Evidence map›Paper›PMID 36121820›Full record

ArticlePloS one2022

Automated prediction of site and sequence of protein modification with ATRP initiators.

Arth Patel, Paige N Smith, Alan J Russell, Sheiliza Carmali

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. 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
0.4field-weighted citation impact, top 44% 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, 4 citations in OpenAlex.

  1. Article
  2. Review
  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 3 institutions in 2 countries.

Arth PatelDepartment of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
Paige N SmithDepartment of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
Alan J RussellDepartment of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
Sheiliza CarmaliSchool of Pharmacy, Queen's University Belfast, Belfast, United Kingdom.ORCID 0000-0003-3436-4745
Carnegie Mellon University · USAmgen (United States) · USQueen's University Belfast · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the most straightforward and commonly used chemical modifications of proteins is to react surface amino groups (lysine residues) with activated esters. This chemistry has been used to generate protein-polymer conjugates, many of which are now approved therapeutics. Similar conjugates have also been generated by reacting activated ester atom transfer polymerization initiators with lysine residues to create biomacromolecular initiators for polymerization reactions. The reaction between activated esters and lysine amino groups is rapid and has been consistently described in almost every publication on the topic as a "random reaction". A random reaction implies that every accessible lysine amino group on a protein molecule is equally reactive, and as a result, that the reaction is indiscriminate. Nonetheless, the literature contradicts itself by also suggesting that some lysine amino groups are more reactive than others (as a function of pKa, surface accessibility, temperature, and local environment). If the latter assumption is correct, then the outcome of these reactions cannot be random at all, and we should be able to predict the outcome from the structure of the protein. Predicting the non-random outcome of a reaction between surface lysines and reactive esters could transform the speed at which active bioconjugates can be developed and engineered. Herein, we describe a robust integrated tool that predicts the activated ester reactivity of every lysine in a protein, thereby allowing us to calculate the non-random sequence of reaction as a function of reaction conditions. Specifically, we have predicted the intrinsic reactivity of each lysine in multiple proteins with a bromine-functionalised N-hydroxysuccinimide initiator molecule. We have also shown that the model applied to PEGylation. The rules-based analysis has been coupled together in a single Python program that can bypass tedious trial and error experiments usually needed in protein-polymer conjugate design and synthesis.

Indexed as

BromineLysineEstersPolymersProtein Processing, Post-TranslationalProteinsBromineEstersLysinePolymersProteins

Identifiers

PMID36121820
PMCPMC9484671
OpenAlexW4296324837

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.