Statistical algorithms for folding and target accessibility prediction and design of nucleic acids

• US 20040002083A1
• Filed: 01/22/2003
• Published: 01/01/2004
• Est. Priority Date: 01/29/2002
• Status: Abandoned Application

• Current Assignee: Health Research Incorporated
• Original Assignee: Health Research Incorporated
• Inventors: Ding, Ye, Lawrence, Charles E.
• Application Number:
  US10/348,935
• Publication Number:
  US 20040002083A1
• Time in Patent Office: Days
• US Class Current: 435/6
• 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 15/10 Nucleic acid folding
• CPC Class Codes: G16B 15/30 Drug targeting using structural data; Docking or binding prediction

Abstract

A method of predicting structural characteristics of a nucleic acid molecule. A method of predicting single-stranded regions in the secondary structure of a nucleic acid molecule in accordance with a probability distribution of structures based on recursively generated partition functions for the identification of accessible sites on target RNA for gene down-regulation and the rational design of antisense oligos, trans-cleaving ribozymes, siRNAss and antisense RNAs, for interaction with other RNA-targeting molecules, and for rational design of nucleic acid probes such as molecular beacons for RNA or DNA targets.

Claims

1. A method of generating a sample of a predetermined number of probable secondary structures of an RNA sequence, comprising the steps of:

a) generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters; and

b) generating secondary structures based on tracebacks using conditional probabilities computed with the partition function.

2. The method of claim 1, wherein the thermodynamics parameters include a predetermined number of free energies for basic structural elements.

3. The method of claim 1, wherein the thermodynamics parameters include free energies for base pair stacking in a helix.

4. The method of claim 1, wherein the partition function generating step generates partition functions for all fragments of the RNA sequence.

17. A method for transmitting information comprising performing a method as claimed in any one of claims 1-8 and transmitting a result thereof.

18. A method for target prediction or for identification of effective sites on target RNA for gene down-regulation, or for identification of single-stranded regions in the secondary structure of an mRNA or viral RNA, or for screening or designing of antisense oligos or ribozymes, or for performing functional genomics, or for drug target validation, or for development of antisense therapeutics, or for the design of oligonucleotide probes, or for enhancing signals on nucleic acids hybridization arrays, or for producing higher quality array data, comprising performing a method as claimed in any one of claims 1-8.

19. A method for transmitting information for or on target prediction or for or on identification of effective sites on target RNA for gene down-regulation, or for or on identification of single-stranded regions in the secondary structure of an mRNA or viral RNA, or for or on screening or designing of antisense oligos or ribozymes, or for or on performing functional genomics, or for or on drug target validation, or for or on development of antisense therapeutics, or for or on the design of oligonucleotide probes, or for or on enhancing signals on nucleic acids hybridization arrays, or for or on producing higher quality array data, comprising performing a method as claimed in any one of claims 1-8, and transmitting a result thereof.

20. The method of claim 19 wherein the transmitting is via email or the internet.

5. A method of generating a probability profile for predicting an accessible site on a target RNA for interaction with a biomolecule, comprising the steps of:

a) generating a sample of one or more probable secondary structures of an RNA sequence by;

i) generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters, and

ii) generating secondary structures based on tracebacks using conditional probabilities computed with the partition functions;

b) estimating a probability that a segment of one or more bases on the target RNA is single-stranded in accordance with an observed frequency in the sample; and

c) repeating the estimating step for all segments on the target RNA.

6. A method of determining an antisense oligo of a predetermined length for an antisense nucleation site on a target RNA, comprising the steps of:

a) generating a sample of one or more probable secondary structures of an RNA sequence by;

i) generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters, and

ii) generating secondary structures based on tracebacks using conditional probabilities computed with the partition functions;

b) estimating a probability that a segment of one or more bases on the target RNA is single-stranded by using an observed frequency in the sample;

c) repeating the estimating step for all segments on the target RNA;

d) identifying a target segment in accordance with the estimated probabilities;

e) determining a base sequence of the target segment; and

f) determining the antisense oligo in accordance with the base sequence.

7. A method of evaluating an antisense oligo for a target RNA, comprising the steps of:

a) generating a sample of one or more probable secondary structures of an RNA sequence by;

i) generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters, and

ii) generating secondary structures based on tracebacks using conditional probabilities computed with the partition functions;

b) estimating a probability that a segment of one or more bases on the target RNA is single-stranded in accordance with an observed frequency in the sample; and

c) repeating the estimating step for all segments on the target RNA;

d) calculating a sampling-probability-weighted binding energy for measuring a nucleation potential of a hybridization between the antisense oligo and the target RNA; and

e) generating an evaluation indicator for the antisense oligo in accordance with the sampling-probability-weighted binding energy and the estimated probabilities for the target RNA.

8. The method of claim 7, wherein the calculating step includes applying the estimated probabilities as weights in a summation of RNA:

DNA thermodynamic parameters for the hybrid.

9. A computer program embodied on a computer-readable medium for generating a sample of a predetermined number of probable secondary structures of an RNA sequence, comprising:

a) an instruction for generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters; and

b) an instruction for generating secondary structures based on tracebacks using conditional probabilities computed with the partition function.

10. A computer program embodied on a computer-readable medium for generating a probability profile for predicting an accessible site on a target RNA for interaction with a biomolecule, comprising:

a) an instruction for generating a sample of one or more probable secondary structures of an RNA sequence by;

i) generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters, and

ii) generating secondary structures based on tracebacks using conditional probabilities computed with the partition functions;

b) an instruction for estimating a probability that a segment of one or more bases on the target RNA is single-stranded in accordance with an observed frequency in the sample, wherein the estimating instruction is repeated for all segments on the target RNA.

11. A computer program embodied on a computer-readable medium for determining an antisense oligo of a predetermined length for an antisense nucleation site on a target RNA, comprising:

a) an instruction for generating a sample of one or more probable secondary structures of an RNA sequence by;

i) generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters, and

ii) generating secondary structures based on tracebacks using conditional probabilities computed with the partition functions;

b) an instruction for estimating a probability that a segment of one or more bases on the target RNA is single-stranded by using an observed frequency in the sample, said estimating instruction being repeated for all segments on the target RNA;

c) an instruction for identifying a target segment in accordance with the estimated probabilities;

d) an instruction for determining a base sequence of the target segment; and

e) an instruction for determining the antisense oligo in accordance with the base sequence.

12. A computer program embodied on a computer-readable medium for evaluating an antisense oligo for a target RNA, comprising:

a) an instruction for generating a sample of one or more probable secondary structures of an RNA sequence by;

i) generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters, and

ii) generating secondary structures based on tracebacks using conditional probabilities computed with the partition functions;

b) an instruction for estimating a probability that a segment of one or more bases on the target RNA is single-stranded in accordance with an observed frequency in the sample, said estimating instruction being repeated for all bases on the target RNA;

c) an instruction for calculating a sampling-probability-weighted free energy for measuring a nucleation potential of a hybridization between the antisense oligo and the target RNA; and

d) an instruction for generating an evaluation indicator for the antisense oligo in accordance with the sampling-probability-weighted binding energy and the estimated probabilities for the target RNA.

13. A process embodied in an instruction signal of a computing device for generating a sample of a predetermined number of probable secondary structures of an RNA sequence, comprising:

a) an instruction for generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters; and

b) an instruction for generating secondary structures based on tracebacks using conditional probabilities computed with the partition functions.

14. A process embodied in an instruction signal of a computing device for generating a probability profile for predicting an accessible site on a target RNA for interaction with a biomolecule, comprising:

a) an instruction for generating a sample of one or more probable secondary structures of an RNA sequence by;

i) generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters, and

ii) generating secondary structures based on tracebacks using conditional probabilities computed with the partition functions;

b) an instruction for estimating a probability that a segment of one or more bases on the target RNA is single-stranded in accordance with an observed frequency in the sample, wherein the estimating instruction is repeated for all segments on the target RNA.

15. A process embodied in an instruction signal of a computing device for determining an antisense oligo of a predetermined length for an antisense nucleation site on a target RNA, comprising:

a) an instruction for generating a sample of one or more probable secondary structures of an RNA sequence by;

i) generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters, and

ii) generating secondary structures based on tracebacks using conditional probabilities computed with the partition functions;

b) an instruction for estimating a probability that a segment of one or more bases on the target RNA is single-stranded by using an observed frequency in the sample, said estimating instruction being repeated for all segments on the target RNA;

c) an instruction for identifying a target segment in accordance with the estimated probabilities;

d) an instruction for determining a base sequence of the target segment; and

e) an instruction for determining the antisense oligo in accordance with the base sequence.

16. A process embodied in an instruction signal of a computing device for evaluating an antisense oligo for a target RNA, comprising:

a) an instruction for generating a sample of one or more probable secondary structures of an RNA sequence by;

i) generating one or more partition functions of a fragment having one or more bases of the RNA sequence in accordance with a predetermined number of thermodynamics parameters, and

ii) generating secondary structures based on tracebacks using conditional probabilities computed with the partition functions;

b) an instruction for estimating a probability that a segment of one or more bases on the target RNA is single-stranded in accordance with an observed frequency in the sample, said estimating instruction being repeated for all segments on the target RNA;

c) an instruction for calculating a sampling-probability-weighted free energy for measuring a nucleation potential of a hybridization between the antisense oligo and the target RNA; and

d) an instruction for generating an evaluation indicator for the antisense oligo in accordance with the sampling-probability-weighted free energy and the estimated probabilities for the target RNA.