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Gibbs Energy and Gene Expression Combined as a New Technique for Selecting Drug Targets for Inhibiting Specific Protein–Protein Interactions
One of the most important aspects of successful cancer therapy is the identification of a target protein for inhibition interaction. Conventionally, this consists of screening a panel of genes to assess which is mutated and then developing a small molecule to inhibit the interaction of two proteins...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10572529/ https://www.ncbi.nlm.nih.gov/pubmed/37834096 http://dx.doi.org/10.3390/ijms241914648 |
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author | Rietman, Edward A. Siegelmann, Hava T. Klement, Giannoula Lakka Tuszynski, Jack A. |
author_facet | Rietman, Edward A. Siegelmann, Hava T. Klement, Giannoula Lakka Tuszynski, Jack A. |
author_sort | Rietman, Edward A. |
collection | PubMed |
description | One of the most important aspects of successful cancer therapy is the identification of a target protein for inhibition interaction. Conventionally, this consists of screening a panel of genes to assess which is mutated and then developing a small molecule to inhibit the interaction of two proteins or to simply inhibit a specific protein from all interactions. In previous work, we have proposed computational methods that analyze protein–protein networks using both topological approaches and thermodynamic quantification provided by Gibbs free energy. In order to make these approaches both easier to implement and free of arbitrary topological filtration criteria, in the present paper, we propose a modification of the topological–thermodynamic analysis, which focuses on the selection of the most thermodynamically stable proteins and their subnetwork interaction partners with the highest expression levels. We illustrate the implementation of the new approach with two specific cases, glioblastoma (glioma brain tumors) and chronic lymphatic leukoma (CLL), based on the publicly available patient-derived datasets. We also discuss how this can be used in clinical practice in connection with the availability of approved and investigational drugs. |
format | Online Article Text |
id | pubmed-10572529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105725292023-10-14 Gibbs Energy and Gene Expression Combined as a New Technique for Selecting Drug Targets for Inhibiting Specific Protein–Protein Interactions Rietman, Edward A. Siegelmann, Hava T. Klement, Giannoula Lakka Tuszynski, Jack A. Int J Mol Sci Communication One of the most important aspects of successful cancer therapy is the identification of a target protein for inhibition interaction. Conventionally, this consists of screening a panel of genes to assess which is mutated and then developing a small molecule to inhibit the interaction of two proteins or to simply inhibit a specific protein from all interactions. In previous work, we have proposed computational methods that analyze protein–protein networks using both topological approaches and thermodynamic quantification provided by Gibbs free energy. In order to make these approaches both easier to implement and free of arbitrary topological filtration criteria, in the present paper, we propose a modification of the topological–thermodynamic analysis, which focuses on the selection of the most thermodynamically stable proteins and their subnetwork interaction partners with the highest expression levels. We illustrate the implementation of the new approach with two specific cases, glioblastoma (glioma brain tumors) and chronic lymphatic leukoma (CLL), based on the publicly available patient-derived datasets. We also discuss how this can be used in clinical practice in connection with the availability of approved and investigational drugs. MDPI 2023-09-27 /pmc/articles/PMC10572529/ /pubmed/37834096 http://dx.doi.org/10.3390/ijms241914648 Text en © 2023 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 | Communication Rietman, Edward A. Siegelmann, Hava T. Klement, Giannoula Lakka Tuszynski, Jack A. Gibbs Energy and Gene Expression Combined as a New Technique for Selecting Drug Targets for Inhibiting Specific Protein–Protein Interactions |
title | Gibbs Energy and Gene Expression Combined as a New Technique for Selecting Drug Targets for Inhibiting Specific Protein–Protein Interactions |
title_full | Gibbs Energy and Gene Expression Combined as a New Technique for Selecting Drug Targets for Inhibiting Specific Protein–Protein Interactions |
title_fullStr | Gibbs Energy and Gene Expression Combined as a New Technique for Selecting Drug Targets for Inhibiting Specific Protein–Protein Interactions |
title_full_unstemmed | Gibbs Energy and Gene Expression Combined as a New Technique for Selecting Drug Targets for Inhibiting Specific Protein–Protein Interactions |
title_short | Gibbs Energy and Gene Expression Combined as a New Technique for Selecting Drug Targets for Inhibiting Specific Protein–Protein Interactions |
title_sort | gibbs energy and gene expression combined as a new technique for selecting drug targets for inhibiting specific protein–protein interactions |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10572529/ https://www.ncbi.nlm.nih.gov/pubmed/37834096 http://dx.doi.org/10.3390/ijms241914648 |
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