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The research group of Professor Carrie Wilmot in the Department of Biochemistry, Molecular Biology, and Biophysics concentrates on understanding the synthesis and function of novel organic, organometallic, and metal-ion cofactors in proteins. (A cofactor is a chemically reactive protein modification or bound non-protein compound that is necessary for the biological activity of a protein, many of which are enzymes.) The ultimate goal of the research is to provide a basis for the development of new and better drugs, for engineering proteins for applications in biotechnology, and for designing simpler industrial catalysts. The researchers’ primary tool is macromolecular X-ray crystallography and mass spectrometry.
The Wilmot group recently published a paper in the Proceedings of the National Academy of Sciences, U.S.A. that describes the actions of the enzyme MauG to catalyze the formation of a tryptophan tryptophylquinone (TTQ) cofactor to activate the enzyme methylamine dehydrogenase (MADH) (“Diradical Intermediate Within the Context of Tryptophan Tryptophylquinone Biosynthesis,” ET Yuki, FG Liu, J Krzystek, S Shin, LMR Jensen, VL Davidson, CM Wilmot, AM Liu, PNAS, 110(1):4569, DOI: 10.1073/pnas.1215011110 (2013)). The oxidation process that results in the formation of tryptophan tryptophylquinone has three distinct steps; the researchers have been able to figure out the progression of the oxidation and identify the structures of the intermediate steps. The computer work was done at MSI’s BSCL. The image above shows the various steps of the process.
Image description: (A) Electron density for the precursor TTQ site in MauG–precursor MADH crystals of different ages. Electron density maps (blue) for the crystals aged for 10, 40, 50, and 130 days were generated from the respective refined structures. The 50- and 130-day electron density images were calculated using the refined 50-day model (cross-linked precursor TTQ) to enable visualization of the positive-difference electron density (green) for the appearance of the second oxygen. (B) The observed rotation in βTrp57-OH during cross-link formation. The figure was produced using PyMOL (www.pymol.org). Image and description © 2013 by National Academy of Sciences, USA.
posted on August 14, 2013
Lazarina Gyoneva is a graduate student in the research group of Professor Victor Barocas (MSI Fellow; Biomedical Engineering). She came to the University of Minnesota as a grad student in 2010 and started using MSI resources in the spring of 2011. Ms. Gyoneva was a finalist in the poster competition at the 2013 MSI Research Exhibition with her poster, “Role of Lateral Interactions in Collagen IV Network Mechanics.” Other MSI PIs who were co-authors on this poster are Yoav Segal (Medicine) and Kevin Dorfman (Chemical Engineering and Materials Science). Ms. Gyoneva sat down with MSI recently to discuss her work.
MSI: What do you use MSI for?
Lazarina Gyoneva: On the computational side, I use mostly the different C++ compilers and MATLAB, and on the analytical side, I use statistical and graphical packages like GraphPad Prism and SAS. I use them through the labs.
MSI: Your poster describes type IV collagen. Can you explain the difference between collagen IV and the kind of collagen we’ve all heard about in the skin?
LG: There are actually over 20 different types of collagen, all products of different genes. The collagen found in skin is type I. Type IV collagen is the type that’s present in basement membranes – the part of the extracellular matrix on which epithelial cells are attached. Type IV collagen is slightly different from type I collagen in its molecular structure and organization. Because of their differences in molecular structure and processing, type I collagen is able to form thick strong fibers while type IV collagen molecules can’t be packed closely enough to form fibers and they self-organize into planar networks.
There are three known kinds of collagen IV. The two most common ones are the so-called “major” and “minor” kinds, and even between them there are differences based on primary and secondary structures of the proteins.
MSI: What are you trying to do in this poster?
LG: We are looking at the role of lateral interactions on the mechanical properties of type IV collagen networks. The two different types of collagen IV, the major and the minor, are believed to have different abilities to form lateral interactions, therefore they can form slightly different networks. The minor chains also have the ability to wind around each other, forming “supercoils,” which probably changes the structure of the network as well as the mechanical properties of the network.
So, we already see that they have some structural differences, and we wanted to know how these structural differences could affect the mechanical properties. The reason we’re interested in that is because, clinically, we know that the minor chains are vital for the proper functioning of the collagen networks of the kidneys and the lens of the eye. When the minor chains are missing from those locations [Ed: a condition called Alport Syndrome], the collagen networks cannot perform their mechanical functions in those locations. We want to know what properties of the minor chains make them so vital.
MSI: How did you use MSI?
LG: We generated networks in MATLAB that represent the major and minor collagen networks. The generated networks have the same connectivity and relative concentrations as the physiological collagen IV networks. We introduced lateral interactions in the minor chain networks constraining the networks a little bit more. In some places, we created “supercoils,” to which we assigned double the stiffness and double the cross-sectional area of normal chains. We then took the generated networks and simulated their mechanical deformation to obtain their stress-strain response. The mechanical simulations are done with a force-balance code in which the boundaries of the networks are stretched first, then all internal segments are allowed to move around until they are in a position at which the sum of the forces on each chain is zero. From the force calculations, we can also calculate the stresses that are applied to these networks.
We generated two different networks, one (kidney) with a higher percentage of minor chains, and another (lens) with a lower percentage of minor chains and we tested what happens when we increase the connectivity of the minor chains.
MSI: Does this research have immediate applications, or is it more basic science?
LG: It’s definitely more on the theoretical side. The main reason we think it’s important to look at this is because not much is known about the mechanical role of the minor chains and what are the primary causes for the disturbances seen in Alport Syndrome when the minor chains are absent. We believe that Alport Syndrome may be caused by a loss of mechanical functionality, initiating a number of secondary biological responses. Current treatments have focused on the biological side but it’s very important to learn more about the primary causes so we can discover ways to treat the diseases earlier.
MSI: Will this eventually have applications for clinical treatment?
LG: I can’t speak yet of direct clinical applications, but what we are learning about the importance of network structure for mechanical properties could have applications not just for Alport Syndrome, but for material science in general. The ability to build biological or synthetic networks that can be easily modified to adjust their mechanical properties would be very desirable.
MSI: How much more needs to be done with this project?
LG: There are definitely a lot of unanswered questions in this area. The networks generated for the simulations are idealized representations. Ideally, we would like to have ultra-high resolution Scanning Electron Microscopy images of actual lens and glomerular basement membranes from which we can extract the exact topology of collagen IV networks. Then we can digitize the real networks and use them for the mechanical stretching simulations. There are some other things that we can look at. For example, we still don’t know how exactly the minor and major chains interact with each other, how they are distributed in basement membranes, if the higher number of cysteines really corresponds to a higher number of lateral interactions, or what is it about the minor chains that makes them form supercoils when the major chains don’t do that. Those are all basic questions that need to be answered.
MSI: Do you make the models using information that you got experimentally?
LG: Some of the parameters used in the computational model are taken from literature on collagen IV and collagen I. We did perform a set of experiments last year that were very informative in quantifying the importance of the minor chain network in contributing additional strength to the basement membrane of the ocular lens. One of the purposes for this computational project was to try to explain some of the experimental results where we used wild-type and Alport mutant mouse lenses and compared their distensibility. We saw that when the minor chains are missing, the lens is much more compliant. This computational study is now trying to explain what it is about the minor chain that gives them additional mechanical strength.
posted on July 31, 2013
With the recent appearance of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV), coronaviruses are once again in the news. These viruses are found worldwide and some of them can create serious illness in humans. SARS (severe acute respiratory syndrome), which is caused by a coronavirus, killed hundreds of people in 2002-2003.
Assistant Professor Fang Li, an MSI Principal Investigator from the Department of Pharmacology in the Medical School, uses structural biology to study diseases including viral infections. This research investigates the structural basis for the receptor recognition mechanisms of viruses. This includes studying the structures and functions of the receptor-binding proteins found on the surfaces of viruses, as well as how they interact with host receptors. These structural studies will allow researchers to develop therapy strategies to fight virus-caused diseases.
Recently, Professor Li and his colleagues determined the crystal structure of the spike protein N-terminal domains (NTDs) of bovine coronavirus (BCoV). This finding was published in the Journal of Biological Chemistry in December 2012 (“Crystal Structure of Bovine Coronavirus Spike Protein Lectin Domain,” GQ Peng, LQ Xu, YL Lin, L Chen, JR Pasquarella, KV Holmes, F Li, Journal of Biological Chemistry, 287:41931, DOI: 10.1074/jbc.M112.418210 (2012)). The research studied the differences in the structure of the NTDs of BCoV and another coronavirus, mouse hepatitis coronavirus (MHC). While both NTDs include a human galactose-binding lectin (galectin) in their NTD structures, the former binds to sugar and the latter to a protein, CEACAM1. The Li group’s studies of the crystal structure of the NTDs show subtle differences in the receptor-binding loops. These results indicate a possible evolution path where a coronavirus incorporated this galectin into its spike proteins, which was altered as the different modern coronaviruses evolved. The researchers used the BSCL for this research.
The Li group has also published additional papers related to their research using MSI. These include:
- “Structural basis for multifunctional roles of mammalian aminopeptidase N,” L Chen, YL Lin, GQ Peng, F Li, Proceedings of the National Academy of Sciences of the United States of America, 109:17966, DOI: 10.1073/pnas.1210123109 (2012)
- “Mechanisms of Host Receptor Adaptation by Severe Acute Respiratory Syndrome Coronavirus,” KL Wu, GQ Peng, M Wilken, RJ Geraghty, F Li, Journal of Biological Chemistry, 287:8904, DOI: 10.1074/jbc.M111.325803 (2012)
Image description: A. Overall structure of BCoV NTD. Two β-sheets of NTD core are colored green and magenta, respectively, and other parts of the NTD are color cyan. N*, N terminus; C*, C terminus. The β-sandwich core structure is indicated as “core.” The two potential sugar-binding pockets above and underneath the core structure are indicated as top and bottom, respectively. B. 2Fo – Fo electron density of a portion of BCoV NTD at 1.5σ. This region includes three of the critical sugar-binding residues. (Peng G et al., “Crystal Structure of Bovine Coronavirus Spike Protein Lectin Domain,” J. Biol. Chem., 287:41931 (2012); ©2012 by the American Society for Biochemistry and Molecular Biology.)
posted on July 17, 2013
Makenzie Provorse is a graduate student in Professor Jiali Gao’s (MSI Fellow) group in the Department of Chemistry. She entered the University of Minnesota in the fall of 2009 and joined the Gao group in January 2010. She’s been using MSI since then.
Ms. Provorse was a finalist at the 2013 MSI Research Exhibition, which was held on April 11, 2013. She submitted a poster entitled "Quantum Coherence in Singlet Fission From Multistate Density Functional Theory (MSDFT)." Recently, MSI talked with Ms. Provorse to discuss her poster and the work she does using MSI.
MSI: What do you use MSI for?
Makenzie Provorse: I mainly run molecular simulation and electronic structure programs on Calhoun and Itasca. They’re the two machines I use the most. For this specific project, we used a locally modified version of GAMESS, a molecular electronic structure theory program, and CHARMM, a molecular simulation package. We do what is called combined QM/MM - quantum mechanics and molecular mechanics - simulations, so we use CHARMM to run molecular dynamics and have it call GAMESS as a subroutine whenever a quantum calculation is needed.
MSI: Can you explain what your poster describes?
MP: Pentacene is a planar [flat] molecule with five hexagonal benzene rings fused together. In the crystal or thin film form, pentacene displays some very unusual properties. Say you have two pentacene molecules side by side in a crystalline lattice. When one molecule absorbs energy from, for example, the sun, this absorbed energy - called a photon - excites an electron from one molecular orbital to another, higher-energy, molecular orbital. This forms an excited electronic state, but - what’s interesting about pentacene - is that through a process called singlet fission, you actually end up with two excited electrons, each on one of the neighboring pentacene molecules. So you’re getting two excited-state molecules from the absorption of just one photon. It’s kind of a two-for-one energy conversion process. The potential application is that we can use pentacene to make much more efficient solar cells as a source for renewable energy.
MSI: And that’s not a violation of thermodynamics laws?
MP: Right, that’s the interesting part! Quantum mechanically, when a molecule is excited from its ground state, which is typically a singlet state - all electrons are paired with one spin up and one spin down - its lowest-energy excited state is also a singlet. That is, after excitation, one electron has moved to a higher-energy molecular orbital, which makes two electrons unpaired, but they retain their respective spin states - one up and one down. The two unpaired electrons can also have the same spin - both spin up or both spin down - called a triplet state, but transitions from a singlet ground state to an excited triplet state are not allowed quantum mechanically. Regardless, the two excited pentacene molecules produced by singlet fission are in fact in the triplet state. So, after a photon is absorbed by a pentacene molecule and it’s excited to the lowest-energy singlet state, then, through some quantum mechanical process, the singlet state transitions to two excited triplet states.
Thermodynamics come into play when looking at the relative energy of the singlet and triplet excited states. Typically, the singlet excited state is lower in energy, but in pentacene, the triplet state is slightly less than half of the singlet state energy, which means that twice the energy of a triplet state is less than the singlet state energy. This quantum phenomenon makes it thermodynamically favorable for pentacene to undergo singlet fission.
The fact that pentacene undergoes singlet fission has been known for a long time. What we’re interested in is how this transition occurs. It’s been hypothesized that singlet fission involves an intermediate state, called a multiexciton (ME), which consists of two excited triplet states coupled together to form an overall singlet excited state. This state is optically-forbidden, meaning that it cannot be populated directly from the ground state, but it’s thought that the excited state pentacene shares its energy with a neighboring pentacene molecule to form a pair of correlated triplet states, each on one pentacene molecule. We’re investigating the way this ME state is populated and how it is coupled with the singlet excited state of a pentacene molecule.
MSI: So, you use the computer programs on the supercomputers to model this process?
MP: Yes, we use the computer programs to model each state, with the electrons excited in various ways, and then we calculate the electronic coupling between the states. There are three states important to the singlet fission process: the initially excited singlet state (S1); a charge-transfer (CT) state; and a pair of correlated triplet states, or a multiexciton (ME). If you go directly from the S1 to ME states, there’s a much smaller coupling than if you couple with the charge-transfer state, S1-to-CT then CT-to-ME. So these calculations show that including the intermediate charge-transfer state is necessary to get significant coupling to produce two excited, triplet state pentacene molecules.
MSI: Is this research something that can be applied immediately, or is it more basic research?
MP: This is basic research, but yes, there have been efforts to fabricate solar cell devices that make use of singlet fission. Here, we focus on understanding the underlying mechanism of this process.
MSI: Do you know if there’s anything else this could be used for?
MP: Mostly, the current interest in singlet fission comes from its potential to improve the efficiency of solar cells. Right now, the theoretical efficiency of single-junction solar cells to convert solar energy into electricity is limited to about 33%, the so-called Shokley-Queisser limit. But, if materials that undergo singlet fission are used, we could exploit this two-for-the-price-of-one energy conversion process and potentially break this limit.
MSI: Would that reduce the cost, if they could be made more efficient?
MP: I don’t know if will reduce the cost. But looking at where solar cells are now, with the materials that are currently used, efficiency is around 11%. One of the key motivations for this project is this quantum-mechanical limit that even if the solar cell is completely 100% efficient in all these other ways, due to the quantum mechanics, 33% efficiency is all you’ll ever get. That’s if everything else is perfect. This project is a way to increase that limit, because we’re getting two excited electrons that can both, potentially, be harvested to generate an electrical current. So, that’s the major advantage of using pentacene, because it undergoes singlet fission, we can break that theoretical barrier. If that’s improved, everything will be improved.
MSI: So, the long-term goals for this research are to prove your theory?
MP: The goal is to investigate the mechanism of how singlet fission happens in these kinds of organic monolayers. If we can understand what drives the reaction and what molecular properties affect this process, then down the road, we can use that knowledge to our advantage.
MSI: Is there anything else you’d like to mention about your work?
MP: Yes, the multistate density functional theory method I used for this poster was developed in our group. Density functional theory is a well-known electronic structure theory method. It’s very efficient computationally, it’s easy, it’s inexpensive, but it’s delocalized. With multistate density functional theory we can localize states on individual pentacene molecules. That’s why we can calculate these couplings. I’m also currently using this MSDFT method to study other processes related to solar energy conversion, such as proton-coupled electron transfer in photosynthesis.
MSI: This method was developed before you joined the Gao group?
MP: Yes, and it’s been ongoing. This project is just one of its many applications. This is a group effort, involving a number of people developing the theory, writing the computer code, and applying and validating the method in practical applications.
MSI: So, this is something that needs the supercomputers.
MP: Oh, definitely.
posted July 3, 2013
MSI Principal Investigator Richard Isaacson (Veterinary and Biomedical Sciences) is using MSI resources as part of his investigations into antibiotics that are used as growth promoters in livestock. Antibiotics have been used in this way for decades, but we don’t know the mechanism by which they promote growth. It is possible that this result is from the control of bacterial growth in the animals’ intestines, or because the antibiotics control specific bacterial populations in the intestinal tract. Recently, there are concerns that the use of these antibiotics may be eliminated or reduced in the future.
These researchers are using a molecular epidemiology approach to see if eliminating the use of these antibiotic growth promoters affects, for better or worse, the health of swine. Another goal is to see whether antibiotic growth promoters mediate their effects by alteration of microflora. They use software available through MSI to generate the data and then to analyze it. Besides various software packages, the group makes use of the Galaxy analytical framework.
Professor Isaacson and members of his research group, including fellow MSI Principal Investigator Srinand Sreevatsan (Veterinary Population Medicine) published a paper concerning this work in the Proceedings of the National Academy of Science in Fall 2012: “Microbial Shifts in the Swine Distal Gut in Response to the Treatment With Antimicrobial Growth Promoter, Tylosin,” HB Kim, K Borewicz, BA White, RS Singer, S Sreevatsan, ZJ Tu, and RE Isaacson, PNAS, 109:15485, DOI: 10.1073/pnas.1205147109 (2012). The figure above shows an analysis that used the Ribosomal Database Project (RDP) classifier to show the composition of the fecal microbiome of pigs receiving tylosin (an antimicrobial growth promoter) and those that did not, and how it changed over time. The graphs show results for treated (T) and non-treated (NT) pigs at different ages at two different farms. (A) RDP classification of the sequence reads from farm 1. (B) RDP classification of the sequence reads from farm 2.
Professor Isaacson and his group also use MSI for other projects, including investigations into the effect of pathogenic bacteria on the gut microbiome and analysis of the human lung microbiome (see “The Lung Microbiome in Moderate and Severe Chronic Obstructive Pulmonary Disease,” AA Pragman, HB Ki, CS Reilly, C Wendt, RE Isaacson,” PLos One, 7:e47305, DOI: 10.1371/journal.pone.0047305 (2012)).