1
|
Guo W, Gao Y, Du D, Sanchez JE, Li Y, Qiu W, Li L. Elucidating the interactions between Kinesin-5/BimC and the microtubule: insights from TIRF microscopy and molecular dynamics simulations. Brief Bioinform 2025; 26:bbaf144. [PMID: 40172259 PMCID: PMC11962974 DOI: 10.1093/bib/bbaf144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2024] [Revised: 03/07/2025] [Accepted: 03/11/2025] [Indexed: 04/04/2025] Open
Abstract
Kinesin-5 s are bipolar motor proteins that contribute to cell division by crosslinking and sliding apart antiparallel microtubules inside the mitotic spindle. However, the mechanism underlying the interactions between kinesin-5 and the microtubule remains poorly understood. In this study, we investigated the binding of BimC, a kinesin-5 motor from Aspergillus nidulans, to the microtubule using a combination of total internal reflection fluorescence (TIRF) microscopy and molecular dynamics (MD) simulations. TIRF microscopy experiments revealed that increasing the concentration of KCl in the motility buffer from 0 mM to 150 mM completely abolishes the ability of BimC to bind to the microtubule. Consistent with this experimental finding, MD simulations demonstrated a significant reduction in the strength of electrostatic interactions between BimC and microtubules at 150 mM KCl compared to 0 mM KCl. Furthermore, we identified several salt bridges at the BimC-microtubule interface, with positively charged residues on BimC interacting with negatively charged residues on the tubulin heterodimer. These results provide mechanistic insights into the role of electrostatic interactions in kinesin-5-microtubule binding, advancing our understanding of the molecular underpinnings of kinesin-5 motility.
Collapse
Affiliation(s)
- Wenhan Guo
- Department of Physics, University of Texas at El Paso, 500 W University Ave, El Paso, TX 79968, United States
| | - Yuan Gao
- Department of Physics, Oregon State University, 1500 Jefferson Way, Corvallis, OR 97330, United States
| | - Dan Du
- Computational Science Program, University of Texas at El Paso, 500 W University Ave, El Paso, TX 79968, United States
| | - Jason E Sanchez
- Computational Science Program, University of Texas at El Paso, 500 W University Ave, El Paso, TX 79968, United States
| | - Yupeng Li
- Department of Pharmaceutical Sciences, University of Texas at El Paso, 500 W University Ave, El Paso, TX 79968, United States
- Border Biomedical Research Center, University of Texas at El Paso, 500 W University Ave, El Paso, TX 79968, United States
| | - Weihong Qiu
- Department of Physics, Oregon State University, 1500 Jefferson Way, Corvallis, OR 97330, United States
| | - Lin Li
- Department of Physics, University of Texas at El Paso, 500 W University Ave, El Paso, TX 79968, United States
- Computational Science Program, University of Texas at El Paso, 500 W University Ave, El Paso, TX 79968, United States
- Border Biomedical Research Center, University of Texas at El Paso, 500 W University Ave, El Paso, TX 79968, United States
| |
Collapse
|
2
|
Fan T, Liu W, Qu R, Zhu J, Shi Y, Liu J, Li X, Zhou Z, Chang Y, Ouyang J, Dai J. Actin polymerization regulates the osteogenesis of hASCs by influencing α-tubulin expression and Eg5 activity. Genes Dis 2025; 12:101380. [PMID: 39584074 PMCID: PMC11585723 DOI: 10.1016/j.gendis.2024.101380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 01/31/2024] [Accepted: 06/09/2024] [Indexed: 11/26/2024] Open
Affiliation(s)
- Tingyu Fan
- Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics & Guangdong Engineering Research Center for Translation of Medical 3D Printing Application & National Virtual & Reality Experimental Education Center for Medical Morphology (Southern Medical University) & National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Wenqing Liu
- Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics & Guangdong Engineering Research Center for Translation of Medical 3D Printing Application & National Virtual & Reality Experimental Education Center for Medical Morphology (Southern Medical University) & National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Rongmei Qu
- Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics & Guangdong Engineering Research Center for Translation of Medical 3D Printing Application & National Virtual & Reality Experimental Education Center for Medical Morphology (Southern Medical University) & National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Jinhui Zhu
- Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics & Guangdong Engineering Research Center for Translation of Medical 3D Printing Application & National Virtual & Reality Experimental Education Center for Medical Morphology (Southern Medical University) & National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Yulian Shi
- Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics & Guangdong Engineering Research Center for Translation of Medical 3D Printing Application & National Virtual & Reality Experimental Education Center for Medical Morphology (Southern Medical University) & National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Jiaxuan Liu
- Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics & Guangdong Engineering Research Center for Translation of Medical 3D Printing Application & National Virtual & Reality Experimental Education Center for Medical Morphology (Southern Medical University) & National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Xiangtian Li
- Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics & Guangdong Engineering Research Center for Translation of Medical 3D Printing Application & National Virtual & Reality Experimental Education Center for Medical Morphology (Southern Medical University) & National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Zhitao Zhou
- Central Laboratory, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Yunbing Chang
- Department of Spine Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Jun Ouyang
- Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics & Guangdong Engineering Research Center for Translation of Medical 3D Printing Application & National Virtual & Reality Experimental Education Center for Medical Morphology (Southern Medical University) & National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Jingxing Dai
- Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics & Guangdong Engineering Research Center for Translation of Medical 3D Printing Application & National Virtual & Reality Experimental Education Center for Medical Morphology (Southern Medical University) & National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, China
| |
Collapse
|
3
|
Guo W, Alarcon E, Sanchez JE, Xiao C, Li L. Modeling Viral Capsid Assembly: A Review of Computational Strategies and Applications. Cells 2024; 13:2088. [PMID: 39768179 PMCID: PMC11674207 DOI: 10.3390/cells13242088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2024] [Revised: 12/14/2024] [Accepted: 12/16/2024] [Indexed: 01/11/2025] Open
Abstract
Viral capsid assembly is a complex and critical process, essential for understanding viral behavior, evolution, and the development of antiviral treatments, vaccines, and nanotechnology. Significant progress in studying viral capsid assembly has been achieved through various computational approaches, including molecular dynamics (MD) simulations, stochastic dynamics simulations, coarse-grained (CG) models, electrostatic analyses, lattice models, hybrid techniques, machine learning methods, and kinetic models. Each of these techniques offers unique advantages, and by integrating these diverse computational strategies, researchers can more accurately model the dynamic behaviors and structural features of viral capsids, deepening our understanding of the assembly process. This review provides a comprehensive overview of studies on viral capsid assembly, emphasizing their critical role in advancing our knowledge. It examines the contributions, strengths, and limitations of different computational methods, presents key computational works in the field, and analyzes milestone studies that have shaped current research.
Collapse
Affiliation(s)
- Wenhan Guo
- Department of Physics, University of Texas at El Paso, El Paso, TX 79968, USA;
| | - Esther Alarcon
- Department of Chemistry and Biochemistry, University of Texas at El Paso, El Paso, TX 79968, USA;
| | - Jason E. Sanchez
- Department of Computational Science, University of Texas at El Paso, El Paso, TX 79968, USA;
| | - Chuan Xiao
- Department of Chemistry and Biochemistry, University of Texas at El Paso, El Paso, TX 79968, USA;
- Department of Computational Science, University of Texas at El Paso, El Paso, TX 79968, USA;
| | - Lin Li
- Department of Physics, University of Texas at El Paso, El Paso, TX 79968, USA;
- Department of Computational Science, University of Texas at El Paso, El Paso, TX 79968, USA;
| |
Collapse
|
4
|
Baig F, Bakdaleyeh M, Bazzi HM, Cao L, Tripathy SK. Dissecting the pH Sensitivity of Kinesin-Driven Transport. J Phys Chem B 2024; 128:11855-11864. [PMID: 39575923 PMCID: PMC11627161 DOI: 10.1021/acs.jpcb.4c03850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 10/11/2024] [Accepted: 10/23/2024] [Indexed: 12/06/2024]
Abstract
Kinesin-1 is a crucial motor protein that drives the microtubule-based movement of organelles, vital for cellular function and health. Mostly studied at pH 6.9, it moves at approximately 800 nm/s, covers about 1 μm before detaching, and hydrolyzes one ATP per 8 nm step. Given that cellular pH is dynamic and alterations in pH have significant implications for disease, understanding how kinesin-1 functions across different pH levels is crucial. To explore this, we executed single-molecule motility assays paired with precise optical trapping techniques over a pH range of 5.5-9.8. Our results show a consistent positive relationship between increasing pH and the enhanced detachment (off rate) and speed of kinesin-1. Measurements of the nucleotide-dependent off rate show that kinesin-1 exhibits the highest rate of ATPase activity at alkaline pH, while it demonstrates the optimal number of ATP turnover and cargo translocation efficiency at the acidic pH. Physiological pH of 6.9 optimally balances the biophysical activity of kinesin-1, potentially allowing it to function effectively across a range of pH levels. These insights emphasize the crucial role of pH homeostasis in cellular function, highlighting its importance for the precise regulation of motor proteins and efficient intracellular transport.
Collapse
Affiliation(s)
- Fawaz Baig
- Department of Natural Sciences, University of Michigan-Dearborn, 4901 Evergreen Road, Dearborn, Michigan 48128, United States
| | - Michael Bakdaleyeh
- Department of Natural Sciences, University of Michigan-Dearborn, 4901 Evergreen Road, Dearborn, Michigan 48128, United States
| | - Hassan M. Bazzi
- Department of Natural Sciences, University of Michigan-Dearborn, 4901 Evergreen Road, Dearborn, Michigan 48128, United States
| | - Lanqin Cao
- Department of Natural Sciences, University of Michigan-Dearborn, 4901 Evergreen Road, Dearborn, Michigan 48128, United States
| | - Suvranta K. Tripathy
- Department of Natural Sciences, University of Michigan-Dearborn, 4901 Evergreen Road, Dearborn, Michigan 48128, United States
| |
Collapse
|
5
|
Romero JM. Structural analysis of the TPI-Manchester, a thermolabile variant of human triosephosphate isomerase. Arch Biochem Biophys 2024; 761:110156. [PMID: 39299479 DOI: 10.1016/j.abb.2024.110156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Revised: 08/27/2024] [Accepted: 09/14/2024] [Indexed: 09/22/2024]
Abstract
Human triosephosphate isomerase G122R, also known as TPI-Manchester, is a thermolabile variant detected in a screening of more than 3400 individuals from a population in Ann Arbor, Michigan. Here, the crystallographic structure of G122R was solved to determine the molecular basis of its thermal stability. Structural analysis revealed an increase in the flexibility of residues at the dimer interface, even though R122 is about 20 Å away, suggesting that long-range electrostatic interactions may play a key role in the mutation effect.
Collapse
Affiliation(s)
- Jorge Miguel Romero
- Centro de Investigaciones en Química Biológica de Córdoba (CIQUIBIC, Universidad Nacional de Córdoba - Consejo Nacional de Investigaciones Científicas y Técnicas (UNC-CONICET)), Departamento de Química Biológica Ranwel Caputto, Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, X5000HUA, Córdoba, Argentina.
| |
Collapse
|
6
|
Guo W, Du D, Zhang H, Sanchez JE, Sun S, Xu W, Peng Y, Li L. Bound ion effects: Using machine learning method to study the kinesin Ncd's binding with microtubule. Biophys J 2024; 123:2740-2748. [PMID: 38160255 PMCID: PMC11393710 DOI: 10.1016/j.bpj.2023.12.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/26/2023] [Accepted: 12/27/2023] [Indexed: 01/03/2024] Open
Abstract
Drosophila Ncd proteins are motor proteins that play important roles in spindle organization. Ncd and the tubulin dimer are highly charged. Thus, it is crucial to investigate Ncd-tubulin dimer interactions in the presence of ions, especially ions that are bound or restricted at the Ncd-tubulin dimer binding interfaces. To consider the ion effects, widely used implicit solvent models treat ions implicitly in the continuous solvent environment without focusing on the individual ions' effects. But highly charged biomolecules such as the Ncd and tubulin dimer may capture some ions at highly charged regions as bound ions. Such bound ions are restricted to their binding sites; thus, they can be treated as part of the biomolecules. By applying multiscale computational methods, including the machine-learning-based Hybridizing Ions Treatment-2 program, molecular dynamics simulations, DelPhi, and DelPhiForce, we studied the interaction between the Ncd motor domain and the tubulin dimer using a hybrid solvent model, which considers the bound ions explicitly and the other ions implicitly in the solvent environment. To identify the importance of treating bound ions explicitly, we also performed calculations using the implicit solvent model without considering the individual bound ions. We found that the calculations of the electrostatic features differ significantly between those of the hybrid solvent model and the pure implicit solvent model. The analyses show that treating bound ions at highly charged regions explicitly is crucial for electrostatic calculations. This work proposes a machine-learning-based approach to handle the bound ions using the hybrid solvent model. Such an approach is not only capable of handling kinesin-tubulin complexes but is also appropriate for other highly charged biomolecules, such as DNA/RNA, viral capsid proteins, etc.
Collapse
Affiliation(s)
- Wenhan Guo
- College of Physical Science and Technology, Central China Normal University, Hubei, China; Computational Science Program, University of Texas at El Paso, El Paso, Texas
| | - Dan Du
- Computational Science Program, University of Texas at El Paso, El Paso, Texas
| | - Houfang Zhang
- College of Physical Science and Technology, Central China Normal University, Hubei, China
| | - Jason E Sanchez
- Computational Science Program, University of Texas at El Paso, El Paso, Texas
| | - Shengjie Sun
- Computational Science Program, University of Texas at El Paso, El Paso, Texas; School of Life Sciences, Central South University, Hunan, China
| | - Wang Xu
- College of Physical Science and Technology, Central China Normal University, Hubei, China
| | - Yunhui Peng
- College of Physical Science and Technology, Central China Normal University, Hubei, China.
| | - Lin Li
- Computational Science Program, University of Texas at El Paso, El Paso, Texas; Department of Physics, University of Texas at El Paso, El Paso, Texas.
| |
Collapse
|
7
|
Chen J, Chen L, Quan H, Lee S, Khan KF, Xie Y, Li Q, Valero M, Dai Z, Xie Y. A Comparative Analysis of SARS-CoV-2 Variants of Concern (VOC) Spike Proteins Interacting with hACE2 Enzyme. Int J Mol Sci 2024; 25:8032. [PMID: 39125601 PMCID: PMC11311974 DOI: 10.3390/ijms25158032] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 07/15/2024] [Accepted: 07/16/2024] [Indexed: 08/12/2024] Open
Abstract
In late 2019, the emergence of a novel coronavirus led to its identification as SARS-CoV-2, precipitating the onset of the COVID-19 pandemic. Many experimental and computational studies were performed on SARS-CoV-2 to understand its behavior and patterns. In this research, Molecular Dynamic (MD) simulation is utilized to compare the behaviors of SARS-CoV-2 and its Variants of Concern (VOC)-Alpha, Beta, Gamma, Delta, and Omicron-with the hACE2 protein. Protein structures from the Protein Data Bank (PDB) were aligned and trimmed for consistency using Chimera, focusing on the receptor-binding domain (RBD) responsible for ACE2 interaction. MD simulations were performed using Visual Molecular Dynamics (VMD) and Nanoscale Molecular Dynamics (NAMD2), and salt bridges and hydrogen bond data were extracted from the results of these simulations. The data extracted from the last 5 ns of the 10 ns simulations were visualized, providing insights into the comparative stability of each variant's interaction with ACE2. Moreover, electrostatics and hydrophobic protein surfaces were calculated, visualized, and analyzed. Our comprehensive computational results are helpful for drug discovery and future vaccine designs as they provide information regarding the vital amino acids in protein-protein interactions (PPIs). Our analysis reveals that the Original and Omicron variants are the two most structurally similar proteins. The Gamma variant forms the strongest interaction with hACE2 through hydrogen bonds, while Alpha and Delta form the most stable salt bridges; the Omicron is dominated by positive potential in the binding site, which makes it easy to attract the hACE2 receptor; meanwhile, the Original, Beta, Delta, and Omicron variants show varying levels of interaction stability through both hydrogen bonds and salt bridges, indicating that targeted therapeutic agents can disrupt these critical interactions to prevent SARS-CoV-2 infection.
Collapse
Affiliation(s)
- Jiawei Chen
- College of Computing, Data Science and Society, University of California, Berkeley, CA 94720, USA;
| | - Lingtao Chen
- College of Computing and Software Engineering, Kennesaw State University, Marietta, GA 30060, USA; (L.C.); (Y.X.); (Q.L.); (M.V.)
| | - Heng Quan
- Department of Civil and Urban Engineering, New York University, Brooklyn, NY 10012, USA;
| | - Soongoo Lee
- Department of Molecular and Cellular Biology, Kennesaw State University, Kennesaw, GA 30144, USA;
| | - Kaniz Fatama Khan
- Department of Chemistry and Biochemistry, Kennesaw State University, Kennesaw, GA 30144, USA;
| | - Ying Xie
- College of Computing and Software Engineering, Kennesaw State University, Marietta, GA 30060, USA; (L.C.); (Y.X.); (Q.L.); (M.V.)
| | - Qiaomu Li
- College of Computing and Software Engineering, Kennesaw State University, Marietta, GA 30060, USA; (L.C.); (Y.X.); (Q.L.); (M.V.)
| | - Maria Valero
- College of Computing and Software Engineering, Kennesaw State University, Marietta, GA 30060, USA; (L.C.); (Y.X.); (Q.L.); (M.V.)
| | - Zhiyu Dai
- Division of Pulmonary and Critical Care Medicine, John T. Milliken Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA;
| | - Yixin Xie
- College of Computing and Software Engineering, Kennesaw State University, Marietta, GA 30060, USA; (L.C.); (Y.X.); (Q.L.); (M.V.)
| |
Collapse
|
8
|
Ricci A, Carradori S, Cataldi A, Zara S. Eg5 and Diseases: From the Well-Known Role in Cancer to the Less-Known Activity in Noncancerous Pathological Conditions. Biochem Res Int 2024; 2024:3649912. [PMID: 38939361 PMCID: PMC11211015 DOI: 10.1155/2024/3649912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 05/06/2024] [Accepted: 06/07/2024] [Indexed: 06/29/2024] Open
Abstract
Eg5 is a protein encoded by KIF11 gene and is primarily involved in correct mitotic cell division. It is also involved in nonmitotic processes such as polypeptide synthesis, protein transport, and angiogenesis. The scientific literature sheds light on the ubiquitous functions of KIF11 and its involvement in the onset and progression of different pathologies. This review focuses attention on two main points: (1) the correlation between Eg5 and cancer and (2) the involvement of Eg5 in noncancerous conditions. Regarding the first point, several tumors revealed an overexpression of this kinesin, thus pushing to look for new Eg5 inhibitors for clinical practice. In addition, the evaluation of Eg5 expression represents a crucial step, as its overexpression could predict a poor prognosis for cancer patients. Referring to the second point, in specific pathological conditions, the reduced activity of Eg5 can be one of the causes of pathological onset. This is the case of Alzheimer's disease (AD), in which Aβ and Tau work as Eg5 inhibitors, or in acquired immune deficiency syndrome (AIDS), in which Tat-mediated Eg5 determines the loss of CD4+ T-lymphocytes. Reduced Eg5 activity, due to mutations of KIF11 gene, is also responsible for pathological conditions such as microcephaly with or without chorioretinopathy, lymphedema, or intellectual disability (MCLRI) and familial exudative vitreous retinopathy (FEVR). In conclusion, this review highlights the double impact that overexpression or loss of function of Eg5 could have in the onset and progression of different pathological situations. This emphasizes, on one hand, a possible role of Eg5 as a potential biomarker and new target in cancer and, on the other hand, the promotion of Eg5 expression/activity as a new therapeutic strategy in different noncancerous diseases.
Collapse
Affiliation(s)
- Alessia Ricci
- Department of Pharmacy, University “G. d'Annunzio” Chieti-Pescara, Chieti, 66100, Italy
| | - Simone Carradori
- Department of Pharmacy, University “G. d'Annunzio” Chieti-Pescara, Chieti, 66100, Italy
| | - Amelia Cataldi
- Department of Pharmacy, University “G. d'Annunzio” Chieti-Pescara, Chieti, 66100, Italy
| | - Susi Zara
- Department of Pharmacy, University “G. d'Annunzio” Chieti-Pescara, Chieti, 66100, Italy
| |
Collapse
|
9
|
Guo W, Gao Y, Du D, Sanchez JE, Visootsat A, Li Y, Qiu W, Li L. How does the ion concentration affect the functions of kinesin BimC. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.31.596855. [PMID: 38853942 PMCID: PMC11160742 DOI: 10.1101/2024.05.31.596855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
BimC family proteins are bipolar motor proteins belonging to the kinesin superfamily which promote mitosis by crosslinking and sliding apart antiparallel microtubules. Understanding the binding mechanism between the kinesin and the microtubule is crucial for researchers to make advances in the treatment of cancer and other malignancies. Experimental research has shown that the ion concentration affects the function of BimC significantly. But the insights of the ion-dependent function of BimC remain unclear. By combining molecular dynamics (MD) simulations with a series of computational approaches, we studied the electrostatic interactions at the binding interfaces of BimC and the microtubule under different KCl concentrations. We found the electrostatic interaction between BimC and microtubule is stronger at 0 mM KCl compared to 150 mM KCl, which is consistent with experimental conclusions. Furthermore, important salt bridges and residues at the binding interfaces of the complex were identified, which illustrates the details of the BimC-microtubule interactions. Molecular dynamics analyses of salt bridges identified that the important residues on the binding interface of BimC are positively charged, while those residues on the binding interface of the tubulin heterodimer are negatively charged. The finding in this work reveals some important mechanisms of kinesin-microtubule binding, which helps the future drug design for cancer therapy.
Collapse
|
10
|
Li X, Liu K, Fang H, Liu Z, Tang Y, Dai P. Electrodynamic interaction between tumor treating fields and microtubule electrophysiological activities. APL Bioeng 2024; 8:026118. [PMID: 38841689 PMCID: PMC11151432 DOI: 10.1063/5.0197900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 05/01/2024] [Indexed: 06/07/2024] Open
Abstract
Tumor treating fields (TTFields) are a type of sinusoidal alternating current electric field that has proven effective in inhibiting the reproduction of dividing tumor cells. Despite their recognized impact, the precise biophysical mechanisms underlying the unique effects of TTFields remain unknown. Many of the previous studies predominantly attribute the inhibitory effects of TTFields to mitotic disruption, with intracellular microtubules identified as crucial targets. However, this conceptual framework lacks substantiation at the mesoscopic level. This study addresses the existing gap by constructing force models for tubulin and other key subcellular structures involved in microtubule electrophysiological activities under TTFields exposure. The primary objective is to explore whether the electric force or torque exerted by TTFields significantly influences the normal structure and activities of microtubules. Initially, we examine the potential effect on the dynamic stability of microtubule structures by calculating the electric field torque on the tubulin dimer orientation. Furthermore, given the importance of electrostatics in microtubule-associated activities, such as chromosome segregation and substance transport of kinesin during mitosis, we investigate the interaction between TTFields and these electrostatic processes. Our data show that the electrodynamic effects of TTFields are most likely too weak to disrupt normal microtubule electrophysiological activities significantly. Consequently, we posit that the observed cytoskeleton destruction in mitosis is more likely attributable to non-mechanical mechanisms.
Collapse
Affiliation(s)
- Xing Li
- College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nan Jing 210016, Jiang Su, China
| | - Kaida Liu
- College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nan Jing 210016, Jiang Su, China
| | - Haohan Fang
- College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nan Jing 210016, Jiang Su, China
| | - Zirong Liu
- College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nan Jing 210016, Jiang Su, China
| | - Yuchen Tang
- College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nan Jing 210016, Jiang Su, China
| | - Ping Dai
- Department of Radiotherapy, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China
| |
Collapse
|
11
|
Wang H, Cui H, Yang X, Peng L. TUBA1C: a new potential target of LncRNA EGFR-AS1 promotes gastric cancer progression. BMC Cancer 2023; 23:258. [PMID: 36941595 PMCID: PMC10026485 DOI: 10.1186/s12885-023-10707-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Accepted: 03/06/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND The lack of obvious symptoms of early gastric cancer (GC) as well as the absence of sensitive and specific biomarkers results in poor clinical outcomes. Tubulin is currently emerging as important regulators of the microtubule cytoskeleton and thus have a strong potential to be implicated in a number of disorders, however, its mechanism of action in gastric cancer is still unclear. Tubulin alpha-1 C (TUBA1C) is a subtype of α-tubulin, high TUBA1C expression has been shown to be closely related to a poor prognosis in various cancers, this study, for the first time, revealed the mechanism of TUBA1C promotes malignant progression of gastric cancer in vitro and in vivo. METHODS The expression of lncRNA EGFR-AS1 was detected in human GC cell lines by qRT-PCR. Mass spectrometry experiments following RNA pulldown assays found that EGFR-AS1 directly binds to TUBA1C, the CCK8, EdU, transwell, wound-healing, cell cycle assays and animal experiments were conducted to investigate the function of TUBA1C in GC. Combined with bioinformatics analyses, reveal interaction between Ki-67, E2F1, PCNA and TUBA1C by western blot. Rescue experiments furtherly demonstrated the relationship of EGFR-AS1and TUBA1C. RESULTS TUBA1C was proved to be a direct target of EGFR-AS1, and TUBA1C promotes gastric cancer proliferation, migration and invasion by accelerating the progression of the cell cycle from the G1 phase to the S phase and activating the expression of oncogenes: Ki-67, E2F1 and PCNA. CONCLUSION TUBA1C is a new potential target of LncRNA EGFR-AS1 promotes gastric cancer progression and could be a novel biomarker and therapeutic target for GC.
Collapse
Affiliation(s)
- Haodong Wang
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, 250000, Jinan, Jinan, China
| | - Huaiping Cui
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, 250000, Jinan, Jinan, China
| | - Xinjun Yang
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, 250000, Jinan, Jinan, China
| | - Lipan Peng
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, 250000, Jinan, Jinan, China.
| |
Collapse
|
12
|
Guo W, Ale TA, Sun S, Sanchez JE, Li L. A Comprehensive Study on the Electrostatic Properties of Tubulin-Tubulin Complexes in Microtubules. Cells 2023; 12:238. [PMID: 36672172 PMCID: PMC9857020 DOI: 10.3390/cells12020238] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/31/2022] [Accepted: 01/02/2023] [Indexed: 01/08/2023] Open
Abstract
Microtubules are key players in several stages of the cell cycle and are also involved in the transportation of cellular organelles. Microtubules are polymerized by α/β tubulin dimers with a highly dynamic feature, especially at the plus ends of the microtubules. Therefore, understanding the interactions among tubulins is crucial for characterizing microtubule dynamics. Studying microtubule dynamics can help researchers make advances in the treatment of neurodegenerative diseases and cancer. In this study, we utilize a series of computational approaches to study the electrostatic interactions at the binding interfaces of tubulin monomers. Our study revealed that among all the four types of tubulin-tubulin binding modes, the electrostatic attractive interactions in the α/β tubulin binding are the strongest while the interactions of α/α tubulin binding in the longitudinal direction are the weakest. Our calculations explained that due to the electrostatic interactions, the tubulins always preferred to form α/β tubulin dimers. The interactions between two protofilaments are the weakest. Thus, the protofilaments are easily separated from each other. Furthermore, the important residues involved in the salt bridges at the binding interfaces of the tubulins are identified, which illustrates the details of the interactions in the microtubule. This study elucidates some mechanistic details of microtubule dynamics and also identifies important residues at the binding interfaces as potential drug targets for the inhibition of cancer cells.
Collapse
Affiliation(s)
- Wenhan Guo
- Computational Science Program, University of Texas at El Paso, El Paso, TX 79902, USA
| | - Tolulope Ayodeji Ale
- Computational Science Program, University of Texas at El Paso, El Paso, TX 79902, USA
| | - Shengjie Sun
- Computational Science Program, University of Texas at El Paso, El Paso, TX 79902, USA
| | - Jason E. Sanchez
- Computational Science Program, University of Texas at El Paso, El Paso, TX 79902, USA
| | - Lin Li
- Computational Science Program, University of Texas at El Paso, El Paso, TX 79902, USA
- Department of Physics, University of Texas at El Paso, El Paso, TX 79902, USA
| |
Collapse
|