IP Library Patent Application 17811091
Patent Application
App. No. 17/811,091

SYSTEM AND METHOD OF ANTIBODY/ MACROMOLECULE DRUG AFFINITY MODIFICATION

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Patent No.
US None
App. No.
17/811,091
Abstract

The present invention provides an affinity modification system of antibody/macromolecular drug, wherein the affinity modification system comprises: an interaction module, set to: input template sequence information of antibody/macromolecular drugs, modification requirements of single/multi-targets of antibody/macromolecular drugs and optional user-defined screening requirements to generate interaction antibody/macromolecular drug sequence information; affinity modification module, set to: according to the interaction antibody/macromolecular drug sequence information, perform corresponding partial or exhaustive numeration of possible sequence in a part of the full variable range to obtain a mutation library, and perform sequence-based affinity prediction on the mutation library based on a deep learning model, so as to obtain the sequence information of the modified antibody/macromolecular drug; an output module, designed to: according to the sequence information of the modified antibody/macromolecular drug, output the sequence information of the candidate antibody/macromolecular drug. The invention also provides a corresponding affinity modification method.

Claims (22)

1 . An affinity modification system of antibody/macromolecular drug, wherein the affinity modification system comprises:

an interaction module, the interaction module is set to: input template sequence information of antibody/macromolecular drugs, modification requirements of single/multi-targets of antibody/macromolecular drugs and optional user-defined screening requirements to generate interaction antibody/macromolecular drug sequence information;

an affinity modification module, the affinity modification module is set to: according to the interaction antibody/macromolecular drug sequence information, perform corresponding partial or exhaustive numeration of possible sequence in a part of the full variable range to obtain a mutation library, and perform sequence-based affinity prediction on the mutation library based on a deep learning model, so as to obtain the sequence information of the modified antibody/macromolecular drug; and

an output module, the output module is designed to: according to the sequence information of the modified antibody/macromolecular drug, output the sequence information of the candidate antibody/macromolecular drug.

2 . The affinity modification system of antibody/macromolecular drug according to claim 1 , wherein,

in the affinity design module, a single quantity level of the mutation library is not less than 10 10 .

3 . The affinity modification system of antibody/macromolecular drug according to claim 1 , wherein,

in the affinity design module, the variable range includes one or more variable regions, variable spaces, variable number of sites, or combinations thereof.

4 . The affinity modification system of antibody/macromolecular drug according to claim 1 , wherein,

in the interaction module, the template sequence information of the antibody/macromolecular drug includes at least one element of a set comprising an antigen/antibody template sequence, a protein/protein template sequence, and a protein/polypeptide template sequence of the antibody/macromolecular drug.

5 . The affinity modification system of antibody/macromolecular drug according to claim 1 , wherein,

in the interaction module, in the modification requirements of single/multiple targets of the antibody/macromolecular drug, further comprising:

at least one element of a set comprising marking the variable range and specifying the variable range; and

defining a modification direction.

6 . The affinity modification system of antibody/macromolecular drug according to any one of claim 1 - 5 , wherein, the output module further comprises a visual analysis display module.

7 . The affinity modification system of antibody/macromolecular drug according to claim 6 , wherein, the visual analysis display module provides the complete sequence information of the sequence information of the candidate antibody/macromolecular drug.

8 . The affinity modification system of antibody/macromolecular drug according to claim 7 , wherein, the visual analysis display module further comprises a comparative analysis of the template sequence information of the antibody/macromolecular drug and the sequence information of the candidate antibody/macromolecular drug in a variable range.

9 . An affinity modification method of antibody/macromolecular drug, wherein the method comprises:

an input template sequence information of antibody/macromolecular drugs, modification requirements of single/multi-targets of antibody/macromolecular drugs, and optional user-defined screening requirements to generate interaction antibody/macromolecular drug sequence information;

according to the interaction antibody/macromolecular drug sequence information, perform partial or exhaustive numeration of possible sequence in a part of the full variable range to obtain a mutation library, and perform a sequence-based affinity prediction on the mutation library based on a deep learning model, so as to obtain the sequence information of the modified antibody/macromolecular drug; and

according to the sequence information of the modified antibody/macromolecular drug, output the sequence information of the candidate antibody/macromolecular drug.

10 . The affinity modification method according to claim 9 , wherein, when performing the partial or exhaustive numeration of possible sequence in a part of the full, a single quantity level of the mutation library is not less than 10 10 .

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 8, 2024
From: PAN, LURONG
To: AINNOCENCE LLC
Reel/Frame 068838/0810 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 3, 2023
From: AINNOCENCE INC.
To: PAN, LURONG, DR.
Reel/Frame 065741/0445 →
NUNC PRO TUNC ASSIGNMENT Recorded Nov 14, 2023
From: AINNOCENCE INC.
To: PAN, LURONG, DR.
Reel/Frame 065549/0701 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 11, 2022
From: KANG, YUE; PAN, LURONG
To: AINNOCENCE TECHNOLOGIES LLC
Reel/Frame 060468/0016 →