# Method for the validation by Western analysis of affinity reagents against post-translationally modified proteins. I. survey of existing antibodies, and II. development of method improvements

> **NIH NIH R43** · ABBRATECH, INC. · 2022 · $339,150

## Abstract

ABSTRACT
The poor reproducibility of published research is a major focus of the scientific community in
recent years. Western analysis Abs are often validated against antigen (Ag) materials such as
mammalian cell lysates which have undergone treatment (e.g., chemical exposure, UV radiation
etc.) to induce (or reduce) modification of residues on a protein of interest. Several stages during
the generation of this material can pose challenges. First, it can be difficult to identify the
appropriate treatment and cell line for the residue of interest. Second, treated cell lysates can be
technically challenging to generate reproducibly. Even with careful adherence to a protocol, these
lysates may have varying degrees of modification present in “treated” and “untreated” samples.
This can lead to incorrect specificity determination for the Ab. A reliable method for validating
PTM-specific Abs would be one where each Ag sample contains the target sequence residue with
either 100% modification or 100% non-modification. We have developed a system that provides
that certainty.

## Key facts

- **NIH application ID:** 10479474
- **Project number:** 1R43GM146473-01
- **Recipient organization:** ABBRATECH, INC.
- **Principal Investigator:** Michael P Weiner
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $339,150
- **Award type:** 1
- **Project period:** 2022-04-01 → 2023-09-18

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10479474

## Citation

> US National Institutes of Health, RePORTER application 10479474, Method for the validation by Western analysis of affinity reagents against post-translationally modified proteins. I. survey of existing antibodies, and II. development of method improvements (1R43GM146473-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10479474. Licensed CC0.

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