapeutic approaches target DUX4. Our previous study identified the chromatin remodeling factor BAZ1A (bromodomain adjacent to zinc finger domain protein 1A) as a promising target for therapeutic development. Her...

Learning Universal Representations of Intermolecular Interactions with ATOMICA

Molecular interactions underlie nearly all biological processes, but many representation learning models either focus on single entities or are trained for a narrow set of interaction settings. Here, we introduce ATOMICA, a geometric deep learning model that learns atomic-scale representations of intermolecular interfaces across five modalities, including proteins, small molecules, metal ions, lip...

Explainable AI for end-to-end pathogen target discovery and molecular design

Drug discovery is often constrained by target identification, a bottleneck especially acute in antimicrobial development and the fight against emergin...

Survival risk heterogeneity among patients with NSCLC receiving nivolumab visualized by risk scores generated from deep learning method DeepSurv using tumor gene mutations

Immunotherapy with immune checkpoint inhibitors and immunotherapy combined with chemotherapy have represented promising treatments for NSCLC patients ...

Multimodal Machine Learning Reveals the Genomic and Proteomic Architecture of Heart Failure with Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) affects over 30 million people and lacks disease-modifying therapies. Although genomic-led drug...

Results of a large scale study of the binding of 50 type IIinhibitors to 348 kinases: The role of protein reorganization

Kinase family proteins constitute the second largest protein class targeted in drug development efforts, most prominently to treat cancer, but also se...

Live high-content imaging with automated analysis reveals mitochondrial changes during vascular calcification

Mitochondrial dysfunction is implicated in a wide range of disorders, including cancer, neurodegeneration, and cardiovascular diseases. Conventional a...

BEACON: predicting side effects and therapeutics outcomes to drugs by Bridging knowlEdge grAph with CONtextual language model

Biomedical knowledge graphs encode millions of relationships between drugs, proteins, pathways, and diseases, yet translating this structured knowledg...

Prognostic Risk Refinement using Artificial Intelligence in HR+/HER2- Early Breast Cancer: Implications for CDK4/6 Eligibility Criteria

Patient selection and enrolment into phase III randomized clinical trials (RCTs) of adjuvant cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitor therap...

TopCysteineDB: A Cysteinome-wide Database Integrating Structural and Chemoproteomics Data for Cysteine Ligandability Prediction.

Development of targeted covalent inhibitors and covalent ligand-first approaches have emerged as a powerful strategy in drug design, with cysteines be...

Deep Learning-Guided Discovery of Celestolide as a Natural Allosteric Inhibitor Targeting CYP51 and Its Application in Strawberry Preservation.

Most CYP51 inhibitors act competitively and are prone to resistance, whereas allosteric inhibitors hold promise but are difficult to develop. In this ...

A deep learning model for structure-based bioactivity optimization and its application in the bioactivity optimization of a SARS-CoV-2 main protease inhibitor.

Bioactivity optimization is a crucial and technical task in the early stages of drug discovery, traditionally carried out through iterative substituen...

Computer-aided drug discovery of a dual-target inhibitor for ovarian cancer: therapeutic intervention targeting CDK1/TTK signaling pathway and structural insights in the NCI-60.

Ovarian cancer remains the third most prevalent and deadliest gynecologic malignancy worldwide, with most patients eventually developing resistance to...

Use of machine learning techniques to predict poor survival after hematopoietic cell transplantation for myelofibrosis.

With the incorporation of effective therapies for myelofibrosis (MF), accurately predicting outcomes after allogeneic hematopoietic cell transplantati...

[Progress in neoadjuvant immunotherapy for locally advanced rectal cancer].

Neoadjuvant chemoradiotherapy (NACRT) is the standard treatment for locally advanced rectal cancer (LARC), yet the pathological complete response (pCR...

RBC balanced immuno-inflammatory signatures identify advanced breast cancer patients on CDK4/6 inhibitors at increased risk of progression and death.

The association of immuno-inflammatory parameters, especially RBC balanced signatures, with survival outcomes and adverse events still require investi...

Structure-based artificial intelligence-aided design of MYC-targeting degradation drugs for cancer therapy.

The MYC protein is an oncoprotein that plays a crucial role in various cancers. Although its significance has been well recognized in research, the de...

Active Learning-Guided Hit Optimization for the Leucine-Rich Repeat Kinase 2 WDR Domain Based on In Silico Ligand-Binding Affinities.

The leucine-rich repeat kinase 2 (LRRK2) is the most mutated gene in familial Parkinson's disease, and its mutations lead to pathogenic hallmarks of t...

Deep learning model for predicting immunotherapy response in patients with advanced NSCLC: Study findings demonstrate a strong and independent deep learning-based feature associated with an immune checkpoint inhibitor response in patients with NSCLC across cohorts.

Machine learning models based on a national-scale cohort accurately identify patients at high risk of deep vein thrombosis following primary total hip arthroplasty.

BACKGROUND: The occurrence of deep venous thrombosis (DVT) following total hip arthroplasty (THA) poses a substantial risk of morbidity and mortality,...