Latest Articles for Drug Development

New methods, including MolSnapper, improve drug design efficiency and effectiveness.

New research highlights a method to boost chemotherapy effectiveness using TopBP1 condensates.

Exploring how machine learning predicts PROTAC effectiveness in drug development.

Exploring how senescence affects cancer growth and treatments.

A study reveals structural differences between fluticasone furoate and propionate.

Humatch streamlines the humanization of antibody drugs for better efficacy and safety.

Exploring how alcohol affects phase transitions in living materials.

A look into how frequency response helps study biochemical networks.

A new AI model enhances the efficiency of clinical trials.

A new model improves therapeutic antibody design efficiency and accuracy.

How counterfactual explanations aid molecular behavior prediction and its implications.

New methods improve molecular design by measuring prediction uncertainty.

Seamless design aims to speed up cancer treatment development.

Researchers explore fungi from bogs for new tuberculosis treatments.

Examining the impact of HDAC inhibitors on lung cancer treatment responses.

Exploring the intersection of quantum computing and molecular chemistry for innovative solutions.

Research reveals distinct methods of poliovirus spread between cells, highlighting non-lytic strategies.

A new method enhances molecular discovery using evolutionary algorithms and language models.

IL-12's impact on immune response and cancer treatment revealed through clinical studies.

A fresh approach enhances drug candidate generation and effectiveness in pharmaceutical research.

A study on targeted chemical release enhances knowledge of protein reactions in living organisms.

Research suggests montelukast may help manage epilepsy by blocking Cav3.1 channels.

FreeCG enhances molecular modeling by improving efficiency and accuracy.

Allo-Allo offers a novel way to identify allosteric sites based on protein sequences.

A new method accelerates the generation of molecular libraries for better medicines.

AFD-X improves protein crystal analysis, enhancing data collection methods.

This article discusses gene expression's role in disease and drug development.

VETE model improves drug response predictions in cancer research.

Exploring the role of knowledge graphs in personalized cancer treatments.

Alpha Flow-Lit improves protein shape generation, enhancing efficiency and accuracy.

Researchers improve protein-DNA binding predictions using advanced methods and machine learning.

HERMES predicts protein mutation effects, aiding in medical research and drug development.

New method improves efficiency in studying protein structures and interactions.

Research reveals improved tools to block TEAD, impacting cancer cell growth.

New method predicts drug binding using protein's 3D structure.

Research reveals difficulties in ALS treatment development through mouse models.

Innovative methods aim to improve cancer treatment predictions.

A new study reveals detailed localization and variability of metabolic proteins in cells.

ProPEC improves predictions of viral protein mutations using deep learning models.

A new framework enhances the discovery of synthetic lethal gene relationships in cancer treatment.