Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
Mol Syst Biol. 2022 Feb;18(2):e10782. doi: 10.15252/msb.202110782.
Computational biologists have labored for decades to produce kinetic models to mechanistically explain complex metabolic phenomena. The estimation of numerical values for the large number of kinetic parameters required for constructing large-scale models has been a major challenge. This collection of kinetic constants has recently been termed the kinetome (Nilsson et al, 2017). In this Commentary, we discuss the recent advances in the field that suggest that the kinetome may be more conserved than expected. A conserved kinetome will accelerate the development of future kinetic models of integrated cellular functions and expand their scope and usability in many fields of biology and biomedicine.
计算生物学家们几十年来一直致力于建立动力学模型,以从机理上解释复杂的代谢现象。构建大规模模型所需的大量动力学参数的数值估计一直是一个主要挑战。这些动力学常数最近被称为动力学组(Nilsson 等人,2017 年)。在本文评论中,我们讨论了该领域的最新进展,这些进展表明动力学组可能比预期的更保守。一个保守的动力学组将加速未来整合细胞功能的动力学模型的发展,并扩大它们在生物学和生物医学许多领域的范围和可用性。