Wu Di, Yue Dajun, You Fengqi, Broadbelt Linda J
Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, 60208, USA.
J Mol Model. 2014 Jun;20(6):2310. doi: 10.1007/s00894-014-2310-9. Epub 2014 Jun 10.
Recent advances in computational approaches for creating pathways for novel biochemical reactions has motivated the development of approaches for identifying enzyme-substrate pairs that are attractive candidates for effecting catalysis. We present an improved structural-based strategy to probe and study enzyme-substrate binding based on binding geometry, energy, and molecule characteristics, which allows for in silico screening of structural features that imbue higher catalytic potential with specific substrates. The strategy is demonstrated using 2-keto acid decarboxylation with various pairs of 2-keto acids and enzymes. We show that this approach fitted experimental values for a wide range of 2-keto acid decarboxylases for different 2-keto acid substrates. In addition, we show that the structure-based methods can be used to select specific enzymes that may be promising candidates to catalyze decarboxylation of certain 2-keto acids. The key features and principles of the candidate enzymes evaluated by the strategy can be used to design novel biosynthesis pathways, to guide enzymatic mutation or to guide biomimetic catalyst design.
用于创建新型生化反应途径的计算方法的最新进展，推动了识别酶-底物对的方法的发展，这些酶-底物对是实现催化作用的有吸引力的候选对象。我们提出了一种改进的基于结构的策略，用于基于结合几何形状、能量和分子特征来探测和研究酶-底物结合，这允许在计算机上筛选赋予特定底物更高催化潜力的结构特征。使用各种2-酮酸和酶对进行2-酮酸脱羧反应来证明该策略。我们表明，这种方法适用于不同2-酮酸底物的多种2-酮酸脱羧酶的实验值。此外，我们表明基于结构的方法可用于选择可能是催化某些2-酮酸脱羧的有前景候选者的特定酶。通过该策略评估的候选酶的关键特征和原理可用于设计新型生物合成途径、指导酶促突变或指导仿生催化剂设计。
