Methods for determining correlated residues in a protein or other biopolymer using molecular dynamics

Patent metadata

Field	Value
Publication number	US-9404928-B2
Application number	US-86643709-A
Country	US
Kind code	B2
Filing date	Feb 5, 2009
Priority date	Feb 5, 2008
Publication date	Aug 2, 2016
Grant date	Aug 2, 2016

Abstract

The invention provides methods and systems of determining biopolymer profiles and correlations between structural units (residues) of a biopolymer based on sampling of the conformational space available to the molecule. The correlations between these structural units can further be used to find networks within a biopolymer such as the coupled residue networks in a protein. The invention also provides for designing and engineering biopolymers including polypeptides, nucleic acids and carbohydrates using the information derived from the conformation clustering and subsequent methods described herein.

First claim

We claim:

1. A method of engineering a polypeptide variant of a polypeptide, wherein the polypeptide comprises a plurality of residues including a first residue and a second residue, the method comprising:
a) performing a simulation to calculate at least one trajectory for a plurality of intra-residue residue metrics using a three-dimensional atomic model of the polypeptide, wherein
a predetermined atom of the first residue and a predetermined atom of the second residue are within a predetermined distance cutoff of each other within the three-dimensional atomic model,
the plurality of intra-residue residue metrics comprises an intra-residue plane or intra-residue dihedral angle metric or an intra-residue distance metric for each respective residue in the plurality of residues, and
the first residue is other than the second residue within the three-dimensional atomic model;

b) determining a first plurality of sub-conformations for the first residue, wherein
each respective sub-conformation in the first plurality of sub-conformations is derived from a conformational frequency for a corresponding cluster of residue conformations for the first residue derived by clustering first conformation information for the first residue in the at least one trajectory calculated by the performing a), wherein the first conformation information comprises all or a subset of the plurality of intra-residue residue metrics for the first residue, wherein the first conformation information consists of conformation information for the first residue in the at least one trajectory calculated by the performing a);

c) determining a second plurality of sub-conformations for the second residue, wherein each respective sub-conformation in the second plurality of sub-conformations is derived from a conformational frequency for a corresponding cluster of residue conformations for the second residue derived by second clustering conformation information for the second residue in the at least one trajectory calculated by the performing a), the second clustering conformation information not including the first clustering conformation information, wherein the second conformation information consists of conformation information for the second residue in the at least one trajectory calculated by the performing a);
d) correlating a first residue sub-conformation in the first plurality of sub-conformations with a second sub-conformation in the second plurality of sub-conformations by confirming that the normalized conditional probability:

P
⁡

(

A
,
B

)

P
⁡

(
A
)

⁢

P
⁡

(
B
)

 deviates from unity, wherein P(A) is a probability of occurrence of the first sub-conformation in the at least one trajectory calculated by the performing a), P(B) is a probability of occurrence of the second sub-conformation in the at least one trajectory calculated by the performing a), and P(A,B) is the joint probability of occurrence of the first sub-conformation and the second sub-conformation in the at least one trajectory calculated by the performing a), thereby determining a correlation between the first residue and the second residue, wherein the performing a), determining b), determining c) and the correlating d) are performed using one or more suitably programmed computers;
e) determining correlated first and second residues of the polypeptide by repeating the determining b), determining c) and correlating d) a plurality of times for different first and second residues of the polypeptide to obtain a plurality of correlated first and second residues of the polypeptide;
f) obtaining a reduced set of correlated first and second residues of the polypeptide by applying a cutoff based on a histogram distribution of the normalized conditional probability of each correlated first and second residues of the plurality of correlated first and second residues of the polypeptide thereby excluding first and second residues with lower normalized conditional probabilities from the reduced set of correlated first and second residues;
g) choosing a correlated first and second residue of the polypeptide in the reduced set of correlated first and second residues of the polypeptide; and
h) making the polypeptide variant comprising the sequence of the polypeptide in which either the chosen correlated first residue of step g), the chosen correlated second residue of step g) or both the chosen correlated first residue and second residue of step g) are mutated, thereby engineering the polypeptide variant.

2. The method of claim 1 wherein the first residue sub-conformation is an off-rotamer conformation of the first residue.

3. The method of claim 1 wherein the first residue sub-conformation is an off-rotamer conformation of the first residue and the second residue sub-conformation is either an off-rotamer conformation or a rotamer conformation of the second residue.

4. The method of claim 1 wherein the plurality of intra-residue residue metrics further comprises a residue metric selected from the group consisting of a position vector and a distance metric.

5. The method of claim 1 wherein the plurality of intra-residue residue metrics comprises the plane angle metric, and wherein the plane angle metric is calculated using a first and a second plane of a residue, the first plane defined by a first set of atoms comprising a backbone atom of the residue and the second plane defined by a second set of atoms comprising an atom selected from the group consisting of a backbone atom and a terminal atom of the residue.

6. The method of claim 5 wherein the first set of atoms consists of a set of three atoms and is selected from the group consisting of (C α , C o , N) and (C α , C o , O).

7. The method of claim 1 wherein the clustering of the determining b) and the clustering of the determining c) is performed using a multidimensional clustering method.

8. The method of claim 1 wherein the polypeptide is selected from the group consisting of a structural protein, an antibody, an enzyme and a signaling protein.

9. The method of claim 1 wherein the polypeptide variant has an altered property compared to the polypeptide, wherein the property is selected from the group consisting of enantioselectivity, substrate specificity, enzyme activity, thermal stability, pH stability, enzyme mechanism and product profile.

10. The method of claim 1 wherein the simulation is performed using a Monte Carlo sampling technique or using data from an experimental method.

11. The method of claim 1 wherein the simulation is performed using data from NMR spectroscopy or X-ray crystallography.

12. A method of engineering a nucleic acid encoding a polypeptide variant of a polypeptide, wherein the polypeptide comprises a plurality of residues including a first residue and a second residue, the method comprising:
a) performing a simulation to calculate at least one trajectory for a plurality of intra-residue residue met

Assignees

• Lario Paula I
• Mullegger Johannes
• Baribeau Anne-Marie
• Dixit Surjit B
• Rodinger Tomas
• Tan Powell Patrick Cheng
• Zymeworks Inc

Inventors

• Lario Paula I
• Mullegger Johannes
• Dixit Surjit B
• Rodinger Tomas
• Tan Powell Patrick Cheng

Classifications

• G16B5/00

  ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks · CPC title

• G16B45/00

  ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks · CPC title

• G01N33/68 Primary

  involving proteins, peptides or amino acids {(involving lipoproteins G01N33/92)} · CPC title

• G16B15/00

  ICT specially adapted for analysing two-dimensional [2D] or three-dimensional [3D] molecular structures, e.g. structural or functional relations or structure alignment · CPC title

• G16B20/00

  ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations · CPC title