Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the Best(train)Best(test) and Fast(train)Fast(test) prediction results. The potential inhibitors were selected from NCI database by screening according to Best(train)Best(test) + Fast(train)Fast(test) prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4017722 | PMC |
http://dx.doi.org/10.1155/2014/359494 | DOI Listing |
Foods
December 2024
School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China.
The bioactive components of chrysanthemum tea are an essential indicator in evaluating its nutritive and commercial values. Combining hyperspectral imaging (HSI) with key wavelength selection and pattern recognition methods, this study developed a novel approach to estimating the content of bioactive components in chrysanthemums, including the total flavonoids (TFs) and chlorogenic acids (TCAs). To determine the informative wavelengths of hyperspectral images, we introduced a variable similarity regularization term into particle swarm optimization (denoted as VSPSO), which can focus on improving the combinatorial performance of key wavelengths and filtering out the features with higher collinearity simultaneously.
View Article and Find Full Text PDFElife
December 2024
Department of Neurology, Medical Research Institute, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China.
Identifying target proteins for bioactive molecules is essential for understanding their mechanisms, developing improved derivatives, and minimizing off-target effects. Despite advances in target identification (target-ID) technologies, significant challenges remain, impeding drug development. Most target-ID methods use cell lysates, but maintaining an intact cellular context is vital for capturing specific drug-protein interactions, such as those with transient protein complexes and membrane-associated proteins.
View Article and Find Full Text PDFbioRxiv
December 2024
Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, 22903.
Evolution has developed a set of principles that determine feasible domain combinations analogous to grammar within natural languages. Treating domains as words and proteins as sentences, made up of words, we apply a linguistic approach to represent the human proteome as an n-gram network. Combining this with network theory and application, we explore the functional language and rules of the human proteome.
View Article and Find Full Text PDFNat Biomed Eng
December 2024
School of Basic Medical Sciences, Tsinghua University, Beijing, China.
Potent agonists of the inducible co-stimulatory receptor 4-1BB are too toxic for patients with advanced cancer. Here, on the basis of observations of a weak agonist of 4-1BB depleting regulatory T (T) cells within the tumour microenvironment without leading to substantial restoration of dysfunctional cytotoxic T cells (CTLs), we show that effective tumour control can be achieved via concurrent T cell depletion and CTL expansion through an anti-4-1BB antibody fused to interleukin-15 (IL-15) via a peptide sensitive to tumour proteases. In mouse models of advanced cancers, intraperitoneal injection of the bifunctional protein attenuated the activity of the interleukin mostly in the periphery of the primary tumour while allowing for the expansion of CTLs within the tumour microenvironment, led to more effective tumour inhibition and to lower systemic toxicity than treating the cancers with combinatorial treatment with unlinked anti-4-1BB antibody and IL-15, and reduced the resistance of tumours to checkpoint blockade.
View Article and Find Full Text PDFVis Comput Ind Biomed Art
December 2024
College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, Zhejiang, 325000, China.
This study presents an energy consumption (EC) forecasting method for laser melting manufacturing of metal artifacts based on fusionable transfer learning (FTL). To predict the EC of manufacturing products, particularly from scale-down to scale-up, a general paradigm was first developed by categorizing the overall process into three main sub-steps. The operating electrical power was further formulated as a combinatorial function, based on which an operator learning network was adopted to fit the nonlinear relations between the fabricating arguments and EC.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!