Drug design is a scientific problem so important that researchers are willing to throw just about any kind of creative problem-solving approach at it, including tech-buzzwords like gamification and augmented reality. The latter approach comes from Arthur Olson's Molecular Graphics Laboratory at the Scripps Research Institute: He uses 3-D printers to spit out physical models of drugs and enzymes, and attaches augmented-reality tags to them so that computer vision can help researchers find the optimal fit.
The reason this approach is worth exploring is that designing drugs comes down to piecing together the molecular structure of their chemical parts in the best possible way, so that they literally latch onto the surface of their targets like a magnetic Tetris piece. Tactile feedback is a very powerful tool for this kind of puzzle-solving, which is where Olson's 3-D-printed models come in--think of it like playing with a Rubik's cube, except the solution may help cure HIV.
But this is science, after all, and fiddling with a physical model won't provide detailed measure-ments of molecular energetics. That's where the augmented reality comes in. A tag on the model is recognized by a webcam and Olson's software, which generates a pixel-accurate digital overlay on a computer screen that the researcher can watch like a real-time heads-up display as she manipulates the model. The digital overlay computes and displays all kinds of scientific detail that isn't manifest in the model, which can help guide the researcher's manipulations into even more productive directions.
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Finding the right molecular "fit" isn't something that can be effectively calculated using brute force--it has to be discovered, using a fusion of human intuition and digital visualization. Olson's interface ingeniously combines both kinds of intelligence in a way that lets them complement each other instead of get in the way, so that unexpected breakthroughs may have a better chance at surfacing.
COMMENTARY: I have always been fascinated with molecular engineering (ME), or the science of manufacturing molecules. ME may be used to create, on an extremely small scale, most typically one at a time, new molecules which may not exist in nature, or be stable beyond a very narrow range of conditions.
Historically, ME is an extremely difficult process, requiring manual manipulation of molecules using devices such as a scanning tunneling microscope (STM), an instrument for imaging surfaces at the atomic leve.
ME is a precision form of chemical engineering-- the design, improvement and maintenance of processes of transforming raw materials or chemicals into more useful or valuable forms.
ME is an important part of pharmaceutical research for new drug design and materials science. Chemical or biological transformations includes protein engineering, the creation of protein molecules, a process that occurs naturally in biochemistry. However, ME provides far more control than genetic modification of an existing genome, which must rely strictly on existing biochemistry to express genes as proteins, and has little power to produce any non-proteins.
In the following video, professor Arthur J. Olson of the Scripps Research Institute demonstrates a 3D printed model of a virus that self assembles when shaken.
Professor Olson is head of the Molecular Graphics Laboratory, which uses 3D computer models, 3D printing, and augmented reality to create tools for life science researchers and educators. He is also the project leader of Fight Aids at Home, a tool that allows home computer users to share their resources as part of a massive project to find new HIV drugs.
Work Of Olson's Molecular Graphics Laboratory
Anti-HIV Drug Design
- HIV-1 protease, or PR, is essential to the replication of human immunodeficiency virus-1, and is consequently the target of major drug design programs worldwide. Our computational work is part of a closely-knit Program, involving several other laboratories, to develop both novel and mature tools to aid in the drug design cycle for anti-retroviral agents. The program consists of the following integrated parts:
- Computational methods for docking active site ligands (inhibitors), and for elaboration and refined design of inhibitor lead compounds;
- Design and chemical synthesis of retroviral protease inhibitors using new chemical approaches;
- X-ray crystallographic studies of the feline immunodeficiency virus (FIV PR) and inhibitor complexes;
- Molecular biology/virology of the FIV system.
- Our laboratory is exploring a new paradigm in distributed computing, by launching www.FightAIDSatHome.org in September 2000. Tens of thousands of people around the world run AutoDock on HIV Protease on their personal computers. The goal? To design better protease inhibitors that are more robust in the face of HIV resistance.
Ligand-Protein Docking
- AutoDock: rapid automated docking of flexible ligands to macromolecules, with estimated free energies of binding and genetic algorithm-based searching.
- Vina: new program for fast receptor-ligand docking and affinity prediction.
- AutoDockTools (ADT) is a GUI that can be used to set up dockings, as well as view and analyze the results.
Python Software Development
- Related links - papers, documentation, tutorials, downloads. (March 2001)
Protein-Protein Docking
- Spherical harmonics approximation of molecular surfaces.
- Evolutionary programming for protein-protein docking.
Protein Folding
Macromolecular Visualization
- Rapid calculation of molecular surfaces.
- Simulation of molecules in living cells.
- Macromolecular animation and illustration.
Tangible Molecular Models
- Tangibles Interfaces for Molecular Biology
- PyARTK: an augmented reality toolkit.
- Images of Molecular Model Prototypes.
Molecular Cell Biology of Tissue Factor and Endothelia
- The goals of this project are elucidation of the molecular biology, structure-functionrelationships and three-dimentional structure of tissue factor.
Courtesy of an article dated October 20, 2011 appearing in Fast Company Design
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