August 2006
Trends and Tools in Bioinformatics and Computational Biology
Wilfred W. Li, University of California, San Diego (UCSD), San Diego Supercomputer Center (SDSC)
Nathan Baker, Washington University in Saint Louis
Kim Baldridge, UCSD, SDSC
J. Andrew McCammon, UCSD
Mark H. Ellisman, UCSD, Center for Research In Biological Systems (CRBS)
Amarnath Gupta, UCSD, SDSC
Michael Holst, UCSD
Andrew D. McCulloch, UCSD
Anushka Michailova, UCSD
Phil Papadopoulos, UCSD, SDSC
Art Olson, The Scripps Research Institute (TSRI)
Michel Sanner, TSRI
Peter W. Arzberger, California Institute for Telecommunications and Information Technology (Calit2), CRBS, UCSD

2. Scientific Drivers and Tools

Understanding the workings of cells, tissues, organs, or entire organisms requires researchers to pull together information from multiple physical scales and across multiple temporal scales. We highlight activities within our collective and collaborative experiences at different or cross scales. These scientific examples are from long running complex multiscale research areas, which drive the development of our technology integration and infrastructure development efforts.

2.1. Continuity 6

The need for integrative analysis in cardiac physiology and pathophysiology is readily appreciated. Common heart diseases are multi-factorial, multi-genic, and linked to other systemic disorders such as diabetes, hypertension, or thyroid disease. The coupling between the L-type Calcium channels (LCCs, also known as dihydropyridine receptors, or DHPRs) and ryanodine receptors (RyRs) are important in the excitation-contraction (E-C) of cardiac myocytes. The influx of calcium releases the calcium store in the Sarcoplasmic reticulum (SR), a phenomenon known as the calcium induced calcium release (CICR). In fact, the latest ionic models of cardiac myocytes include more than 20 ionic fluxes and 40 ordinary differential equations.1 Computational methods and ionic models for cardiac electromechanics at different scales have also been developed and are available in the software package Continuity. Figure 2 shows an example of how Continuity is used to help develop dual pacemaker systems that are helping to save people’s lives today 14. Continuity is used by a number of researchers in the field of cardiac biomechanics, and receives regular acknowledgment in peer-reviewed publications.15 16 Continuity 6 is continuously being improved to support larger scale simulations, for example using the MYMPI package,17 a standards-driven MPI libraries for Python developed by NBCR to improve the parallel computation efficiency.

Figure 2

Figure 2. Effects of left and right ventricular pacing compared with normal sinus rhythm on the temporal sequences of electrical activation (left column) and mechanical shortening (middle column) in a three-dimensional model of the canine heart. Activation-shortening delays (right column) are heterogeneous, even during normal sinus rhythm. Simulations rendered using Continuity developed by NBCR.

In ventricular myocytes, the dyadic cleft is a periplasmic space that spans about 10 nm between the voltage-gated LCCs/DHPRs on the transverse tubule (TT) membrane, and RyRs on the SR. Within the dyadic cleft, the small reaction volume and the exceedingly low number of reactant molecules means that the reaction system is better described by stochastic behavior, rather than continuous, deterministic reaction-diffusion “partial differential equations.”18 19 This system is one of the focal points of NBCR research at the molecular scale, and for cross scale integrations, with the development of highly realistic 3D models based on electron tomography from the National Center for Microcopy and Imaging Research (NCMIR).

2.2. PMV, Vision, AutoDock Tools & AutoDock

The Python Molecular Viewer (PMV) is a component based software package (Figure 3) written in Python and contains an accompanying visual programming tool called Vision.20 PMV is among the first molecular visualization software packages that takes advantage of grid services, using the web service toolkit Opal developed by NBCR, to access remote databases and computational resources (Figure 3A). Many key packages from the PMV/Vision framework have been reused in Continuity 6, the multiscale modeling platform for cardiac electrophysiology and biomechanics.

In addition, AutoDock Tools (ADT) 21 has been developed as a module inside PMV for the popular molecular docking software package AutoDock. AutoDock is a world famous software package and has been used in developing inhibitors for many important diseases.22 23 The FightAids@Home project has been using AutoDock to screen for HIV inhibitors and is now running on the World Community Grid, an IBM philanthropic activity.24 ADT greatly simplifies the preparation and post analysis procedures of AutoDock (Figure 3B).

Figure 3A
Figure 3B
Figure 3C
Figure 3. A) PMV is used to visualize the viral capsid proteins using the web service toolkit Opal based database access to the Viper Database. B) AutoDock Tools is used to visualize the ligand-protein interactions inside the HIV protease active site. C) Relaxed Complex Method and AutoDock are used to develop novel HIV inhibitors that have led to new drugs designed by Merck that are now in clinical trials.

Pages: 1 2 3 4 5 6 7 8 9 10 11

Reference this article
Li, W. W., Baker, N., Baldridge, K., McCammon, J. A., Ellisman, M. H., Gupta, A., Holst, M., McCulloch, A. D., Michailova, A., Papadopoulos, P., Olson, A., Sanner, M., Arzberger P. W. "National Biomedical Computation Resource (NBCR): Developing End-to-End Cyberinfrastructure for Multiscale Modeling in Biomedical Research," CTWatch Quarterly, Volume 2, Number 3, August 2006. http://www.ctwatch.org/quarterly/articles/2006/08/national-biomedical-computation-resource/

Any opinions expressed on this site belong to their respective authors and are not necessarily shared by the sponsoring institutions or the National Science Foundation (NSF).

Any trademarks or trade names, registered or otherwise, that appear on this site are the property of their respective owners and, unless noted, do not represent endorsement by the editors, publishers, sponsoring institutions, the National Science Foundation, or any other member of the CTWatch team.

No guarantee is granted by CTWatch that information appearing in articles published by the Quarterly or appearing in the Blog is complete or accurate. Information on this site is not intended for commercial purposes.