Method for designing compounds and compositions useful for targeting high stoichiometric complexes to treat conditions, including treatment of viruses, bacteria, and cancers having acquired drug resistance

Patent metadata

Field	Value
Publication number	US-10975412-B2
Application number	US-201615572038-A
Country	US
Kind code	B2
Filing date	May 6, 2016
Priority date	May 7, 2015
Publication date	Apr 13, 2021
Grant date	Apr 13, 2021

Abstract

A method is described for the identification of multi-subunit biocomplex drug targets. The method includes identifying a target that performs a biological function, wherein the target comprises one or more subunits, wherein a minimum number of the one or more subunits is inactivated to inhibit the biological function. The method includes selecting a drug that binds specifically to each subunit of the one or more subunits with a target probability. The method describes a relationship between inhibition efficiency of the drug and total number of the one or more subunits using a binomial distribution, wherein the inhibition efficiency comprises a probability that the delivered drug blocks the biological function. The method includes confirming empirically the relationship using an experimental target. The method includes administering the drug to the target to treat a multi-drug resistant disease, wherein the target comprises a biological complex in a mammalian subject.

First claim

What is claimed is:

1. A method for the identification of multi-subunit biocomplex drug targets, the method comprising,
identifying a target that performs a biological function, wherein the target comprises one or more subunits, wherein a minimum number (K) of the one or more subunits is inactivated (M) to inhibit the biological function;
selecting a drug that binds specifically to each subunit of the one or more subunits with a target probability (p), wherein the target probability comprises a common probability for each subunit that the drug delivered to the target inactivates the subunit;
describing a relationship between inhibition efficiency of the drug and total number (Z) of the one or more subunits using a binomial distribution, wherein the inhibition efficiency comprises a probability that the delivered drug blocks the biological function, wherein the inhibition efficiency is computed with respect to the minimum number and the total number;
confirming empirically the relationship using an experimental target, wherein the target includes the experimental target;
administering the drug to the target to treat a multi-drug resistant disease, wherein the target comprises a biological complex in a mammalian subject.

2. The method of claim 1 , wherein variable N represents an active subunit of the one or more subunits, wherein Z=M+N.

3. The method of claim 1 , wherein q=1−p.

4. The method of claim 3 , wherein a probability that the target includes M inactivated subunits and N active units is given by the binomial expression

(

Z
!

)

(

N
!

)

⁢

(

M
!

)

⁢

p
M

⁢

q
N

.

5. The method of claim 4 , wherein the inhibition efficiency is given by the binomial equation

∑

M
=
1

Z

⁢

⁢

(

Z
!

M
!

⁢

(

Z
-
M

)

!

)

⁢

p
M

⁢

q

Z
-
M

.

6. The method of claim 5 , wherein K=1 and Z>1.

7. The method of claim 6 , wherein the inhibition efficiency is given by 1−q z .

8. The method of claim 1 , wherein the experimental target comprises a component or subunit of a multimeric biocomplex or a biological nanomotor.

9. The method of claim 8 , wherein the nanomotor comprises a linear motor, a rotation motor, or a revolution motor.

10. The method of claim 8 , wherein the nanomotor comprises an ATPase component.

11. The method of claim 8 , wherein the multimeric biocomplex comprises a receptor, a channel, an enzyme, or a transporter.

12. The method of claim 8 , wherein the multimeric biocomplex comprises a homomeric biocomplex.

13. The method of claim 8 , wherein the multimeric biocomplex comprises a dimer, a hetero-oligomer, or a homo-oligomer.

14. The method of claim 8 , wherein the number of components or subunits is at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12.

15. The method of claim 8 , wherein the nanomotor is a bacteriophage Phi29 DNA packaging motor.

16. The method of claim 15 , wherein the bacteriophage Phi29 DNA packaging motor comprises a genomic dsDNA component, a packaging RNA component, an ATPase gp16 component, an ATP component, or a combination thereof.

17. The method of claim 16 , wherein each Phi29 DNA packaging motor component comprises the experimental target.

18. The method of claim 15 , wherein the bacteriophage Phi29 DNA packaging motor comprises 1 copy of genomic dsDNA, and wherein the copy comprises a subunit.

19. The method of claim 15 , wherein the bacteriophage Phi29 DNA packaging motor comprises 6 copies of packaging RNA, and wherein the copies comprise subunits.

20. The method of claim 15 , wherein the bacteriophage Phi29 DNA packaging motor comprises 6 copies of gp16, and wherein the copies comprise subunits.

21. The method of claim 15 , wherein the bacteriophage Phi29 DNA packaging motor comprises 10,000 copies of ATP, and wherein the copies comprise subunits.

22. The method of claim 1 , wherein the multi-drug resistant disease is caused by a multidrug-resistant organism.

23. The method of claim 22 , wherein the multidrug-resistant organism is a bacterium, a fungus, a virus, or a parasite.

24. A method for increasing inhibition efficiency of a multimeric biocomplex, the method comprising,
identifying a target that performs a biological function, wherein the target comprises one or more subunits, wherein a minimum number of the one or more subunits is inactivated to inhibit the biological function;
selecting a drug that binds specifically to each subunit of the one or more subunits with a target probability, wherein the target probability comprises a common probability for each subunit that the drug delivered to the target inactivates the subunit;
describing a relationship between inhibition efficiency of the drug and total number of t

Assignees

• Univ Kentucky Res Found

Inventors

• Guo Peixuan
• Shu Dan

Classifications

• G16B15/30

  Drug targeting using structural data; Docking or binding prediction · CPC title

• G01N2333/195

  from bacteria · CPC title

• G01N2333/005

  from viruses · CPC title

• G16C20/20

  Identification of molecular entities, parts thereof or of chemical compositions · CPC title

• G01N2500/00

  Screening for compounds of potential therapeutic value · CPC title