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Enzymes

Enzymes

Inside living organisms, enzymes act as catalysts for many biochemical reactions involved in cellular metabolism. The role of enzymes is to reduce the activation energies of biochemical reactions by forming complexes with its substrates. The lowering of activation energies favor an increase in the rates of biochemical reactions.
Enzyme deficiencies can often translate into life-threatening diseases. For example, a genetic abnormality resulting in the deficiency of the enzyme G6PD...

Introduction to Mechanisms of Enzyme Catalysis

Introduction to Mechanisms of Enzyme Catalysis

For many years, scientists thought that enzyme-substrate binding took place in a simple "lock-and-key" fashion. This model stated that the enzyme and substrate fit together perfectly in one instantaneous step. However, current research supports a more refined view scientists call induced fit. The induced-fit model expands upon the lock-and-key model by describing a more dynamic interaction between enzyme and substrate. As the enzyme and substrate come together, their interaction causes...

Induced-fit Model

Induced-fit Model

Most chemical reactions in cells require enzymes—biological catalysts that speed up the reaction without being consumed or permanently changed. They reduce the activation energy needed to convert the reactants into products. Enzymes are proteins, that usually work by binding to a substrate—a reactant molecule that they act upon.
Enzymes exhibit substrate specificity, meaning that they can only bind to certain substrates. This is mainly determined by the shape and chemical...

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Updated: Jun 14, 2025

A Toolkit to Enable Hydrocarbon Conversion in Aqueous Environments

A Toolkit to Enable Hydrocarbon Conversion in Aqueous Environments

Published on: October 2, 2012

Automating the Analysis of Substrate Reactivity through Environment Interaction Mapping.

Thiago H da Silva¹, Jalen Lu¹, Zayah Cortright¹

¹Department of Chemistry and Biochemistry, Boise, Idaho 83725, United States.

Journal of Chemical Information and Modeling

|May 29, 2025

Summary

This summary is machine-generated.

This study presents a new automated method to explore how atoms and molecules interact with surfaces. It uses symmetry-invariant features and machine learning for efficient and comprehensive analysis of interaction sites, even for complex systems.

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Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes

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Published on: January 16, 2016

Area of Science:

Materials Science
Computational Chemistry
Surface Science

Background:

Understanding substrate-adsorbate interactions is vital for catalysis, solvation, and molecular recognition.
Conventional methods for determining interaction configurations often lack efficiency and struggle with low-symmetry or poorly understood systems.

Purpose of the Study:

To develop a systematic and automated methodology for exploring substrate-adsorbate configuration spaces.
To enable comprehensive and non-redundant sampling of interaction sites, independent of substrate dimensionality.

Main Methods:

Defining and discretizing a contact space around the substrate.
Employing symmetry-invariant descriptors to characterize local atomic environments.
Utilizing unsupervised machine learning for clustering and hierarchical analysis of interaction sites.

Main Results:

The automated method successfully recovers symmetry intuition and identifies high-symmetry sites on ideal substrates.
The approach demonstrates adaptability and seamless application to substrates with lower symmetry.
Comprehensive and non-redundant sampling of the configuration space is achieved.

Conclusions:

This novel methodology offers an efficient and systematic way to explore complex interaction configurations.
The approach is broadly applicable across various scientific domains requiring the study of surface interactions.
It overcomes limitations of traditional methods, particularly for systems lacking high symmetry.