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Amino acids

Amino acids

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...

Protein Organization

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....

Conserved Binding Sites

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...

Predicting Molecular Geometry

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries

Structure of Amines

Structure of Amines

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’...

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

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Updated: Sep 8, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

Geometry-based distance for clustering amino acids.

Samira F Abushilah^1,2, Charles C Taylor¹, Arief Gusnanto¹

¹Department of Statistics, University of Leeds, Leeds, UK.

Journal of Applied Statistics

|June 16, 2022

Summary

This summary is machine-generated.

This study introduces a novel method for clustering amino acids using geometric properties, specifically dihedral angles, to improve protein structure prediction. The approach yields meaningful amino acid clusters, enhancing functional and structural analysis.

Keywords:

Circular distance energy statistic hierarchical clustering permutation two-sample test similarity indices squared Euclidean distance

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Area of Science:

Bioinformatics
Computational Biology
Structural Biology

Background:

Amino acid clustering is crucial for protein functional and structural prediction.
Existing methods rely on physical/biochemical properties, which are less directly linked to protein structure.
Geometric characteristics, like dihedral angles, offer a more direct link to protein structure.

Purpose of the Study:

To propose a novel method for amino acid clustering based on geometric characteristics.
To utilize the p-value from a test of equality of dihedral-angle distributions as a distance measure.
To improve the accuracy and interpretability of amino acid clusters for protein analysis.

Main Methods:

Modified an energy test to handle bivariate angular data.
Employed a permutation method to obtain p-values for clustering.
Applied the p-value-based distance measure to cluster amino acids.

Main Results:

The proposed method successfully generated sensible amino acid clusters.
Specific amino acids like Glycine, Proline, and Asparagine formed distinct clusters.
A simulation study indicated the approach has good working characteristics.

Conclusions:

Clustering amino acids based on dihedral-angle distributions is a viable and effective approach.
This geometric-based method offers a more direct link to protein structure than traditional methods.
The findings have implications for advancing protein functional and structural prediction.