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Related Concept Videos

Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Structure of Amines01:19

Structure of Amines

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The hybridized nitrogen atom in amines possesses a lone pair of electrons and is bound to three substituents with a bond angle of around 108°, which is less than the tetrahedral angle of 109.5°. However, the C–N–H bond angle is slightly larger at 112°, with a carbon–nitrogen bond length of 147 pm. This carbon–nitrogen bond length of of amines is longer than the carbon–oxygen bond of alcohols (143 pm) but shorter than alkanes’...
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Amino acids03:42

Amino acids

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Amino acids are the monomers that comprise proteins. Each amino acid has the same fundamental structure, which consists of a central carbon atom, or the alpha (α) carbon, bonded to an amino group (NH2), a carboxyl group (COOH), and to a hydrogen atom. Every amino acid also has another atom or group of atoms bonded to the central atom known as the R group. There are 20 common amino acids present in proteins, each with a different R group. Variation in the amino acid sequence is responsible...
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Amino Acid Biosynthetic Pathways01:29

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Amino acid biosynthesis is essential for cell growth, protein synthesis, and metabolic regulation. Cells generate essential and non-essential amino acids from metabolic intermediates to sustain vital biological functions. These intermediates originate from key metabolic pathways: glycolysis, the tricarboxylic acid (TCA) cycle, and the pentose phosphate pathway. Important precursors include α-ketoglutarate, pyruvate, oxaloacetate, phosphoenolpyruvate, and erythrose-4-phosphate, which...
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Basicity of Aliphatic Amines01:21

Basicity of Aliphatic Amines

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Amines can behave as Brønsted–Lowry bases by accepting a proton from the acid to form corresponding conjugate acids. Due to a lone pair of nonbonding electrons, aliphatic amines can also act as Lewis bases by forming a covalent bond with an electrophile.
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Amines: Introduction01:07

Amines: Introduction

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Amines are organic derivatives of ammonia. They are formed by replacing one or more ammonia protons with alkyl or aryl groups. Depending upon the number of organyl groups bonded to nitrogen, amines are classified as primary, secondary, or tertiary. Primary amines have one organyl group attached to the nitrogen atom, while secondary and tertiary amines have two and three organyl groups attached to the nitrogen atom, respectively.
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Related Experiment Video

Updated: Oct 13, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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Amino acid environment affinity model based on graph attention network.

Xueheng Tong1, Shuqi Liu1, Jiawei Gu1

  • 1College of Computer Science and Technology, Jilin University, Qianjing Street 2699, Changchun, Jilin 130012, China.

Journal of Bioinformatics and Computational Biology
|November 15, 2021
PubMed
Summary
This summary is machine-generated.

We developed a graph attention network model to predict amino acid environment affinity in proteins. This method accurately identifies protein sites, outperforming previous techniques by 30% for structural and functional analysis.

Keywords:
Deep learninggraph attention networksgraph neural networkprotein structure

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Machine Learning

Background:

  • Proteins, essential for life, possess complex spatial structures critical for their function.
  • Understanding amino acid environment affinity is key for protein structural and functional studies, including mutation analysis and functional site detection.

Purpose of the Study:

  • To develop a novel model for predicting amino acid environment affinity using graph attention networks.
  • To enhance the accuracy of identifying protein structure microenvironments and their functional relevance.

Main Methods:

  • Constructed protein graphs based on inter-amino acid distances.
  • Extracted structural features for each amino acid node.
  • Applied a graph attention network (GAN) model to predict amino acid affinities.

Main Results:

  • The proposed graph attention network model effectively captures amino acid environment affinities.
  • Achieved a significant performance improvement of nearly 30% compared to a 3DCNN-based method.
  • Demonstrated the model's capability in identifying functionally relevant protein sites.

Conclusions:

  • The graph attention network model offers a powerful approach for analyzing protein structures and functions.
  • This method advances the field of computational biology by improving the prediction of amino acid environment affinity.
  • The developed model has potential applications in drug discovery and protein engineering.