See also stories tagged with Drug discovery
Turbulence, the chaotic, irregular motion that causes the bumpiness we sometimes experience on an airplane, has intrigued scientists for centuries. At the Okinawa Institute of Science and Technology (OIST), researchers are ...
Researchers have discovered that a virus living inside the fungus Aspergillus fumigatus significantly boosts the fungus's ability to survive stress and cause severe infections in mammals. Removing the virus made the fungus ...
Most of the drugs, plastics, and industrial materials widely used today are produced through chemical reactions. In general, most high-performance and sophisticated substances have complex structures, and their assembly involves ...
Until now, the early phase of drug discovery for the development of new therapeutics has been both cost- and time-intensive. Researchers at KIT (Karlsruhe Institute of Technology) have now developed a platform on which extremely ...
Until now, the early phase of drug discovery for the development of new therapeutics has been both cost- and time-intensive. Researchers at KIT (Karlsruhe Institute of Technology) have now developed a platform on which extremely ...
Using machine learning, MIT chemical engineers have created a computational model that can predict how well any given molecule will dissolve in an organic solvent—a key step in the synthesis of nearly any pharmaceutical. ...
A new discovery from researchers at Northeastern University has uncovered previously unknown aspects of plant evolution, with major implications for creating new lifesaving drugs.
The trouble with many drugs is that they go where they shouldn't, producing unwanted side effects. Psychiatric drugs might cause dissociation, painkillers can induce nausea and chemotherapy often damages healthy cells. Now ...
Dr. Jake Johnson, cardiology resident at North Carolina State University's College of Veterinary Medicine, is the author of a recent article published in Frontiers in Veterinary Science. Here, he discusses his findings and ...
Deep learning models have shown great potential in predicting and engineering functional enzymes and proteins. Does this prowess extend to other fields of biology as well?
