Computational Approaches for Studying Enzyme Mechanism Part A

2007 ◽  
Author(s):  
Shiyu Xu ◽  
Ganglin Chen ◽  
Yaping Zhu ◽  
Jie Zhang ◽  
Michael Payne ◽  
...  

2019 ◽  
Author(s):  
Keiei Kumon ◽  
Masahiro Higashi ◽  
Shinji Saito ◽  
Shigehiko Hayashi

Many enzyme molecules exhibit characteristic global and slow dynamics which furnish them with allostery realizing remarkable molecular functionalities more than simple chemical catalysis. However, molecular mechanism of a catalytic reaction associated with the molecular flexibility of enzymes is not well-understood. Here we report a hybrid molecular simulation study on GTPase activity of a Ras-GAP protein complex for cell signaling termination. We unveiled that extensive conformational changes of the protein complex and exclusion of internal water molecules are induced upon the transition state (TS) formation in the catalytic reaction and significantly lower the reaction activation free energy. We also revealed that tumor-related mutations perturb those conformational changes upon the TS formation, leading to reduction of the catalytic activity. The findings of the remarkably dynamic protein conformation directly linking to the catalytic reaction have broad implications for understanding of enzyme mechanism and for developments of allosteric drugs and novel catalysts.


2012 ◽  
Vol 39 (11) ◽  
pp. 1029-1036
Author(s):  
Da-Fei XIE ◽  
Peng LI ◽  
Fei LI ◽  
Xiao-Chen BO ◽  
Sheng-Qi WANG

2020 ◽  
Vol 27 (1) ◽  
pp. 32-41 ◽  
Author(s):  
Subhash C. Basak ◽  
Apurba K. Bhattacharjee

Background: In view of many current mosquito-borne diseases there is a need for the design of novel repellents. Objective: The objective of this article is to review the results of the researches carried out by the authors in the computer-assisted design of novel mosquito repellents. Methods: Two methods in the computational design of repellents have been discussed: a) Quantitative Structure Activity Relationship (QSAR) studies from a set of repellents structurally related to DEET using computed mathematical descriptors, and b) Pharmacophore based modeling for design and discovery of novel repellent compounds including virtual screening of compound databases and synthesis of novel analogues. Results: Effective QSARs could be developed using mathematical structural descriptors. The pharmacophore based method is an effective tool for the discovery of new repellent molecules. Conclusion: Results reviewed in this article show that both QSAR and pharmacophore based methods can be used to design novel repellent molecules.


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