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Related Concept Videos

Introduction to Functional Groups02:08

Introduction to Functional Groups


Functional groups are group of atoms with specific chemical properties that occur within organic molecules and sometimes denoted as “R”. Functional groups are found along the carbon backbone of macromolecules can form chains or rings of carbon atoms. Functional groups can “functionalize” a compound by enabling it to adopt different physical and chemical properties.
Types of common functional groups
The table below summarizes some of the major functional groups in organic chemistry. (The...
Overview of Advanced Functional Groups02:22

Overview of Advanced Functional Groups


Functional groups are groups of atoms with specific chemical properties that occur within organic molecules and are sometimes denoted as “R”. Functional groups can “functionalize” a compound by enabling it to adopt different physical and chemical properties.
Types of Advanced Functional Groups
The table below summarizes some of the major functional groups in organic chemistry.
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
Functional Classification of Joints01:09

Functional Classification of Joints

Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An immobile...
Classification of Neurotransmitters01:30

Classification of Neurotransmitters

Neurotransmitters play a crucial role in the communication between neurons in the autonomic nervous system. Neurons in the autonomic nervous system can be cholinergic or adrenergic depending on the neurotransmitters synthesized. Cholinergic neurons use acetylcholine as their primary neurotransmitter. This includes all the preganglionic fibers of the sympathetic and pre- and postganglionic fibers of the parasympathetic nervous systems. In addition, neurons of the somatic nervous system also use...
Classification of Systems-I01:26

Classification of Systems-I

Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:

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Updated: Jun 26, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Enzyme functional classification using artificial intelligence.

Ha Rim Kim1, Hongkeun Ji1, Gi Bae Kim2

  • 1Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 four), KAIST Institute for BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea; Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.

Trends in Biotechnology
|March 28, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) accelerates enzyme function prediction, overcoming experimental limitations. Deep learning models enhance accuracy by automatically extracting features, paving the way for novel enzyme discovery.

Keywords:
EC numberGO termdeep learningenzymemachine learningmetabolism

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Area of Science:

  • Biochemistry
  • Bioinformatics
  • Artificial Intelligence

Background:

  • Enzymes are crucial for cellular metabolism, but experimental function elucidation is slow and costly.
  • Developing high-throughput and scalable methods for enzyme function prediction is a key research challenge.

Purpose of the Study:

  • To review advancements in artificial intelligence (AI)-driven enzyme functional annotation.
  • To compare traditional machine learning (ML) with state-of-the-art deep learning (DL) approaches in this field.

Main Methods:

  • Discussion of AI-driven methods for enzyme function prediction.
  • Highlighting the transition from traditional ML to DL techniques.
  • Examining the capability of DL models to automatically extract features from raw data.

Main Results:

  • Deep learning models demonstrate enhanced performance in enzyme function prediction due to automated feature extraction.
  • AI approaches offer scalable and high-throughput solutions compared to traditional experimental methods.

Conclusions:

  • AI, particularly deep learning, significantly improves enzyme functional annotation.
  • Future directions include integrating generative AI and big bio data for novel enzyme discovery and de novo enzyme design.