AI Medical Compendium Journal:
Molecules (Basel, Switzerland)

Showing 51 to 60 of 243 articles

Diffusion-Limited Processes in Hydrogels with Chosen Applications from Drug Delivery to Electronic Components.

Molecules (Basel, Switzerland)
Diffusion is one of the key nature processes which plays an important role in respiration, digestion, and nutrient transport in cells. In this regard, the present article aims to review various diffusion approaches used to fabricate different functio...

MATH: A Deep Learning Approach in QSAR for Estrogen Receptor Alpha Inhibitors.

Molecules (Basel, Switzerland)
Breast cancer ranks as the second leading cause of death among women, but early screening and self-awareness can help prevent it. Hormone therapy drugs that target estrogen levels offer potential treatments. However, conventional drug discovery entai...

Recent Advances in Deep Learning for Protein-Protein Interaction Analysis: A Comprehensive Review.

Molecules (Basel, Switzerland)
Deep learning, a potent branch of artificial intelligence, is steadily leaving its transformative imprint across multiple disciplines. Within computational biology, it is expediting progress in the understanding of Protein-Protein Interactions (PPIs)...

A Novel LSTM-Based Machine Learning Model for Predicting the Activity of Food Protein-Derived Antihypertensive Peptides.

Molecules (Basel, Switzerland)
Food protein-derived antihypertensive peptides are a representative type of bioactive peptides. Several models based on partial least squares regression have been constructed to delineate the relationship between the structure and activity of the pep...

Deep Learning for Identifying Promising Drug Candidates in Drug-Phospholipid Complexes.

Molecules (Basel, Switzerland)
Drug-phospholipid complexing is a promising formulation technology for improving the low bioavailability of active pharmaceutical ingredients (APIs). However, identifying whether phospholipid and candidate drug can form a complex through in vitro tes...

DeepBindGCN: Integrating Molecular Vector Representation with Graph Convolutional Neural Networks for Protein-Ligand Interaction Prediction.

Molecules (Basel, Switzerland)
The core of large-scale drug virtual screening is to select the binders accurately and efficiently with high affinity from large libraries of small molecules in which non-binders are usually dominant. The binding affinity is significantly influenced ...

Mathematical Geometry and Groups for Low-Symmetry Metal Complex Systems.

Molecules (Basel, Switzerland)
Since chemistry, materials science, and crystallography deal with three-dimensional structures, they use mathematics such as geometry and symmetry. In recent years, the application of topology and mathematics to material design has yielded remarkable...

Challenges for Kinetics Predictions via Neural Network Potentials: A Wilkinson's Catalyst Case.

Molecules (Basel, Switzerland)
Ab initio kinetic studies are important to understand and design novel chemical reactions. While the Artificial Force Induced Reaction (AFIR) method provides a convenient and efficient framework for kinetic studies, accurate explorations of reaction ...

Support Vector Machine-Based Global Classification Model of the Toxicity of Organic Compounds to .

Molecules (Basel, Switzerland)
is widely used as the model species in toxicity and risk assessment. For the first time, a global classification model was proposed in this paper for a two-class problem (Class - 1 with log1/IBC ≤ 4.2 and Class + 1 with log1/IBC > 4.2, the unit of I...

Ensemble Learning, Deep Learning-Based and Molecular Descriptor-Based Quantitative Structure-Activity Relationships.

Molecules (Basel, Switzerland)
A deep learning-based quantitative structure-activity relationship analysis, namely the molecular image-based DeepSNAP-deep learning method, can successfully and automatically capture the spatial and temporal features in an image generated from a thr...