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RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data

S-palmitoylation is a reversible covalent post-translational modification of cysteine thiol side chain by palmitic acid. S-palmitoylation plays a critical role in a variety of biological processes and is engaged in several human diseases. Therefore, identifying specific sites of this modification is...

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Autores principales: Bandyopadhyay, Soumyendu Sekhar, Halder, Anup Kumar, Zaręba-Kozioł, Monika, Bartkowiak-Kaczmarek, Anna, Dutta, Aviinandaan, Chatterjee, Piyali, Nasipuri, Mita, Wójtowicz, Tomasz, Wlodarczyk, Jakub, Basu, Subhadip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8467992/
https://www.ncbi.nlm.nih.gov/pubmed/34576064
http://dx.doi.org/10.3390/ijms22189901
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author Bandyopadhyay, Soumyendu Sekhar
Halder, Anup Kumar
Zaręba-Kozioł, Monika
Bartkowiak-Kaczmarek, Anna
Dutta, Aviinandaan
Chatterjee, Piyali
Nasipuri, Mita
Wójtowicz, Tomasz
Wlodarczyk, Jakub
Basu, Subhadip
author_facet Bandyopadhyay, Soumyendu Sekhar
Halder, Anup Kumar
Zaręba-Kozioł, Monika
Bartkowiak-Kaczmarek, Anna
Dutta, Aviinandaan
Chatterjee, Piyali
Nasipuri, Mita
Wójtowicz, Tomasz
Wlodarczyk, Jakub
Basu, Subhadip
author_sort Bandyopadhyay, Soumyendu Sekhar
collection PubMed
description S-palmitoylation is a reversible covalent post-translational modification of cysteine thiol side chain by palmitic acid. S-palmitoylation plays a critical role in a variety of biological processes and is engaged in several human diseases. Therefore, identifying specific sites of this modification is crucial for understanding their functional consequences in physiology and pathology. We present a random forest (RF) classifier-based consensus strategy (RFCM-PALM) for predicting the palmitoylated cysteine sites on synaptic proteins from male/female mouse data. To design the prediction model, we have introduced a heuristic strategy for selection of the optimum set of physicochemical features from the AAIndex dataset using (a) K-Best (KB) features, (b) genetic algorithm (GA), and (c) a union (UN) of KB and GA based features. Furthermore, decisions from best-trained models of the KB, GA, and UN-based classifiers are combined by designing a three-star quality consensus strategy to further refine and enhance the scores of the individual models. The experiment is carried out on three categorized synaptic protein datasets of a male mouse, female mouse, and combined (male + female), whereas in each group, weighted data is used as training, and knock-out is used as the hold-out set for performance evaluation and comparison. RFCM-PALM shows ~80% area under curve (AUC) score in all three categories of datasets and achieve 10% average accuracy (male—15%, female—15%, and combined—7%) improvements on the hold-out set compared to the state-of-the-art approaches. To summarize, our method with efficient feature selection and novel consensus strategy shows significant performance gains in the prediction of S-palmitoylation sites in mouse datasets.
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spelling pubmed-84679922021-09-27 RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data Bandyopadhyay, Soumyendu Sekhar Halder, Anup Kumar Zaręba-Kozioł, Monika Bartkowiak-Kaczmarek, Anna Dutta, Aviinandaan Chatterjee, Piyali Nasipuri, Mita Wójtowicz, Tomasz Wlodarczyk, Jakub Basu, Subhadip Int J Mol Sci Article S-palmitoylation is a reversible covalent post-translational modification of cysteine thiol side chain by palmitic acid. S-palmitoylation plays a critical role in a variety of biological processes and is engaged in several human diseases. Therefore, identifying specific sites of this modification is crucial for understanding their functional consequences in physiology and pathology. We present a random forest (RF) classifier-based consensus strategy (RFCM-PALM) for predicting the palmitoylated cysteine sites on synaptic proteins from male/female mouse data. To design the prediction model, we have introduced a heuristic strategy for selection of the optimum set of physicochemical features from the AAIndex dataset using (a) K-Best (KB) features, (b) genetic algorithm (GA), and (c) a union (UN) of KB and GA based features. Furthermore, decisions from best-trained models of the KB, GA, and UN-based classifiers are combined by designing a three-star quality consensus strategy to further refine and enhance the scores of the individual models. The experiment is carried out on three categorized synaptic protein datasets of a male mouse, female mouse, and combined (male + female), whereas in each group, weighted data is used as training, and knock-out is used as the hold-out set for performance evaluation and comparison. RFCM-PALM shows ~80% area under curve (AUC) score in all three categories of datasets and achieve 10% average accuracy (male—15%, female—15%, and combined—7%) improvements on the hold-out set compared to the state-of-the-art approaches. To summarize, our method with efficient feature selection and novel consensus strategy shows significant performance gains in the prediction of S-palmitoylation sites in mouse datasets. MDPI 2021-09-14 /pmc/articles/PMC8467992/ /pubmed/34576064 http://dx.doi.org/10.3390/ijms22189901 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bandyopadhyay, Soumyendu Sekhar
Halder, Anup Kumar
Zaręba-Kozioł, Monika
Bartkowiak-Kaczmarek, Anna
Dutta, Aviinandaan
Chatterjee, Piyali
Nasipuri, Mita
Wójtowicz, Tomasz
Wlodarczyk, Jakub
Basu, Subhadip
RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data
title RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data
title_full RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data
title_fullStr RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data
title_full_unstemmed RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data
title_short RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data
title_sort rfcm-palm: in-silico prediction of s-palmitoylation sites in the synaptic proteins for male/female mouse data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8467992/
https://www.ncbi.nlm.nih.gov/pubmed/34576064
http://dx.doi.org/10.3390/ijms22189901
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