AI Medical Compendium Topic:
Drug Design

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MvMRL: a multi-view molecular representation learning method for molecular property prediction.

Briefings in bioinformatics
Effective molecular representation learning is very important for Artificial Intelligence-driven Drug Design because it affects the accuracy and efficiency of molecular property prediction and other molecular modeling relevant tasks. However, previou...

Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides.

Briefings in bioinformatics
With their diverse biological activities, peptides are promising candidates for therapeutic applications, showing antimicrobial, antitumour and hormonal signalling capabilities. Despite their advantages, therapeutic peptides face challenges such as s...

NGCN: Drug-target interaction prediction by integrating information and feature learning from heterogeneous network.

Journal of cellular and molecular medicine
Drug-target interaction (DTI) prediction is essential for new drug design and development. Constructing heterogeneous network based on diverse information about drugs, proteins and diseases provides new opportunities for DTI prediction. However, the ...

Piquing artificial intelligence towards drug discovery: Tools, techniques, and applications.

Drug development research
The purpose of this study was to discuss how artificial intelligence (AI) methods have affected the field of drug development. It looks at how AI models and data resources are reshaping the drug development process by offering more affordable and exp...

A new paradigm for applying deep learning to protein-ligand interaction prediction.

Briefings in bioinformatics
Protein-ligand interaction prediction presents a significant challenge in drug design. Numerous machine learning and deep learning (DL) models have been developed to accurately identify docking poses of ligands and active compounds against specific t...

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...

Estimating protein-ligand interactions with geometric deep learning and mixture density models.

Journal of biosciences
Understanding the interactions between a ligand and its molecular target is crucial in guiding the optimization of molecules for any drug design workflow. Multiple experimental and computational methods have been developed to better understand these...

PD-1 Targeted Antibody Discovery Using AI Protein Diffusion.

Technology in cancer research & treatment
The programmed cell death protein 1 (PD-1, CD279) is an important therapeutic target in many oncological diseases. This checkpoint protein inhibits T lymphocytes from attacking other cells in the body and thus blocking it improves the clearance of tu...

Leveraging Artificial Intelligence for Synergies in Drug Discovery: From Computers to Clinics.

Current pharmaceutical design
Over the period of the preceding decade, artificial intelligence (AI) has proved an outstanding performance in entire dimensions of science including pharmaceutical sciences. AI uses the concept of machine learning (ML), deep learning (DL), and neura...

Peptidic Compound as DNA Binding Agent: Fragment-based Design, Machine Learning, Molecular Modeling, Synthesis, and DNA Binding Evaluation.

Protein and peptide letters
BACKGROUND: Cancer remains a global burden, with increasing mortality rates. Current cancer treatments involve controlling the transcription of malignant DNA genes, either directly or indirectly. DNA exhibits various structural forms, including the G...