The project, “Targeting FABPs,” is designated to the Institute for Chemical Biology & Drug Discovery (ICB&DD) at Stony Brook. Led by Principal Investigator Dale Deutsch, Professor of Biochemistry and Cell Biology, and a member of the ICB&DD, the project involves researchers and students from four different Stony Brook University academic departments, the ICB&DD, and the Laufer Center for Quantitative and Physical Biology.

FABPs are a family of small soluble protein carriers for fatty substances in cellular metabolism that transport the neurotransmitter known as AEA (endocannabinoid anadamide) from the cell membrane to interior of the cell where the AEA is destroyed which causes pain signals to increase. AEA and other endocannabinoids are compounds in the brain, similar to THC (the active ingredient in marijuana), which plays a role in numerous physiological processes, including appetite, memory and pain. With the NIDA funding, the research team is trying to determine if by inhibiting FABPs, the breakdown of AEAs is reduced and thereby pain can be minimized.

“The major goal of our drug discovery proposal is to develop drugs that inhibit these neurotransmitter transporters,” said Deutsch. “We expect that by targeting FABPs with certain compounds made by the ICB & DD group, endocannabinoid levels will increase within the brain, essentially resulting in anti-pain and anti-inflammatory effects.”

Deutsch said the team’s targeted strategy that reduces neurotransmitter breakdown may alleviate symptoms of drug withdrawal as does the nicotine patch for smokers or methadone for opiate replacement. He added that an additional advantage of the strategy is that by creating neurotransmitter levels to increase naturally, pain would theoretically be curbed without negative side effects, such as motor coordination problems.

A series of findings since the project began have helped to advance the research. First, in 2007 Dr. Martin Kaczocha, then a graduate student in Deutsch's laboratory, now an Assistant Professor in the Department of Anesthesiology, identified the FABPs as transporters for endocannabinoids. This discovery was published in an article that appeared in the April 14, 2009 issue of the Proceedings of the National Academy of Sciences (PNAS) entitled “Identification of intracellular carriers for the endocannabinoid anandamide.”

The research project built up further momentum later that year when Deutsch and Kaczocha presented Dr. Iwao Ojima, Stony Brook University Distinguished Professor of Chemistry and Director of the ICB&DD, with the concept of the therapeutic potential of small molecules that target FABPs. Through the ICB&DD, additional researchers became involved in the project. The expanded ICB&DD research team discovered a class of compounds that display significant inhibitory activity against FABPs. By using a computer modeling process led by collaborator Dr. Robert Rizzo, Associate Professor of the Department of Applied Mathematics and Statistics and member of the Laufer Center, the team screened more than one million compounds and identified lead compounds with molecule binding profiles similar to oleic acid, a natural FABP substrate. They selected 48 of these identified compounds, and are using chemical synthesis methods to identify other potential AEA-inhibitory agents that are both effective and safe.

Rizzo said as the research progressed he found it especially exciting to work “hand in hand with traditional experimental laboratories to identify and design inhibitors which target a specific protein.”

“It turned out that the core structure of what our research team determined to be the most promising compounds, known as ‘truxilloids,’ are found in a traditional Chinese medicine, called ‘incarvillaterine,’ which have been used for centuries to treat rheumatism and pain,” said Deutsch.

The investigators published their results on “truxilloids” in research article that appeared in the December 7, 2012 edition of PLOS ONE entitled, “Targeting Fatty Acid Binding Protein (FABP) Anandamide Transporters – A Novel Strategy for Development of Anti-Inflammatory and Anti-Nociceptive Drugs.” They showed that inhibition of FABPs and the subsequent elevation of the neurotransmitter AEA is a promising new targeted treatment approach against pain and inflammation.

“This collaborative effort among our ICB&DD faculty has the potential to lead to new treatments for many diseases and conditions that affect millions worldwide,” said Ojima. “The NIDA grant is a major step that will help provide the resources to discover and develop novel therapeutics, as well as shed light on the fascinating neurobiological processes involving FABP. This is exemplary multidisciplinary and collaborative research that the ICB&DD has been successfully promoting.”

Bill Berger (BS, Chemistry ’05) a PhD candidate in Dr. Ojima’s laboratory who will defend his dissertation on this work in December this year, synthesized and purified a variety of truxillic acid analogs, a crucial step that led to the identification of the most promising FABP inhibitors. He described this research project "as a high point in my PhD career, especially when in 2012 I described these findings to 300 leading scientists at the International Cannabinoid Research Society in Germany."

“Bill Berger has been the driving force for the promotion of this project from the onset of his multidisciplinary collaboration,” said Ojima. “He has a truly exceptional ability to execute chemical synthesis, computational biology and drug design with an excellent understanding of biology. He is an independent and creative thinker, but at the same time an excellent team player. Thus, he worked closely with Rizzo, Kaczocha, Deutsch and me without any difficulty in understanding all aspects of the project.”

Brian Ralph, a junior Biology major at Stony Brook (with a focus in Quantitative Biology), a co-author on the PLOS ONE paper, biochemically screened compounds selected by the virtual program and discovered the top inhibitor, the current drug lead in the project, alpha-truxilic acid. He subsequently pursued binding studies of several alpha-truxilic acid analogues to determine how strongly each structure interacted with the target FABPs and to identify which analogue would be the best potential inhibitor of these proteins.

The research team also includes Dr. Trent Balius and William Joseph Allen in SBU’s Department of Applied Mathematics and Statistics; structural biologist Dr. Huilin Li who has dual appointments in the SBU Department of Biochemistry and Brookhaven National Laboratory; and, Dr. Samir Haj-Dahmane of the Research Institute on Addictions at the University of Buffalo.

Initial funding for the research began with a SBU-BNL seed grant to Dr. Deutsch and Dr. Li from Stony Brook University and Brookhaven National Laboratory in 2010, followed by a Stony Brook University School of Medicine Targeted Research Opportunities (TRO) Fusion award to Drs. Deutsch, Li, and Ojima as well as a New York State SUNY REACH grant for Drs. Deutsch and Haj-Dahmane. Dr. Deutsch also received a previous single investigator grant from the NIH to research FABPs.

Maslov and Pang set out to determine not only why some specialized genes or computer programs are very common while others are fairly rare, but to see how many components in any system are so important that they can't be eliminated. "If a bacteria genome doesn't have a particular gene, it will be dead on arrival," Maslov said. "How many of those genes are there? The same goes for large software systems. They have multiple components that work together and the systems require just the right components working together to thrive.'"

Using data from the massive sequencing of bacterial genomes, now a part of the DOE Systems Biology Knowledgebase (KBase), Maslov and Pang examined the frequency of usage of crucial bits of genetic code in the metabolic processes of 500 bacterial species and found a surprising similarity with the frequency of installation of 200,000 Linux packages on more than 2 million individual computers. Linux is an open source software collaboration that allows designers to modify source code to create programs for public use.

The most frequently used components in both the biological and computer systems are those that allow for the most descendants. That is, the more a component is relied upon by others, the more likely it is to be required for full functionality of a system.

It may seem logical, but the surprising part of this finding is how universal it is. "It is almost expected that the frequency of usage of any component is correlated with how many other components depend on it," said Maslov. "But we found that we can determine the number of crucial components – those without which other components couldn't function – by a simple calculation that holds true both in biological systems and computer systems."For both the bacteria and the computing systems, take the square root of the interdependent components and you can find the number of key components that are so important that not a single other piece can get by without them.

Maslov's finding applies equally to these complex networks because they are both examples of open access systems with components that are independently installed. "Bacteria are the ultimate BitTorrents of biology," he said, referring to a popular file-sharing protocol. "They have this enormous common pool of genes that they are freely sharing with each other. Bacterial systems can easily add or remove genes from their genomes through what's called horizontal gene transfer, a kind of file sharing between bacteria," Maslov said.

The same goes for Linux operating systems, which allow free installation of components built and shared by a multitude of designers independently of one another. The theory wouldn't hold true for, say, a Windows operating system, which only runs proprietary programs.

Maslov is co-principal investigator in the KBase program, which is led by principal investigator Adam Arkin of DOE's Lawrence Berkeley National Laboratory, with additional co-principal investigators Rick Stevens of DOE's Argonne National Laboratory and Robert Cottingham of DOE's Oak Ridge National Laboratory.  Supported by DOE's Office of Science, the KBase program provides a high-performance computing environment that enables researchers to access, integrate, analyze and share large-scale genomic data to facilitate scientific collaboration and accelerate the pace of scientific discovery. 

DOE's Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov.

An NPR interview with Maslov on April 2 can be found on iTunes. Articles in Phys Rev and Gismodo also describe this work.

In a review article published in the Nov. 23, 2012 issue of the journal Science, Stony Brook University researchers reviewed the progress on a 50-year-old puzzle called the Protein Folding Problem. Ken Dill and Justin MacCallum of Stony Brook’s Louis and Beatrice Laufer Center for Physical and Quantitative Biology show how a community of scientific researchers rose to tackle a grand-challenge problem of very basic science that had no obvious payoff at the time.

“Protein folding is a quintessential basic science. There has been no specific commercial target, yet the collateral payoffs have been broad and deep,” the researchers said in their paper, The Protein Folding Problem, 50 Years On. 

{youtube}http://www.youtube.com/watch?v=SxAqyw9hr4k&feature=relmfu|560|315|1{/youtube} 
“We have learned that proteins fold rapidly because random thermal motions cause conformational changes leading energetically downhill toward the native structure, a principle that is captured in funnel-shaped energy landscapes. And thanks in part to the large Protein Data Bank of known structures, predicting protein structures is now far more successful than was thought possible in the early days. What began as three questions of basic science one half-century ago has now grown into the full-fledged research field of protein physical science.”

This year marks the 50th anniversary of the 1962 Nobel Prize in Chemistry awarded to Max Perutz and John Kendrew for their pioneering work in determining the structure of globular proteins. That work laid the foundation for structural biology, which interprets molecular level biological mechanisms in terms of the structures of proteins and other biomolecules. Their work also raised the question of how protein structures are explained by physical principles.

Since Perutz and Kendrew discovered the structures of two proteins, nearly 80,000 protein structures have been discovered.  The protein folding "problem" arose when Perutz and Kendrew were unable to make sense of how the folded structure of the protein molecule was related to its sequence of bead types.  Ever since then, there has been great interest in understanding the protein-folding "code": how does a given string of amino acids lead to a particular balled-up ("native") structure of a protein?

Proteins are molecules that perform the basic functions in biological cells – converting food to growth, to repairing DNA molecules and damaged cell parts, to motion in muscles, to transduction of signals in the brain and light in the eye, for example.  Humans have about 20,000 different types of protein molecules.  Each performs a different function.  The abilities of proteins to perform such a broad array of powerful chemical functions arise from a peculiar principle of chemical structure and function, namely the folding of each protein.  A protein is miniature string of beads, like a pearl necklace, where the bead-like component pieces are called amino acids.  Amino acids come in 20 different types.  The folding principle is that different sequences of amino acids strung together cause different protein molecules to ball-up in very specific, but different, ways, giving rise to their very different functionalities.  

The protein folding problem became a set of three inter-related puzzles: What is the folding code?  How does the protein find its one native structure in fractions of a second inside the cell (the needle-in-a-haystack problem)?  And: Can we make a computer method that can discover new structures of proteins from the large number of amino acid sequences that are now known? 

Dill, Director of the Laufer Center and Distinguished Professor of Physics and Chemistry, and MacCallum, a junior fellow at the Laufer Center, describe how huge advances have been made on all three fronts.  They detail some very important collateral payoffs of this work that was completely unanticipated at the time, including the development of the IBM Blue Gene computer and distributed-grid computing, computer-based methods for discovering new pharmaceuticals, a deeper understanding of molecular mechanisms in biology, a deeper understanding of the inter-atomic interactions inside proteins (that has also involved Stony Brook Laufer Center researchers Carlos Simmerling, David Green, and Rob Rizzo), and a new class of very promising polymer materials called "foldamers".  

Dill and MacCallum argue that what started out as one compelling question of basic science has now become an entire field of theoretical and experimental approaches in which many questions are now leading to a few answers and many more questions.

“Communicating science is not about losing accuracy; you can still convey your ideas precisely but with less detail so that people understand what you are doing and why. You want to make your audience curious and then let them ask afterward for details. If you start with the details ... you'll never get your science across.”

How did you get interested in science?

“Since I was small I had lots of opportunities - my dad is a scientist, and there were plenty of books around me so I guess that sparked my interest in science. I was born in Barcelona, Spain but I came to the US for middle school, which helped me learn English … which made it so much easier for me in science.”

What brought you to Stony Brook?

“I did my undergrad in Chemistry and my PhD in DNA flexibility at the University of Barcelona. When I started looking for a Postdoc position I interviewed with Ken Dill at the University of California San Francisco to study protein folding. When I got to San Francisco I was told it was likely that Ken’s group was going to move to Stony Brook. Ken gave me the options of looking for another group at UCSF, working remotely from UCSF or moving with him to a new center full of new opportunities … so I decided to come to Stony Brook.” Alberto is now a Postdoctoral Associate in the new Laufer Center for Physical and Quantitative Biology under the direction of Professor Dill.

“Initially I was afraid of leaving UCSF because of the high level of NIH funding awarded there and because there were several Nobel Laureates on campus so I thought I might not have the same level of opportunities at SBU as I would at UCSF, but actually I’ve increased my network considerably since coming to Stony Brook. And also working with the Postdoc Working Group allows me to take part in shaping events for Postdocs on campus, which is a very rewarding experience.”

What accomplishments are you most proud of since arriving at Stony Brook?

“I just finished participating in CASP, an event that takes place every other year, which stands for Critical Assessment for Structural Prediction. The competition runs throughout the summer and consists of regularly receiving different protein sequences for which you have three weeks to predict the structure. Basically the competition is a way of blind testing protein predictions methods from all around the world. At the present time the methods to characterize proteins directly via experiments are expensive and limited, so we are trying to use computational tools to allow us to get some insight. This competition gave us the chance to use some of the new resources at the Laufer Center and assess the effectiveness of our methods and how they compare to cheaper but less principle-based methods.

“In a nutshell, proteins do most things inside us. We want to know what proteins look like so we can better understand how they work and how to correct them when they go wrong. Basically there are two approaches for predicting a protein’s structure. One approach is: if it looks like a duck and quacks like a duck then it must be a duck so it must have a duck’s shape, and applying that approach to proteins means that similar protein sequences probably have the same structure.

“Our approach is based on physics. We say: here are the equations of motions and these are the laws of physics governing different kinds of interactions in a given protein. We allow these interactions to drive the protein from its initial disordered state until we get a folded protein. This approach is much more computationally intense, but the insights we get are much more realistic. We just finished the competition last week and will find out how we did in about a month.”

What are your future goals?

“In the short-term I plan to continue working at the Laufer Center and to take advantage of the opportunities here to grow as a scientist and as a person, to better prepare myself for the next stage which will hopefully be a tenure track position … somewhere.”

What advice might you have for other Postdocs here at Stony Brook?

“While you are a Postdoc, try to plan where you see yourself in a year’s time and work towards that goal. Also keep an open mind: No matter how much you plan, things change in your life and you have to adapt. Don’t get frustrated by a change in your plans … and network … a lot.”

What is your favorite word or phrase?

“Move slow, think fast.”

What is your favorite sound?

“Its absence.” 

What is your favorite hobby?

“Sports, especially soccer, reading and trying to learn Japanese.”

For more information about the upcoming Postdoc Research Symposium, please visit http://www.stonybrook.edu/commcms/postdoc/archivedevents/researchsymposium/researchsymp.html.

To learn more about Alberto Perez, you can visit his website at: http://alberto4web.wordpress.com

Less vulnerable to chemical or metabolic breakdown than proteins, peptoids are promising for diagnostics, pharmaceuticals, and as a platform to build bioinspired nanomaterials, as scientists can build and manipulate peptoids with great precision. But to design peptoids for a specific function, scientists need to first untangle the complex relationship between a peptoid’s composition and its function-defining folded structure.

Past efforts to predict protein structure have met with limited success, but now a scientific team led by Glenn Butterfoss, and Barney Yoo, research scientists at New York University, in collaboration with investigators from the U.S. Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab), Stony Brook University and Temple University have demonstrated that a computer modeling approach similar to one used to predict protein structures can accurately predict peptoid conformation as well.

The authors describe this accomplishment in a new paper in the Proceedings of the National Academy of Sciences (PNAS) titled, “De novo structure prediction and experimental characterization of folded peptoid oligomers,” coauthored by Jonathan Jaworski, Ilya Chorny, Ken Dill (Director of the Laufer Center), Ronald Zuckermann, Richard Bonneau, Kent Kirshenbaum, and Vincent Voelz.

“Natural selection has engineered protein sequences that can self-assemble into molecular machines with specific functions. Why can’t we do the same with biologically inspired synthetic materials?” Voelz, Principal Investigator with Temple University, explains.

With this mission in mind, the collaborative team of scientists developed the project two years ago at the 7^th Peptoid Summit, a – conference devoted to peptoid research hosted by Berkeley Lab’s Molecular Foundry.

“The research was carried out by a remarkable, interdisciplinary team of scientists,” says Kent Kirshenbaum of NYU. “Some of the team have worked together on this truly difficult problem for almost 20 years. The researchers include both experimentalists and theorists who have been able to guide one another in discovering how these peptoid molecules fold.”

Together, they proposed a ‘blind structure prediction’ challenge. This self-assessment technique, responsible for the enormous progress in the world of protein structure modeling, allows scientists to test the fidelity of their computational models by predicting the three-dimensional structure of a known molecule and then comparing their proposed structure to the X-ray crystallography results.

An analogous, combined experimental-computational method was employed by the peptoid team in an effort to advance the computational design of peptoid structure. X-ray crystal structures for three peptoid molecules, two small and linear and one larger and cyclical, were simultaneously determined, but not disclosed to the theoretical modelers. The experimentalists then used a combination of two simulation techniques, Replica Exchange Molecular Dynamics (REMD) simulation and Quantum Mechanical refinement (QM). REMD can efficiently predict the preferred general conformations, and the QM calculations further refine the conformational prediction. In combination, these two calculations accurately define the physical structures of molecules.

The proposed structural predictions of the peptoid molecules did exceedingly well at calculating the actual folded conformations. The first two blind predictions were calculated for two linear, small N-alkyl and N-aryl peptoid trimers. Of these, the N-aryl peptoid trimer was the best blind prediction, matching the crystal described conformation to within 0.2 Å. The N-alkyl trimer prediction matched less well with the crystal results because of its increased flexibility.

The greater challenge facing the group was structural prediction of the larger, cyclic peptoid nonamer. Six different possible conformations were considered for the final, submitted prediction and the top pick proved to agree best with the crystallography results to an accuracy of 1.0 Å.

This success suggests that reliable structure prediction for complex three-dimensional folds is within reach, an enormous step forward on the path to reliable and efficient computational peptoid design.

“This will hopefully break open the field of peptoid structure prediction and design, an area we desperately need to guide our more well-developed synthetic efforts,”

says Ron Zuckermann, co-author and director of the Biological Nanostructures Facility at Berkeley Lab’s Molecular Foundry.

“It is an exciting time for peptoid research,” says author Glenn Butterfoss, research scientist with NYU. “The community of labs working on these molecules is growing, and both the diversity and creativity of recent studies is quite astonishing. We hope our work here, aimed toward understanding the structural behavior of peptoids in three dimensional space, serves as a building block for future efforts to design peptoid molecules with practical functions.”

Portions of this work were performed at the Molecular Foundry, Lawrence Berkeley National Laboratory, and supported by the DOE Office of Science. Additional funding came from the Defense Threat Reduction Agency, the NSF and the NIH.

“This is not a matter of just curiosity. Most medicines interact with proteins and alter their behavior,” explained Stony Brook biochemist Alberto Perez, one of the lead researchers on the project. “If we want to design better medicines, we need to know what proteins look like.”

The award, which comes from the DOE’s Advanced Scientific Computing Research Leadership Computing Challenge, is for up to two million processing hours on the Titan supercomputer at Oak Ridge. Titan is an upgrade of Jaguar, a supercomputer that was recently named the sixth most powerful in the world by the TOP500 ranking system. Some scientists believe that Titan will contend for the number-one spot when it comes online later this year.

Titan has an unusual configuration: it will run on graphical processing units (GPUs) i addition to central processing units (CPUs). GPUs, originally developed by the technology company NVIDIA to render images in video games, are particularly efficient for repetitive tasks. By re-appropriating GPUs to solve scientific problems, Titan will become part of a burgeoning new approach in computational analysis.

Perez’s team will use Titan to run AMBER, a software package that simulates the effect of different force fields on organic molecules such as proteins to determine the most likely folding configuration. This method is a fast and effective complement to conventional protein imaging methods such as x-ray crystallography or nuclear magnetic resonance imaging.

“With the GPU port to AMBER, we are able to obtain in days in one single GPU the sampling that we were able to accomplish in several months of simulation using multiple CPUs,” said Perez.

The trick is finding the right set of rules to limit AMBER’s massive search. The team believes they will be successful by focusing on the “first principles” that govern physical interactions in molecules while simplifying the representation of electron and nucleus behavior. These restraints are built into AMBER’s classical molecular dynamics machinery.

The team plans to test their approach in the Critical Assessment of Protein Structure (CASP), a competition in which groups have just three weeks to guess at a particular protein’s folds. Having the opportunity to run a simulation on Titan will be a big advantage.

“Getting into the competition is part of the motivation, but it’s not the whole story,” said Yan Li, a physicist at Brookhaven. If their model scores well against CASP’s experimentally derived structure, then they want to apply their approach to membrane proteins, which are important therapeutic targets that are particularly difficult to crystallize. “Eventually, we want to make the method more rigorous,” Li said.

Perez and Li are joined on the project by Stony Brook’s Laufer Center Director Ken A. Dill and Junior Fellow Justin MacCallum; Brookhaven Computational Science Interim Director Mike McGuigan; and Vageli Coutsias, a mathematics professor at the University of New Mexico.

“It’s not just inter-institutional. It’s interdisciplinary. We want to take advantage of the expertise of biology, chemistry, and physics,” Li said. 

The plant, Rafflesia cantleyi, is an obligate holoparasite dependent on its host, Tetrastigma rafflesiae, a member of the grape family, for sustenance. Rafflesias have the largest known flowers at approximately three feet across.

A team of researchers led by Professor Rest and Professor Davis collaborated to systematically investigate the extent of horizontal gene transfer between these two plants. By looking at the transcriptome, the transcribed products of switched on genes, they found 49 genes transcribed by the parasite, accounting for 2% of their total transcriptome, which originally belonged to the host. Three quarters of these transcripts appear to have replaced the parasites' own version.

"This research suggests that this horizontal gene transfer may be important to the parasitic lifestyle of this very unusual plant," said Professor Rest. "These transferred genes have been integrated and are expressed in the host genome." The transferred genes have a wide range of functions, appear to be fully operational, and have become integrated into the nuclei of the parasite's cells. Such gene transfer between species is common in bacteria, but rare in more complex organisms.

"Our study suggests that the Rafflesia genome may have evolved to mimic the genome of its host," said Professor Rest. "This study highlights the power of genomics to learn about the life history and evolutionary strategies of the diversity of life."

Professor Rest's lab uses both bioinformatic and experimental approaches to study the evolution of gene regulation and the consequences of variation in gene expression on the fitness of organisms. He is an associate member of the Laufer Center for Physical and Quantitative Biology <http://laufercenter.stonybrook.edu/> at Stony Brook and has published 18 articles in various publications, including: PLoS ONE, Human Molecular Genetics, Journal of Molecular Evolution, BMC Biology, Infection, Genetics and Evolution and more. He received his BS in Biology from Drake University (1999) and his PhD in Ecology and Evolutionary Biology from the University of Michigan (2004).

The Laufer Center, which is housed in a newly remodeled building (formerly the Stony Brook University Life Sciences Library), started operation in February of 2011 with a major philanthropic gift in loving memory of Louis and Beatrice Laufer by their children Henry and Marsha Laufer, Helen Laufer Kaplan and Howard Kaplan, and Jeffrey and Barbara Laufer. The Center supports two endowed professorships and an endowed chair.
 
The Laufer family is very pleased to partner with Stony Brook University in creating the Louis and Beatrice Laufer Center for Physical and Quantitative Biology," said Drs. Henry and Marsha Laufer in a joint statement. "This new facility that houses the Center is not only spacious and lovely, but is also ideally located adjacent to the Life Sciences Building and across the street from the Health Sciences Center. We wish the very best to the faculty and staff of the Laufer Center, and look forward to the excellent science that they will produce here.  We thank Stony Brook University for all that they have done to make possible the Laufer Center."

The Laufer Center was designed by architect Jim Braddock of the New York City architectural firm of Mitchell-Giurgola. The Center houses a 73-seat teleconferencing auditorium, a Mediascape collaborative research station and an advanced GPU + CPU computing cluster that currently gives the Center the power of nearly 9000 computer cores. 
  
Research at the Center focuses on solving challenging problems at the interface between the physical and life sciences. As an example, a deeper knowledge of the physical bonding forces within molecules will help to improve the computer algorithms that are increasingly used to design next-generation pharmaceuticals and biotech drugs, and to understand the mechanisms of action of proteins. In addition, a deeper understanding of the mathematical principles that describe the network of interrelationships among the thousands of biochemical reactions and genetic control circuits inside cells will aid in developing next-generation approaches for curing diseases. 
  
“On behalf of Stony Brook University, we are deeply honored that the Laufer Family is tying the legacy of their parents to the future of Stony Brook with the establishment of the Louis and Beatrice Laufer Center for Physical and Quantitative Biology,” said Samuel L. Stanley Jr., MD, President of Stony Brook University. “There is no doubt that this state of the art Center, under the direction of Ken Dill, creates a new nexus for excellence in the studies at the intersection of physics, mathematics, chemistry, computational science and biology. This is a place where we can assemble the brightest minds and provide them with the opportunity to succeed so they can discover new medicines, continue to decipher the human genome and further our understanding of how healthy biological cells work and how diseased cells fail, and we thank the Laufer family for making it possible.” 
  
Laufer Center researchers come from a broad community including Stony Brook departments of chemistry, physics, applied mathematics and statistics, computer science, molecular genetics and microbiology; Cold Spring Harbor Laboratory and Brookhaven National Laboratory. A novel aspect of the Center’s research is a core-team approach to problem solving and outreach. 

"The Laufer Center provides us with a tremendous opportunity for the development of interdisciplinary approaches to advance biology and medicine through discoveries in physics, mathematics, and computational science," said Dennis N. Assanis, Stony Brook University Provost and Senior Vice President for Academic Affairs. "Stony Brook's west campus has strengths in many of the critically important areas needed to support scientific inquiry and new discovery, such as outstanding departments of physics, applied math, computer science, chemistry, microbiology, and evolution and ecology. By partnering the strengths of these areas with SBU's distinguished medical school, as well as Brookhaven National Laboratory and Cold Spring Harbor Laboratory, the Laufer Center will help us provide fundamental solutions to some of the most difficult medical problems facing us today--problems that will require expertise in both the life sciences and physical sciences."

“In addition to performing research, we train Ph.D. students, mentor postdoctoral researchers, and host regular scientific seminars from distinguished outside scientists,” said Ken A. Dill, Director of the Center, a member of the National Academy of Sciences and a past president of the Biophysical Society. He is known internationally for his pioneering work on the physical forces that give rise to the structures and properties of protein molecules. Dr. Dill has dual faculty appointments at Stony Brook in the Department of Physics and Astronomy and the Department of Chemistry. 
 
The Center will house four to six research groups under the Directorship of Dr. Dill and Associate Director, Carlos Simmerling, an Associate Professor in Computational Structural Biology. It serves as a core on Long Island of scientific and educational activity in computational and physical biology. The Center’s 13 affiliated faculty lead research groups from physics, mathematics, chemistry, computer science and biology at Stony Brook, as well as Brookhaven National Laboratory and Cold Spring Harbor Laboratory. 
  
The Laufer Center also will sponsor an interdisciplinary graduate training program, directed by David Green, a computational biophysicist and Assistant Professor of Applied Mathematics and Statistics at Stony Brook.

The article above comes from SBU's General University News.  The Opening was also covered in Newsday.