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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 ACR binding proteins. The red bars represent the highest value of a GScore between each pair of 3D patterns related with ACR binding sites. 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
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Fig5: Similarity of the sequence and the 3D patterns in the ACR binding proteins. The red bars represent the highest value of a GScore between each pair of 3D patterns related with ACR binding sites. 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

Mentions: ACR is an anti-diabetic drug used to treat type 2 diabetes mellitus [50]. Its structure corresponds to an oligosaccharide of 5 cyclic units and has been co-crystallized in more than 20 diverse proteins such as glucoamylase II, GacH receptor, glucodextranase, glycoside hydrolase, amylomaltase, among others. Recently ACR has been mentioned as one of the most promiscuous drugs available in the market, and its protein-drug interaction analysis has shown the occurrence of six distinct conformers, which is reflected in 5 clusters of different structural conformations. At the sequence level, more diversity is found and 12 clusters were described [37]. Despite this heterogeneity, Geomfinder was able to detect GScore values higher than 50 % when comparing 3D patterns contained within ACR binding sites in 11 of 13 pairs of proteins evaluated. This finding suggest that the promiscuity of ACR is associated with the existence of similar 3D patterns occurring at the binding sites of the different proteins targeted by the drug. This is in agreement with literature evidence showing that binding site similarity is a crucial feature underlying drug promiscuity [37]. Remarkably, using the same threshold value (50 %), CLICK and PocketMatch software identified structural similarities in 6 and 3 of the 13 pairs compared, respectively (Fig. 5). Furthermore we used the tools ProBIS [25], MultiBind [51] and SiteEngine [52] to evaluate the two pairs of proteins which did not show similar 3D patterns related with the ACR binding site using Geomfinder (PDBid 1AGM versus 3AIC and 1ULV versus 3WEM). As shown in the Table 1, the ACR binding sites of these proteins have different amino acids composition, 3D orientations and physico-chemical properties, confirming the estimations of Geomfinder.


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 ACR binding proteins. The red bars represent the highest value of a GScore between each pair of 3D patterns related with ACR binding sites. 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
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig5: Similarity of the sequence and the 3D patterns in the ACR binding proteins. The red bars represent the highest value of a GScore between each pair of 3D patterns related with ACR binding sites. 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
Mentions: ACR is an anti-diabetic drug used to treat type 2 diabetes mellitus [50]. Its structure corresponds to an oligosaccharide of 5 cyclic units and has been co-crystallized in more than 20 diverse proteins such as glucoamylase II, GacH receptor, glucodextranase, glycoside hydrolase, amylomaltase, among others. Recently ACR has been mentioned as one of the most promiscuous drugs available in the market, and its protein-drug interaction analysis has shown the occurrence of six distinct conformers, which is reflected in 5 clusters of different structural conformations. At the sequence level, more diversity is found and 12 clusters were described [37]. Despite this heterogeneity, Geomfinder was able to detect GScore values higher than 50 % when comparing 3D patterns contained within ACR binding sites in 11 of 13 pairs of proteins evaluated. This finding suggest that the promiscuity of ACR is associated with the existence of similar 3D patterns occurring at the binding sites of the different proteins targeted by the drug. This is in agreement with literature evidence showing that binding site similarity is a crucial feature underlying drug promiscuity [37]. Remarkably, using the same threshold value (50 %), CLICK and PocketMatch software identified structural similarities in 6 and 3 of the 13 pairs compared, respectively (Fig. 5). Furthermore we used the tools ProBIS [25], MultiBind [51] and SiteEngine [52] to evaluate the two pairs of proteins which did not show similar 3D patterns related with the ACR binding site using Geomfinder (PDBid 1AGM versus 3AIC and 1ULV versus 3WEM). As shown in the Table 1, the ACR binding sites of these proteins have different amino acids composition, 3D orientations and physico-chemical properties, confirming the estimations of Geomfinder.

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