Homology modeling and molecular dynamics simulations of MUC1-9/H-2Kb complex suggest novel binding interactions

International audienceHuman MUC1 is over-expressed in human adenocarcinomas and has been used as a target for immunotherapy studies. The 9-mer MUC1-9 peptide has been identified as one of the peptides which binds to murine MHC class I H-2K. The structure of MUC1-9 in complex with H-2K has been modeled and simulated with classical molecular dynamics, based on the x-ray structure of the SEV9 peptide/H-2K complex. Two independent trajectories with the solvated complex (10 ns in length) were produced. Approximately 12 hydrogen bonds were identified during both trajectories to contribute to peptide/MHC complex, as well as 1-2 water mediated hydrogen bonds. Stability of the complex was also confirmed by buried surface area analysis, although the corresponding values were about 20% lower than those of the original x-ray structure. Interestingly, a bulged conformation of the peptide's central region, partially characterized as a -turn, was found exposed form the binding groove. In addition, P1 and P9 residues remained bound in the A and F binding pockets, even though there was a suggestion that P9 was more flexible. The complex lacked numerous water mediated hydrogen bonds that were present in the reference peptide x-ray structure. Moreover, local displacements of residues Asp4, Thr5 and Pro9 resulted in loss of some key interactions with the MHC molecule. This might explain the reduced affinity of the MUC1-9 peptide, relatively to SEV9, for the MHC class I H-2K

Fuel type mapping using object-based image analysis of DMC and Landsat-8 OLI imagery

Efficient forest fire management requires precise and up-to-date knowledge regarding the composition and spatial distribution of forest fuels at various spatial and temporal scales. Fuel-type maps are essential for effective fire prevention strategies planning, as well as the alleviation of the environmental impacts of potential wildfire events. The aim of this study was to assess and compare the potential of Disaster Monitoring Constellation and Landsat-8 OLI satellite images (Operational Land Imager), combined with Object-Based Image Analysis (GEOBIA), in operational mapping of the Mediterranean fuel types at a regional scale. The results showcase that although the images of both sensors can be used with GEOBIA analysis for the generation of accurate fuel-type maps, only the OLI images can be considered as applicable for regional mapping of the Mediterranean fuel types on an operational basis

The Ac-RGD-NH2 peptide as a probe of slow conformational exchange of short linear peptides in DMSO

According to general belief, the conformational information on short linear peptides in solution derived at ambient temperature from NMR spectrometry represents a population-weighted average over all members of an ensemble of rapidly interconverting conformations. Usually the search for discrete conformations is concentrated at low temperatures especially when sharp NMR resonances are detected at room temperature. Using the peptide Ac-RGD-NH2 (Ac-Arg-Gly-Asp-NH2, Ac: acetyl) as a model system and following a new approach, we have been able to demonstrate that short linear peptides can adopt discrete conformational states in DMSO-d6 (DMSO: dimethylsulfoxide) which vary in a way critically dependent on the reconstitution conditions used before their dissolution in DMSO-d6. The conformers are stabilized by intramolecular hydrogen bonds, which persist at high temperatures and undergo a very slow exchange with their extended structures in the NMR chemical shift time scale. The reported findings provide clear evidence for the occurrence of solvent-induced conformational exchange and point to DMSO as a valuable medium for folding studies of short linear peptides. © 2003 Wiley Periodicals, Inc

Overview of the SLAVE learning algorithm: A review of its evolution and prospects

Inductive learning has been—and still is—one of the most important methods that can be applied in classification problems. Knowledge is usually represented using rules that establish relationships between the problem variables. SLAVE (Structural Learning Algorithm in a Vague Environment) was one of the first fuzzy-rule learning algorithms, and since its first implementation in 1994 it has been frequently used to benchmark new algorithms. Over time, the algorithm has undergone several modifications, and identifying the different versions developed is not an easy task. In this work we present a study of the evolution of the SLAVE algorithm from 1996 to date, marking the most important landmarks as definitive versions. In order to add these final versions to the KEEL platform, Java implementations have been developed. Finally, we describe the parameters used and the results obtained in the experimental study

BARD: a global and regional validation burned area database

The FireCCI project is part of the European Space Agency's (ESA) Climate Change Initiative (CCI) programme. The project focuses on the Fire Disturbance Essential Climate Variable(ECV) and specifically on 'Burned Area' (BA) products. The main objective of the FireCCI project is the development and improvement of the burned area detection algorithms, including the product validation protocols. The FireCCI project has developed several global BA products: FireCCI31 and FireCCI41 based on MERIS data, FireCCI50 and the last version FireCCI51 based on MODIS data at 250 m spatial resolution (Chuvieco, et al., 2018; Lizundia-Loiola, et al., 2020). In addition, high resolution BA products have been produced for regional or continental scale (e.g. FireCCISFD11 (Roteta, et al., 2019) based on Sentinel-2 data, for Sub-Saharan Africa at 20 m spatial resolution, and FireCCIS1SA10 (Belenguer-Plomer, et al., 2019) derived from Sentinel-1 for 2017 for the Amazon basin in South America). Moreover, the FireCCI project has promoted the research on BA validation methodologies generating statistically rigorous protocols to implement the accuracy assessment of BA product according the CEOS LPVS stage 3 validation requeriments (Padilla, et al., 2014; 2015; 2017). As a result of this research and the BA product validation activities, several global and regional burned area reference datasets were generated and compiled to create a Burned Area Reference Database (BARD) for validation. Contributions from other international projects and researches as BAECV CONUS, BrFLAS, and NOFFI, have significantly increased the BARD database

Synthesis of a proline-rich [60]fullerene peptide with potential biological activity

A proline-rich 60fullerene peptide was synthesized by use of (i) a 1,3-dipolar cycloaddn. of an N-substituted glycine deriv. to 60fullerene (F60), (ii) esterification of the isolated alc. with the C-terminal amino acid of the desired peptide sequence, and finally (iii) coupling of the remaining hexapeptide to give the final product H-Pro-Pro-Gly-Met-Arg-Pro-Pro-O(CH2)2O(CH2)2N(CH2)2-F60 as a TFA salt, with oxidized methionine (I). Product I was found to be biol. active against sera from MCTD (Mixed connective Tissue Disease) and SLE (Systemic Lupus Erythematosus) patients (ELISA expt.)