Classification and retrieval of CAD three dimensional models based on neural network

2021 ◽  
Author(s):  
Mingxia Zhao
2021 ◽  
Vol 67 (3) ◽  
pp. 268-277
Author(s):  
P.M. Vassiliev ◽  
A.A. Spasov ◽  
A.N. Kochetkov ◽  
M.A. Perfilev ◽  
A.R. Koroleva

RAGE signal transduction via the RAGE-NF-κB signaling pathway is one of the mechanisms of inflammatory reactions that cause severe complications in diabetes mellitus. RAGE inhibitors are promising pharmacological compounds that require the development of new predictive models. Based on the methodology of artificial neural networks, consensus ensemble neural network multitarget model has been constructed. This model describes the dependence of the level of the RAGE inhibitory activity on the affinity of compounds for 34 target proteins of the RAGE-NF-κB signal pathway. For this purpose an expanded database of valid three-dimensional models of target proteins of the RAGE-NF-κB signal chain was created on the basis of a previously created database of three-dimensional models of relevant biotargets. Ensemble molecular docking of known RAGE inhibitors from a verified database into the sites of added models of target proteins was performed, and the minimum docking energies for each compound in relation to each target were determined. An extended training set for neural network modeling was formed. Using seven variants of sampling by the method of artificial multilayer perceptron neural networks, three ensembles of classification decision rules were constructed to predict three level of the RAGE-inhibitory activity based on the calculated affinity of compounds for significant target proteins of the RAGE-NF-κB signaling pathway. Using a simple consensus of the second level, the predictive ability of the created model was assessed and its high accuracy and statistical significance were shown. The resultant consensus ensemble neural network multitarget model has been used for virtual screening of new derivatives of different chemical classes. The most promising substances have been synthesized and sent for experimental studies.


2021 ◽  
Vol 22 (1) ◽  
pp. 48-55
Author(s):  
O. G. Gvozdev ◽  
V. A. Kozub ◽  
N. V. Kosheleva ◽  
A. B. Murynin ◽  
A. A. Richter

A method has been developed for constructing three-dimensional models of rigid objects on the earth’s surface using one satellite image using the example of railway infrastructure. The method consists in step-by-step processing of satellite images with sequential application of two convolutional neural networks. In the first processing step, a satellite image is segmented by a neural network to select a plurality of objects of predetermined classes. At the second stage of processing with the help of neural network local analysis of image areas detected by results of the first stage of processing is performed. The results of the second processing step are used to estimate the parameters of the 3D model of the object. The possibilities of the method are shown by the example of processing a satellite image of the railway infrastructure. The following classes of informative areas are considered: building, wall edge, roof edge, building shadow, railway infrastructure, car, highway; rails, poles and shadows from poles (taken as reference objects for estimating scaling coefficients in certain directions). An example is given of using the developed method of highlighting typical railway infrastructure objects and for subsequent evaluation of the parameters of a three-dimensional building model partially obscured by trees.


1975 ◽  
Vol 39 (8) ◽  
pp. 544-546
Author(s):  
HL Wakkerman ◽  
GS The ◽  
AJ Spanauf

2020 ◽  
Vol 17 (4) ◽  
pp. 342-351
Author(s):  
Sergio A. Durán-Pérez ◽  
José G. Rendón-Maldonado ◽  
Lucio de Jesús Hernandez-Diaz ◽  
Annete I. Apodaca-Medina ◽  
Maribel Jiménez-Edeza ◽  
...  

Background: The protozoan Giardia duodenalis, which causes giardiasis, is an intestinal parasite that commonly affects humans, mainly pre-school children. Although there are asymptomatic cases, the main clinical features are chronic and acute diarrhea, nausea, abdominal pain, and malabsorption syndrome. Little is currently known about the virulence of the parasite, but some cases of chronic gastrointestinal alterations post-infection have been reported even when the infection was asymptomatic, suggesting that the cathepsin L proteases of the parasite may be involved in the damage at the level of the gastrointestinal mucosa. Objective: The aim of this study was the in silico identification and characterization of extracellular cathepsin L proteases in the proteome of G. duodenalis. Methods: The NP_001903 sequence of cathepsin L protease from Homo sapienswas searched against the Giardia duodenalisproteome. The subcellular localization of Giardia duodenaliscathepsin L proteases was performed in the DeepLoc-1.0 server. The construction of a phylogenetic tree of the extracellular proteins was carried out using the Molecular Evolutionary Genetics Analysis software (MEGA X). The Robetta server was used for the construction of the three-dimensional models. The search for possible inhibitors of the extracellular cathepsin L proteases of Giardia duodenaliswas performed by entering the three-dimensional structures in the FINDSITEcomb drug discovery tool. Results: Based on the amino acid sequence of cathepsin L from Homo sapiens, 8 protein sequences were identified that have in their modular structure the Pept_C1A domain characteristic of cathepsins and two of these proteins (XP_001704423 and XP_001704424) are located extracellularly. Threedimensional models were designed for both extracellular proteins and several inhibitory ligands with a score greater than 0.9 were identified. In vitrostudies are required to corroborate if these two extracellular proteins play a role in the virulence of Giardia duodenalisand to discover ligands that may be useful as therapeutic targets that interfere in the mechanism of pathogenesis generated by the parasite. Conclusion: In silicoanalysis identified two proteins in the Giardia duodenalisprotein repertoire whose characteristics allowed them to be classified as cathepsin L proteases, which may be secreted into the extracellular medium to act as virulence factors. Three-dimensional models of both proteins allowed the identification of inhibitory ligands with a high score. The results suggest that administration of those compounds might be used to block the endopeptidase activity of the extracellular cathepsin L proteases, interfering with the mechanisms of pathogenesis of the protozoan parasite Giardia duodenalis.


2011 ◽  
Vol 49 (4) ◽  
pp. 326-327 ◽  
Author(s):  
Karen A. Eley ◽  
Robin Richards ◽  
Dermot Dobson ◽  
Alf Linney ◽  
Stephen R. Watt-Smith

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