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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.


Similar 3D patterns between 4QIP and 3U90. 4QIP and 3U90 proteins are depicted in gray and brown respectively. SDS is shown in yellow and circles indicate the most similar pairs of 3D patterns detected
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Fig10: Similar 3D patterns between 4QIP and 3U90. 4QIP and 3U90 proteins are depicted in gray and brown respectively. SDS is shown in yellow and circles indicate the most similar pairs of 3D patterns detected

Mentions: We compared the structures of the intracellular apoferritin protein from Equus caballus [PDBid: 3U90] (174 residues) with the major birch pollen allergen Bet v1 protein from Betula pendula [PDBid: 4QIP] (159 residues). Both proteins have been co-crystallized with sodium dodecyl sulfate (SDS) and share a 35 % of their amino acids sequences. In our tests, Geomfinder did not find similar 3D patterns corresponding to their SDS binding sites. This result indicates that even though both proteins share a common ligand, the binding sites and the binding mode of SDS at these sites are not similar. Nevertheless, Geomfinder identified some similar 3D patterns in both proteins. Thus, the best GScore (67,7 %) detected patterns defined from the virtual reference Atom1043 (3U90) and Atom2088 (4QIP). Interestingly, the 3D pattern denoted by the virtual reference Atom2088 (4QIP) was located in the SDS binding site whereas the 3D pattern defined by the virtual reference Atom1043 (3U90) was located in an extracellular zone of the protein (Fig. 10). After an evaluation with the software MetaPocket [56], a possible ligand-binding site was identified in the same zone that was defined by the virtual reference Atom1043 in the protein 3U90 (residues ALA14 and ALA15; Additional file 1: Figure S2). This result suggests that these proteins might still share a similar binding site, and could interact with some currently unknown common ligands.


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)

Similar 3D patterns between 4QIP and 3U90. 4QIP and 3U90 proteins are depicted in gray and brown respectively. SDS is shown in yellow and circles indicate the most similar pairs of 3D patterns detected
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig10: Similar 3D patterns between 4QIP and 3U90. 4QIP and 3U90 proteins are depicted in gray and brown respectively. SDS is shown in yellow and circles indicate the most similar pairs of 3D patterns detected
Mentions: We compared the structures of the intracellular apoferritin protein from Equus caballus [PDBid: 3U90] (174 residues) with the major birch pollen allergen Bet v1 protein from Betula pendula [PDBid: 4QIP] (159 residues). Both proteins have been co-crystallized with sodium dodecyl sulfate (SDS) and share a 35 % of their amino acids sequences. In our tests, Geomfinder did not find similar 3D patterns corresponding to their SDS binding sites. This result indicates that even though both proteins share a common ligand, the binding sites and the binding mode of SDS at these sites are not similar. Nevertheless, Geomfinder identified some similar 3D patterns in both proteins. Thus, the best GScore (67,7 %) detected patterns defined from the virtual reference Atom1043 (3U90) and Atom2088 (4QIP). Interestingly, the 3D pattern denoted by the virtual reference Atom2088 (4QIP) was located in the SDS binding site whereas the 3D pattern defined by the virtual reference Atom1043 (3U90) was located in an extracellular zone of the protein (Fig. 10). After an evaluation with the software MetaPocket [56], a possible ligand-binding site was identified in the same zone that was defined by the virtual reference Atom1043 in the protein 3U90 (residues ALA14 and ALA15; Additional file 1: Figure S2). This result suggests that these proteins might still share a similar binding site, and could interact with some currently unknown common ligands.

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.