A project for the advancement of molecular simulations.
Molecular interactions are the fundamental basis upon which life exists. More specifically, interactions between specific atoms (as defined by their subatomic particles) make up the foundational framework of the biophysical properties of life. A vast array of molecules are involved in sustaining life, ranging from smaller molecules (such as H₂O, glucose, individual amino acids, lipids, etc.) to larger and more complex macromolecules (such as proteins, DNA, RNA, etc.). The known atomic composition of these molecules in combination with properties of molecular physics can be used to generate computational simulations reflecting their natural existence. Such simulations can integrate and account for varying physiological environments, mutagenically-induced variation in structural conformation, multi-component interactions, among numerous other variables. These simulations are designed to run alongside real-time physical screens for confirmation of accuracy. The incorporation of machine learning serves as an avenue for identifying drug targets and the development of novel therapeutic candidates at speeds exponentially greater than laborious manual research. Running advanced simulations without diminished accuracy requires remarkable and previously unavailable computational resources, a barrier which can now be overcome through advancements in the field of supercomputing.
Discovering and designing the next generation of therapeutics for chronic disease.
Human gene therapy has been a topic of controversy for decades, comprising of both successes and failures. Behind this matter is an unmet need for the multitude of genetic disorders lacking absolute treatments. The past decade has witnessed the revolutionary emergence and continued refinement of numerous gene-editing tools. These include CRISPR/Cas, multiple DNA & RNA variants, viral & nano-particle based delivery mechanisms, among others. Translational and therapeutic advances have arisen from progress in both practicality and safety, with multiple clinical trials using these tools currently underway. However, there are still many barriers left to overcome. Gene therapy applications are still in their infancy, and require further research and development. STEM Biomedical strives to continue this research to fulfill the promising potential of gene therapy as a viable treatment for numerous diseases.
Molecular graphics and analyses performed with UCSF Chimera, developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco, with support from NIH P41-GM103311. UCSF Chimera--a visualization system for exploratory research and analysis. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. J Comput Chem. 2004 Oct;25(13):1605-12.