Improved large-scale prediction of growth inhibition patterns using the NCI60 cancer cell line panel

International audienceMotivation: Recent large-scale omics initiatives have catalogued the somatic alterations of cancer cell line panels along with their pharmacological response to hundreds of compounds. In this study, we have explored these data to advance computational approaches that enable more effective and targeted use of current and future anticancer therapeutics.Results: We modelled the 50% growth inhibition bioassay end-point (GI50) of 17 142 compounds screened against 59 cancer cell lines from the NCI60 panel (941 831 data-points, matrix 93.08% complete) by integrating the chemical and biological (cell line) information. We determine that the protein, gene transcript and miRNA abundance provide the highest predictive signal when modelling the GI50 endpoint, which significantly outperformed the DNA copy-number variation or exome sequencing data (Tukey’s Honestly Significant Difference, P <0.05). We demonstrate that, within the limits of the data, our approach exhibits the ability to both interpolate and extrapolate compound bioactivities to new cell lines and tissues and, although to a lesser extent, to dissimilar compounds. Moreover, our approach outperforms previous models generated on the GDSC dataset. Finally, we determine that in the cases investigated in more detail, the predicted drug-pathway associations and growth inhibition patterns are mostly consistent with the experimental data, which also suggests the possibility of identifying genomic markers of drug sensitivity for novel compounds on novel cell lines

Temperature Accelerated Molecular Dynamics with Soft-Ratcheting Criterion Orients Enhanced Sampling by Low-Resolution Information

International audienceMany proteins exhibit an equilibrium between multiple conformations, some of them being characterized only by low-resolution information. Visiting all conformations is a demanding task for computational techniques performing enhanced but unfocused exploration of collective variable (CV) space. Otherwise, pulling a structure toward a target condition biases the exploration in a way difficult to assess. To address this problem, we introduce here the soft-ratcheting temperature-accelerated molecular dynamics (sr-TAMD), where the exploration of CV space by TAMD is coupled to a soft-ratcheting algorithm that filters the evolving CV values according to a predefined criterion. Any low resolution or even qualitative information can be used to orient the exploration. We validate this technique by exploring the conformational space of the inactive state of the catalytic domain of the adenyl cyclase AC from Bordetella pertussis. The domain AC gets activated by association with calmodulin (CaM), and the available crystal structure shows that in the complex the protein has an elongated shape. High-resolution data are not available for the inactive, CaM-free protein state, but hydrodynamic measurements have shown that the inactive AC displays a more globular conformation. Here, using as CVs several geometric centers, we use sr-TAMD to enhance CV space sampling while filtering for CV values that correspond to centers moving close to each other, and we thus rapidly visit regions of conformational space that correspond to globular structures. The set of conformations sampled using sr-TAMD provides the most extensive description of the inactive state of AC up to now, consistent with available experimental information

Lobeline Docking on AChBP and Nicotinic Receptors: Discriminating Importance of the Pocket Geometry and of the Ligand Configuration

Article signalé par l'éditeur en open access plus : http://www.eurekaselect.com/node/634/letters-in-drug-design-discovery/issue/9/503/1/4249International audienceDocking of lobeline, a partial agonist of nicotinic acetylcholine receptors (nAChRs), was investigated at once into crystallographic structures of acetylcholine binding proteins (AChBP) and into 7 and 42 nAChRs homology models, and compared to behavior of full agonists, nicotine and epibatidine. The homology models were built using as templates the different pocket geometries established in crystallographic AChBP structures. Systematic cross-docking of each ligand into binding pockets of the two other ligands as well as its self-docking into its own pocket were performed in order to better understand the structural features determining the binding of these three ligands chosen for their molecular diversity. In AChBPs, epibatidine and nicotine display similar docking scores in their own pocket and in other ligands pockets: in particular, they also dock favorably into the lobeline pocket. In opposite, lobeline displays different features: it only binds favorably to its own pocket in AChBPs. Furthermore, the docking poses observed starting from lobeline stereoisomers support the importance of the intramolecular hydrogen bond between the alcohol function of the-phenyl-hydroxyethyl arm and the piperidinium proton for the lobeline binding to AChBP. For homology models, cross-dockings are still discriminating and the specificity of lobeline for its binding pocket is conserved

Allosteric Communication within the Cytoplasmic Region of the Histidine Kinase CpxA, Revealed by Molecular Dynamics Simulations of the Wild-Type and M228V Proteins

International audienceThe histidine kinases belong to the family of two-component systems, which serves in bacteria to couple environmental stimuli to adaptive responses. Most of the histidine kinases are homodimers, in which the HAMP and DHp domains assemble into an elongated helical region flanked by two CA domains. Recently, X-ray crystallographic structures of the cytoplasmic region of the Escherichia coli histidinekinase CpxA were determined [1] and a phosphotransferase-defective mutant, M228V, located in HAMP, was identified

The interval branch-and-prune algorithm for the protein structure determination

1123156A56A61st Annual Meeting of the Biophysical-Society11 a 15 de fevereiro de 2017New Orleans, LABiophysical SocietyNew Orleans Ernest N. Morial Convention Cente

The ligand transition.

<p>A and B: residues-lobeline donor/acceptor distances (see legends); C: lobeline and protein residues configuration before the OH transition; D: after the OH transition.</p

Two dimensional histograms.

<p>Two dimensional histograms n(, LYS143/TYR188 closest donor/acceptor distance). A: simulation P; B: P1; C: P1+L; D and E: TAMD from the P1 initial condition at 3 kcal/mol and 5 kcal/mol; F and G: TAMD from the P1-40 ns initial condition at 3 kcal/mol and 5 kcal/mol; H and I: TAMD from P1+L initial condition at 3 kcal/mol and 5 kcal/mol.</p

Protein-lobeline donor/acceptor distances.

<p>Protein-lobeline donor/acceptor distances involved in the ligand transition in some representative subunits along the TAMD trajectories. First row from top:(P1+L)₃ trajectory; second row: (P1+L)₅; third row: (P1+L)₇; fourth row: (P1+L)₁₀. Left column: LOB-NH/W147-CO (black), LOB-OH/S146-CO (green), LOB-OH/W147-CO (red) and LOB-OH/Y55-OH (purple) hydrogen bond distances. Right column: LOB-OH/Y93-OH (black) and LOB-OH/Y188-OH (green) hydrogen bond distances.</p

The structure of AChBP.

<p>The five homomeric subunits in AChBP are labeled S1, S2, S3, S4, S5, in a clockwise direction as viewed from the apical side and colored black, red, green, blue, yellow respectively. A) View from the apical side of the AChBP protein, shown as a cartoon model; B) Side view; C) The AChBP subunit interface bound to the ligand lobeline, represented in sticks. The relevant loops on both the principal and complementary subunit are indicated.</p