Hemophilia

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, trad...

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...

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...

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

Neoadjuvant chemoradiotherapy (NACRT) is the standard treatment for locally advanced rectal cancer (...

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 signifi...

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, a...

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.

Identification of therapeutics against PfPK6 protein of Plasmodium falciparum: Structure and Deep Learning approach.

The Plasmodium falciparum Protein Kinase 6 (PfPK6) is a serine/threonine protein kinase categorized ...

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) po...

Dumpling GNN: Hybrid GNN Enables Better ADC Payload Activity Prediction Based on the Chemical Structure.

Antibody-drug conjugates (ADCs) are promising cancer therapeutics, but optimizing their cytotoxic pa...

Transforming Healthcare: The Role of Artificial Intelligence.

The integration of artificial intelligence (AI) into healthcare is revolutionising the industry by e...

Protein Profiles Predict Treatment Responses to the PI3K Inhibitor Umbralisib in Patients with Chronic Lymphocytic Leukemia.

PURPOSE: The management of chronic lymphocytic leukemia (CLL) has significantly improved with target...

Single-cell mitochondrial morphomics reveals cellular heterogeneity and predicts complex I, III, and ATP synthase Inhibition responses.

Mitochondrial heterogeneity drives diverse cellular responses in neurodegenerative diseases, complic...

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic di...

Identification of predictive subphenotypes for clinical outcomes using real world data and machine learning.

Predicting treatment response is an important problem in real-world applications, where the heteroge...

Blood-brain barrier crossing biopolymer targeting c-Myc and anti-PD-1 activate primary brain lymphoma immunity: Artificial intelligence analysis.

Primary Central Nervous System Lymphoma is an aggressive central nervous system neoplasm with poor r...

Clinical characteristics, outcomes, and predictive modeling of patients diagnosed with immune checkpoint inhibitor therapy-related pneumonitis.

PURPOSE: The aim of this study is to better characterize the clinical characteristics and outcomes o...

Advancing promiscuous aggregating inhibitor analysis with intelligent machine learning classification.

Small molecules have been playing a crucial role in drug discovery; however, some exhibit nonspecifi...

Discovery of hematopoietic progenitor kinase 1 inhibitors using machine learning-based screening and free energy perturbation.

Hematopoietic progenitor kinase 1 (HPK1) is a key negative regulator of T-cell receptor (TCR) signal...

Machine Learning-Based Discovery of a Novel Noncovalent MurA Inhibitor as an Antibacterial Agent.

The bacterial cell wall is crucial for maintaining the integrity of bacterial cells. UDP-N-acetylglu...

COX-2 Inhibitor Prediction With KNIME: A Codeless Automated Machine Learning-Based Virtual Screening Workflow.

Cyclooxygenase-2 (COX-2) is an enzyme that plays a crucial role in inflammation by converting arachi...