AIMC Topic: Drug Development
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Performance of Force-Field- and Machine Learning-Based Scoring Functions in Ranking MAO-B Protein-Inhibitor Complexes in Relevance to Developing Parkinson's Therapeutics.
International journal of molecular sciences
Oct 16, 2020
Monoamine oxidase B (MAOB) is expressed in the mitochondrial membrane and has a key role in degrading various neurologically active amines such as benzylamine, phenethylamine and dopamine with the help of Flavin adenine dinucleotide (FAD) cofactor. T...
A Novel Strategy for the Development of Vaccines for SARS-CoV-2 (COVID-19) and Other Viruses Using AI and Viral Shell Disorder.
Journal of proteome research
Oct 2, 2020
A model that predicts levels of coronavirus (CoV) respiratory and fecal-oral transmission potentials based on the shell disorder has been built using neural network (artificial intelligence, AI) analysis of the percentage of disorder (PID) in the nuc...
Artificial Intelligence Effecting a Paradigm Shift in Drug Development.
SLAS technology
Sep 17, 2020
The inverse relationship between the cost of drug development and the successful integration of drugs into the market has resulted in the need for innovative solutions to overcome this burgeoning problem. This problem could be attributed to several f...
A learning-based method for drug-target interaction prediction based on feature representation learning and deep neural network.
BMC bioinformatics
Sep 17, 2020
BACKGROUND: Drug-target interaction prediction is of great significance for narrowing down the scope of candidate medications, and thus is a vital step in drug discovery. Because of the particularity of biochemical experiments, the development of new...
Quantitative retrospective natural history modeling for orphan drug development.
Journal of inherited metabolic disease
Sep 8, 2020
The natural history of most rare diseases is incompletely understood and usually relies on studies with low level of evidence. Consistent with the goals for future research of rare disease research set by the International Rare Diseases Research Cons...
Comparison of Conventional Statistical Methods with Machine Learning in Medicine: Diagnosis, Drug Development, and Treatment.
Medicina (Kaunas, Lithuania)
Sep 8, 2020
Futurists have anticipated that novel autonomous technologies, embedded with machine learning (ML), will substantially influence healthcare. ML is focused on making predictions as accurate as possible, while traditional statistical models are aimed a...
Ontological approach to the knowledge systematization of a toxic process and toxic course representation framework for early drug risk management.
Scientific reports
Sep 3, 2020
Various types of drug toxicity can halt the development of a drug. Because drugs are xenobiotics, they inherently have the potential to cause injury. Clarifying the mechanisms of toxicity to evaluate and manage drug safety during drug development is ...
The use of knowledge management tools in viroinformatics. Example study of a highly conserved sequence motif in Nsp3 of SARS-CoV-2 as a therapeutic target.
Computers in biology and medicine
Aug 13, 2020
Knowledge management tools that assist in systematic review and exploration of scientific knowledge generally are of obvious potential importance in evidence based medicine in general, but also to the design of therapeutics based on the protein subse...
The combination of artificial intelligence and systems biology for intelligent vaccine design.
Expert opinion on drug discovery
Jul 14, 2020
INTRODUCTION: A new body of evidence depicts the applications of artificial intelligence and systems biology in vaccine design and development. The combination of both approaches shall revolutionize healthcare, accelerating clinical trial processes a...
Drug-target interaction prediction using semi-bipartite graph model and deep learning.
BMC bioinformatics
Jul 6, 2020
BACKGROUND: Identifying drug-target interaction is a key element in drug discovery. In silico prediction of drug-target interaction can speed up the process of identifying unknown interactions between drugs and target proteins. In recent studies, han...
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