Evidence map›Paper›PMID 36346603›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Optimizing Antibody-Antigen Binding Affinities with the ADAPT Platform.

Traian Sulea, Christophe Deprez, Christopher R Corbeil, Enrico O Purisima

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Comparative Performance of High-Throughput Methods for Protein pJournal of chemical information and modeling · 2023
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Traian SuleaNational Research Council Canada, Human Health Therapeutics Research Centre, Montreal, QC, Canada.
Christophe DeprezNational Research Council Canada, Human Health Therapeutics Research Centre, Montreal, QC, Canada.
Christopher R CorbeilNational Research Council Canada, Human Health Therapeutics Research Centre, Montreal, QC, Canada.
Enrico O PurisimaNational Research Council Canada, Human Health Therapeutics Research Centre, Montreal, QC, Canada. enrico.purisima@nrc-cnrc.gc.ca.
National Research Council Canada · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ADAPT (Assisted Design of Antibody and Protein Therapeutics) platform guides the selection of mutants that improve/modulate the affinity of antibodies and other biologics. Predicted affinities are based on a consensus z-score from three scoring functions. Computational predictions are interleaved with experimental validation, significantly enhancing the robustness of the design and selection of mutants. A key step is an initial exhaustive virtual single-mutant scan that identifies hot spots and the mutations predicted to improve affinity. A small number of proposed single mutants are then produced and assayed. Only the validated single mutants (i.e., having improved affinity) are used to design double and higher-order mutants in subsequent rounds of design, avoiding the combinatorial explosion that arises from random mutagenesis. Typically, with a total of about 30-50 designed single, double, and triple mutants, affinity improvements of 10- to 100-fold are obtained.

Indexed as

AntibodiesAntibody AffinityMutagenesisMutationAntibodiesAffinity maturationAntibody designConsensus scoringProtein engineeringVirtual mutagenesisZ-score

Identifiers

PMID36346603
OpenAlexW4308583764

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.