Evidence map›Paper›PMID 39955695›Full record

ArticleAmino acids2025

L-tyrosine inhibits the formation of amyloid fibers of human lysozyme at physiological pH and temperature.

Santos López, Arturo Rojo-Domínguez, Roxana López-Simeon, Alejandro Sosa-Peinado, Hugo Nájera

Abstract read
In one paragraph

Article in Amino acids, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Santos LópezPosgrado en Ciencias Naturales E Ingeniería, Universidad Autónoma Metropolitana-Cuajimalpa, Alcaldía Cuajimalpa de Morelos, Av. Vasco de Quiroga 4871, Colonia Santa Fe Cuajimalpa, Ciudad de México, 05348, México.
Arturo Rojo-DomínguezDepartamento de Ciencias Naturales, Universidad Autónoma Metropolitana-Cuajimalpa, Alcaldía Cuajimalpa de Morelos, Av. Vasco de Quiroga 4871, Colonia Santa Fe Cuajimalpa, 05348, Ciudad de Mexico, Mexico.
Roxana López-SimeonDepartamento de Ciencias Naturales, Universidad Autónoma Metropolitana-Cuajimalpa, Alcaldía Cuajimalpa de Morelos, Av. Vasco de Quiroga 4871, Colonia Santa Fe Cuajimalpa, 05348, Ciudad de Mexico, Mexico.
Alejandro Sosa-PeinadoLaboratorio de Biosensores y Modelaje Molecular, Departamento de Bioquímica, Facultad de Medicina, Universidad Nacional Autónoma de México, 04510, Ciudad de Mexico, Mexico.
Hugo NájeraDepartamento de Ciencias Naturales, Universidad Autónoma Metropolitana-Cuajimalpa, Alcaldía Cuajimalpa de Morelos, Av. Vasco de Quiroga 4871, Colonia Santa Fe Cuajimalpa, 05348, Ciudad de Mexico, Mexico. hnajera@cua.uam.mx.

Funding

Consejo Nacional de Humanidades Ciencia y Tecnología 945717
6 · The paper itself

Abstract

Amyloid fibers are implicated in numerous diseases, making their study crucial for identifying effective therapeutic compounds. This research highlights the ability of L-tyrosine to inhibit the formation of amyloid fibers in human lysozyme. At a 1:1 molar ratio under physiological conditions (pH 7.4, 37 °C), L-tyrosine significantly reduces amyloid fiber formation, as evidenced by a decrease in thioflavin T fluorescence. Differential scanning calorimetry (DSC) shows a major energy requirement for temperature denaturation when the lysozyme is in the presence of L-tyrosine. Additionally, chemical denaturation experiments reveal a shift in the intrinsic fluorescence spectrum of lysozyme in the presence of L-tyrosine, indicating a direct interaction. Computational docking studies with Molecular Operating Environment (MOE) further confirm that L-tyrosine binds effectively, exhibiting similar binding energies to those of the natural substrate. This study underscores L-tyrosine's potential as a strong inhibitor of amyloid fiber formation, demonstrating its stabilizing effect on lysozyme and its promise in therapeutic applications.

Indexed as

AmyloidMuramidaseTyrosineCalorimetry, Differential ScanningHumansHydrogen-Ion ConcentrationMolecular Docking SimulationProtein DenaturationTemperatureAmyloidMuramidaseTyrosineDockingInhibitionL-tyrosineLysozyme

Identifiers

PMID39955695
PMCPMC11830642

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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.