The intrachain fluorescence quenching of the fluorophore 2,3-diazabicyclo[2.2.2]oct-2-ene (DBO) is measured in short peptide fragments, namely the two strands and the turn of the N-terminal beta-hairpin of ubiquitin. The investigated peptides adopt a random-coil conformation in aqueous solution according to CD and NMR experiments. The combination of quenchers with different quenching efficiencies, namely tryptophan and tyrosine, allows the extrapolation of the rate constants for end-to-end collision rates as well as the dissociation of the end-to-end encounter complex. The measured activation energies for fluorescence quenching demonstrate that the end-to-end collision process in peptides is partially controlled by internal friction within the backbone, while measurements in solvents of different viscosities (H2O, D2O, and 7.0 M guanidinium chloride) suggest that solvent friction is an additional important factor in determining the collision rate. The extrapolated end-to-end collision rates, which are only slightly larger than the experimental rates for the DBO/Trp probe/quencher system, provide a measure of the conformational flexibility of the peptide backbone. The chain flexibility is found to be strongly dependent on the type of secondary structure that the peptides represent. The collision rates for peptides derived from the beta-strand motifs (ca. 1 x 10(7) s(-1)) are ca. 4 times slower than that derived from the beta-turn. The results provide further support for the hypothesis that chain flexibility is an important factor in the preorganization of protein fragments during protein folding. Mutations to the beta-turn peptide show that subtle sequence changes strongly affect the flexibility of peptides as well. The protonation and charge status of the peptides, however, are shown to have no significant effect on the flexibility of the investigated peptides. The meaning and definition of end-to-end collision rates in the context of protein folding are critically discussed.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1021/ja0466053 | DOI Listing |
Sensors (Basel)
December 2024
Ubicom Laboratory, Department of Electrical, Electronic and Computer Engineering, University of Ulsan, Ulsan 44610, Republic of Korea.
The proposed protocol features reliable and fast image transmission while periodically transmitting scalar data without interruption by allowing two networks, a LoRa network and a wireless sensor network, with different transmission characteristics to cooperate. It adopts the RT-LoRa protocol for periodic scalar data transmission and uses a WSN-based pipelined transmission method that leverages single-hop message transmission of a LoRa network for image transmission. Thus, it can not only eliminate the control message overhead for time synchronization, slot scheduling, and path establishment for pipelined image transmission in WSNs but also eliminate interferences within WSNs, such as data collisions and data and message collisions, during pipelined image transmission, thereby enabling high reliability and fast transmission.
View Article and Find Full Text PDFJ Imaging
December 2024
School of Innovation, Design and Technology (IDT), Mälardalen University, 72123 Västerås, Sweden.
As the demand for autonomous driving (AD) systems has increased, the enhancement of their safety has become critically important. A fundamental capability of AD systems is object detection and trajectory forecasting of vehicles and pedestrians around the ego-vehicle, which is essential for preventing potential collisions. This study introduces the Deep learning-based Acceleration-aware Trajectory forecasting (DAT) model, a deep learning-based approach for object detection and trajectory forecasting, utilizing raw sensor measurements.
View Article and Find Full Text PDFJ Chem Phys
October 2024
College of Mathematics and Physics, Chengdu University of Technology, Chengdu 610059, China.
The dynamical and conformational properties of the comb polymer with various rigidities of the backbone and arms in steady shear flow are studied by using a hybrid mesoscale simulation approach that combines multiparticle collision dynamics with standard molecular dynamics. First, during the process of the comb polymer undergoing periodic tumbling motion, we find that the rigidity of the arms always promotes the tumbling motion of the comb polymer, but the rigidity of the backbone shifts from hindering to promoting it with increasing the rigidity of the arms. In addition, the comb polymer transitions from vorticity tumbling to gradient tumbling with the increase in shear rate.
View Article and Find Full Text PDFSci Rep
September 2024
Department of Electronics and Communication Engineering, Government College of Technology, Coimbatore, 641013, India.
A Wireless Sensor Network (WSN) is usually made up of a large number of discrete sensor nodes, each of which requires restricted resources, including memory, computing power, and energy. To extend the network lifetime, these limited resources must be used effectively. In WSN, clustering constitutes one of the best methods for optimizing network longevity and energy conservation.
View Article and Find Full Text PDFSensors (Basel)
July 2024
Department of Laser Technologies, FTMC-Center for Physical Sciences and Technology, Savanoriu Ave. 231, LT-02300 Vilnius, Lithuania.
The wide-ranging applications of the Internet of Things (IoT) show that it has the potential to revolutionise industry, improve daily life, and overcome global challenges. This study aims to evaluate the performance scalability of mature industrial wireless sensor networks (IWSNs). A new classification approach for IoT in the industrial sector is proposed based on multiple factors and we introduce the integration of 6LoWPAN (IPv6 over low-power wireless personal area networks), message queuing telemetry transport for sensor networks (MQTT-SN), and ContikiMAC protocols for sensor nodes in an industrial IoT system to improve energy-efficient connectivity.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!