Machine-learning methods for ligand–protein molecular docking

K Crampon, A Giorkallos, M Deldossi, S Baud… - Drug discovery today, 2022 - Elsevier
Artificial intelligence (AI) is often presented as a new Industrial Revolution. Many domains
use AI, including molecular simulation for drug discovery. In this review, we provide an …

Revolutionizing medicinal chemistry: the application of artificial intelligence (AI) in early drug discovery

R Han, H Yoon, G Kim, H Lee, Y Lee - Pharmaceuticals, 2023 - mdpi.com
Artificial intelligence (AI) has permeated various sectors, including the pharmaceutical
industry and research, where it has been utilized to efficiently identify new chemical entities …

DeepSurf: a surface-based deep learning approach for the prediction of ligand binding sites on proteins

SK Mylonas, A Axenopoulos, P Daras - Bioinformatics, 2021 - academic.oup.com
Motivation The knowledge of potentially druggable binding sites on proteins is an important
preliminary step toward the discovery of novel drugs. The computational prediction of such …

Machine learning and deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry

SA Kumar, TD Ananda Kumar… - Future Medicinal …, 2022 - Taylor & Francis
Predicting novel small molecule bioactivities for the target deconvolution, hit-to-lead
optimization in drug discovery research, requires molecular representation. Previous reports …

Recent advances in machine learning variant effect prediction tools for protein engineering

J Horne, D Shukla - Industrial & engineering chemistry research, 2022 - ACS Publications
Proteins are Nature's molecular machinery and comprise diverse roles while consisting of
chemically similar building blocks. In recent years, protein engineering and design have …

An improved small object detection method based on Yolo V3

C ** of allosteric protein landscapes to deep learning of allostery and hidden allosteric sites: zooming in on “allosteric intersection” of …
G Verkhivker, M Alshahrani, G Gupta, S **ao… - International Journal of …, 2023 - mdpi.com
The recent advances in artificial intelligence (AI) and machine learning have driven the
design of new expert systems and automated workflows that are able to model complex …

Optimizing protein sequence classification: integrating deep learning models with Bayesian optimization for enhanced biological analysis

UK Lilhore, S Simiaya, M Alhussein, N Faujdar… - BMC Medical Informatics …, 2024 - Springer
Efforts to enhance the accuracy of protein sequence classification are of utmost importance
in driving forward biological analyses and facilitating significant medical advancements. This …