Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

Data Mining Practical Machine Learning Tools and Techniques

The Taverna workflow tool suite (http://www.taverna.org.uk) is designed to combine distributed Web Services and/or local tools into complex analysis pipelines. These pipelines can be executed on local desktop machines or through larger infrastructure (such as supercomputers, Grids or cloud environments), using the Taverna Server. In bioinformatics, Taverna workflows are typically used in the areas of high-throughput omics analyses (for example, proteomics or transcriptomics), or for evidence gathering methods involving text mining or data mining. Through Taverna, scientists have access to several thousand different tools and resources that are freely available from a large range of life science institutions. Once constructed, the workflows are reusable, executable bioinformatics protocols that can be shared, reused and repurposed. A repository of public workflows is available at http://www.myexperiment.org. This article provides an update to the Taverna tool suite, highlighting new features and developments in the workbench and the Taverna Server.

/pdf/the-taverna-workflow-suite-designing-and-executing-workflows-29tfomis0g.pdf

The Taverna workflow suite: designing and executing workflows of Web Services on the desktop, web or in the cloud

Alzheimer’s disease is the most common neurodegenerative disease, and there are no mechanism-based therapies. The disease is defined by the presence of abundant neurofibrillary lesions and neuritic plaques in the cerebral cortex. Neurofibrillary lesions comprise paired helical and straight tau filaments, whereas tau filaments with different morphologies characterize other neurodegenerative diseases. No high-resolution structures of tau filaments are available. Here we present cryo-electron microscopy (cryo-EM) maps at 3.4–3.5 A resolution and corresponding atomic models of paired helical and straight filaments from the brain of an individual with Alzheimer’s disease. Filament cores are made of two identical protofilaments comprising residues 306–378 of tau protein, which adopt a combined cross-β/β-helix structure and define the seed for tau aggregation. Paired helical and straight filaments differ in their inter-protofilament packing, showing that they are ultrastructural polymorphs. These findings demonstrate that cryo-EM allows atomic characterization of amyloid filaments from patient-derived material, and pave the way for investigation of a range of neurodegenerative diseases. High-resolution structures of tau filaments shed light on the ultrastructure of neurofibrillary lesions in Alzheimer’s disease. Alzheimer's disease is defined by the presence of abundant neurofibrillary lesions and neuritic plaques in the cerebral cortex. The lesions are made of paired helical and straight tau filaments (PHFs and SFs, respectively). Different tau filaments characterize other neurodegenerative diseases, suggesting that molecular conformers of aggregated tau underlie human tauopathies. No high-resolution structures of tau filaments are currently available. Here, Sjors Scheres and colleagues present cryo-electron microscopy (cryo-EM) maps at 3.5 A resolution and corresponding atomic models of PHFs and SFs from the brain of an individual with Alzheimer's disease. Their results show that cryo-EM enables atomic characterization of amyloid filaments from patient-derived material and could be used to study a range of neurodegenerative diseases.

Cryo-EM structures of tau filaments from Alzheimer's disease

http://csmres.co.uk/cs.public.upd/article-downloads/Machine-learning-approaches-in-drug-discovery-methods-and-applications.pdf

Machine-learning approaches in drug discovery: methods and applications.

Open-Source Chemoinformatics Software

Background TNF deregulation plays a critical role in the pathogenesis of a range of immune-mediated diseases. On the other hand, RANKL, a member of the TNF family, regulates osteoclast formation and bone resorption. Inhibitors of these trimeric molecules have been used to treat patients suffering from chronic inflammatory diseases and osteoporosis, respectively. Our aim has been to create an integrated pipeline which through comprehensive computational and experimental methods would lead to the discovery of small molecule dual inhibitors of TNF and RANKL. Materials and methods Structure and ligand–based modelling as well as molecular dynamics were applied for the virtual screening and identification of small-molecules that act as dual inhibitors of TNF and RANKL via their shared trimerization interface. The highest ranking compounds were then tested in vitro in the L929 cell assay to assess their ability to inhibit the cytotoxic effect of TNF. Additionally, TNF-TNFRI binding inhibition was tested through ELISA. The successful compounds were also evaluated ex vivo in mouse bone marrow cells stimulated with RANKL and M-CSF to inhibit RANKL-dependent osteoclast differentiation. The cytotoxic effects of the compounds were also assessed. Results A consensus predictive model based on several known TNF inhibitors generated a priority list of 9 small molecules as candidates for TNF function inhibition. The model was made freely available through the Enalos Cloud platform. In vitro evaluation of the compounds led to the selection of two small molecules (T8 and T23) that inhibit TNF function, with IC50s similar to a previously-described inhibitor (SPD304), albeit displaying reduced toxicity. Both compounds were found to significantly inhibit RANKL in inducing the formation of osteoclasts. Further screening of compounds using the same approach led to identification of three additional nontoxic inhibitors of TNF that act at a nanomolar range. Conclusion Five new small molecule inhibitors of TNF have been identified. Two of them (T8 and T23) have been already confirmed as RANKL inhibitors. The compounds are currently under in vivo evaluation and their further optimisation may contribute to the development of novel dual inhibitor therapeutics.

https://ard.bmj.com/content/annrheumdis/76/Suppl_1/A59.1.full.pdf

05.17 An integrated chemoinformatics-aided pipeline for the discovery of small–molecule dual inhibitors of tnf and rankl

Robust experimental evidence has highlighted the role of Autotaxin (ATX)/Lysophosphatidic acid (LPA) axis not only in the pathogenesis of chronic inflammatory conditions and especially in fibroproliferative diseases but also in several types of cancer. As a result, different series of substrate-, lipid-based and small-molecule ATX inhibitors have been identified thus far by both academia and pharma. The "crowning achievement" of these drug discovery campaigns was the development and entry of the first-in-class ATX inhibitor (ziritaxestat, GLPG-1690) in advanced clinical trials against idiopathic pulmonary fibrosis. Herein, the potency optimization efforts of a new series of Autotaxin inhibitors, namely 2-substituted-2,6-dihydro-4H-thieno[3,4-c]pyrazol-1-substituted amide, is described using a previously identified novel chemical scaffold as a "hit". The mode of inhibition of the most promising ATX inhibitors was investigated, while their cellular activity, aqueous solubility and cytotoxicity were evaluated. Our pharmacological results were corroborated by chemoinformatic tools (molecular docking and molecular dynamics simulations) deployed, to provide insight into the binding mechanism of the synthesized inhibitors to ATX. 

Georgia Melagraki

Papers

Open-Source Chemoinformatics Software

05.17 An integrated chemoinformatics-aided pipeline for the discovery of small–molecule dual inhibitors of tnf and rankl

"Hit" to lead optimization and chemoinformatic studies for a new series of Autotaxin inhibitors.

Reducing health & environmental impacts of chemical warfare agents: Computational chemistry contributions.

Accelerating the Identification of Chemistry-Driven Bioactive Compounds within a Multi-Objective Optimization Framework