Bindungsaffinitäten von Wirt‐Gast‐, Protein‐Ligand‐ und Protein‐Übergangszustands‐Komplexen

Abstract

Die Affinitäten von Wirten – ausgehend von kleinen synthetischen Cavitanten bis hin zu großen Proteinen – für organische Moleküle sind gut dokumentiert. Die mittleren Assoziationskonstanten für die Bindung organischer Moleküle durch Cyclodextrine, synthetische Wirte und Albumine in Wasser sowie von katalytischen Antikörpern oder Enzymen für Substrate betragen im Allgemeinen 103.5±2.5 M−1. Die Bindungsaffinitäten steigen bei der Komplexierung von Übergangszuständen und biologischen Antigenen durch Antikörper oder von Enzymen durch Inhibitoren auf 108±2 M−1 und auf 1016±4 M−1 für Enzym‐Übergangszustands‐Komplexe. Die Gründe für die unterschiedlichen Stabilitäten dieser Wirt‐Gast‐Systeme sollen hier untersucht werden, und wir beschreiben Ansätze zur computergestützten Analyse der Wirt‐Gast‐Komplexbildung in Lösung. Bei vielen Komplexklassen besteht eine ungefähre Korrelation der Bindungsaffinität mit der Größe der Oberfläche, die bei der Komplexierung vergraben wird. Enzyme folgen dieser Korrelation nicht, sondern binden Übergangszustände sehr viel stärker als es anhand der Oberfläche zu erwarten wäre.

What is Cooperativity?

“…Furthermore, most natural and artificial examples of strong positive cooperativity are cases of chelate cooperativity. Typical microscopic association constants in supramolecular systems are in the range 10 2 -10 4 m À1 with typical effective molarities in the range 10 À3 -10 1 m, [39] which lead to K EM values of 10 À1 -10 5 , whereas the value of a is typically 10 À3 -10 2 . [10,21] Many apparent cases of strong positive allosteric cooperativity actually involve chelation.…”

The Cucurbit[n]uril Family

“…[70] The average binding affinity for 1257 a-, b-, and g-CD complexes [71] (K a = 10 2.5AE1.1 m À1 ) is an order of magnitude smaller and more narrowly distributed than the corresponding value for 973 synthetic host-guest pairs in water (K a = 10 3.4AE1.6 m À1 ). A similar analysis using the 56 CB [6]·guest pairs reported by Mock and Shih [72] yields K a = 10 3.8AE1.5 m À1 .…”

Computational Enzyme Design

“…Catalytic proficiencies range from K tx À1 = 10 4.6 m À1 to K tx À1 = 10 8.6 m À1 , and so the transition states of the reactions they catalyze are bound more strongly than the substrates (K M À1 = 10 3.5AE1.0 m À1 ). [13,30] Natures enzymes, on the other hand, exert massive [8,34] Naturally, the catalytic efficiency (k cat /K M ) of such enzymes is often limited only by the diffusion rate of the substrate and ranges from 10 4 to 10 9 m À1 s À1 . In comparison, catalytic antibodies fall short of this limit by 4 orders of magnitude or more (k cat /K M = 10 2 -10 5 m À1 s À1 ).…”

“…[6] Remarkably, K tx À1 spans 21 orders of magnitude (10 8 to 10 29 m À1 ) [6,8] for enzymes that have been studied to date, [6,[9][10][11][12] with an average K tx À1 value of 10 16.0AE4.0 m À1 . [13] This value corresponds to an average DG value for transition-state binding of 22 kcal mol À1 , but can range up to 38 kcal mol À1 , much higher than a noncovalent TS binding free energy of 15 kcal mol À1 .…”

“…Furthermore, it can be desirable to try and unite catalytic turnover with substrate-, stereo-, regio-, or chemoselectivity as well as a tolerance towards organic solvents, elevated temperatures, and chemical degradation. Many different approaches of this type have been reviewed extensively: these include bioinformatics approaches, [14,15] natural evolution based engineering, [16] host-guest and supramolecular chemistry, [13] directed evolution, [17][18][19][20][21] catalytic antibodies, [22][23][24] organocatalysis, [25] rational structure-based protein engineering, [26] and computational protein design. [27] In this Review we describe the computational "insideout" approach to enzyme design, and the beginnings of what we strive to develop into a robust technology to make catalysts for synthesis, biotechnology, and therapeutics.…”