能源景观
蛋白质折叠
人口
功能(生物学)
变构调节
折叠(DSP实现)
转化式学习
能量(信号处理)
内在无序蛋白质
范式转换
计算机科学
数据科学
结构生物学
化学
物理
选择(遗传算法)
统计物理学
认知科学
构象集合
计算生物学
纳米技术
蛋白质结构
势能
原籍国
蛋白质功能
分子机器
分子动力学
国家(计算机科学)
认识论
作者
Ruth Nussinov,Clil Regev,Hyunbum Jang
标识
DOI:10.1017/s0033583526100134
摘要
Abstract In an editorial for a Special Issue, Nussinov and Wolynes explored the energy landscapes of biomolecular function, questioning whether they constituted a second molecular biology revolution. With more than a decade having passed and science having progressed significantly, we revisit this question. Statistical energy landscapes not only visualize folding funnels but also quantify the likelihoods of different states, embodying the foundational physical-chemical principles of protein actions. Building upon the theory of energy landscapes, the conformational selection and population shift paradigm posited that since all functional conformations already pre-exist in a dynamic equilibrium, a ligand ‘selects’ and stabilizes a state from this pre-existing pool, resulting in re-equilibration, or shift, of the population. The principle that it established — that function harnesses transitions between pre-existing conformations — revolutionized the understanding of allostery and, broadly, regulation. This paradigm challenged and superseded the decades-old, albeit persisting, belief of only one (or two; ‘open’ and ‘closed’) protein conformations. It also indicates that for engineered proteins to exert effective function, we must account for the timescales of flipping between energy landscape states, for example, by tuning the barrier heights. Returning to the question of whether landscapes constituted a second biomolecular biology revolution, we consider their bedrock contributions, which are far beyond the original protein folding funnels. They established the principle of multiple dynamic conformational states ‘jumping’ over barriers during population shifts. By leveraging core concepts like conformational ensembles, modern molecular biology has achieved breakthroughs such as next-generation allosteric drugs, indeed leading to a transformative era in molecular science.
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