ArticleBiophysical journal2008
Influence of macromolecular crowding on protein-protein association rates--a Brownian dynamics study.
Article in Biophysical journal, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed, 98 citations in OpenAlex.
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- Similarity Metrics for Subcellular Analysis of FRET Microscopy Videos.The journal of physical chemistry. B · 2024Article
- Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments.Chemical reviews · 2024Review
- Molecular Crowding: The History and Development of a Scientific Paradigm.Chemical reviews · 2024Review
- Effects of Homogeneous and Heterogeneous Crowding on Translational Diffusion of Rigid Bovine Serum Albumin and Disordered Alfa-Casein.International journal of molecular sciences · 2023Article
- Brownian Motion in Optical Tweezers, a Comparison between MD Simulations and Experimental Data in the Ballistic Regime.Polymers · 2023Article
- Dissecting the general mechanisms of protein cage self-assembly by coarse-grained simulations.Protein science : a publication of the Protein Society · 2023Article
- Coarse-Grained Simulations of Release of Drugs Housed in Flexible Nanogels: New Insights into Kinetic Parameters.Polymers · 2022Article
- Challenges and frontiers of computational modelling of biomolecular recognition.QRB discovery · 2022Article
- Classification of protein-protein association rates based on biophysical informatics.BMC bioinformatics · 2021Article
- Article
- Understanding the Impacts of Conformational Dynamics on the Regulation of Protein-Protein Association by a Multiscale Simulation Method.Journal of chemical theory and computation · 2020Article
- Using Coarse-Grained Simulations to Characterize the Mechanisms of Protein-Protein Association.Biomolecules · 2020Article
- Desiccation-induced cell damage in bacteria and the relevance for inoculant production.Applied microbiology and biotechnology · 2020Review
- Multiscale simulation unravel the kinetic mechanisms of inflammasome assembly.Biochimica et biophysica acta. Molecular cell research · 2020Article
- Understanding biochemical processes in the presence of sub-diffusive behavior of biomolecules in solution and living cells.Biophysical reviews · 2019Review
- A Multiscale Model for the Self-Assembly of Coat Proteins in Bacteriophage MS2.Journal of chemical information and modeling · 2019Article
- Modeling Crowded Environment in Molecular Simulations.Frontiers in molecular biosciences · 2019Review
- Integrating Structural Information to Study the Dynamics of Protein-Protein Interactions in Cells.Structure (London, England : 1993) · 2018Article
- Characterizing the Surface Coverage of Protein-Gold Nanoparticle Bioconjugates.Bioconjugate chemistry · 2018Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The high total concentration of macromolecules, often referred to as macromolecular crowding, is one of the characteristic features of living cells. Macromolecular crowding influences interactions between many types of macromolecules, with consequent effects on, among others, the rates of reactions occurring in the cell. Simulations to study the influence of crowding on macromolecular association rate were performed using a modified Brownian dynamics protocol. The calculated values of the time-dependent self-diffusion coefficients in different crowding conditions are in a very good agreement with those obtained by other authors. Simulations of the complex formation between the monoclonal antibody HyHEL-5 and its antigen hen egg lysozyme, both represented at atomic level detail, show that the calculated association rates strongly depend on the volume excluded by crowding. The rate obtained for the highest concentration of crowding particles is greater than twofold higher than the rate for proteins without crowding.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.