How many modelers?

March 8th, 2010 by Gerhard Goldbeck-Wood, PhD

How many of “us” are out there? I mean how many people doing modeling and simulation? I’d really like to know, ideally broken down by discipline, such as Materials Science vs Life Science, and quantum, classical and mesoscale.

Alas, there are preciously few statistics on that, so when I read in the Monthly Update (Feb 2010) of the Psi-k network that they conducted a study on size of the ab initio simulation community, it got my immediate attention.

Representing a network of people from the quantum mechanics field, Peter Dederichs, Volker Heine and colleagues Phivos Mavropoulos and Dirk Tunger from Research Center Jülich searched publications by keywords such as ‘ab initio’, and made sure not to double-count authors. In fact they tend to underestimate by assuming people with the same surname and first initial are the same. As Prof Dederichs, the chair of the network tells me, checks were also made to ensure that papers from completely different fields are not included. Also they estimate that their keyword range underestimates the number of papers by about 10%. Of course there are those that didn’t publish a paper in 2008, the year for which the study was done. Moreover, Dederichs says, there are those who published papers which don’t have proper keywords like “ab initio” or “first principles” in the abstract or title, so they are not found in the search. All of that is likely to compensate for counting co-authors that are not actually modelers.

All in all, they come up with about 23,000 people! And the number of publications in the field indicates a linear rise year on year.

That’s quite a lot more than they expected, and I agree. The global distribution was also surprising, with about 11,000 in Europe, about 5,600 in America, and 5,700 in East Asia (China, Japan, Korea, Taiwan and Singapore). That’s a lot of QM guys, especially here in Europe. Now, there will be a response from the US on that one I guess?

I wonder how many classical modelers there are. I’d hazard a guess that the number of classical modelers is about half those in the QM community, at least in the Materials Science field. Assuming that the mesoscale modeling community is quite small, that would make for a total of at least 30,000 modelers worldwide.

What is your view, or informed opinion? Anybody else knows about or has done some studies? I am going to open up a poll in the right sidebar on the number of people involved in quantum, classical and mesoscale modeling in total. It would be great to hear also how you came up with your selection.

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Materials and Energy: A Maturing Relationship

February 11th, 2010 by Gerhard Goldbeck-Wood, PhD

After simple combustion, and the nuclear option, the relationship between materials and energy is as topical as ever. Taking a new turn in the 21st century the couple have matured into exploring more subtle ways to relate to each other. What am I talking about? Well, there are so many ways in which materials affect energy and energy is affected by materials, i.e. energy generation, storage, conservation and the efficient use of energy. In all of these, insights at the atomistic and quantum level help us to design cleaner energy sources, and find less wasteful ways of using energy. To find out more on how modelling supports the discovery and understanding of new materials for fuel cells and batteries, please check out the Materials Studio 5.0 Webinar Series.  Following the recent webinar on fuel cell catalysts (for which you can still access the recording), we have two more webinars scheduled on the topic:

February 17th, 2pm GMT/6am PST: Atomic-Scale Insights into Materials for Clean Energy. The webinar will be given by Prof Saiful Islam from University of Bath, who is a renowned expert in the field: check out the interviews, podcasts and publications.

March 16th, 3pm GMT/8am PDT:  High-throughput Quantum Chemistry and Virtual Screening for Lithium Ion Battery Electrolyte Materials . George Fitzgerald will include results from a collaboration with Mitsubishi Chemical Inc which was also published in The Journal of Power Sources.

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DFT Redux

January 14th, 2010 by George Fitzgerald, PhD

I thought I’d start the year with an easy blog, simply following up on my earlier ramblings of 25 October 2009: DFT Goes (Even More) Mainstream. In that article I discussed the success of Density FunctionalTheory (DFT) and used the annual number of publications as a metric. The numbers show that publications grew by over 25% per annum, but the results for 2009 were naturally incomplete.

Happily the trend continued through 2009 for a total of 4621 DFT references in ACS Journals. Here are a few of my favorite publications, thought not all are drawn from the ACS citations. Yes, of course, these use Accelrys DFT packages, but they are still pretty cool articles:

Let me and my readers know what you think are the most interesting DFT articles from 2009.

†Strictly speaking, this was not QSAR, Quantitative Structure-Activity Relationship, because they didn’t actually base predictions on the structure. I use the term here more generally to refer to relationships that predict complex properites like catalytic activity, on the basis of simpler properties, like workfunction.

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Warren.

December 4th, 2009 by Accelrys Team

Like hundreds of scientists around the world, I too was shocked to hear the news about Warren DeLano’s sudden passing away on Nov 3rd. He was young, extremely bright, and had a contagious enthusiasm about his passion: PyMOL, the open source and most widely used molecular visualization tool around.

Axel Brunger and Jim Wells contributed a brief article to this week’s issue of Nature (Structural and Molecular Biology).  I encourage all scientists around the world to read this article: http://www.nature.com/nsmb/journal/v16/n12/pdf/nsmb1209-1202.pdf. I had met Warren personally several times and after reading this article, I know I was privileged to have known him.

Warren DeLano speaking at the Open Source Bioinformatics conference 2005 part of the Annual Meeting of the International Society for Computational Biology (http://open-bio.org/bosc2005/finalProgram/images/ WarrenDelano.JPG).

Warren DeLano speaking at the Open Source Bioinformatics conference 2005 part of the Annual Meeting of the International Society for Computational Biology (http://open-bio.org/bosc2005/finalProgram/images/ WarrenDelano.JPG).

An excerpt from the article (volume 16 number 12 december 2009 nature structural & molecular biology, p1202):

“For Warren, programming was not just a job or a means to another goal—it was like playing a musical instrument. The programs he designed were symphonies in computational space: integrated, complex and elegant at the same time. What’s more, these masterpieces can be played by everyone…
For Warren’s superb thesis, published as a first-author paper in Science entitled “Convergent solutions to binding at a protein-protein interface”
(W.L. DeLano, M.H. Ultsch, A.M. de Vos and J.A. Wells, Science 287, 1279–1283, 2000), he was awarded the annual Julius Krevans Award for the best PhD thesis at UCSF. Not bad for a computational geek.”

Unlike our other blogs, this blog isn’t scientific but is a celebration of a scientist whose contribution to the community is immeasurable.

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Take the leap: Materials Studio 5.0

October 16th, 2009 by Gerhard Goldbeck-Wood, PhD

Just back from the EUGM and Nanotech Consortium Meeting, a week of lively discussions (and foosball matches ;-) and of course our announcement of the release of Materials Studio 5.0. It’s been great finally to talk about and demo all the new features, which we are all so excited about. Getting the requests in for shipment of the new version already … well, it won’t be long.

You can read more about Materials Studio 5.0 at a high level in our Press Release, or in more detail in our ‘What’s New’ document. Perhaps you have read the ‘Transforming Materials Modeling’ tag line in there: imagine the discussions we’ve had about that: “Is it really?” “What is transforming…” and so on. But honestly it is what we are aiming to do with Materials Studio, and there are many things in the 5.0 release that make a real difference.

My take right now from the discussions at the Consortium and User Group Meetings is that the efficiency you gain because of the integration and flexibility this new release provides is quite a step change. The new Amorphous Cell for example got some wows from Materials Science and Life Science folks alike. It’s really a kind of universal structure builder. Want to build a nanocomposite, for example with nanotubes and polymers around them: not a problem. And perhaps there is some small molecule inside the tube: easy.  And what about a protein soaked in a solution: consider it done!

For the second ‘transforming’ example, for me it’s Kinetix, the new Kinetic Monte Carlo module we built for the Nanotech Consortium. I alluded to Kinetic Monte Carlo development earlier, and thanks to a great collaboration with Tonek Jansen and Johan Lukkien from TU Eindhoven, you can now simulate processes such as a Fuel Cell cathode reaction in Materials Studio, over real time scales of minutes. Considering we start at femtoseconds, that’s quite a leap anyway.

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Can Automated NMR Analysis Cure Gephyrophobia?

October 8th, 2009 by Max Petersen, Ph.D.

It wasn’t until my career steered towards marketing that I was diagnosed with gephyrophobia – the pathological fear of bridges. Certainly, years of riding motorcycles in Southern California’s backcountry never triggered this anxiety disorder, but the realization that a simple query on istockphoto for “bridge” and “puzzle” returns 56 variations of chasmcrossing stereotypisms. My guess is that if you are gainfully employed and work outside the shelter of academic or government institutions, you have been exposed: The “bridge” as a symbol. To make you work better. With your colleagues. With other departments. In general: To cross a chasm.

A car about to cross a chasm. Or is it?

A car about to cross a chasm. Or is it?

Working as a product manager for Pipeline Pilot, I had no choice but to face my fears. There are no two ways to put it: Pipeline Pilot is a “bridge,” it helps scientists and departments work together – better.  Now, don’t get me wrong – I have nothing against teamwork, I think it makes it worthwhile commuting 60 miles to work every day and wondering what frequent flyer status comes after “Platinum.”  My fears are empty marketing promises that create customer reactions ranging anywhere from confusion to disappointment.

Customers I mainly interact with work in analytical labs. Last time I checked, they are concerned with analyzing boatloads of data in the shortest time possible. Sure, they could use a bridge when it comes time to toss the results over the fence to the chemists that originally requested the work. And after quite a bit of effort from my colleagues in  Cambridge R&D, we can now process NMR data in Pipeline Pilot. And although I have no delusions of grandeur that Accelrys would invest in this project simply to address my exotic condition, I still hope that the next time I drive over the Bay Bridge to see my favorite customer, my heart will be beating at its customary 120 bmp.

I would also like to thank all the great people at Modgraph helping us integrate their first rate NMR prediction engine, NMRPredict, into Pipeline Pilot. Not only would our NMR release have been significantly less complete, but it makes Accelrys’ vision come alive that Pipeline Pilot is an open integration platform for scientific applications.

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Life in 3D, where biology meets chemistry

September 8th, 2009 by Accelrys Team

Why do we view life in 3D rather than 2D? I am not thinking fundamental physics here (which may consider 12D or more), rather what advantages do we have in perceiving chemical and biological molecules as more than two dimensional entities? Are there any benefits to viewing synthetic schemes  and reaction mechanisms as more than two dimensional, likewise can regarding proteins/DNA/RNA as more than sequences and collections of secondary structures bring us additional insights?

There is an argument to be made that the intersection of biology and chemistry is best viewed in 3D.  Just ask your local crystallographer! Life really does happen in 3D. When trying to understand how simple molecules interact with their complex targets, three-dimensional visualization can be indispensible! Nearly 60,000 (and growing) PDB structures can’t be wrong.

There is no consensus on how “best” to view molecular structures or complexes and therefore, a number of solutions are available. Everyone has their personal preference – I find that the DSVisualizer provides all the flexibility and customizability I would like … and it’s free to everyone. That said, I would love to know what your personal favorite visualizer is and why? Vote for your personal favorite over in the right sidebar, and explain why below in the comments.

Visualizer

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In search of a lead – one fragment at a time!

July 21st, 2009 by Accelrys Team

The quest to find novel lead compounds is still the same, but the computational paradigms tend to shift. It is evident from the recent scientific conferences and publications that fragment based design (FBD) is a popular method in finding novel compounds against biological targets of interest.

FBD is predominantly an experimental approach whereby research groups are using well established techniques, such as NMR and X-ray crystallography, for finding small molecules that bind to proteins.

It wasn’t until recently that computational approaches started to take on the buzzword, or perhaps some of the computational methods were ahead of their times! Such is the case with an algorithm called “Multiple Copy Simultaneous Search” or MCSS. A popular request came via our Discovery Studio (DS) users to see this algorithm from InsightII environment into a more user friendly DS.

It was in 1991 that Martin Karplus and co-workers at Harvard University had first published this force-field based method and demonstrated its used in fragment-based design. Since then, MCSS has been successfully applied by several research groups in generating ideas and suggesting binding modes of small molecules. Why the MCSS name? The algorithm takes a small molecule fragment, makes hundreds of copies of it, and then simultaneously minimizes them in the receptor cavity. Fragments with favorable binding energy are ranked for analysis.  Efficient and clever.

So, by popular demand, we have developed an enhanced MCSS algorithm in Discovery Studio 2.5, which promises to help chemists and modelers in their search of a lead compound – one fragment at a time.

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