Carlos P. Sosa

Multilevel Parallelization of AutoDock 4.2.

BackgroundVirtual (computational) screening is an increasingly important tool for drug discovery. AutoDock is a popular open-source application for performing molecular docking, the prediction of ligand-receptor interactions. AutoDock is a serial application, though several previous efforts have parallelized various aspects of the program. In this paper, we report on a multi-level parallelization of AutoDock 4.2 (mpAD4).ResultsUsing MPI and OpenMP, AutoDock 4.2 was parallelized for use on MPI-enabled systems and to multithread the execution of individual docking jobs. In addition, code was implemented to reduce input/output (I/O) traffic by reusing grid maps at each node from docking to docking. Performance of mpAD4 was examined on two multiprocessor computers.ConclusionsUsing MPI with OpenMP multithreading, mpAD4 scales with near linearity on the multiprocessor systems tested. In situations where I/O is limiting, reuse of grid maps reduces both system I/O and overall screening time. Multithreading of AutoDocks Lamarkian Genetic Algorithm with OpenMP increases the speed of execution of individual docking jobs, and when combined with MPI parallelization can significantly reduce the execution time of virtual screens. This work is significant in that mpAD4 speeds the execution of certain molecular docking workloads and allows the user to optimize the degree of system-level (MPI) and node-level (OpenMP) parallelization to best fit both workloads and computational resources.

Massively parallel genomic sequence search on the Blue Gene/P architecture

This paper presents our first experiences in mapping and optimizing genomic sequence search onto the massively parallel IBM Blue Gene/P (BG/P) platform. Specifically, we performed our work on mpiBLAST, a parallel sequence-search code that has been optimized on numerous supercomputing environments. In doing so, we identify several critical performance issues. Consequently, we propose and study different approaches for mapping sequence-search and parallel I/O tasks on such massively parallel architectures. We demonstrate that our optimizations can deliver nearly linear scaling (93% efficiency) on up to 32,768 cores of BG/P. In addition, we show that such scalability enables us to complete a large-scale bioinformatics problem --- sequence searching a microbial genome database against itself to support the discovery of missing genes in genomes --- in only a few hours on BG/P. Previously, this problem was viewed as computationally intractable in practice.

Parallel genomic sequence-search on a massively parallel system

In the life sciences, genomic databases for sequence search have been growing exponentially in size. As a result, faster sequence-search algorithms to search these databases continue to evolve to cope with algorithmic time complexity. The ubiquitous tool for such search is the Basic Local Alignment Search Tool (BLAST) [1] from the National Center for Biotechnology Information (NCBI). Despite continued algorithmic improvements in BLAST, it cannot keep up with the rate at which the database is exponentially increasing in size. Therefore, parallel implement-ations such as mpiBLAST have emerged to address this problem. The performance of such implementations depends on a myriad of factors including algorithmic, architectural, and mapping of the algorithm to the architecture. This paper describes modifications and extensions to a parallel and distributed-memory version of BLAST called mpiBLAST-PIO and how it maps to a massively parallel system, specifically IBM Blue Gene/L (BG/L). The extensions include a virtual file manager, a multiple master run-time model, efficient fragment distribution, and intelligent load balancing. In this study, we have shown that our optimized mpiBLAST-PIO on BG/L using a query with 28014 sequences and the NR and NT databases scales to 8192 nodes (two cores per node). The cases tested here are well suited for a massively parallel system.

Norathyriol Suppresses Skin Cancers Induced by Solar Ultraviolet Radiation by Targeting ERK Kinases

Ultraviolet (UV) irradiation is the leading factor in the development of skin cancer, prompting great interest in chemopreventive agents for this disease. In this study, we report the discovery of norathyriol, a plant-derived chemopreventive compound identified through an in silico virtual screening of the Chinese Medicine Library. Norathyriol is a metabolite of mangiferin found in mango, Hypericum elegans, and Tripterospermum lanceolatum and is known to have anticancer activity. Mechanistic investigations determined that norathyriol acted as an inhibitor of extracellular signal-regulated kinase (ERK)1/2 activity to attenuate UVB-induced phosphorylation in mitogen-activated protein kinases signaling cascades. We confirmed the direct and specific binding of norathyriol with ERK2 through a cocrystal structural analysis. The xanthone moiety in norathyriol acted as an adenine mimetic to anchor the compound by hydrogen bonds to the hinge region of the protein ATP-binding site on ERK2. Norathyriol inhibited in vitro cell growth in mouse skin epidermal JB6 P+ cells at the level of G(2)-M phase arrest. In mouse skin tumorigenesis assays, norathyriol significantly suppressed solar UV-induced skin carcinogenesis. Further analysis indicated that norathyriol mediates its chemopreventive activity by inhibiting the ERK-dependent activity of transcriptional factors AP-1 and NF-κB during UV-induced skin carcinogenesis. Taken together, our results identify norathyriol as a safe new chemopreventive agent that is highly effective against development of UV-induced skin cancer.

Threshold occupancy and specific cation binding modes in the hammerhead ribozyme active site are required for active conformation

The relationship between formation of active in-line attack conformations and monovalent (Na(+)) and divalent (Mg(2+)) metal ion binding in hammerhead ribozyme (HHR) has been explored with molecular dynamics simulations. To stabilize repulsions between negatively charged groups, different requirements of the threshold occupancy of metal ions were observed in the reactant and activated precursor states both in the presence and in the absence of a Mg(2+) in the active site. Specific bridging coordination patterns of the ions are correlated with the formation of active in-line attack conformations and can be accommodated in both cases. Furthermore, simulation results suggest that the HHR folds to form an electronegative recruiting pocket that attracts high local concentrations of positive charge. The present simulations help to reconcile experiments that probe the metal ion sensitivity of HHR catalysis and support the supposition that Mg(2+), in addition to stabilizing active conformations, plays a specific chemical role in catalysis.

Multilevel X-Pol: a fragment-based method with mixed quantum mechanical representations of different fragments.

The explicit polarization (X-Pol) method is a fragment-based quantum mechanical model, in which a macromolecular system or other large or complex system in solution is partitioned into monomeric fragments. The present study extends the original X-Pol method, where all fragments are treated using the same electronic structure theory, to multilevel representations, called multilevel X-Pol, in which different electronic structure methods are used to describe different fragments. The multilevel X-Pol method has been implemented into a locally modified version of Gaussian 09. A key ingredient that is used to couple interfragment electrostatic interactions at different levels of theory is the use of the response density for the post-self-consistent-field energy. (The response density is also called the generalized density.) The method is useful for treating fragments in a small region of the system such as a solute molecule or the substrate and amino acids in the active site of an enzyme with a high-level theory, and the fragments in the rest of the system by a lower-level and computationally more efficient method. Multilevel X-Pol is illustrated here by applications to hydrogen bonding complexes in which one fragment is treated with the hybrid M06 density functional, Møller-Plesset perturbation theory, or coupled cluster theory, and the other fragments are treated by Hartree-Fock theory or the B3LYP or M06 hybrid density functionals.

Parallelization of Nullspace Algorithm for the computation of metabolic pathways.

Elementary mode analysis is a useful metabolic pathway analysis tool in understanding and analyzing cellular metabolism, since elementary modes can represent metabolic pathways with unique and minimal sets of enzyme-catalyzed reactions of a metabolic network under steady state conditions. However, computation of the elementary modes of a genome- scale metabolic network with 100-1000 reactions is very expensive and sometimes not feasible with the commonly used serial Nullspace Algorithm. In this work, we develop a distributed memory parallelization of the Nullspace Algorithm to handle efficiently the computation of the elementary modes of a large metabolic network. We give an implementation in C++ language with the support of MPI library functions for the parallel communication. Our proposed algorithm is accompanied with an analysis of the complexity and identification of major bottlenecks during computation of all possible pathways of a large metabolic network. The algorithm includes methods to achieve load balancing among the compute-nodes and specific communication patterns to reduce the communication overhead and improve efficiency.

Quercetin-3-methyl ether suppresses proliferation of mouse epidermal JB6 P+ cells by targeting ERKs

Chemoprevention has been acknowledged as an important and practical strategy for the management of skin cancer. Quercetin-3-methyl ether, a naturally occurring compound present in various plants, has potent anticancer-promoting activity. We identified this compound by in silico virtual screening of the Traditional Chinese Medicine Database using extracellular signal-regulated kinase 2 (ERK2) as the target protein. Here, we showed that quercetin-3-methyl ether inhibited proliferation of mouse skin epidermal JB6 P+ cells in a dose- and time-dependent manner by inducing cell cycle G(2)-M phase accumulation. It also suppressed 12-O-tetradecanoylphorbol-13-acetate-induced neoplastic cell transformation in a dose-dependent manner. Its inhibitory effect was greater than quercetin. The activation of activator protein-1 was dose-dependently suppressed by quercetin-3-methyl ether treatment. Western blot and kinase assay data revealed that quercetin-3-methyl ether inhibited ERKs kinase activity and attenuated phosphorylation of ERKs. Pull-down assays revealed that quercetin-3-methyl ether directly binds with ERKs. Furthermore, a loss-of-function ERK2 mutation inhibited the effectiveness of the quercetin-3-methyl ether. Overall, these results indicated that quercetin-3-methyl ether exerts potent chemopreventive activity by targeting ERKs.

An Efficient Parallel Implementation of the Hidden Markov Methods for Genomic Sequence-Search on a Massively Parallel System

Bioinformatics databases used for sequence comparison and sequence alignment are growing exponentially. This has popularized programs that carry out database searches. Current implementations of sequence alignment methods based on hidden Markov models (HMM) have proven to be computationally intensive and, hence, amenable to architectures with multiple processors. In this paper, we describe a modified version of the original parallel implementation of HMMs on a massively parallel system. This is part of the HMMER bioinformatics code. HMMER 2.3.2 uses profile HMMs for sensitive database searching based on statistical descriptions of a sequence familys consensus (Durbin et al., 1998), Two of the nine programs were further parallelized to take advantage of the large number of processors, namely, hmmsearch and hmmpfam. For our study, we start by porting the parallel virtual machine (PVM) versions of these two programs currently available as part of the HMMER suite of programs. We report the performance of these nonoptimized versions as baselines. Our work also includes the introduction of an alternate sequence file indexing, multiple-master configuration, dynamic data collection and, finally, load balancing via the indexed sequence files. This set of optimizations constitutes our modified version for massively parallel systems. Our results show parallel performance improvements of more than one order of magnitude (16 times) for hmmsearch and hmmpfam.

Ab Initio Conformational Space Study of Model Compounds of O‐Glycosides of Serine Diamide

Relative stabilities of rotamers of the N-acetyl-O-(2-acetamido-2-deoxy-alpha-D-galactopyranosyl)-L-seryl-N-methyl amide (1) and eleven analogous molecules containing beta-galactose, alpha- and beta-mannose, alpha- and beta-glucose, and L-threonine were calculated to learn whether they could explain the natural preference for 1 in linkages between the carbohydrate and protein in glycoproteins. The lowest energy rotamers of four O-glycoside models of serine diamide were identified with a Monte Carlo search coupled with molecular mechanics (MM2*). These rotamers were further optimized with an ab initio level of theory (HF/6-31G(d)). Subsequently, B3LYP/6-31 + G(d) single point energies were calculated for the most stable HF structures. The most favorable interactions are present in 1 and its glucose analogue. The monosaccharide for the carbohydrate antenna is anchored to the serine residue with an AcNH...O=C-NHMe hydrogen bond in the most stable rotamers. The mannose analogue and the beta-anomers are considerably less stable according to the MM2* and especially to the ab inito energy values. The three analogues have HF/6-31 G(d) energies which are 4-6 kcal mol-1 higher; the single point B3LYP/6-31 + G(d)//HF/6-31 G(d) calculations yield preferences of 3-5 kcal mol-1 for 1. The most stable L-threonine analogues show a behaviour very similarly to the corresponding serine analogues. The ZPE and thermal correction components of the calculated delta H298 and delta G298 values are relatively small (< 0.4 kcal mol-1). However, the T delta S298 term can be as large as 2.6 kcal mol-1. The entropy terms stabilize the alpha-anomers relative to beta-anomers, and ManNAc relative to GalNAc. The largest stabilization effect is observed for one of the rotamers of the alpha-anomer of ManNAc.