AIMC Topic: Molecular Docking Simulation

Clear Filters Showing 801 to 810 of 854 articles

Comprehensive Review on Drug-target Interaction Prediction - Latest Developments and Overview.

Current drug discovery technologies
Drug-target interactions (DTIs) are an important part of the drug development process. When the drug (a chemical molecule) binds to a target (proteins or nucleic acids), it modulates the biological behavior/function of the target, returning it to its...

Artificial Intelligence-based database for prediction of protein structure and their alterations in ocular diseases.

Database : the journal of biological databases and curation
The aim of the study is to establish an online database for predicting protein structures altered in ocular diseases by Alphafold2 and RoseTTAFold algorithms. Totally, 726 genes of multiple ocular diseases were collected for protein structure predict...

[Advancements in virtual screening techniques for study of enzyme inhibitor compounds].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica
Enzymes are closely associated with the onset and progression of numerous diseases, making enzymes a primary target in innovative drug development. However, the challenge remains in identifying compounds that exhibit potent inhibitory effects on the ...

[Exploring the mechanisms of ferroptosis in non-obstructive azoospermia based on bioinformatics and machine learning].

Zhonghua nan ke xue = National journal of andrology
OBJECTIVE: To explor the potential mechanisms of ferroptosis involvement in non-obstructive azoospermia based on bioinformatics and machine learning methods.

Protein-ligand binding affinity prediction exploiting sequence constituent homology.

Bioinformatics (Oxford, England)
MOTIVATION: Molecular docking is a commonly used approach for estimating binding conformations and their resultant binding affinities. Machine learning has been successfully deployed to enhance such affinity estimations. Many methods of varying compl...

MPI-VGAE: protein-metabolite enzymatic reaction link learning by variational graph autoencoders.

Briefings in bioinformatics
Enzymatic reactions are crucial to explore the mechanistic function of metabolites and proteins in cellular processes and to understand the etiology of diseases. The increasing number of interconnected metabolic reactions allows the development of in...

The LightDock Server: Artificial Intelligence-powered modeling of macromolecular interactions.

Nucleic acids research
Computational docking is an instrumental method of the structural biology toolbox. Specifically, integrative modeling software, such as LightDock, arise as complementary and synergetic methods to experimental structural biology techniques. Ubiquitous...

A fully differentiable ligand pose optimization framework guided by deep learning and a traditional scoring function.

Briefings in bioinformatics
The recently reported machine learning- or deep learning-based scoring functions (SFs) have shown exciting performance in predicting protein-ligand binding affinities with fruitful application prospects. However, the differentiation between highly si...

Recent Trends in Computer-aided Drug Design for Anti-cancer Drug Discovery.

Current topics in medicinal chemistry
Cancer is considered one of the deadliest diseases globally, and continuous research is being carried out to find novel potential therapies for myriad cancer types that affect the human body. Researchers are hunting for innovative remedies to minimiz...