The Society for Neuroscience announced today that it has awarded the Swartz Prize for Theoretical and Computational Neuroscience to Emery N. Brown, Edward Hood Taplin Professor of Medical Engineering and Computational Neuroscience at MIT.

Brown, a member of The Picower Institute for Learning and Memory and the Institute for Medical Engineering and Science as well as the Warren M. Zapol Professor at Harvard Medical School, is a neuroscientist, a statistician, and a practicing anesthesiologist at Massachusetts General Hospital. His research has produced principled and efficient new methods for decoding patterns of neural and brain network activity and has an advanced neuroscientific understanding of how anesthetics affect the brain, which can improve patient care. {module INSIDE STORY}

"Dr. Brown's seminal scientific contributions to neural signal processing and the theory of anesthetic mechanisms, together with his service as an educator and a physician, make him highly deserving of the 2020 Swartz Prize," SfN President Barry Everitt said in a press release announcing the award. "Dr. Brown has demonstrated an unusually broad knowledge of neuroscience, a deep understanding of theoretical and computational tools, and an uncanny ability to find explanatory simplicity lurking beneath complicated observational phenomena."

In its announcement, the world's largest neuroscience organization elaborated on the breadth and depth of Brown's influence in many lines of research.

"Brown's insights and approaches have been critical to the development of some of the first models estimating functional connectivity among a group of simultaneously recorded neurons," SfN's announcement stated. "He has contributed statistical methods to analyze recordings of circadian rhythms and signal processing methods to analyze neuronal spike trains, local field potentials, and EEG recordings."

With regard to anesthesiology, the statement continued: "Brown has proposed that the altered arousal states produced by the principal classes of anesthetics can be characterized by analyzing the locations of their molecular targets, along with the anatomy and physiology of the circuits that connect these locations. Overall, his systems neuroscience paradigm, supported by mechanistic modeling and cutting-edge statistical evaluation of evidence, is transforming anesthesiology from an empirical, clinical practice into a principled neuroscience-based discipline.

Brown said the recognition made him thankful for the chances his research, teaching, and medical practice have given him to work with colleagues and students.

"Receiving the Swartz Prize is a great honor," he said. "The Prize recognizes my group's work to characterize more accurately the properties of neural systems by developing and applying statistical methods and signal processing algorithms that capture their dynamical features. It further recognizes our efforts to uncover the neurophysiological mechanisms of how anesthetics work and to translate those insights into new practices for managing patients receiving anesthesia care.

"Finally," he added, "Receipt of the Swartz Prize makes me eternally grateful for the outstanding colleagues, graduate students, post-doc, undergraduates, research assistants, and staff with whom I have had the good fortune to work."

The prize, which includes $30,000, is being awarded during SfN's Awards Announcement Week Oct. 26-29.

Researchers harness information theory to better understand how to make complex and compact molecules resembling those in nature.

A team led by scientists at Scripps Research has developed a theoretical approach that could ease the process of making highly complex, compact molecules.

Such molecules are often found in plants and other organisms, and many are considered desirable starting points for developing potential new drugs. But they also tend to be highly challenging for chemists to construct and modify in the lab--a process called synthesis.

The team used supercomputer modeling and a theoretical framework centered on the concept of "information density" to illuminate chemistry principles underlying their landmark 2019 synthesis of the molecule bilobalide, which is produced in the leaves of the ginkgo tree, Ginkgo biloba. Bilobalide is a particularly complex and compact molecule that has shown promise as a potential neurological or psychiatric drug. {module INSIDE STORY} 

The scientists believe that the theoretical fruits of their new study, published in the Journal of the American Chemical Society, will enable chemists to devise more efficient syntheses of such challenging natural molecules--potentially opening up a new realm of powerfully bioactive compounds for development into medicines and other products.

"When we initially achieved our synthesis of bilobalide, we were essentially following our intuition, but in this new study we dug down to understand how the chemistry actually works and developed principles that we think can be applied to other challenges in organic synthesis," says Ryan Shenvi, Ph.D., a professor of chemistry at Scripps Research and the senior author of the study.

Creating a valuable natural compound

Bilobalide--which evolved in the ginkgo tree, likely to protect its leaves from insects--blocks an insect nerve-cell receptor called RDL. The fact that the molecule kills insects yet seems quite safe in mammals and dissipates quickly in the environment has attracted interest for safe crop protection.

Bilobalide holds strong promise for medicinal use, with evidence that it's relatively safe for humans. It blocks human brain-cell receptors called GABAA receptors, which are evolutionary cousins of insect RDL receptors. An intriguing 2007 study found that the compound could reverse cognitive and memory deficits in mice with a neurological condition modeling human Down syndrome, while other studies have suggested it may protect brain cells from certain kinds of harm.

Although natural bilobalide is synthesized by specialized enzymes in the ginkgo tree's cells, chemists would like to be able to make it in the lab with organic chemistry techniques. In this way, they could obtain large quantities of the compound and modify it to explore and optimize its properties.

But the synthesis of bilobalide has always been a major challenge for scientists because the molecule packs a relatively complex set of atoms--including eight reactive oxygens--into an odd and highly compact chemical structure. If they could overcome that challenge, chemists would have a way to make molecules of potentially enormous value.

"When you have complexity that is condensed to that extent, you start to see interesting emergent properties," Shenvi says.

'Information density' brings a deep understanding

In the study, Shenvi and his colleagues evaluated their 11-step synthesis of bilobalide, achieved in 2019, as well as two longer bilobalide syntheses that had been published previously.

With the help of computational modeling from collaborator Kendall Houk, Ph.D., the Saul Winstein Distinguished Research Chair in Organic Chemistry at UCLA, and a formal theory of "molecular information content" published in 2016 by German researcher Thomas Böttcher, they developed a concept of "information density"--essentially, complexity divided by molecular volume--and used that to analyze the bilobalide syntheses.

Their analysis showed that bilobalide, even compared with other naturally derived, compact, and biologically active molecules, has a very high information density and that its information content comes principally from its oxygen atoms and asymmetric carbon backbone.

The work revealed that the Shenvi lab's synthesis of bilobalide was efficient due to fragment coupling--merging already-complex oxygen-containing molecules--and then making careful modifications to overcome the unusual emergent properties of the system.

The chemistry principles the team developed make sense of their bilobalide synthesis and its greater efficiency over prior syntheses, but are also applicable to many other unsolved problems involving natural-molecule synthesis, the researchers say.

As part of the work, co-author Stefano Forli, Ph.D., wrote a computer script in the Python coding language to automate the calculation of molecular information, which can be otherwise laborious, at the rate of more than 100,000 molecules per minute. (The script is available for download.) Forli is an assistant professor in Scripps Research's Department of Integrative Structural and Computational Biology.

Collaborating investigator Marisa Roberto, Ph.D., a professor in the Department of Molecular Medicine at Scripps Research, studied the activity of bilobalide and another information-dense molecule, jiadifenolide, which Shenvi's team also recently synthesized. In rodent studies, she found that both bilobalide and jiadifenolide showed promise as relatively potent and safe GABAA blockers, suggesting the potential for being translated into drugs for psychiatric conditions involving abnormal GABAA activity.

"The GABA system is dramatically altered in neuropsychiatric disorders such as alcoholism and other forms of addiction, for which one or both of these compounds might one day prove useful," Roberto says.