2017/10/31 by Wonseok Hwang, Changbong Hyeon · 1 citation
Biochemistry, Genetics and Molecular Biology · Engineering · Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #Biochemical engineering #Biological system #Biology #Computer science #Data mining #Efficient energy use #Energy (signal processing) #Engineering #Kinesin #Materials science #Molecular motor #Nanopore and Nanochannel Transport Studies #Nanotechnology #Physics #Process (computing) #Relation (database) #Variance (accounting) #cond-mat.soft #cond-mat.stat-mech #physics.bio-ph #q-bio.BM #stochastic dynamics and bifurcation
paper · pdf · doi:10.1021/acs.jpclett.7b03197
published as J. Phys. Chem. Lett., 2018, 9 (3), pp 513-520 · 6 figures, 15 supplementary figures
openalex publication_date 2018/01/13 · arxiv created 2019/06/06 · arxiv updated 2019/06/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
An efficient molecular motor would deliver cargo to the target site at a high speed and in a punctual manner while consuming a minimal amount of energy. According to a recently formulated thermodynamic principle, referred to as the thermodynamic uncertainty relation, the travel distance of a motor and its variance are, however, constrained by the free energy being consumed. Here we use the principle underlying the uncertainty relation to quantify the transport efficiency of molecular motors for varying ATP concentration ([ATP]) and applied load (f). Our analyses of experimental data find that transport efficiencies of the motors studied here are semioptimized under the cellular condition. The efficiency is significantly deteriorated for a kinesin-1 mutant that has a longer neck-linker, which underscores the importance of molecular structure. It is remarkable to recognize that, among many possible directions for optimization, biological motors have evolved to optimize the transport efficiency in particular.