Hemophilia

Analytical Quality by Design for Chiral Pharmaceuticals: A Robust HPLC Method for Upadacitinib Enantiomeric Quantification.

Ensuring the enantiomeric purity of chiral pharmaceuticals is paramount for patient safety and therapeutic efficacy. Upadacitinib (UPA), a vital Janus kinase 1 (JAK-1) inhibitor for rheumatoid arthritis treatment, exemplifies this need. This study represents the development of a robust HPLC method, engineered using analytical quality by design (AQbD), for the simultaneous quantification of UPA and...

Molecular Determinants of Orthosteric-allosteric Dual Inhibition of PfHT1 by Computational Assessment

To overcome antimalarial drug resistance, carbohydrate derivatives as selective PfHT1 inhibitor have been suggested in recent experimental work with orthosteric and allosteric dual binding pockets. Inspired by this promising therapeutic strategy, herein, molecular dynamics simulations are performed to investigate the molecular determinants of co-administration on orthosteric and allosteric inhib...

Predicting Nanoparticle Effects on Small Biomolecule Functionalities Using the Capability of Scikit-learn and PyTorch: A Case Study on Inhibitors of the DNA Damage-Inducible Transcript 3 (CHOP)

The presented study contributes to ongoing research that aims to overcome challenges in predicting the bio-applicability of nanoparticles. The appro...

Predicting Targeted Therapy Resistance in Non-Small Cell Lung Cancer Using Multimodal Machine Learning

Lung cancer is the primary cause of cancer death globally, with non-small cell lung cancer (NSCLC) emerging as its most prevalent subtype. Among NSC...

ProtoBERT-LoRA: Parameter-Efficient Prototypical Finetuning for Immunotherapy Study Identification

Identifying immune checkpoint inhibitor (ICI) studies in genomic repositories like Gene Expression Omnibus (GEO) is vital for cancer research yet re...

Hierarchical Functional Group Ranking via IUPAC Name Analysis for Drug Discovery: A Case Study on TDP1 Inhibitors

The article proposes a computational approach that can generate a descending order of the IUPAC-notated functional groups based on their importance ...

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-acetylglucosamine 1-carboxyethylene transferase (MurA) is a...

Deep Learning Model for Predicting Immunotherapy Response in Advanced Non-Small Cell Lung Cancer.

IMPORTANCE: Only a small fraction of patients with advanced non-small cell lung cancer (NSCLC) respond to immune checkpoint inhibitor (ICI) treatment....

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 arachidonic acid into prostaglandins. The overexpression...

Prediction of Binding Affinity for ErbB Inhibitors Using Deep Neural Network Model with Morgan Fingerprints as Features

The ErbB receptor family, including EGFR and HER2, plays a crucial role in cell growth and survival and is associated with the progression of variou...

Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity

Despite increased understanding of psoriasis pathogenesis, molecular classification of clinical phenotypes and disease severity is poorly defined. Kno...

Structure-based Generation of a Secondary Nucleation Inhibitor in α-Synuclein Aggregation Using a Conditional Diffusion Model

The process of α-synuclein aggregation results in the formation of amyloid fibrils, which accumulate in the brain of patients affected by Parkinson’s ...

Transcriptional Signatures of Field Cancerization in Gastric Cancer

The high rate of local recurrence in gastric adenocarcinoma (GA) suggests that carcinogenesis is not a focal event but a field-wide process. This phen...

Pocket-based molecule generation with an SE(3)-equivariant language model leads to a potent and selective HPK1 inhibitor with in vivo efficacy

Deep learning shows promise in structure-based drug discovery, yet challenges persist in generating pharmacologically plausible molecules with valid 3...

In Silico Design of APOE ɛ4 Interaction Inhibitor Peptides for Alzheimer’s Disease

Protein-protein interactions (PPIs) are essential for cellular functions, and their aberrant formation contributes to neurodegenerative diseases. Alzh...

Discovery of RdRp Thumb-1 as a novel broad-spectrum antiviral family of targets and MDL-001 as a potent broad-spectrum inhibitor thereof

Multiple positive-sense, single-stranded RNA (+ssRNA) viruses cause human diseases, ranging from mild colds to deadly pandemics. These viruses share a...

Single-cell lineage trajectory defines CDK inhibitor-sensitive cells-of-origin in esophageal squamous cell cancer

Understanding the cells of origin is essential for overcoming therapy resistance in esophageal squamous cell carcinoma (ESCC). We utilized machine lea...

A General Transformer-Based Multi-Task Learning Framework for Predicting Interaction Types between Enzyme and Small Molecule

Predicting enzyme–small molecule interactions is critical for drug discovery and generally understanding the biochemical processes of life. While rece...

Scaling Large Language Models for Next-Generation Single-Cell Analysis

Single-cell RNA sequencing has transformed our understanding of cellular diversity, yet current singlecell foundation models (scFMs) remain limited in...

AlphaMissense pathogenicity scores predict response to immunotherapy and enhances the predictive capability of tumor mutation burden

Tumor Mutational Burden (TMB) is a widely used biomarker for selecting cancer patients for immune checkpoint inhibitor (ICI) therapy. However, TMB alo...