CUDASW++2.0: enhanced Smith-Waterman protein database search on CUDA-enabled GPUs based on SIMT and virtualized SIMD abstractions

<p>Abstract</p> <p>Background</p> <p>Due to its high sensitivity, the Smith-Waterman algorithm is widely used for biological database searches. Unfortunately, the quadratic time complexity of this algorithm makes it highly time-consuming. The exponential growth of biological databases further deteriorates the situation. To accelerate this algorithm, many efforts have been made to develop techniques in high performance architectures, especially the recently emerging many-core architectures and their associated programming models.</p> <p>Findings</p> <p>This paper describes the latest release of the CUDASW++ software, CUDASW++ 2.0, which makes new contributions to Smith-Waterman protein database searches using compute unified device architecture (CUDA). A parallel Smith-Waterman algorithm is proposed to further optimize the performance of CUDASW++ 1.0 based on the single instruction, multiple thread (SIMT) abstraction. For the first time, we have investigated a partitioned vectorized Smith-Waterman algorithm using CUDA based on the virtualized single instruction, multiple data (SIMD) abstraction. The optimized SIMT and the partitioned vectorized algorithms were benchmarked, and remarkably, have similar performance characteristics. CUDASW++ 2.0 achieves performance improvement over CUDASW++ 1.0 as much as 1.74 (1.72) times using the optimized SIMT algorithm and up to 1.77 (1.66) times using the partitioned vectorized algorithm, with a performance of up to 17 (30) billion cells update per second (GCUPS) on a single-GPU GeForce GTX 280 (dual-GPU GeForce GTX 295) graphics card.</p> <p>Conclusions</p> <p>CUDASW++ 2.0 is publicly available open-source software, written in CUDA and C++ programming languages. It obtains significant performance improvement over CUDASW++ 1.0 using either the optimized SIMT algorithm or the partitioned vectorized algorithm for Smith-Waterman protein database searches by fully exploiting the compute capability of commonly used CUDA-enabled low-cost GPUs.</p

Chemogenomic Analysis of G-Protein Coupled Receptors and Their Ligands Deciphers Locks and Keys Governing Diverse Aspects of Signalling

Understanding the molecular mechanism of signalling in the important super-family of G-protein-coupled receptors (GPCRs) is causally related to questions of how and where these receptors can be activated or inhibited. In this context, it is of great interest to unravel the common molecular features of GPCRs as well as those related to an active or inactive state or to subtype specific G-protein coupling. In our underlying chemogenomics study, we analyse for the first time the statistical link between the properties of G-protein-coupled receptors and GPCR ligands. The technique of mutual information (MI) is able to reveal statistical inter-dependence between variations in amino acid residues on the one hand and variations in ligand molecular descriptors on the other. Although this MI analysis uses novel information that differs from the results of known site-directed mutagenesis studies or published GPCR crystal structures, the method is capable of identifying the well-known common ligand binding region of GPCRs between the upper part of the seven transmembrane helices and the second extracellular loop. The analysis shows amino acid positions that are sensitive to either stimulating (agonistic) or inhibitory (antagonistic) ligand effects or both. It appears that amino acid positions for antagonistic and agonistic effects are both concentrated around the extracellular region, but selective agonistic effects are cumulated between transmembrane helices (TMHs) 2, 3, and ECL2, while selective residues for antagonistic effects are located at the top of helices 5 and 6. Above all, the MI analysis provides detailed indications about amino acids located in the transmembrane region of these receptors that determine G-protein signalling pathway preferences

IL-15 adjuvanted multivalent vaccinia-based universal influenza vaccine requires CD4+ T cells for heterosubtypic protection

Session - Medical SciencesCurrent influenza vaccines are ineffective against novel viruses and the source or the strain of the next outbreak of influenza is unpredictable; therefore, establishing universal immunity by vaccination to limit the impact of influenza remains a high priority. To meet this challenge, a novel vaccine has been developed using the immunogenic live vaccinia virus as a vaccine vector, expressing multiple H5N1 viral proteins (HA, NA, M1, M2, and NP) together with IL-15 as a molecular adjuvant. Previously, this vaccine demonstrated robust sterile cross-clade protection in mice against H5 influenza viruses, and herein its use has been extended to mediate heterosubtypic immunity toward viruses from both group 1 and 2 HA lineages. The vaccine protected mice against lethal challenge by increasing survival and significantly reducing lung viral loads against the most recent human H7N9, seasonal H3N2, pandemic-2009 H1N1, and highly pathogenic H7N7 influenza A viruses. Influenza-specific antibodies elicited by the vaccine failed to neutralize heterologous viruses and were unable to confer protection by passive transfer. Importantly, heterologous influenza-specific CD4(+) and CD8(+) T-cell responses that were elicited by the vaccine were effectively recalled and amplified following viral challenge in the lungs and periphery. Selective depletion of T-cell subsets in the immunized mice revealed an important role for CD4(+) T cells in heterosubtypic protection, despite low sequence conservation among known MHC-II restricted epitopes across different influenza viruses. This study illustrates the potential utility of our multivalent Wyeth/IL-15/5Flu as a universal influenza vaccine with a correlate of protective immunity that is independent of neutralizing antibodies.link_to_OA_fulltex

Structure-based discovery of opioid analgesics with reduced side effects

Morphine is an alkaloid from the opium poppy used to treat pain. The potentially lethal side effects of morphine and related opioids—which include fatal respiratory depression—are thought to be mediated by μ-opioid-receptor (μOR) signalling through the β-arrestin pathway or by actions at other receptors. Conversely, G-protein μOR signalling is thought to confer analgesia. Here we computationally dock over 3 million molecules against the μOR structure and identify new scaffolds unrelated to known opioids. Structure-based optimization yields PZM21—a potent G(i) activator with exceptional selectivity for μOR and minimal β-arrestin-2 recruitment. Unlike morphine, PZM21 is more efficacious for the affective component of analgesia versus the reflexive component and is devoid of both respiratory depression and morphine-like reinforcing activity in mice at equi-analgesic doses. PZM21 thus serves as both a probe to disentangle μOR signalling and a therapeutic lead that is devoid of many of the side effects of current opioids