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Drug Evaluation, Preclinical

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Prediction of protein-ligand binding affinity via deep learning models.

Briefings in bioinformatics
Accurately predicting the binding affinity between proteins and ligands is crucial in drug screening and optimization, but it is still a challenge in computer-aided drug design. The recent success of AlphaFold2 in predicting protein structures has br...

AI-Driven Enhancements in Drug Screening and Optimization.

Methods in molecular biology (Clifton, N.J.)
The greatest challenge in drug discovery remains the high rate of attrition across the different phases of the process, which cost the industry billions of dollars every year. While all phases remain crucial to ensure pharmaceutical-level safety, qua...

Machine learning on ligand-residue interaction profiles to significantly improve binding affinity prediction.

Briefings in bioinformatics
Structure-based virtual screenings (SBVSs) play an important role in drug discovery projects. However, it is still a challenge to accurately predict the binding affinity of an arbitrary molecule binds to a drug target and prioritize top ligands from ...

Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM, pharmacophore and docking model.

Journal of enzyme inhibition and medicinal chemistry
Cyclin-dependent kinase 2 (CDK2) is the family of Ser/Thr protein kinases that has emerged as a highly selective with low toxic cancer therapy target. A multistage virtual screening method combined by SVM, protein-ligand interaction fingerprints (PLI...

Large-scale single-molecule imaging aided by artificial intelligence.

Microscopy (Oxford, England)
Single-molecule imaging analysis has been applied to study the dynamics and kinetics of molecular behaviors and interactions in living cells. In spite of its high potential as a technique to investigate the molecular mechanisms of cellular phenomena,...

Current Advances and Limitations of Deep Learning in Anticancer Drug Sensitivity Prediction.

Current topics in medicinal chemistry
Anticancer drug screening can accelerate drug discovery to save the lives of cancer patients, but cancer heterogeneity makes this screening challenging. The prediction of anticancer drug sensitivity is useful for anticancer drug development and the i...

Strategies for Design of Molecular Structures with a Desired Pharmacophore Using Deep Reinforcement Learning.

Chemical & pharmaceutical bulletin
The goal of drug design is to discover molecular structures that have suitable pharmacological properties in vast chemical space. In recent years, the use of deep generative models (DGMs) is getting a lot of attention as an effective method of genera...

Identification of Key Features of CNS Drugs Based on SVM and Greedy Algorithm.

Current computer-aided drug design
INTRODUCTION: The research and development of drugs, related to the central nervous system (CNS) diseases is a long and arduous process with high cost, long cycle and low success rate. Identification of key features based on available CNS drugs is of...

Studies for Bacterystic Evaluation against of 2-Naphthoic Acid Analogues.

Current topics in medicinal chemistry
BACKGROUND: Staphylococcus aureus is a gram-positive spherical bacterium commonly present in nasal fossae and in the skin of healthy people; however, in high quantities, it can lead to complications that compromise health. The pathologies involved in...