ترجمه فارسی مقاله قوانین مکانیکی جهانی برای طراحی نوین آنزیم ها

• کتاب صدها نکته فارسی (خودمونی) – نسخه PDF — زبان ساده و کاربردی
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• کتاب صدها پرسش و پاسخ تشریحی – نسخه PDF
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• کتاب پرسش و پاسخ چهارگزینه‌ای – نسخه یادگیری سریع
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• کتاب پرسش و پاسخ چهارگزینه‌ای – نسخه خودآزمایی
  — پاسخ‌ها در انتهای بخش‌ها برای سنجش واقعی یادگیری
  مشاهده نمونه نسخه آزمونی

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چکیده

Enzymes are nano-scale machines that have evolved to drive chemical reactions out of equilibrium in the right place at the right time. Thermodynamically favourable reactions such as ATP hydrolysis are used by the cell to convert chemical energy into useful structure, function, and mechanical work. This includes the `fuelled' catalysis of chemical reactions that would otherwise be thermodynamically unfavourable. Given the complexity and specificity of enzymatic function, bottom-up design of enzymes presents a daunting task that is far more challenging than making passive molecules with specific binding affinities or building nano-scale mechanically active devices. Here, we present a thermodynamically-consistent model for the operation of such a fuelled enzyme, which uses the energy from a favourable reaction to undergo non-equilibrium conformational changes that in turn catalyze a chemical reaction on an attached substrate molecule. We show that enzymatic function can emerge through a bifurcation upon appropriate implementation of momentum conservation on the effective reaction coordinates of the low dimensional description of the enzyme, and thanks to a generically present dissipative coupling. By considering the different aspects of the dynamics, such as the interplay of the non-equilibrium drive and the geometry of the enzyme-substrate complex, we propose three golden rules that should be universally applicable for de novo design of enzymes, as they are based on generic ingredients and physical constraints. These rules lead to optimal combinations of parameters, which can vastly accelerate reactions, while at the same time decreasing the energy dissipation of the combined reaction process, or, in other words, to an efficient enzyme. Our results can complement the recently developed strategies for de novo enzyme design based on machine learning approaches.

چکیده به فارسی (ترجمه ماشینی)