PROCESS FOR IDENTIFYING SIMILAR 3D SUBSTRUCTURES ONTO 3D ATOMIC STRUCTURES AND ITS APPLICATIONS

• US 20100268476A1
• Filed: 04/01/2010
• Published: 10/21/2010
• Est. Priority Date: 06/06/2002
• Status: Abandoned Application

• Current Assignee: Centre National De La Recherche Scientifique, Université Claude Bernard Lyon 1
• Original Assignee: Centre National De La Recherche Scientifique, Université Claude Bernard Lyon 1
• Inventors: Geourjon, Christophe, Jambon, Martin, Deleage, Gilbert
• Application Number:
  US12/752,458
• Publication Number:
  US 20100268476A1
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: G16B 15/00 ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
• CPC Class Codes: G16B 15/30 Drug targeting using structural data; Docking or binding prediction
• CPC Class Codes: G16C 20/40 Searching chemical structures or physicochemical data
• CPC Class Codes: G16C 20/70 Machine learning, data mining or chemometrics

Abstract

Our disclosure pertains to the field of structural biology and relates to a process to compare various three-dimensional (3D) structures and to identify functional similarities among them. Our process of comparison of 3D atomic structures is based on the comparisons of defined chemical groups onto the 3D atomic structures and allows the detection of local similarities even when neither the fold nor sequence for example aminoacid sequences for polypeptides sequences or nucleotide sequences for nucleic acid sequences are conserved. This process requires the attribution of selected physico-chemical parameters to each atom of a 3D atomic structure, then the representation of each 3D atomic structure by a graph of chemical groups.

Claims

1. A computer-implemented process for identifying and displaying 3D atomic substructures on a 3D atomic structure of a first macromolecule having a plurality of individual atoms comprising:

a) providing a programmed computer which performs steps (b)-(j) using a microprocessor and a computer visual display;

b) attributing to each individual atom of a 3D atomic structure of a macromolecule a structural parameter combining atomic local density D, local center of mass C and orientation in relation to position P;

c) constructing chemical groups by setting individual atoms of a macromolecule having similar structural parameters;

d) constructing clusters of at least three chemical groups of a macromolecule by setting the chemical groups whose reciprocal distances are constrained;

e) constructing an input graph of the clusters constructed in step (d);

f) for a set of individual macromolecules, storing the constructed clusters and the corresponding input graphs in a reference computer database;

g) using the programmed computer to compare clusters constructed in step (d) and the input graph constructed in step (e) for a first macromolecule, to the clusters constructed in step (d) and the input graph constructed in step (e) for the set of individual macromolecules stored in the reference computer database constructed in step (f);

h) identifying a similar 3D atomic substructure on the first macromolecule with the programmed computer by recognizing the clusters of the first macromolecule sharing similar 3D atomic substructures with the clusters of the individual macromolecules in the set stored in the reference computer database;

i) determining with the programmed computer a functional 3D atomic substructure on the first macromolecule by correlating the similar 3D atomic substructure on the first macromolecule with a known biochemical activity of a similar 3D atomic substructure in an individual macromolecule of the set stored in the reference computer database; and

j) displaying a visual representation of the determined functional 3D atomic substructure on the first macromolecule on the computer visual display;

whereby a 3D atomic substructure on a 3D atomic structure of a first macromolecule having a plurality of individual atoms is identified and displayed.

2. The process according to claim 1, wherein the atomic local density D is calculated for each atom A relative to position P defined by coordinates (x_p, y_p, z_p) as a function of density m, modulated by a weight function w, according to:

3. The process according to claim 2, wherein the weight function w is a spherical function

4. The process according to claim 1, wherein a local center of mass C(P) for a given atom A occupying a position P is calculated as a point with cartesian coordinates (x_C, y_C, z_C) matching the following:

5. The process according to claim 4, wherein the weight function w is a spherical function:

6. The process according to claim 1, wherein in step (b), the orientation of each atom A occupying a position P and having a local center of mass C(P) is calculated by a density gradient represented by a vector {right arrow over (CP)}.

7. The process according to claim 1, wherein the reciprocal distances between the chemical groups in step (d) are 2 to 20 Å

.

8. The process according to claim 1, wherein constructing clusters in step (d) comprises orienting of the clusters against the 3D atomic structure.

9. The process according to claim 8, wherein the orientation of the constructed cluster against the 3D atomic structure is operated by a scalar triple product of three vectors {right arrow over (CP₁)}, {right arrow over (CP₂)}, {right arrow over (CP₃)}, wherein C is the center of the local centers of mass of each chemical group and P_i, P_j, P_k are three distinct points in the cluster.

10. The process according to claim 1, wherein the comparison of a given pair of clusters in step (g) comprises the identification of at least one structural similarity selected from the group consisting of:

same chemical groups and similar orientation,

similar length of reciprocal distances between chemical groups,

similar local density of the chemical groups,

similar orientation of the constructed clusters, and

capability of binding flexible ligands using the same kind of weak chemical bonds.

11. The process according to claim 10, wherein after the identification of at least two structural similarities, a global score is calculated as a function of combining several parameters indicating the similarity of the clusters, the parameters being selected from the group consisting of:

volume of chemical groups,

scarcity of the chemical groups,

quality of the superposition with respect to the standard deviation,

quality of the superposition with respect to the orientation of the chemical groups, and

similarity of the atomic environment.

12. The process according to claim 11, applied to the capability of binding flexible ligands using the same kind of weak chemical bonds.

13. The process according to claim 12, wherein the capability may be estimated by analysis of the deviation of short range distances between chemical groups.

14. The process according to claim 11, wherein the similarity between atomic environment comprises calculation of a score by comparing the volumes of atoms around each converted pair of chemical groups.

15. The process according to claim 14, wherein the score is calculated by the function:

16. The process according to claim 1, wherein before step (d) a further step (k) comprising the restriction of the constructed chemical groups is performed by the selection of chemical groups at locations where the local atomic density is below a definite threshold.

17. The process according to claim 1, wherein before step (d), a further step (l) comprising the restriction of the constructed chemical groups is performed with at least one step of:

the automatic selection of the most exposed chemical groups using a local density function and a selected threshold,

the semi-automatic selection of chemical groups that are interacting with a given set of chemical groups, and

the manual selection of subsets of chemical groups.

18. The process according to claim 1, further comprising a refinement step comprising:

i) converting the pairs of clusters identified in step (h) comprising clusters of the first macromolecule sharing similar 3D substructures and the clusters of the individual macromolecules to converted pairs of chemical groups, and

ii) minimizing the reciprocal distances between the converted pairs of chemical groups with a distance function.

19. The process according to claim 18, wherein steps (i) and (ii) are iteratively repeated using variable selection thresholds.

20. The process according to claim 18, wherein the reciprocal distances between converted pairs of chemical groups are calculated by the function:

dist(g₁,g₂)=α

·

∥

pos(g₁)−

pos(g₂)∥

+β

·

|D(g₁)−

D(g₂)|+γ

·

orient(g₁,g₂)

wherein pos(g) is the position of chemical group g after optimal superimposition of a given set of converted pairs, D(g) local density, orient(g₁,g₂) is the difference in orientation between chemical groups g₁ and g₂ after optimal superimposition, and α

, β and

γ

are normalizing coefficients calculated such that the average value of each term is ⅓

, on the basis of a statistical set of pairs of similar chemical groups.

21. The process according to claim 1, further comprising a step (m) of clustering pairs of clusters identified in step (h) comprising clusters of the first macromolecule sharing similar 3D substructures and the clusters of the individual macromolecules into a larger pair of clusters sharing similar 3D structures.

22. The process according to claim 1, wherein the macromolecule is a covalent or weak assembly of at least one molecule selected from the group consisting of natural and artificial proteins, oligopeptides, polypeptides, nucleic acids, natural and artificial oligonucleotides, natural and artificial oligosaccharides and polysaccharides, glycoproteins, lipoproteins, lipids, ions, water, natural and synthetic polymers, non-polymeric structures, and natural and artificial inorganic molecules.

23. The process according to claim 1, wherein the macromolecules are restricted to the 3D atomic substructure of a functional site.

24. The process according to claim 23, wherein the functional site is selected from the group consisting of enzymatic active sites, sites of reversible or irreversible binding of specific classes of molecules, sites sensitive to physico-chemical changes in the environment, chemical groups involved in energy conversion, self modification locations, antigenic parts of a molecule, mimetic sites, consensus sites, highly variable sites, sites necessary for initiating or interrupting a biological pathway, sites with particular physico-chemical properties, sites with particular chemical composition, a site marking a protein taxon, immunoglobulin domains, DNA consensus sequences, gene expression signals, promoter elements, RNA processing signals, translational initiation sites, recognition motifs of a large variety of sequence-specific DNA-binding proteins, protein and nucleic acid compositional domains, glutamine-rich activation domains, CpG island, interaction site between a protein and a ligand, and functional sugar binding site.

25. The process according to claim 1, wherein the 3D atomic structures are 3D structural sites obtained from combinatorial, or conventional screening.

26. The process according to claim 1, further comprising (m) the calculation of the average orientations of two 3D atomic substructures identified as A and B with respect to the orientation of their individual atoms and displaying a visual representation of the 3D atomic substructures of A and B, wherein the visual representation is by graphic projections matching the following conditions:

a) the average orientation of the 3D atomic substructure identified as A is orthogonal to the projection plane; and

b) the 3D atomic substructure identified as B is optimally superimposed on the 3D atomic substructure identified as A.

27. A computer-implemented method for identifying and displaying 3D atomic substructures on a 3D atomic structure of a first macromolecule having a plurality of individual atoms comprising:

a) providing a first programmed computing device which performs steps (b)-(f) and (i)-(l) using a microprocessor connected to a computer visual display device, a second programmed computing device which performs step (g) using a microprocessor and comprises a reference database, and a connection for communication between the first computing device and the second computing device;

b) attributing on the first computing device to each individual atom of a 3D atomic structure of a macromolecule a structural parameter combining atomic local density D, local center of mass C and orientation in relation to position P;

c) constructing on the first computing device chemical groups by setting individual atoms of a macromolecule having similar structural parameters;

d) constructing on the first computing device clusters of at least three chemical groups of a macromolecule by setting the chemical groups whose reciprocal distances are constrained;

e) constructing on the first computing device an input graph of the clusters constructed in step (d);

f) sending via the connection the constructed clusters and the corresponding input graphs for a set of individual macromolecules from the first computing device to the second computing device;

g) storing the constructed clusters and the corresponding input graphs in the reference computer database of the second computing device;

h) delivering to the first computing device the constructed clusters and the corresponding input graphs from the reference computer database of the second computing device via the connection;

i) comparing on the first computing device the clusters constructed in step (d) and the input graph constructed in step (e) for a first macromolecule, to the clusters constructed in step (d) and the input graph constructed in step (e) for the set of individual macromolecules stored in the reference computer database constructed of the second computing device in step (g);

j) identifying on the first computing device a similar 3D atomic substructure on the first macromolecule by recognizing the clusters of the first macromolecule sharing similar 3D atomic substructures with the clusters of the individual macromolecules in the set retrieved from the reference computer database of the second computing device;

k) determining on the first computing device a functional 3D atomic substructure on the first macromolecule by correlating the similar 3D atomic substructure on the first macromolecule with a known biochemical activity of a similar 3D atomic substructure in an individual macromolecule of the set stored in the reference computer database on the second computing device; and

l) displaying on the computer visual display device of the first computing device a visual representation of the determined functional 3D atomic substructure on the first macromolecule;

whereby a 3D atomic substructure on a 3D atomic structure of a first macromolecule having a plurality of individual atoms is identified and displayed.

28. A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, said computer readable program code adapted to be executed to implement a method for generating a report or visual display, said method comprising:

a) providing a system, wherein the system comprises distinct software modules and a computer visual display device, and wherein the distinct software modules comprise a construction module, a graphing module, a storage module, a comparison module, an identification module, a determination module and a data display module;

b) attributing to each individual atom of a 3D atomic structure of a macromolecule a structural parameter combining atomic local density D, local center of mass C and orientation in relation to position P with the construction module;

c) constructing chemical groups by setting individual atoms of a macromolecule having similar structural parameters with the construction module;

d) constructing clusters of at least three chemical groups of a macromolecule by setting the chemical groups whose reciprocal distances are constrained with the construction module;

e) constructing an input graph of the clusters constructed in step (d) with the graphing module;

f) storing the constructed clusters and the corresponding input graphs for a set of individual macromolecules with the storage module;

g) comparing with the comparison module the clusters constructed in step (d) and the input graph constructed in step (e) for a first macromolecule, to the clusters constructed in step (d) and the input graph constructed in step (e) for the set of individual macromolecules stored by the storage module in step (f);

h) identifying with the identification module a similar 3D atomic substructure on the first macromolecule by recognizing the clusters of the first macromolecule sharing similar 3D atomic substructures with the clusters of the individual macromolecules stored by the storage module in step (f);

i) determining with the determination module a functional 3D atomic substructure on the first macromolecule by correlating the similar 3D atomic substructure on the first macromolecule with a known biochemical activity of a similar 3D atomic substructure in an individual macromolecule of the set stored by the storage module in step (f); and

j) displaying on the computer visual display device a report or visual representation of the determined functional 3D atomic substructure on the first macromolecule with the display module.

29. A computer-implemented process for identifying and displaying 3D atomic substructures on a 3D atomic structure of a first macromolecule having a plurality of individual atoms comprising:

a) providing a programmed computer which performs steps (c)-(j) using a microprocessor that executes multiple arithmetic operations to evaluate complex mathematical expressions during a comparison of 3D macromolecular substructures;

b) providing a computer visual display to optionally visualize any detected correlation of similar 3D atomic substructures;

c) attributing to each individual atom of a 3D atomic structure of a macromolecule a structural parameter combining atomic local density D, local center of mass C and orientation in relation to position P;

d) constructing chemical groups by setting individual atoms of a macromolecule having similar structural parameters;

e) constructing clusters of at least three chemical groups of a macromolecule by setting the chemical groups whose reciprocal distances are constrained;

f) constructing an input graph of the clusters constructed in step (e);

g) for a set of individual macromolecules, storing the constructed clusters and the corresponding input graphs of the set in a reference computer database to organize information in a suitable form for deleting records, adding new entries or searching for a specific input graph;

h) using the programmed computer to compare the clusters constructed in step (e) and the input graph constructed in step (f) for a first macromolecule, to the clusters constructed in step (e) and the input graph constructed in step (f) for the set of individual macromolecules stored in the reference computer database constructed in step (g);

i) identifying a similar 3D atomic substructure on the first macromolecule with the programmed computer by recognizing the clusters of the first macromolecule sharing similar 3D atomic substructures with the clusters of the individual macromolecules in the set stored in the reference computer database;

j) determining with the programmed computer a functional 3D atomic substructure on the first macromolecule by correlating the similar 3D atomic substructure on the first macromolecule with a known biochemical activity of a similar 3D atomic substructure in an individual macromolecule of the set stored in the reference computer database; and

k) displaying a visual representation of the determined functional 3D atomic substructure on the first macromolecule on the computer visual display;

whereby a 3D atomic substructure on a 3D atomic structure of a first macromolecule having a plurality of individual atoms is identified and displayed.

30. A computer-implemented method for identifying and displaying 3D atomic substructures on a 3D atomic structure of a first macromolecule having a plurality of individual atoms comprising:

a) providing a first programmed computing device which performs steps (c)-(g) and (i)-(m) using a microprocessor that evaluates at least a million individual arithmetic operations per second and evaluates every mathematical expression resulting from a detection of correlation between 3D macromolecular atomic substructure;

b) providing a second programmed computing device which performs steps (h)-(i) using a microprocessor connected to a computer visual display device to optionally visualize a two-dimensional plot of any detected correlation between 3D macromolecular atomic substructures;

said second computing device comprising a reference database and a data connection for communication between the first computing device and the second computing device;

c) attributing on the first computing device to each individual atom of a 3D atomic structure of a macromolecule a structural parameter combining atomic local density D, local center of mass C and orientation in relation to position P;

d) constructing on the first computing device chemical groups by setting individual atoms of a macromolecule having similar structural parameters;

e) constructing on the first computing device clusters of at least three chemical groups of a macromolecule by setting the chemical groups whose reciprocal distances are constrained;

f) constructing on the first computing device an input graph of the clusters constructed in step (e);

g) sending via the connection the constructed clusters and the corresponding input graphs for a set of individual macromolecules from the first computing device to the second computing device;

h) storing the constructed clusters and the corresponding input graphs in the reference computer database of the second computing device;

i) delivering to the first computing device the constructed clusters and the corresponding input graphs from the reference computer database of the second computing device via the connection;

j) comparing on the first computing device the clusters constructed in step (d) and the input graph constructed in step (f) for a first macromolecule, to the clusters constructed in step (c) and the input graph constructed in step (f) for the set of individual macromolecules stored in the reference computer database constructed of the second computing device in step (h);

k) identifying on the first computing device a similar 3D atomic substructure on the first macromolecule by recognizing the clusters of the first macromolecule sharing similar 3D atomic substructures with the clusters of the individual macromolecules in the set retrieved from the reference computer database of the second computing device;

l) determining on the first computing device a functional 3D atomic substructure on the first macromolecule by correlating the similar 3D atomic substructure on the first macromolecule with a known biochemical activity of a similar 3D atomic substructure in an individual macromolecule of the set stored in the reference computer database on the second computing device; and

m) displaying on the computer visual display device of the first computing device a visual representation of the determined functional 3D atomic substructure on the first macromolecule;

whereby a 3D atomic substructure on a 3D atomic structure of a first macromolecule having a plurality of individual atoms is identified and displayed.