Evidence map›Paper›PMID 39197156›Full record

ArticleACS synthetic biology2024

Approaching Optimal pH Enzyme Prediction with Large Language Models.

Mark Zaretckii, Pavel Buslaev, Igor Kozlovskii, Alexander Morozov, Petr Popov

Abstract read
In one paragraph

Article in ACS synthetic biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

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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

5 authors.

Mark ZaretckiiTetra D AG, Shaffhausen 8200, Switzerland.
Pavel BuslaevNanoscience Center and Department of Chemistry, University of Jyväskylä, Jyväskylä 40014, Finland.ORCID 0000-0003-2031-4691
Igor KozlovskiiTetra D AG, Shaffhausen 8200, Switzerland.ORCID 0000-0001-6552-0881
Alexander MorozovIndependent researcher, Moscow 119991, Russia.
Petr PopovTetra D AG, Shaffhausen 8200, Switzerland.ORCID 0000-0003-3745-7154

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Enzymes are widely used in biotechnology due to their ability to catalyze chemical reactions: food making, laundry, pharmaceutics, textile, brewing─all these areas benefit from utilizing various enzymes. Proton concentration (pH) is one of the key factors that define the enzyme functioning and efficiency. Usually there is only a narrow range of pH values where the enzyme is active. This is a common problem in biotechnology to design an enzyme with optimal activity in a given pH range. A large part of this task can be completed

Indexed as

EnzymesMachine LearningComputer SimulationHydrogen-Ion ConcentrationEnzymesenzyme optimal pHlarge language modelsmachine learningprotein engineering

Identifiers

PMID39197156
PMCPMC11421216

What OpenQuestion holds

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Registered trials

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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.