AIMC Topic: Molecular Docking Simulation

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Predicting molecular docking of per- and polyfluoroalkyl substances to blood protein using generative artificial intelligence algorithm DiffDock.

BioTechniques
This study computationally evaluates the molecular docking affinity of various perfluoroalkyl and polyfluoroalkyl substances (PFAs) towards blood proteins using a generative machine-learning algorithm, DiffDock, specialized in protein-ligand blind-do...

Exploring the potential of machine learning to design antidiabetic molecules: a comprehensive study with experimental validation.

Journal of biomolecular structure & dynamics
Recent advances in hardware and software algorithms have led to the rise of data-driven approaches for designing therapeutic modalities. One of the major causes of human mortality is diabetes. Thus, there is a tremendous opportunity for research into...

Equivariant Flexible Modeling of the Protein-Ligand Binding Pose with Geometric Deep Learning.

Journal of chemical theory and computation
Flexible modeling of the protein-ligand complex structure is a fundamental challenge for in silico drug development. Recent studies have improved commonly used docking tools by incorporating extra-deep learning-based steps. However, such strategies l...

Generation of focused drug molecule library using recurrent neural network.

Journal of molecular modeling
CONTEXT: With the wide application of deep learning in drug research and development, de novo molecular design methods based on recurrent neural network (RNN) have strong advantages in drug molecule generation. The RNN model can be used to learn the ...

LCK-SafeScreen-Model: An Advanced Ensemble Machine Learning Approach for Estimating the Binding Affinity between Compounds and LCK Target.

Molecules (Basel, Switzerland)
The lymphocyte-specific protein tyrosine kinase (LCK) is a critical target in leukemia treatment. However, potential off-target interactions involving LCK can lead to unintended consequences. This underscores the importance of accurately predicting t...

Integration of Deep Learning and Sequential Metabolism to Rapidly Screen Dipeptidyl Peptidase (DPP)-IV Inhibitors from .

Molecules (Basel, Switzerland)
Traditional Chinese medicine (TCM) possesses unique advantages in the management of blood glucose and lipids. However, there is still a significant gap in the exploration of its pharmacologically active components. Integrated strategies encompassing ...

Anti-inflammatory and urease inhibitory iridoid glycosides from Nyctanthes arbor-tristis Linn.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Nyctanthes arbor-tristis Linn. has been used by Ayruvedic physicians for the cure of different diseases including ulcers, gastric and inflammatory diseases.

Virtual screening and invitro evaluation of cyclooxygenase inhibitors from using the machine learning tool.

Journal of biomolecular structure & dynamics
has a variety of compounds, and some of these compounds may have anti-inflammatory and antioxidant properties. In the present study, we identified the compounds in the leaf extract of through Gas Chromatography-Mass Spectrometry (GC-MS) analysis an...

The water-soluble subfraction from Artemisia argyi alleviates LPS-induced inflammatory responses via multiple pathways and targets in vitro and in vivo.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: As a traditional Chinese medicine, Artemisia argyi has been used medicinally and eaten for more than 2000 years in China. It is widely reported in treating inflammatory diseases such as eczema, dermatitis, arthritis, a...

Integrated Molecular Modeling and Machine Learning for Drug Design.

Journal of chemical theory and computation
Modern therapeutic development often involves several stages that are interconnected, and multiple iterations are usually required to bring a new drug to the market. Computational approaches have increasingly become an indispensable part of helping r...