• Subscribe

'One-stop shop' saves time & money for life sciences

Close-up of the protein Glucosylceramidase, associated with Gaucher Disease in humans.
This is an image of an active site close-up of the protein called Glucosylceramidase, a malfunctioning protein which can cause Gaucher Disease, the most common lipid (fat) storage disease. It's a genetic disease in which a fatty substance accumulates in the cells and certain organs of humans. Here, the experimentally determined crystal structure of the healthy protein (green) is compared to the experimental structure of the most common mutation N370S (blue). And a model of the same mutation predicted with Molecular Dynamics (MD). Two loops and several amino acids (E325, E340, C342 & N370) are in focus as they are involved in the molecular mechanism. In the original publication of this work Offan and his colleagues showed that blind MD-based predictions can be as accurate as experimentally derived results. Image courtesy Marc Offman.

Researchers in the life sciences have more than doubled the speed and halved the cost of doing their computations thanks to ScalaLife.

ScalaLife, a European Commission FP7-funded project, provides services to connect researchers in the computational life sciences with software developers and experts, enabling faster research on high-performance computers.

Computing has become an indispensable tool for life science research, including protein dynamics, structure predictions, bioinformatics, and neuroinformatics.

"But, some life science researchers coming from a biology background, for example, are not very familiar with best practices for using powerful software applications, and thus do not efficiently utilize the hardware resources at their disposal," said Rossen Apostolov, ScalaLife's technical director, during his presentation last month at the EGI Community Forum in Munich, Germany.

It is common for scientists who are new to computational biology to start with online tutorials to help them understand how to use a parallel computing software application for structural analysis of proteins.

However, advice by application experts can significantly reduce the time for running these computations. For example, applying best practice for simple optimizations and runtime settings on GROMACS, a popular application for molecular dynamics simulations, can increase the speed of simulations two or three times. This is where ScalaLife comes in.

"General users can find some of the applications very hard to understand. The goal of our project is to connect software users with the software developers. To help accelerate research, ScalaLife provides a 'one-stop-shop' knowledge base and expert support center for computational life science communities," Apostolov said. "We provide experts who give advice on how to optimally use these codes. So much is lost when there is a lack of communication between life scientists and computer scientists."

Not lost in translation

Molecular Dynamics simulation, comparing the healthy (blue) and mutated (red) Glucosylceramidase protein.
A Molecular Dynamics simulation comparing the superimposed healthy (blue) and mutated (red) Glucosylceramidase protein. The cylinders in focus are protein helices important for function and flexibility. The proteins are simulated with a small drug molecule (faint colors). With the drug, the mutated protein (red) behaves more similarly to the healthy protein and there is no shift is found in the small helix. Without the drug, the smaller helix of the malfunctioning protein would be displaced and thus cause changes which are important for the chemical reaction normally facilitated by this protein. Click on the image to watch the simulation. Image courtesy Marc Offman.

ScalaLife has already helped scientists publish research on clinically-related biology. Marc Offman is a bioinformatics researcher for ROSTLAB at the Technical University Munich and the Leibniz Supercomputing Centre in Germany.

ScalaLife is helping Offman's study of the molecular changes in proteins and how this impacts human disease. This will help his future goal of personalized medicine for everyone.

"At the moment, we are still in the process of creating, collecting, and analyzing data," Offman said. "With the molecular dynamics simulation method, we try to compute and predict how big molecules, such as proteins, behave in water. If our simulations show something abnormal we might be able to learn if, or even why, this might be a problem to the cell and ultimately the whole organism."

Offman developed a pipeline that automatically prepares molecular simulations, optimizes their performance, and checks the end results. Other users can access the pipeline's final report and make a careful analysis of the results.

"The software pipeline, developed as part of the ScalaLife project, was used to investigate what happens in newly identified malfunctioning proteins related to Parkinson's disease. This work was published in The American Journal of Human Genetics in 2011," Offman said. "I am also involved in teaching. We teach our students how to investigate problems found in altered proteins using software developed in ScalaLife. The increasing availability of high-performance computing facilities and projects such as ScalaLife push development and progress. I strongly believe that these efforts will eventually help to achieve new breakthroughs in natural sciences, particular in the field of clinically-related biology."

Reducing the billion dollar cost of drug development

Image of 40 mg Nexium (esomeprazole magnesium) pills against a black background..
Nexium (esomeprazole magnesium) pills used to treat ulcers in human disease. Image courtesy Wikimedia Commons.

ScalaLife helps users collaborate with other researchers to improve their code and get access to European e-infrastructures such as the European Grid Infrastructure and the Partnership for Advanced Computing in Europe (PRACE). Apostolov said that by giving users just a little help, their software could be significantly accelerated in certain cases.

"Right now, we're focusing on the direct interaction with users and sharing knowledge of how to efficiently use applications on high-performance computing systems. If the project is successful, then we could develop similar centers for other communities in the computational sciences as well," Apostolov said.

In the long-term, ScalaLife could potentially have some impact in reducing the average $1.2 billion dollar cost of generating each new drug as well, according to Apostolov.

"The future of structure-based drug discovery relies on software tools capable to scale on multi-core high-performance computers. ScalaLife will provide the life science community with a fast and flexible access to high-performance computing resources," said Modesto Orozco, life science director at the Barcelona Supercomputing Center in Spain.

This potential future goal is one that Apostolov and the ScalaLife team understand could reap benefits for all.

"Computational methods are currently an integral part of drug development processes; for example, screening large libraries of potential drug candidates," Apostolov said. "Faster simulations will deliver quicker results. Also, accelerating large-scale computing projects will save a lot of electricity for computing centers."

Join the conversation

Do you have story ideas or something to contribute? Let us know!

Copyright © 2023 Science Node ™  |  Privacy Notice  |  Sitemap

Disclaimer: While Science Node ™ does its best to provide complete and up-to-date information, it does not warrant that the information is error-free and disclaims all liability with respect to results from the use of the information.


We encourage you to republish this article online and in print, it’s free under our creative commons attribution license, but please follow some simple guidelines:
  1. You have to credit our authors.
  2. You have to credit ScienceNode.org — where possible include our logo with a link back to the original article.
  3. You can simply run the first few lines of the article and then add: “Read the full article on ScienceNode.org” containing a link back to the original article.
  4. The easiest way to get the article on your site is to embed the code below.