High performance computing in biology: multimillion atom simulations of nanoscale systems

Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nano-scale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail.     

Evidence Against the “Y–T Coupling” Mechanism of Activation in the Response Regulator NtrC

The dominant theory on the mechanism of response regulators activation in two-component bacterial signaling systems is the “Y–T coupling” mechanism, wherein the χ₁ rotameric state of a highly conserved aromatic residue correlates with the activation of the protein via structural rearrangements coupled to a conserved tyrosine. In this paper, we present evidence that, in the receiver domain of the response regulator nitrogen regulatory protein C (NtrC^R), the interconversion of this tyrosine (Y101) between its rotameric states is actually faster than the rate of inactive/active conversion and is not correlated to the activation process. Data gathered from NMR relaxation dispersion experiments show that a subset of residues surrounding the conserved tyrosine sense a process that is occurring at a faster rate than the inactive/active conformational transition. We show that this process is related to χ₁ rotamer exchange of Y101 and that mutation of this aromatic residue to a leucine eliminated this second faster process without affecting activation. Computational simulations of NtrC^R in its active conformation further demonstrate that the rotameric state of Y101 is uncorrelated with the global conformational transition during activation. Moreover, the tyrosine does not appear to be involved in the stabilization of the active form upon phosphorylation and is not essential in propagating the signal downstream for ATPase activity of the central domain. Our data provide experimental evidence against the generally accepted “Y–T coupling” mechanism of activation in NtrC^R.     

Group-based variant calling leveraging next-generation supercomputing for large-scale whole-genome sequencing studies

Motivation

Next-generation sequencing (NGS) technologies have become much more efficient, allowing whole human genomes to be sequenced faster and cheaper than ever before. However, processing the raw sequence reads associated with NGS technologies requires care and sophistication in order to draw compelling inferences about phenotypic consequences of variation in human genomes. It has been shown that different approaches to variant calling from NGS data can lead to different conclusions. Ensuring appropriate accuracy and quality in variant calling can come at a computational cost.

Results

We describe our experience implementing and evaluating a group-based approach to calling variants on large numbers of whole human genomes. We explore the influence of many factors that may impact the accuracy and efficiency of group-based variant calling, including group size, the biogeographical backgrounds of the individuals who have been sequenced, and the computing environment used. We make efficient use of the Gordon supercomputer cluster at the San Diego Supercomputer Center by incorporating job-packing and parallelization considerations into our workflow while calling variants on 437 whole human genomes generated as part of large association study.

Conclusions

We ultimately find that our workflow resulted in high-quality variant calls in a computationally efficient manner. We argue that studies like ours should motivate further investigations combining hardware-oriented advances in computing systems with algorithmic developments to tackle emerging ‘big data’ problems in biomedical research brought on by the expansion of NGS technologies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0736-4) contains supplementary material, which is available to authorized users.     

Photosynthesis and the Web: 2001

First, a brief history of the Internet and the World Wide Web is presented. This is followed by relevant information on photosynthesis-related web sites grouped into several categories: (1) large group sites, (2) comprehensive overview sites, (3) specific subject sites, (4) individual researcher sites, (5) kindergarten through high school (K-12) educational sites, (6) books and journals, and, 7) other useful sites. A section on searching the Web is also included. Finally, we have included an appendix with all of the web sites discussed herein as well as other web sites that space did not allow. Readers are requested to send comments, corrections and additions to gov@uiuc.edu. This revised version was published online in June 2006 with corrections to the Cover Date.