{"title":"Computer simulation reveals the effect of severing enzymes on dynamic and stabilized microtubules.","authors":"Aritra Sen, Ambarish Kunwar","doi":"10.1088/1478-3975/acc301","DOIUrl":null,"url":null,"abstract":"<p><p>Microtubule (MT) severing enzymes Katanin and Spastin cut the MT into smaller fragments and are being studied extensively using<i>in-vitro</i>experiments due to their crucial role in different cancers and neurodevelopmental disorders. It has been reported that the severing enzymes are either involved in increasing or decreasing the tubulin mass. Currently, there are a few analytical and computational models for MT amplification and severing. However, these models do not capture the action of MT severing explicitly, as these are based on partial differential equations in one dimension. On the other hand, a few discrete lattice-based models were used earlier to understand the activity of severing enzymes only on stabilized MTs. Hence, in this study, discrete lattice-based Monte Carlo models that included MT dynamics and severing enzyme activity have been developed to understand the effect of severing enzymes on tubulin mass, MT number, and MT length. It was found that the action of severing enzyme reduces average MT length while increasing their number; however, the total tubulin mass can decrease or increase depending on the concentration of GMPCPP (Guanylyl-(<i>α</i>,<i>β</i>)-methylene-diphosphonate)-which is a slowly hydrolyzable analogue of GTP (Guanosine triphosphate). Further, relative tubulin mass also depends on the detachment ratio of GTP/GMPCPP and Guanosine diphosphate tubulin dimers and the binding energies of tubulin dimers covered by the severing enzyme.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1088/1478-3975/acc301","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Microtubule (MT) severing enzymes Katanin and Spastin cut the MT into smaller fragments and are being studied extensively usingin-vitroexperiments due to their crucial role in different cancers and neurodevelopmental disorders. It has been reported that the severing enzymes are either involved in increasing or decreasing the tubulin mass. Currently, there are a few analytical and computational models for MT amplification and severing. However, these models do not capture the action of MT severing explicitly, as these are based on partial differential equations in one dimension. On the other hand, a few discrete lattice-based models were used earlier to understand the activity of severing enzymes only on stabilized MTs. Hence, in this study, discrete lattice-based Monte Carlo models that included MT dynamics and severing enzyme activity have been developed to understand the effect of severing enzymes on tubulin mass, MT number, and MT length. It was found that the action of severing enzyme reduces average MT length while increasing their number; however, the total tubulin mass can decrease or increase depending on the concentration of GMPCPP (Guanylyl-(α,β)-methylene-diphosphonate)-which is a slowly hydrolyzable analogue of GTP (Guanosine triphosphate). Further, relative tubulin mass also depends on the detachment ratio of GTP/GMPCPP and Guanosine diphosphate tubulin dimers and the binding energies of tubulin dimers covered by the severing enzyme.
期刊介绍:
Physical Biology publishes articles in the broad interdisciplinary field bridging biology with the physical sciences and engineering. This journal focuses on research in which quantitative approaches – experimental, theoretical and modeling – lead to new insights into biological systems at all scales of space and time, and all levels of organizational complexity.
Physical Biology accepts contributions from a wide range of biological sub-fields, including topics such as:
molecular biophysics, including single molecule studies, protein-protein and protein-DNA interactions
subcellular structures, organelle dynamics, membranes, protein assemblies, chromosome structure
intracellular processes, e.g. cytoskeleton dynamics, cellular transport, cell division
systems biology, e.g. signaling, gene regulation and metabolic networks
cells and their microenvironment, e.g. cell mechanics and motility, chemotaxis, extracellular matrix, biofilms
cell-material interactions, e.g. biointerfaces, electrical stimulation and sensing, endocytosis
cell-cell interactions, cell aggregates, organoids, tissues and organs
developmental dynamics, including pattern formation and morphogenesis
physical and evolutionary aspects of disease, e.g. cancer progression, amyloid formation
neuronal systems, including information processing by networks, memory and learning
population dynamics, ecology, and evolution
collective action and emergence of collective phenomena.