AIMC Topic: Drug Discovery
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ChemMORT: an automatic ADMET optimization platform using deep learning and multi-objective particle swarm optimization.
Briefings in bioinformatics
Jan 22, 2024
Drug discovery and development constitute a laborious and costly undertaking. The success of a drug hinges not only good efficacy but also acceptable absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties. Overall, up to 5...
Integrative approach for predicting drug-target interactions via matrix factorization and broad learning systems.
Mathematical biosciences and engineering : MBE
Jan 18, 2024
In the drug discovery process, time and costs are the most typical problems resulting from the experimental screening of drug-target interactions (DTIs). To address these limitations, many computational methods have been developed to achieve more acc...
ASD2023: towards the integrating landscapes of allosteric knowledgebase.
Nucleic acids research
Jan 5, 2024
Allosteric regulation, induced by perturbations at an allosteric site topographically distinct from the orthosteric site, is one of the most direct and efficient ways to fine-tune macromolecular function. The Allosteric Database (ASD; accessible onli...
USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING APPROACHES TO ENHANCE CANCER THERAPY AND DRUG DISCOVERY: A NARRATIVE REVIEW.
Journal of Ayub Medical College, Abbottabad : JAMC
Jan 1, 2024
BACKGROUND: This paper looks at how AI and machine learning have been applied over the last ten years to the development of anti-cancer drugs. By speeding up the synthesis of more desirable compounds and the identification of new ones, artificial int...
Advances in Protein-Ligand Binding Affinity Prediction via Deep Learning: A Comprehensive Study of Datasets, Data Preprocessing Techniques, and Model Architectures.
Current drug targets
Jan 1, 2024
BACKGROUND: Drug discovery is a complex and expensive procedure involving several timely and costly phases through which new potential pharmaceutical compounds must pass to get approved. One of these critical steps is the identification and optimizat...
Development of Drug Discovery Platforms Using Artificial Intelligence and Cheminformatics.
Chemical & pharmaceutical bulletin
Jan 1, 2024
Recently, remarkable progress has been achieved in artificial intelligence (AI), including machine learning. Various AI models have been proposed for drug discovery, including the design of small molecules, activity prediction, and three-dimensional ...
Computational Methods and Artificial Intelligence in the Discovery and Development of Therapeutic Peptides and Beyond.
Current medicinal chemistry
Jan 1, 2024
Leveraging Artificial Intelligence for Synergies in Drug Discovery: From Computers to Clinics.
Current pharmaceutical design
Jan 1, 2024
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...
Developing a GNN-based AI model to predict mitochondrial toxicity using the bagging method.
The Journal of toxicological sciences
Jan 1, 2024
Mitochondrial toxicity has been implicated in the development of various toxicities, including hepatotoxicity. Therefore, mitochondrial toxicity has become a major screening factor in the early discovery phase of drug development. Several models have...
Revolutionizing Drug Discovery: The Role of Artificial Intelligence and Machine Learning.
Current pharmaceutical design
Jan 1, 2024
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