Hemophilia

Computational hybrid framework integrating clinical-mutation profiling and physics-based simulations to predict structural tolerance of Bruton tyrosine kinase (BTK) and sustained ARQ 531 binding.

Bruton tyrosine kinase (BTK) is a non-receptor tyrosine kinase crucial for relaying signals from the B cell antigen receptor (BCR) in cancerous B lymphocytes. It has been reported that mutations in this protein cause resistance to various covalent and non-covalent drugs. Therefore, we employed a computational genomic mutation screening strategy, combined with molecular simulation, to assess the im...

New treatments to rabies virus infections.

Rabies disease is the deadliest of all virus infections. Till now, vaccination is the most effective and reliable treatment for controlling rabies. However, despite the high efficiency of inactivated vaccines, multiple-dose vaccinations and the high costs of post exposure prophylaxis cause a large economic burden, especially in tropical regions with limited storages of vaccines. New platforms of R...

Machine learning-enabled early risk stratification of β-Iactam-induced electrolyte imbalances.

AIMS: To estimate the incidence of β-lactam/β-lactamase inhibitor - associated electrolyte imbalances and develop an internally validated, interpretab...

Unveiling the TP5 dual binding mechanism and structure-based search for potential dual inhibitors of tubulin and PD-L1.

The dual inhibition of microtubule dynamics and immune checkpoint signaling represents a promising strategy in cancer therapy by simultaneously disrup...

Generative AI Uncovers Novel Chrebp/Txnip Axis Inhibitors with Potential Anti-inflammatory Activity.

Type 2 diabetes is driven in part by metabolic inflammation, where activation of the Chrebp/Txnip axis promotes NLRP3 inflammasome assembly, leading t...

GRU-based de novo design and in-silico prioritization of EZH2 inhibitors.

EZH2 (Enhancer-Homozygous Protein 2), as a key epigenetic regulator, is closely associated with multiple cancers. Consequently, the design of EZH2-tar...

AI-driven generative framework integrating ML-QSAR and fragment learning for isoform-selective PI3K inhibitor design.

Isoform-selective inhibition of class I phosphoinositide 3-kinases (PI3Ks) remains a major challenge in oncology and immune-mediated diseases, where d...

Combination Immunotherapy as a Promising Strategy to Overcome Immunotherapy Resistance: From Emergence to Next-Generation Approaches.

Advances in immunotherapy, particularly with immune checkpoint inhibitors, have improved clinical outcomes in various cancer subtypes; however, resist...

TRKB-based signature identifies high-risk squamous cell carcinoma cases and TRKB blockade reprograms tumor and stromal cells toward suppressive phenotypes.

BACKGROUND: Cutaneous squamous cell carcinoma (cSCC) is a common age-related cancer, with a subset prone to recurrence and metastasis. Currently, no u...

A machine learning model integrating circulating Temra cell transcriptional profiles to predict immunotherapy efficacy.

BACKGROUND: While immunotherapy has transformed treatment paradigms for cancer, durable response rates remain below 30%. Currently available biomarker...

Identification and validation of key genes as diagnostic biomarkers for epilepsy using bioinformatics and machine learning.

Epilepsy is a common neurological disorder with a complex molecular pathogenesis. Approximately one-third of patients experience drug-resistant seizur...

Integrated virtual screening, machine learning and molecular dynamics identify novel phytochemical FabI inhibitors against MRSA.

Methicillin-resistant Staphylococcus aureus (MRSA) infections pose a critical global health threat, necessitating the discovery of novel antibacterial...

Machine learning derived proliferating T cell-related signature: a novel biomarker for prognosis and treatment efficacy in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) exhibits profound molecular heterogeneity, and reliable biomarkers for predicting clinical outcome...

ALDH1L2 induces resistance to chemotherapy in small cell lung cancer by inhibiting ferroptosis.

Small cell lung cancer (SCLC) is known for its rapid growth and early metastasis, and SCLC patients are highly susceptible to chemoresistance. Studies...

Integrated in silico and in vitro screening approaches for the discovery of small-molecule inhibitors of β-carbonic anhydrases.

INTRODUCTION: β-Carbonic anhydrases (β-CAs) are zinc-dependent metalloenzymes that catalyze the reversible hydration of carbon dioxide to bicarbonate ...

Immunotherapy in Triple-Negative Breast Cancer: From Molecular Mechanisms to Precision Medicine-Overcoming Resistance and Optimizing Clinical Outcomes.

Triple-negative breast cancer (TNBC) is the most violent type of breast cancer, in which estrogen receptors (ER), progesterone receptors (PR), and hum...

Prediction of immune checkpoint inhibitor-related pneumonitis in lung cancer: development and validation of multiple machine learning models.

SCMO: a deep learning model integrating the single-cell resolution TME ecosystem and multi-omics for survival prediction in CRC patients.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of global cancer mortality, highlighting the need for precise survival prediction to guide...

A Metabolomic Signature Predicts Gout Flare Clinical Outcome Associated with Colchicine Prophylaxis.

OBJECTIVE: This study investigated that serum metabolomics, prior to ULT initiation, could serve as a biomarker for responsiveness to colchicine proph...

CSF proteomics identifies ADGRG1 as a predictive biomarker of intrathecal immune checkpoint inhibitor response in leptomeningeal metastasis.

BACKGROUND: Leptomeningeal metastasis (LM) is a fatal complication of advanced cancer with limited therapeutic options and poor prognosis. Immune chec...