Drug combination therapy has gradually become a promising treatment strategy for complex or co-existing diseases. As drug-drug interactions (DDIs) may cause unexpected adverse drug reactions, DDI prediction is an important task in pharmacology and cl...
Journal of chemical information and modeling
37857374
We introduce an exploratory active learning (AL) algorithm using Gaussian process regression and marginalized graph kernel (GPR-MGK) to sample chemical compound space (CCS) at minimal cost. Targeting 251,728 enumerated alkane molecules with 4-19 carb...
Journal of computer-aided molecular design
37847342
In this work, we develop a method for generating targeted hit compounds by applying deep reinforcement learning and attention mechanisms to predict binding affinity against a biological target while considering stereochemical information. The novelty...
Journal of biomolecular structure & dynamics
38133953
The Adenosine A receptor (AAR) is considered a novel potential target for the immunotherapy of cancer, and AAR antagonists have an inhibitory effect on tumor growth, proliferation, and metastasis. In our previous studies, we identified a class of ben...
Neoantigens are tumor-derived peptides and are biomarkers that can predict prognosis related to immune checkpoint inhibition by estimating their binding to major histocompatibility complex (MHC) proteins. Although deep neural networks have been prima...
In the field of molecular simulation for drug design, traditional molecular mechanic force fields and quantum chemical theories have been instrumental but limited in terms of scalability and computational efficiency. To overcome these limitations, ma...
Tuberculosis (TB) is one of the life-threatening infectious diseases with prehistoric origins and occurs in almost all habitable parts of the world. TB mainly affects the lungs, and its etiological agent is Mycobacterium tuberculosis (Mtb). In 2022, ...
Inhibiting the enzymes carbonic anhydrase I (CA I) and carbonic anhydrase II (CA II) presents a potential avenue for addressing nervous system ailments such as glaucoma and Alzheimer's disease. Our study explored harnessing explainable artificial int...
Artificial intelligence (AI) molecular generation is a highly promising strategy in the drug discovery, with deep reinforcement learning (RL) models emerging as powerful tools. This study introduces a fragment-by-fragment growth RL forward molecular...
Polymer memristors represent a highly promising avenue for the advancement of next-generation computing systems. However, the intrinsic structural heterogeneity characteristic of most polymers often results in organic polymer memristors displaying er...