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Geomfinder: a multi-feature identifier of similar three-dimensional protein patterns: a ligand-independent approach.

Núñez-Vivanco G, Valdés-Jiménez A, Besoaín F, Reyes-Parada M - J Cheminform (2016)

Bottom Line: Nevertheless, many of the protein structures stored in public databases do not provide information about the location and characteristics of ligand binding sites and/or other important 3D patterns such as allosteric sites, enzyme-cofactor interaction motifs, etc.Thus: (a) Geomfinder detected identical pairs of 3D patterns in a series of monoamine oxidase-B structures, which corresponded to the effectively similar ligand binding sites at these proteins; (b) we identified structural similarities among pairs of protein structures which are targets of compounds such as acarbose, benzamidine, adenosine triphosphate and pyridoxal phosphate; these similar 3D patterns are not detected using sequence-based methods; (c) the detailed evaluation of three specific cases showed the versatility of Geomfinder, which was able to discriminate between similar and different 3D patterns related to binding sites of common substrates in a range of diverse proteins.Although the software is not intended for simultaneous multiple comparisons in a large number of proteins, it can be particularly useful in cases such as the structure-based design of multitarget drugs, where a detailed analysis of 3D patterns similarities between a few selected protein targets is essential.

View Article: PubMed Central - PubMed

Affiliation: Escuela de Ingeniería Civil en Bioinformática, Universidad de Talca, Avenida Lircay s/n, Talca, Chile ; Centro de Bioinformática y Simulación Molecular, Universidad de Talca, 2 Norte 685, Talca, Chile.

ABSTRACT

Background: Since the structure of proteins is more conserved than the sequence, the identification of conserved three-dimensional (3D) patterns among a set of proteins, can be important for protein function prediction, protein clustering, drug discovery and the establishment of evolutionary relationships. Thus, several computational applications to identify, describe and compare 3D patterns (or motifs) have been developed. Often, these tools consider a 3D pattern as that described by the residues surrounding co-crystallized/docked ligands available from X-ray crystal structures or homology models. Nevertheless, many of the protein structures stored in public databases do not provide information about the location and characteristics of ligand binding sites and/or other important 3D patterns such as allosteric sites, enzyme-cofactor interaction motifs, etc. This makes necessary the development of new ligand-independent methods to search and compare 3D patterns in all available protein structures.

Results: Here we introduce Geomfinder, an intuitive, flexible, alignment-free and ligand-independent web server for detailed estimation of similarities between all pairs of 3D patterns detected in any two given protein structures. We used around 1100 protein structures to form pairs of proteins which were assessed with Geomfinder. In these analyses each protein was considered in only one pair (e.g. in a subset of 100 different proteins, 50 pairs of proteins can be defined). Thus: (a) Geomfinder detected identical pairs of 3D patterns in a series of monoamine oxidase-B structures, which corresponded to the effectively similar ligand binding sites at these proteins; (b) we identified structural similarities among pairs of protein structures which are targets of compounds such as acarbose, benzamidine, adenosine triphosphate and pyridoxal phosphate; these similar 3D patterns are not detected using sequence-based methods; (c) the detailed evaluation of three specific cases showed the versatility of Geomfinder, which was able to discriminate between similar and different 3D patterns related to binding sites of common substrates in a range of diverse proteins.

Conclusions: Geomfinder allows detecting similar 3D patterns between any two pair of protein structures, regardless of the divergency among their amino acids sequences. Although the software is not intended for simultaneous multiple comparisons in a large number of proteins, it can be particularly useful in cases such as the structure-based design of multitarget drugs, where a detailed analysis of 3D patterns similarities between a few selected protein targets is essential.

No MeSH data available.


Related in: MedlinePlus

Similarity of the sequence and the 3D patterns in the Monoamine Oxidase B proteins. The red bars represent the highest value of a GScore between each pair of 3D patterns related with MAO-B binding sites. The sequence similarity between each pair of MAO proteins is shown in the purple bars. The blue and green bars show the similarity measured by the PocketMatch and the Click software, respectively. All pair of MAO proteins evaluated together with the % of similarity of all methods, are described in the X axis. The protein sequences were obtained with the babel software, using as input the structures obtained from the PDB database
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Fig4: Similarity of the sequence and the 3D patterns in the Monoamine Oxidase B proteins. The red bars represent the highest value of a GScore between each pair of 3D patterns related with MAO-B binding sites. The sequence similarity between each pair of MAO proteins is shown in the purple bars. The blue and green bars show the similarity measured by the PocketMatch and the Click software, respectively. All pair of MAO proteins evaluated together with the % of similarity of all methods, are described in the X axis. The protein sequences were obtained with the babel software, using as input the structures obtained from the PDB database

Mentions: Our first evaluation was done with 38 crystallographic structures of the human Monoamine Oxidase-B (MAO-B; Additional file 2: Table S1). This enzyme is located in the mitochondrial outer membrane and catalyzes the oxidative deamination of biogenic and xenobiotic amines [46]. In all structures available, MAO-B has a co-factor flavin-adenine-dinucleotide (FAD) covalently bound and its location is the reference for a conserved catalytic binding site in this family of proteins [47]. Several compounds which differ in their pharmacodynamics and structure have been co-crystallized with MAO-B (e.g. 1,4-Diphenyl-2-butene, Isatin, n-Propargyl-1(s)-aminoindan, (3R)-3-(prop-2-ynylamino)-2,3-dihydro-1H-inden-5-ol, among others). These differences generate distinct biological responses such as the reversible or the irreversible inhibition of the enzyme. In our tests, Geomfinder was able to detect identical pairs of 3D patterns (pairs of 3D patterns with a  %) corresponding to the ligand binding sites of all MAO-B structures (Fig. 4). Since the pairs compared involved the same protein co-crystallized with different inhibitors (Additional file 1: Figure S3), it was not surprising that a high degree of similarity was also found using either global sequence or ligand-independent alignment methods. Thus, a 100 % of similarity was identified with both, the pairwise alignment algorithm of Smith-Waterman implemented on the EMBOSS Website [48] and the CLICK software [49]. Noteworthy, the same performance was not attained using methods, such as PocketMatch [40], which consider the structure of the ligands as the starting point to calculate a similarity score (Fig. 4). Hence, our results confirm the suitability of Geomfinder to recognize, in spite of the presence or absence of ligands, similar 3D patterns (in this case ligand-binding sites) that are effectively similar or identical.


Geomfinder: a multi-feature identifier of similar three-dimensional protein patterns: a ligand-independent approach.

Núñez-Vivanco G, Valdés-Jiménez A, Besoaín F, Reyes-Parada M - J Cheminform (2016)

Similarity of the sequence and the 3D patterns in the Monoamine Oxidase B proteins. The red bars represent the highest value of a GScore between each pair of 3D patterns related with MAO-B binding sites. The sequence similarity between each pair of MAO proteins is shown in the purple bars. The blue and green bars show the similarity measured by the PocketMatch and the Click software, respectively. All pair of MAO proteins evaluated together with the % of similarity of all methods, are described in the X axis. The protein sequences were obtained with the babel software, using as input the structures obtained from the PDB database
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4834829&req=5

Fig4: Similarity of the sequence and the 3D patterns in the Monoamine Oxidase B proteins. The red bars represent the highest value of a GScore between each pair of 3D patterns related with MAO-B binding sites. The sequence similarity between each pair of MAO proteins is shown in the purple bars. The blue and green bars show the similarity measured by the PocketMatch and the Click software, respectively. All pair of MAO proteins evaluated together with the % of similarity of all methods, are described in the X axis. The protein sequences were obtained with the babel software, using as input the structures obtained from the PDB database
Mentions: Our first evaluation was done with 38 crystallographic structures of the human Monoamine Oxidase-B (MAO-B; Additional file 2: Table S1). This enzyme is located in the mitochondrial outer membrane and catalyzes the oxidative deamination of biogenic and xenobiotic amines [46]. In all structures available, MAO-B has a co-factor flavin-adenine-dinucleotide (FAD) covalently bound and its location is the reference for a conserved catalytic binding site in this family of proteins [47]. Several compounds which differ in their pharmacodynamics and structure have been co-crystallized with MAO-B (e.g. 1,4-Diphenyl-2-butene, Isatin, n-Propargyl-1(s)-aminoindan, (3R)-3-(prop-2-ynylamino)-2,3-dihydro-1H-inden-5-ol, among others). These differences generate distinct biological responses such as the reversible or the irreversible inhibition of the enzyme. In our tests, Geomfinder was able to detect identical pairs of 3D patterns (pairs of 3D patterns with a  %) corresponding to the ligand binding sites of all MAO-B structures (Fig. 4). Since the pairs compared involved the same protein co-crystallized with different inhibitors (Additional file 1: Figure S3), it was not surprising that a high degree of similarity was also found using either global sequence or ligand-independent alignment methods. Thus, a 100 % of similarity was identified with both, the pairwise alignment algorithm of Smith-Waterman implemented on the EMBOSS Website [48] and the CLICK software [49]. Noteworthy, the same performance was not attained using methods, such as PocketMatch [40], which consider the structure of the ligands as the starting point to calculate a similarity score (Fig. 4). Hence, our results confirm the suitability of Geomfinder to recognize, in spite of the presence or absence of ligands, similar 3D patterns (in this case ligand-binding sites) that are effectively similar or identical.

Bottom Line: Nevertheless, many of the protein structures stored in public databases do not provide information about the location and characteristics of ligand binding sites and/or other important 3D patterns such as allosteric sites, enzyme-cofactor interaction motifs, etc.Thus: (a) Geomfinder detected identical pairs of 3D patterns in a series of monoamine oxidase-B structures, which corresponded to the effectively similar ligand binding sites at these proteins; (b) we identified structural similarities among pairs of protein structures which are targets of compounds such as acarbose, benzamidine, adenosine triphosphate and pyridoxal phosphate; these similar 3D patterns are not detected using sequence-based methods; (c) the detailed evaluation of three specific cases showed the versatility of Geomfinder, which was able to discriminate between similar and different 3D patterns related to binding sites of common substrates in a range of diverse proteins.Although the software is not intended for simultaneous multiple comparisons in a large number of proteins, it can be particularly useful in cases such as the structure-based design of multitarget drugs, where a detailed analysis of 3D patterns similarities between a few selected protein targets is essential.

View Article: PubMed Central - PubMed

Affiliation: Escuela de Ingeniería Civil en Bioinformática, Universidad de Talca, Avenida Lircay s/n, Talca, Chile ; Centro de Bioinformática y Simulación Molecular, Universidad de Talca, 2 Norte 685, Talca, Chile.

ABSTRACT

Background: Since the structure of proteins is more conserved than the sequence, the identification of conserved three-dimensional (3D) patterns among a set of proteins, can be important for protein function prediction, protein clustering, drug discovery and the establishment of evolutionary relationships. Thus, several computational applications to identify, describe and compare 3D patterns (or motifs) have been developed. Often, these tools consider a 3D pattern as that described by the residues surrounding co-crystallized/docked ligands available from X-ray crystal structures or homology models. Nevertheless, many of the protein structures stored in public databases do not provide information about the location and characteristics of ligand binding sites and/or other important 3D patterns such as allosteric sites, enzyme-cofactor interaction motifs, etc. This makes necessary the development of new ligand-independent methods to search and compare 3D patterns in all available protein structures.

Results: Here we introduce Geomfinder, an intuitive, flexible, alignment-free and ligand-independent web server for detailed estimation of similarities between all pairs of 3D patterns detected in any two given protein structures. We used around 1100 protein structures to form pairs of proteins which were assessed with Geomfinder. In these analyses each protein was considered in only one pair (e.g. in a subset of 100 different proteins, 50 pairs of proteins can be defined). Thus: (a) Geomfinder detected identical pairs of 3D patterns in a series of monoamine oxidase-B structures, which corresponded to the effectively similar ligand binding sites at these proteins; (b) we identified structural similarities among pairs of protein structures which are targets of compounds such as acarbose, benzamidine, adenosine triphosphate and pyridoxal phosphate; these similar 3D patterns are not detected using sequence-based methods; (c) the detailed evaluation of three specific cases showed the versatility of Geomfinder, which was able to discriminate between similar and different 3D patterns related to binding sites of common substrates in a range of diverse proteins.

Conclusions: Geomfinder allows detecting similar 3D patterns between any two pair of protein structures, regardless of the divergency among their amino acids sequences. Although the software is not intended for simultaneous multiple comparisons in a large number of proteins, it can be particularly useful in cases such as the structure-based design of multitarget drugs, where a detailed analysis of 3D patterns similarities between a few selected protein targets is essential.

No MeSH data available.


Related in: MedlinePlus