Reduced Distance Matrix to Verify the Similarity between Protein Structures

Monteiro, Otaviano Martins; Dias, Sandro Renato; Rodrigues, Thiago de Souza

doi:10.1590/1678-4324-2021200118

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Article - Engineering, Technology and Techniques • Braz. arch. biol. technol. 64 • 2021 • https://doi.org/10.1590/1678-4324-2021200118 copy

Reduced Distance Matrix to Verify the Similarity between Protein Structures

Authorship SCIMAGO INSTITUTIONS RANKINGS

HIGHLIGHTS

Development of a reduced distance matrix, approximately 70% less than [¹1 Monteiro OM, Dias SR, Rodrigues TS. [Development of a Methodology Based on a Distance Matrix for Verifying Protein Similarities]. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics. 2020; 7(1): 0103691-7. doi: 10.5540/03.2020.007.01.0369.
https://doi.org/10.5540/03.2020.007.01.0... ].

The reduced distance matrix has a shorter processing time than the algorithms [¹1 Monteiro OM, Dias SR, Rodrigues TS. [Development of a Methodology Based on a Distance Matrix for Verifying Protein Similarities]. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics. 2020; 7(1): 0103691-7. doi: 10.5540/03.2020.007.01.0369.
https://doi.org/10.5540/03.2020.007.01.0...

2 Dias SR, Garrat RC, Nagem RAP. Proposition of Site-Directed Mutagenesis of Proteins Based on a Residue-Residue Interaction Database. The Brazilian Society for Biochemistry and Molecular Biology [Internet]. 2011 Apr 30. [cited 2019 Nov 29]; 3(1). Available from: http://www.sbbq.org.br/reuniao/cdrom/ra2011/resumos/R8102.pdf
http://www.sbbq.org.br/reuniao/cdrom/ra2... -³3 Pires DEV, Minardi RCM, Santos MA, Silveira CH, Campos FF, Meira W. aCSM: noise-free graph-based signatures to large-scale receptor-based ligand prediction. Bioinformatics. 2013 Apr 01;29(7):855-61. doi: 10.1093/bioinformatics/btt058. PubMed PMID: 23396119.
https://doi.org/10.1093/bioinformatics/b... ].

Several clusters were constructed with similar protein interactions.

The reduced distance matrix obtained satisfactory accuracy.

Abstract

This paper focuses on developing a reduced distance matrix to improve the computational performance during the protein interactions clustering. This proposed matrix considers as centroids two alpha carbon atoms from a protein structure and stores the distances between these centroids and the other atoms from this same structure. Each row in this matrix represents a database record and each column is a distance value. Through this build matrix, clusters were performed using K-Means Clustering. The precision and performance of this presented technique were compared with aCSM, RID and another distance matrix methodology that considers the distances between all atoms from each protein structure. The results were satisfactory. The reduced distance matrix obtained a high precision and the best computational performance.

Keywords:
protein interactions; reduced distance matrix; clustering

Columns		Field	Definition
1 - 6	Record name	ATOM
7 - 11	Integer	Serial	Atom serial number
12 - 16	Atom	Name	Atom name
17	Character	AltLoc	Alternate location indication
18 - 20	Residue name	ResName	Residue name
22	Character	ChainID	Chain identify
23 - 26	Integer	ResSec	Residue sequence number
27	AChar	iCode	Code insertion of residues
31 - 38	Float (8,3)	X	Orthogonal coordinate for X
39 - 46	Float (6,2)	Y	Orthogonal coordinate for Y
47 - 54	Float (6,2)	Z	Orthogonal coordinate for Z
55 - 60	Float (6,2)	Occupancy	Occupancy
61 - 66	Float (6,2)	TempFactor	Temperature factor
77 - 78	LString (2)	Element	Element symbol right- justified
79 - 80	LString (2)	Charge	Charge on the Atom

Positions	Definition
1 - 11	Euclidian distance between the leftmost Carbon atom and the other 11 atoms
12 - 21	Euclidean distance between the Nitrogen and the other atoms, except the leftmost Carbon
22 - 30	Euclidean distance between the left CA and the other atoms, except the first two atoms
31 - 38	Euclidean distance between the Carbon and the other atoms, except the first three atoms
39 - 45	Euclidean distance between the Oxygen and the other atoms, except the first four atoms
46 - 51	Euclidean distance between the Nitrogen and the other atoms, except the first five atoms
52 - 56	Euclidean distance between the first Carbon in the right side and other atoms on the right
57 - 60	Euclidean distance between the Nitrogen in the right side and the other 4 remaining atoms
61 - 63	Euclidean distance between the right CA and the other 3 remaining atoms
64 - 65	Euclidean distance between the Carbon and the others 2 remaining atoms
66	Euclidean distance between the last 2 atoms (Nitrogen and Oxygen)

Technique	Reduced Distance Matrix			Complete Distance Matrix
Quantity of clusters	500	750	1,000	500	750	1,000
0% to 10%	486	338	318	442	345	281
10% to 20%	1,727	1,249	968	1,473	1,069	763
20% to 30%	1,432	1,303	1,105	1,421	1,033	962
30% to 40%	1,319	1,171	1,162	1,114	1,299	1,084
40% to 50%	1,225	1,041	947	1,051	912	890
50% to 60%	1,341	1,166	1,009	1,389	1,023	904
60% to 70%	1,368	1,202	1,110	1,311	1,017	1,070
70% to 80%	1,880	1,821	1,579	1,058	1,319	969
80% to 90%	2,215	2,199	2,088	2,209	1,582	1,382
90% to 100%	3,390	4,893	6,097	4,915	6,784	8,078

Technique	Reduced Distance Matrix			Complete Distance Matrix
Quantity of clusters	500	750	1,000	500	750	1,000
Build the matrix	00:02	00:02	00:02	00:10	00:10	00:10
Clustering	00:20	00:29	00:49	00:40	01:09	01:23
Total time	00:22	00:31	00:51	00:50	01:19	01:33

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[1] *Correspondence: otavianomartins@hotmail.com(O.M.M.).