Li Yamei, Kitadai Norio, Nakamura Ryuhei
Earth-Life Science Institute, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan.
Biofunctional Catalyst Research Team, RIKEN Center for Sustainable Resource Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan.
Life (Basel). 2018 Oct 10;8(4):46. doi: 10.3390/life8040046.
Prebiotic organic synthesis catalyzed by Earth-abundant metal sulfides is a key process for understanding the evolution of biochemistry from inorganic molecules, yet the catalytic functions of sulfides have remained poorly explored in the context of the origin of life. Past studies on prebiotic chemistry have mostly focused on a few types of metal sulfide catalysts, such as FeS or NiS, which form limited types of products with inferior activity and selectivity. To explore the potential of metal sulfides on catalyzing prebiotic chemical reactions, here, the chemical diversity (variations in chemical composition and phase structure) of 304 natural metal sulfide minerals in a mineralogy database was surveyed. Approaches to rationally predict the catalytic functions of metal sulfides are discussed based on advanced theories and analytical tools of electrocatalysis such as proton-coupled electron transfer, structural comparisons between enzymes and minerals, and in situ spectroscopy. To this end, we introduce a model of geoelectrochemistry driven prebiotic synthesis for chemical evolution, as it helps us to predict kinetics and selectivity of targeted prebiotic chemistry under "chemically messy conditions". We expect that combining the data-mining of mineral databases with experimental methods, theories, and machine-learning approaches developed in the field of electrocatalysis will facilitate the prediction and verification of catalytic performance under a wide range of pH and Eh conditions, and will aid in the rational screening of mineral catalysts involved in the origin of life.
由地球上储量丰富的金属硫化物催化的益生元有机合成是理解生物化学从无机分子进化而来的关键过程,然而在生命起源的背景下,硫化物的催化功能仍未得到充分探索。过去关于益生元化学的研究大多集中在少数几种金属硫化物催化剂上,如FeS或NiS,它们形成的产物类型有限,活性和选择性较差。为了探索金属硫化物催化益生元化学反应的潜力,我们在此调查了矿物学数据库中304种天然金属硫化物矿物的化学多样性(化学成分和相结构的变化)。基于质子耦合电子转移、酶与矿物的结构比较以及原位光谱等先进的电催化理论和分析工具,讨论了合理预测金属硫化物催化功能的方法。为此,我们引入了一个地球电化学驱动的益生元合成化学进化模型,因为它有助于我们预测在“化学混乱条件”下目标益生元化学的动力学和选择性。我们期望将矿物数据库的数据挖掘与电催化领域开发的实验方法、理论和机器学习方法相结合,将有助于在广泛的pH和Eh条件下预测和验证催化性能,并有助于合理筛选参与生命起源的矿物催化剂。