Electrostatic Basis of Enzyme Catalysis

Náray‐Szabó, Gábor; Fuxreiter, Mónika; Warshel, Arieh

doi:10.1007/0-306-46934-0_6

Cited by 17 publications

(18 citation statements)

References 214 publications

(222 reference statements)

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“…Simulation approaches that focus on the electrostatic aspects of enzyme catalysis (i.e., the difference between the stabilization in the enzyme and solution) appear to give much more quantitative results than those that focus on the quantum mechanical aspects of the problem but overlook the proper treatment of long-range effects (see discussion in Ref. [145]). In fact, some problems can be effectively treated even by PB approaches (see, for example, Ref.…”

Section: Enzyme Catalysismentioning

confidence: 99%

Electrostatics of Proteins: Principles, Models and Applications

Braun‐Sand¹,

Warshel²

2005

Protein Folding Handbook

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Section: Enzyme Catalysismentioning

confidence: 99%

Electrostatics of Proteins: Principles, Models and Applications

Braun‐Sand¹,

Warshel²

2005

Protein Folding Handbook

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“…If Q N = 0 we return to relations (12), (14), and therefore, simulate a jump from the boundary in accordance with (13). So, we see that the probability of termination of the constructed Markov chain depends only on kd i .…”

Section: ∂G) Then the Next Point Is Chosen Isotropically Onmentioning

confidence: 93%

“…It is a common knowledge (see e.g. [13]) that the expression for electrostatic energy depends on the thermodynamic process that led to the resulting charge distribution. In the case when all response functions are linear, the electrostatic free energy of the molecule is given by…”

Section: Mathematical Statement Of the Problemmentioning

confidence: 99%

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Monte Carlo Method for Calculating the Electrostatic Energy of a Molecule

Mascagni

Simonov

2003

Lecture Notes in Computer Science

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Abstract. The problem of computing the electrostatic energy of a large molecule is considered. It is reduced to solving the Poisson equation inside and the linear Poisson-Boltzmann equation in the exterior, coupled by boundary conditions. A Monte Carlo estimate for the potential point values, their derivatives, and the energy is constructed. The estimate is based on the walk on spheres and Green's function first passage algorithms; the walk in subdomains technique; and finite-difference approximations of the boundary condition. Results of some illustrative calculations are presented.

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“…The reasons for this election are based on the assumption that relates the potential bioactivity of drugs with their chemical reactivity from the molecular point of view 10,11 and also that when a group of descriptors cannot be cast in a QSAR mathematical formulation because of the limited availability of information, the knowledge of the chemical reactivity of a small group of molecules may still provide useful results that can serve as a guide for the purpose of the research.…”

Section: Introductionmentioning

confidence: 99%

Computational Peptidology Assisted by Conceptual Density Functional Theory for the Study of Five New Antifungal Tripeptides

Flores-Holgúın

Frau

2019

ACS Omega

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A well-behaved model chemistry previously validated for the study of the chemical reactivity of peptides was considered for the calculation of the molecular properties and structures of a group of five new antifungal tripeptides, namely (2 R )-2-[(2 S )-2-[(2 S )-2-amino-3-phenylpropanamido]propanamido]-5-[(diaminomethylidene)amino]pentanoic acid, (2 S )-2-[(2 S )-2-[(2 S )-2-amino-3-phenyl propanamido]propanamido]-3-(4-hydroxyphenyl)propanoic acid, (2 S )-2-[(2 S )-2-[(2 S )-2-amino-3-phenylpropanamido]-3-methylbutanamido]-3-(4-hydroxyphenyl)propanoic acid, (2 R )-2-[(2 S )-2-[(2 S )-2-amino-3-phenylpropanamido]-3-(1 H -indol-3-yl)propanamido]-3-sulfanylpropanoic acid, and (2 S )-2-[(2 S )-2-[(2 S )-2-amino-3-phenylpropanamido]-3-(1 H -indol-3-yl)propanamido]-3-(4-hydroxyphenyl)propanoic acid, according to their amino acid sequences. A methodology based on conceptual density functional theory was chosen for the determination of the reactivity descriptors. The molecular active sites were associated with the active regions of the molecules that were associated with the nucleophilic, electrophilic, and radical Fukui functions. Additionally, the p K a values for the different peptides are predicted with great accuracy, which constitutes a useful knowledge for the process of drug design. Finally, the bioactivity scores for the new antifungal peptides are predicted through a homology methodology relating them with the calculated reactivity descriptors.

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Electrostatic Basis of Enzyme Catalysis

Cited by 17 publications

References 214 publications

Electrostatics of Proteins: Principles, Models and Applications

Electrostatics of Proteins: Principles, Models and Applications

Monte Carlo Method for Calculating the Electrostatic Energy of a Molecule

Computational Peptidology Assisted by Conceptual Density Functional Theory for the Study of Five New Antifungal Tripeptides

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