title: Comparative Computational Study of Serine Peptidase and Cysteine Peptidase Mechanisms
Creators: name: Gisdon, Florian
Publisher: name: University of Bayreuth
Year: 2022
Subjects: subject: Cysteine peptidases
subject: serine peptidases
subject: reaction path search
subject: continuum electrostatics
subject: phytochelatin-synthase-like enzyme
subject: 500
subject: 570

description: In biochemistry, detailed knowledge about the properties of an investigated biological system is fundamental to understand its behavior and its function. Experimental results are often limited to describe such properties in every detail. The branch of computational biochemistry can contribute more information to macroscopic measurements, and reveal microscopic details, which go beyond the scope of laboratory experiments. Computational research can also guide experimental measurements. Thereby both fields are not in competition but complement each other. The research of computational biochemists is based on the description of biological systems with an appropriate computational model regarding the scientific issue. Suitable models can be explicit with detailed descriptions of atoms and their components, or implicit to simulate physical properties of whole parts of the investigated system. Models of different abstraction levels can also be combined, which allows to investigate large systems with high accuracy of the relevant parts. In this thesis I used continuum electrostatic, and hybrid quantum mechanical/molecular mechanical models. The tools of computational biochemists are the algorithms, which are applied on the constructed models. For analysis of protonation characteristics, I applied continuum electrostatic models with Monte Carlo based sampling algorithms, which have been developed within the group. To investigate mechanistic details and kinetics of enzyme catalysis, reaction paths were analyzed. An essential element in my reaction path investigation of peptidase mechanisms was the conjugate peak refinement (CPR) algorithm. The algorithm was modified, and implemented as PyCPR by me together with a colleague for the Python-based framework pDynamo. PyCPR is a chain-of-states method, which represents a reaction path as discretized but linked structures. The algorithm is based on the characteristics of a saddle point, with focus to approach a saddle point region within an iterative procedure to gradually find the transition state of reaction steps. The reliable performance of PyCPR was confirmed by our pro vided examples on the conformational change of butane, and on the mechanism of the glycyl radical enzyme 4-hydroxyphenylacetate decarboxylase. Within my thesis, PyCPR was used for detailed analysis of the similar but different cysteine and serine peptidase mechanisms. Peptidases are enzymes with diverse functionality and perform important tasks in peptide degradation, pathogenic defense, or regulation in cellular pathways. It is known, that cysteine peptidase catalysis proceeds stepwise with an ion-pair intermediate, and serine peptidase catalysis proceeds concerted. However, the reason for a concerted mechanism in serine peptidases is poorly understood. The analysis of the electrostatic potential confirmed the common opinion of a positive potential around the cysteine, which stabilizes the emerging thiolate in cyteine peptidases. Contrary to this, I found a negative potential within serine peptidases. Analysis of protonation characteristics showed, that such a negative potential in serine peptidases is essential to enhance the basicity of the catalytic histidine, which facilitates proton acceptance from serine. As a consequence no ion-pair state intermediate is stabilized. But the negative potential further supports the concerted mechanism by increasing the nucleophilic potential of the catalytic serine. In addition to that, the active site geometry of serine peptidases has to be compact to allow for the simultaneous events of proton transfer to histidine and nucleophilic attack. These findings are in line with the experimentally measured inactivity of cysteine peptidases with their catalytic cysteine mutated into serine. At first I investigated the mechanism of a cysteine peptidase, which we also characterized in the laboratory. As expected, mutation of the catalytic cysteine to a serine led to inactivation, by which the substrate was bound non-processed within the binding pocket. This structure was used for further computational research. Reaction path analysis of this mutant serine peptidase revealed a much too high energy required for serine-based catalysis within the catalytic site of a cysteine peptidase. Computational analysis presented here showed, that additional transfer of features of the environment of the active site is required for serine peptidase activity. In the context of this thesis, a reaction path search algorithm was implemented, and a procedure was established to investigate reaction path charac teristics. With the application of the reaction path search procedure, together with other methods, I investigated a cysteine peptidase, and compared it to its inactive serine variant and a natural serine peptidase. By that, I revealed further details about serine peptidase catalysis, and the necessity for serine peptidases to have a concerted mechanism, which is facilitated by the surrounding of the catalytic triad.