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LAP: Liability Antibody Profiler by sequence & structural mapping of natural and therapeutic antibodies.
- Source :
-
PLoS computational biology [PLoS Comput Biol] 2024 Mar 05; Vol. 20 (3), pp. e1011881. Date of Electronic Publication: 2024 Mar 05 (Print Publication: 2024). - Publication Year :
- 2024
-
Abstract
- Antibody-based therapeutics must not undergo chemical modifications that would impair their efficacy or hinder their developability. A commonly used technique to de-risk lead biotherapeutic candidates annotates chemical liability motifs on their sequence. By analyzing sequences from all major sources of data (therapeutics, patents, GenBank, literature, and next-generation sequencing outputs), we find that almost all antibodies contain an average of 3-4 such liability motifs in their paratopes, irrespective of the source dataset. This is in line with the common wisdom that liability motif annotation is over-predictive. Therefore, we have compiled three computational flags to prioritize liability motifs for removal from lead drug candidates: 1. germline, to reflect naturally occurring motifs, 2. therapeutic, reflecting chemical liability motifs found in therapeutic antibodies, and 3. surface, indicative of structural accessibility for chemical modification. We show that these flags annotate approximately 60% of liability motifs as benign, that is, the flagged liabilities have a smaller probability of undergoing degradation as benchmarked on two experimental datasets covering deamidation, isomerization, and oxidation. We combined the liability detection and flags into a tool called Liability Antibody Profiler (LAP), publicly available at lap.naturalantibody.com. We anticipate that LAP will save time and effort in de-risking therapeutic molecules.<br />Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: TS, SW, PD, TG are employees of NaturalAntibody. TK, MO, AK are employees of Pure Biologics. AB is an employee of AstraZeneca. SK is an employee of Moderna, Inc. and may hold stocks/stock options in this and other biopharma companies.<br /> (Copyright: © 2024 Satława et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Subjects :
- Probability
Antibodies therapeutic use
High-Throughput Nucleotide Sequencing
Subjects
Details
- Language :
- English
- ISSN :
- 1553-7358
- Volume :
- 20
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- PLoS computational biology
- Publication Type :
- Academic Journal
- Accession number :
- 38442111
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1011881