Structural bioinformatics
However, the sequence implies restrictions that allow the formation of conserved local conformations of the polypeptide chain, such as alpha-helix, beta-sheets, and loops (secondary structure[3]).
The most common types of visualization are: The classic DNA duplexes structure was initially described by Watson and Crick (and contributions of Rosalind Franklin).
The DNA molecule is composed of three substances: a phosphate group, a pentose, and a nitrogen base (adenine, thymine, cytosine, or guanine).
The DNA double helix structure is stabilized by hydrogen bonds formed between base pairs: adenine with thymine (A-T) and cytosine with guanine (C-G).
In addition, the combination of a set of criteria, for example, physicochemical properties, distance, geometry, and angles, have been used to improve the contact determination.
The number of structure data available at PDB has increased each year, being obtained typically by X-ray crystallography, NMR spectroscopy, or cryo-electron microscopy.
Comparisons among a large set of proteins using RMSD still is a challenge due to the high computational cost of structural alignments.
Structural signatures based on graph distance patterns among atom pairs have been used to determine protein identifying vectors and to detect non-trivial information.
[24] Furthermore, linear algebra and machine learning can be used for clustering protein signatures, detecting protein-ligand interactions, predicting ΔΔG, and proposing mutations based on Euclidean distance.
Despite the new algorithms and methods proposed in the last years, de novo protein structure prediction is still considered one of the remain outstanding issues in modern science.
[29] Another validation strategy is calculating φ and ψ backbone dihedral angles of all residues and construct a Ramachandran plot.
The side-chain of amino acids and the nature of interactions in the backbone restrict these two angles, and thus, the visualization of allowed conformations could be performed based on the Ramachandran plot.
A high quantity of amino acids allocated in no permissive positions of the chart is an indication of a low-quality modeling.
Molecular docking aims to predict possible poses (binding modes) of the ligand when it interacts with specific regions on the receptor.
However, docking also can be used to detect associations and binding modes among proteins, peptides, DNA or RNA molecules, carbohydrates, and other macromolecules.
