Since enzymes are involved in most life processes, it is crucial to gain a detailed understanding of their action. The importance of such an understanding is highlighted by the fact that many diseases can be controlled by developing drugs that block the action of enzymes in crucial biological pathways of pathogens that cause these diseases. Quantifying the analysis of enzyme catalysis can be greatly advanced by computer simulation approaches that correlate enzyme structures with their activity. Here the progress should involve both advances in quantifying the fundamental basis of enzyme catalysis and in developing practical predictive power in studies of diverse classes of enzymes. Thus we propose to continue in advancing the frontiers of this field, while shifting a significant part of our focus to the the emerging field of enzyme design. The advances on this front should provide a deeper understanding of catalysis, help in controlling what a given enzyme is doing as well as the use of specialized enzymes. We note, however, that the progress in enzyme design has not yet led to designer enzymes that rival native enzymes. Thus, it is clear that the potential of this field can be greatly enhanced by computational approaches that evaluate the activation barriers of the reactions that are being catalyzed. In order to progress in both quantifying enzyme design and in enhancing the general understanding of enzyme catalysis, we propose parallel advances in the following directions: (i) We will validate the reliability of our EVB-based computer-aided enzyme design by reproducing the observed catalytic effects of key designer enzymes. (ii) We will continue to develop more quantitative design concepts as well as fast screening methods. After exploring the predictive power of these approaches, we will use them in collaboration with research groups that are involved in actual enzyme design experiments. (iii) We will continue to advance quantitative computational methods including the paradynamics QM(ai)/MM-FEP approach that should help us to obtain activation free energies of enzymatic reactions by ab initio methods. (iv) We will quantify the relationship between folding and stability and explore the relationship between thermostability and catalysis. (v) We will explore the catalytic effect of directed evolution, trying to elucidate its relationship to natural evolution. (vi) We will conduct studies of several important classes of enzymatic reactions. (vii) We will continue with the systematic examination of different nonelectrostatic catalytic proposals.

Public Health Relevance

Detailed understanding of enzyme action is crucial for rational development of drugs that block biological pathways of pathogens that lead to devastating diseases. Key progress in this direction has started to emerge from computer simulations of different classes of enzymes, and further progress can be obtained by advancing the field of enzyme design, where the ability to predict how to design a better enzyme can be used as a stringent test of our understanding of enzyme catalysis and as a guide for practical advances. Here we propose to continue to push the frontiers in modeling of enzymatic reactions, while providing major help in fundamental understanding of structure-catalysis correlation, in rational enzyme design and in accelerating the progress in fighting diseases associated with enzyme action.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM024492-37
Application #
8627932
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Preusch, Peter C
Project Start
1978-01-01
Project End
2018-03-31
Budget Start
2014-04-01
Budget End
2015-03-31
Support Year
37
Fiscal Year
2014
Total Cost
$324,166
Indirect Cost
$117,230
Name
University of Southern California
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90089
Yoon, Hanwool; Warshel, Arieh (2017) Simulating the fidelity and the three Mg mechanism of pol ? and clarifying the validity of transition state theory in enzyme catalysis. Proteins 85:1446-1453
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Jindal, Garima; Warshel, Arieh (2017) Misunderstanding the preorganization concept can lead to confusions about the origin of enzyme catalysis. Proteins 85:2157-2161
Astumian, R Dean; Mukherjee, Shayantani; Warshel, Arieh (2016) The Physics and Physical Chemistry of Molecular Machines. Chemphyschem 17:1719-41
Matute, Ricardo A; Yoon, Hanwool; Warshel, Arieh (2016) Exploring the mechanism of DNA polymerases by analyzing the effect of mutations of active site acidic groups in Polymerase ?. Proteins 84:1644-1657
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Vorobyov, Igor; Kim, Ilsoo; Chu, Zhen T et al. (2016) Refining the treatment of membrane proteins by coarse-grained models. Proteins 84:92-117
Kim, Ilsoo; Warshel, Arieh (2016) A Microscopic Capacitor Model of Voltage Coupling in Membrane Proteins: Gating Charge Fluctuations in Ci-VSD. J Phys Chem B 120:418-32

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