Related Experiment Video
Updated: Jun 7, 2025
Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Machine Learning to Predict Potential Energy Surface of Resveratrol Drug: A Quantum-Level Calculation
Hossein Shirani1, Seyed Majid Hashemianzadeh1
1Molecular Simulation Research Laboratory, Department of Chemistry, Iran University of Science and Technology, Tehran 16846-13114, Iran.
None:
The ANI-1x neural network potential, trained on the density functional theory data set, as a quantum-level machine learning calculation has been investigated to forecast the potential energy surfaces of the Resveratrol (3,5,4'-trihydroxy-trans-stilbene) antiparkinsonian drug in a very short computing time. A comprehensive validation of the ANI-1x deep learning technique was provided on the Resveratrol molecule using density functional theory at the wB97X/6-31G(d) level of theory. The results showcased in this study will offer significant insights into pharmaceutical computational research, medicinal chemistry, drug discovery and design, thereby making a valuable contribution.
More Related Videos
Related Concept Videos
01:49Conserved Binding Sites
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
02:40Ligand Binding Sites
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...