A Critical Assessment of Computer-Aided Approaches for Identifying FAK Inhibitors

Focal Adhesion Kinase (FAK) is a key regulator of tumor cell migration and survival, and its persistent overexpression in aggressive cancers has motivated ongoing efforts to identify novel small-molecule inhibitors. Despite this interest, progress in discovering new potent scaffolds has been limited...

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Detalles Bibliográficos
Autores: Quispe, Patricia A., Lietha, Daniel, León, Ignacio E., Lavecchia, Martín
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/412247
Acceso en línea:http://hdl.handle.net/10261/412247
Access Level:acceso abierto
Palabra clave:FAK
Virtual-screening
Inhibitors
Computational simulations
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spelling A Critical Assessment of Computer-Aided Approaches for Identifying FAK InhibitorsQuispe, Patricia A.Lietha, DanielLeón, Ignacio E.Lavecchia, MartínFAKVirtual-screeningInhibitorsComputational simulationsFocal Adhesion Kinase (FAK) is a key regulator of tumor cell migration and survival, and its persistent overexpression in aggressive cancers has motivated ongoing efforts to identify novel small-molecule inhibitors. Despite this interest, progress in discovering new potent scaffolds has been limited. In this work, we applied a multistep computational workflow followed by experimental testing to refine hit selection and reduce the false positives typically associated with docking. DrugBank and several commercial libraries were screened using Exponential Consensus Ranking (ECR) docking, and molecular dynamics simulations were used to assess pose stability and interaction persistence. A subset of predicted binders was then tested in MG-63 (bone cancer) and MDA-MB-231 (breast cancer) cells using cell viability and wound-healing assays, followed by direct autophosphorylation assays with recombinant FAK. Several repurposed compounds, including clofazimine and tafamidis, produced clear dose-dependent effects on cell migration, although their inhibitory activity in biochemical assays remained weak (IC50 values above 100 μ M), far from the potency of the reference inhibitor TAE226. Retrospective analysis of the computational workflow showed that standard MM-GBSA calculations did not correlate with these experimental outcomes. However, incorporating explicit water molecules through the NWAT-MMGBSA approach improved agreement with the biochemical data and helped to rationalize the limited affinity observed experimentally. Taken together, the results underline the relevance of explicit solvation in modeling the FAK active site and suggest that refined solvent-aware protocols may provide more reliable guidance for future screening efforts.This research was funded by Universidad Nacional de La Plata (UNLP, grant PPID SX006, 11/X958), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET, grant PIP 2051), and Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT), Argentina.This research was funded by Universidad Nacional de La Plata (UNLP, grant PPID SX006, 11/X958), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET, grant PIP 2051), and Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT), Argentina.Peer reviewedMultidisciplinary Digital Publishing InstituteUniversidad Nacional de La PlataConsejo Nacional de Investigaciones Científicas y Técnicas (Argentina)Agencia Nacional de Promoción Científica y Tecnológica (Argentina)Quispe, Patricia A. [0000-0002-3969-5909]Lietha, Daniel [0000-0002-6133-6486]Lavecchia, Martín [0000-0001-8678-4237]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2026202620252026info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/412247reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésThe underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.3390/kinasesphosphatases3040027https://doi.org/10.3390/kinasesphosphatases3040027Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4122472026-05-22T06:33:51Z
dc.title.none.fl_str_mv A Critical Assessment of Computer-Aided Approaches for Identifying FAK Inhibitors
title A Critical Assessment of Computer-Aided Approaches for Identifying FAK Inhibitors
spellingShingle A Critical Assessment of Computer-Aided Approaches for Identifying FAK Inhibitors
Quispe, Patricia A.
FAK
Virtual-screening
Inhibitors
Computational simulations
title_short A Critical Assessment of Computer-Aided Approaches for Identifying FAK Inhibitors
title_full A Critical Assessment of Computer-Aided Approaches for Identifying FAK Inhibitors
title_fullStr A Critical Assessment of Computer-Aided Approaches for Identifying FAK Inhibitors
title_full_unstemmed A Critical Assessment of Computer-Aided Approaches for Identifying FAK Inhibitors
title_sort A Critical Assessment of Computer-Aided Approaches for Identifying FAK Inhibitors
dc.creator.none.fl_str_mv Quispe, Patricia A.
Lietha, Daniel
León, Ignacio E.
Lavecchia, Martín
author Quispe, Patricia A.
author_facet Quispe, Patricia A.
Lietha, Daniel
León, Ignacio E.
Lavecchia, Martín
author_role author
author2 Lietha, Daniel
León, Ignacio E.
Lavecchia, Martín
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidad Nacional de La Plata
Consejo Nacional de Investigaciones Científicas y Técnicas (Argentina)
Agencia Nacional de Promoción Científica y Tecnológica (Argentina)
Quispe, Patricia A. [0000-0002-3969-5909]
Lietha, Daniel [0000-0002-6133-6486]
Lavecchia, Martín [0000-0001-8678-4237]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv FAK

Virtual-screening
Inhibitors
Computational simulations
topic FAK
Virtual-screening
Inhibitors
Computational simulations
description Focal Adhesion Kinase (FAK) is a key regulator of tumor cell migration and survival, and its persistent overexpression in aggressive cancers has motivated ongoing efforts to identify novel small-molecule inhibitors. Despite this interest, progress in discovering new potent scaffolds has been limited. In this work, we applied a multistep computational workflow followed by experimental testing to refine hit selection and reduce the false positives typically associated with docking. DrugBank and several commercial libraries were screened using Exponential Consensus Ranking (ECR) docking, and molecular dynamics simulations were used to assess pose stability and interaction persistence. A subset of predicted binders was then tested in MG-63 (bone cancer) and MDA-MB-231 (breast cancer) cells using cell viability and wound-healing assays, followed by direct autophosphorylation assays with recombinant FAK. Several repurposed compounds, including clofazimine and tafamidis, produced clear dose-dependent effects on cell migration, although their inhibitory activity in biochemical assays remained weak (IC50 values above 100 μ M), far from the potency of the reference inhibitor TAE226. Retrospective analysis of the computational workflow showed that standard MM-GBSA calculations did not correlate with these experimental outcomes. However, incorporating explicit water molecules through the NWAT-MMGBSA approach improved agreement with the biochemical data and helped to rationalize the limited affinity observed experimentally. Taken together, the results underline the relevance of explicit solvation in modeling the FAK active site and suggest that refined solvent-aware protocols may provide more reliable guidance for future screening efforts.
publishDate 2025
dc.date.none.fl_str_mv 2025
2026
2026
2026
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/412247
url http://hdl.handle.net/10261/412247
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.3390/kinasesphosphatases3040027
https://doi.org/10.3390/kinasesphosphatases3040027
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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