Insertion and deletion analyses of a protein have been less common than point mutation analyses, partly due to the lack in effective methods. This is the case with the green fluorescent protein (GFP), which is so widely applied in molecular biology and other fields. In this paper we first introduce a systematic approach for generating insertion/deletion mutants of GFP. A new technology of Y-ligation-based block shuffling (YLBS) was successfully applied to produce size-altered GFPs, providing insertion-containing GFPs of fluorescence, though no deletion type of fluorescence was obtained so far as examined. The analysis of these proteins suggested that size alteration (deletion/insertion) is acceptable so far as some type of rearrangement in a local structure can accommodate it. This paper demonstrates that YLBS can generate insertion and deletion mutant libraries systematically, which are beneficial in the study of structure-function relationship.
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http://dx.doi.org/10.1016/s0014-5793(03)01308-5 | DOI Listing |
J Phys Chem B
January 2025
Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR 6303 CNRS-Université de Bourgogne, 21078 Dijon Cedex, France.
Biological peptides have emerged as promising candidates for data storage applications due to their versatility and programmability. Recent advances in peptide synthesis and sequencing technologies have enabled the development of peptide-based data storage systems for realizing novel information storage technologies with enhanced capacity, durability, and data access speeds. In this study, we performed coarse-grained peptide sequencing of 12 distinct sequences through single-layer MoS solid-state nanopores (SSNs) using molecular dynamics (MD).
View Article and Find Full Text PDFPeerJ Comput Sci
September 2024
College of Computer and Information Engineering, Henan Normal University, Xinxiang, Henan, China.
Background: With the development of steganography technology, lawbreakers can implement covert communication in social networks more easily, exacerbating network security risks. Sterilization of image steganography methods can eliminate secret messages to block the transmission of illegal covert communication. However, existing methods overly rely on cover-stego image pairs and are unable to sanitize unknown image, which reduces stego image blocking rate in social networks.
View Article and Find Full Text PDFBioengineering (Basel)
October 2024
Department of Computer Science, College of Computers and Information Technology, Taif University, Taif 21944, Saudi Arabia.
Medical professionals primarily utilize medical images to detect anomalies within the interior structures and essential organs concealed by the skeletal and dermal layers. The primary purpose of medical imaging is to extract image features for the diagnosis of medical conditions. The processing of these images is indispensable for evaluating a patient's health.
View Article and Find Full Text PDFExpert Opin Drug Saf
December 2024
Parkinson's Disease Center and Movement Disorders Clinic, Department of Neurology, Baylor College of Medicine, Houston, TX, USA.
Introduction: Drug-induced parkinsonism (DIP) is one of the most common iatrogenic movement disorders. It is characterized by tremors, slowness of movement, and shuffling gait with postural instability, clinically indistinguishable from idiopathic Parkinson's disease. Prior exposure to antipsychotic medications or other dopamine receptor blocking agents (DRBAs) is required for the diagnosis.
View Article and Find Full Text PDFSensors (Basel)
October 2024
School of Information Engineering, Minzu University of China, Beijing 100081, China.
This research aims to overcome three major challenges in foreign object detection on power transmission lines: data scarcity, background noise, and high computational costs. In the improved YOLOv8 algorithm, the newly introduced lightweight GSCDown (Ghost Shuffle Channel Downsampling) module effectively captures subtle image features by combining 1 × 1 convolution and GSConv technology, thereby enhancing detection accuracy. CSPBlock (Cross-Stage Partial Block) fusion enhances the model's accuracy and stability by strengthening feature expression and spatial perception while maintaining the algorithm's lightweight nature and effectively mitigating the issue of vanishing gradients, making it suitable for efficient foreign object detection in complex power line environments.
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