Swarm robotics has been attracting much attention in recent years in the field of robotics. This chapter describes a methodology for the construction of molecular swarm robots through precise control of active self-assembly of microtubules (MTs). Detailed protocols are presented for the construction of molecular robots through conjugation of DNA to MTs and demonstration of swarming of the MTs. The swarming is mediated by DNA-based interaction and photoirradiation which act as processors and sensors respectively for the robots. Furthermore, the required protocols to utilize the swarming of MTs for molecular computation is also described.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/978-1-0716-1983-4_14 | DOI Listing |
Front Biosci (Landmark Ed)
November 2024
Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 230022 Hefei, Anhui, China.
Background: Aneuploidy is crucial yet under-explored in cancer pathogenesis. Specifically, the involvement of brain expressed X-linked gene 4 () in microtubule formation has been identified as a potential aneuploidy mechanism. Nevertheless, 's comprehensive impact on aneuploidy incidence across different cancer types remains unexplored.
View Article and Find Full Text PDFJ Integr Neurosci
December 2024
Department of Human Anatomy, School of Basic Medical Sciences, Wannan Medical College, 241002 Wuhu, Anhui, China.
Background: K48-linked ubiquitin chain (Ub-K48) is a crucial ubiquitin chain implicated in protein degradation within the ubiquitin-proteasome system. However, the precise function and molecular mechanism underlying the role of Ub-K48 in the pathogenesis of Alzheimer's disease (AD) and neuronal cell abnormalities remain unclear. The objective of this study was to examine the function of K48 ubiquitination in the etiology of AD, and its associated mechanism of neuronal apoptosis.
View Article and Find Full Text PDFJACS Au
December 2024
Key Laboratory of Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun 130023, P. R. China.
In this study, we developed a machine-learning-aided protein design strategy for engineering hemoglobin (VHb) as carbene transferase. A Natural Language Processing (NLP) model was used for the first time to construct an algorithm (EESP, enzyme enantioselectivity score predictor) and predict the enantioselectivity of VHb. We identified critical amino acid residue sites by molecular docking and established a simplified mutation library by site-saturated mutagenesis.
View Article and Find Full Text PDFJACS Au
December 2024
Faculty of Synthetic Biology, Shenzhen University of Advanced Technology, Shenzhen 518055, China.
The origin of life on Earth remains one of the most perplexing challenges in biochemistry. While numerous bottom-up experiments under prebiotic conditions have provided valuable insights into the spontaneous chemical genesis of life, there remains a significant gap in the theoretical understanding of the complex reaction processes involved. In this study, we propose a novel approach using a roto-translationally invariant potential (RTIP) formulated with pristine Cartesian coordinates to facilitate the simulation of chemical reactions.
View Article and Find Full Text PDFJ Inflamm Res
December 2024
Beijing Institute of Heart, Lung and Blood Vessel Diseases, The Key Laboratory of Remodeling Cardiovascular Diseases, Ministry of Education, Collaborative Innovation Center for Cardiovascular Disorders, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Aim: To investigate the regulatory mechanism of CXCL16 molecule-related ( extract-induced antigen presentation in a mouse asthma model based on the long non-coding RNA (lncRNA) and mRNA expression profile.
Methods: knockout mice and wild-type mice were administered with . extract by intratracheal instillations to induce asthma airway inflammation.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!