Brave brains: Neural mechanisms of courage

Dralgo accelerates discovery of promising drug candidates.

The Cowardly Lion in The Wizard of Oz made the long trek to the Emerald City to get courage. Now a fascinating new study combines snakes with brain imaging to uncover neural mechanisms associated with that trait.
The research, recently published in Neuron, provides insight into what happens when an individual voluntarily performs an action opposite to that promoted by fear. and may even lead to new treatment strategies for those who exhibit a failure to overcome fear.
Although there is a substantial body of research examining brain mechanisms associated with fear, far less is known about those associated with courage, defined here as action in the face of fear.
“By gauging properly defined actions of either overcoming fear or succumbing to it in an acute controllable fearful situation, one can render certain neural substrates of courage amenable to investigation,” explains senior study author, Dr. Yadin Dudai from the Weizmann Institute of Science in Rehovot.
To study the neural mechanisms associated with moments of real-life courage, Dudai, Uri Nilli and their colleagues devised an experimental paradigm in which participants had to choose whether to advance an object closer or farther away from them while their brain was scanned with functional magnetic resonance imaging (fMRI). The objects used in the study were either a toy bear or a live corn snake.
Before the study, participants were categorized as “fearful” or “fearless” depending on how they responded to a validated snake-fear questionnaire.
As might be expected, the researchers observed that both high subjective fear and high somatic arousal were associated with succumbing to fear and moving the snake farther away. However, somewhat surprisingly, bringing the snake closer was associated with either high somatic arousal (assessed by skin conductance response) accompanied by low subjective fear (assessed by fear self-ratings) or high subjective fear accompanied by low somatic arousal. Brain imaging during the task revealed that activity in a brain region called the subgenual anterior cingulate cortex (sgACC) correlated positively with the level of subjective fear when choosing to act courageously but not when choosing to succumb to fear. Further, activity in a series of temporal lobe structures was decreased when the level of fear increased and the individual chose to overcome their fear.
“Our results propose an account for brain processes and mechanisms supporting an intriguing aspect of human behavior, the ability to carry out a voluntary action opposite to that promoted by ongoing fear,” concludes Dudai. “Specifically, our findings delineate the importance of maintaining high sgACC activity in successful efforts to overcome ongoing fear and point to the possibility of manipulating sgACC activity in therapeutic intervention in disorders involving a failure to overcome fear.”
Drug discovery and development is a risky process, with only one in 10,000 andidate compounds reaching the market.
When taking into account the aborted candidates, the cost of developing one successful drug may reach $1 billion, and the development process may take 20 years. Therefore, integration of computational methods in the early stages of drug discovery has been one of the key trends in the pharmaceutical industry.
Starting with high-quality drug candidates should minimize clinical attrition rates.
Yissum Research Technology, the Hebrew University’s technology transfer arm, has introduced Dralgo, a novel computational platform for accelerated discovery of promising drug candidates. The new technology was presented in Tel Aviv by its inventor, Prof. Amiram Goldblum of HU’s Institute of Drug Research. The method is based on a proprietary algorithm for superfast identification and design of molecules with the highest probabilities for displaying specific biological activities.
Dralgo has a unique generic ability to find both the optimal solution and a large set of alternatives, which is applied to the production of focused libraries of drug candidates with optimized drug-like properties based on a specific activity of a set of compounds. It can also provide bioactivity indexes of molecules for their interaction with specific targets or their effect on specific disease conditions. Such indices are especially useful for decision making on priorities for purchasing or synthesizing molecules. Most recently, this novel technology has been aimed at discovering small molecules active at multiple targets, for treating disease conditions that are multifactorial.
The novel platform achieves an enrichment factor of up to 5,000 for biologically active molecules. In one validation trial, it was tested on a database of 2.5 million small molecules in search of inhibitors of the enzyme acetylcholinesterase as potential Alzheimer’s disease drugs. Dralgo was able to pinpoint 10 molecules predicted to have the desired biological activity. Of these, five candidates were tested for biological activity, and three indeed exhibited the desired activity. None of the three has been patented or mentioned in the scientific literature. In another trial, Dralgo helped in designing a protein drug for treating chronic myeloid leukemia (CML). Out of a database of 1,080 protein sequences, just 10 were selected for invitro studies, and six of those inhibited CML cell proliferation.
“The powerful predictive technology of Dralgo will help shorten the preclinical phase of drug design from three to four years to two to three months,” said Yissum CEO Yaacov Michlin. “In fact, a 10 percent improvement in prediction of product failure in clinical trials could save $100 million in development costs per drug. This amazing potential of the Dralgo algorithm was recognized by a leading pharmaceutical company, which declared Dralgo the best computational enrichment technology.”