Biophysical Insights into the Binding Interactions of Inhibitors (ICA-1S/1T) Targeting Protein Kinase C-ι

The overexpression of atypical protein kinase C-iota (PKC-ι) is a biomarker for carcinogenesis in various cell types, such as glioma, ovarian, renal, etc., manifesting as a potential drug target. In previous in vitro studies, ICA-1S and ICA-1T, experimental candidates for inhibiting PKC-ι, have demonstrated their specificity and promising efficacy against various cancers. Moreover, the in vivo studies have demonstrated low toxicity levels in acute and chronic murine models. Despite these prior developments, the binding affinities of the inhibitors were never thoroughly explored from a biophysical perspective. Here, we present the biophysical characterizations of PKC-ι in combination with ICA-1S/1T. Various methods based on molecular docking, light scattering, intrinsic fluorescence, thermal denaturation, and heat exchange were applied. The biophysical characteristics including particle sizing, thermal unfolding, aggregation profiles, enthalpy, entropy, free energy changes, and binding affinity (Kd) of the PKC-ι in the presence of ICA-1S were observed. The studies indicate the presence of domain-specific stabilities in the protein–ligand complex. Moreover, the results indicate a spontaneous reaction with an entropic gain, resulting in a possible entropy-driven hydrophobic interaction and hydrogen bonds in the binding pocket. Altogether, these biophysical studies reveal important insights into the binding interactions of PKC-ι and its inhibitors ICA-1S/1T.

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Journal
Biophysica
Published
2025-08-11
DOI
https://doi.org/10.3390/biophysica5030036
Primary Topic
Computational Drug Discovery Methods
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article
Field-Weighted Citation Impact
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article

Biophysical Insights into the Binding Interactions of Inhibitors (ICA-1S/1T) Targeting Protein Kinase C-ι

Mildred Acevedo‐Duncan, Tracess Smalley, Aleksandra Karolak, Radwan Ebna Noor et al.
Biophysica
Computational Drug Discovery Methods
article

Biophysical Insights into the Binding Interactions of Inhibitors (ICA-1S/1T) Targeting Protein Kinase C-ι

Mildred Acevedo‐Duncan, Tracess Smalley, Aleksandra Karolak, Radwan Ebna Noor, James W. Leahy, Wayne C. Guida, Shahedul Islam, Dimitra Keramisanou, Ioannis Gelis, Mark Eschenfelder, Katarzyna Mizgalska, Aaron Joshua Astalos
article en

Abstract

The overexpression of atypical protein kinase C-iota (PKC-ι) is a biomarker for carcinogenesis in various cell types, such as glioma, ovarian, renal, etc., manifesting as a potential drug target. In previous in vitro studies, ICA-1S and ICA-1T, experimental candidates for inhibiting PKC-ι, have demonstrated their specificity and promising efficacy against various cancers. Moreover, the in vivo studies have demonstrated low toxicity levels in acute and chronic murine models. Despite these prior developments, the binding affinities of the inhibitors were never thoroughly explored from a biophysical perspective. Here, we present the biophysical characterizations of PKC-ι in combination with ICA-1S/1T. Various methods based on molecular docking, light scattering, intrinsic fluorescence, thermal denaturation, and heat exchange were applied. The biophysical characteristics including particle sizing, thermal unfolding, aggregation profiles, enthalpy, entropy, free energy changes, and binding affinity (Kd) of the PKC-ι in the presence of ICA-1S were observed. The studies indicate the presence of domain-specific stabilities in the protein–ligand complex. Moreover, the results indicate a spontaneous reaction with an entropic gain, resulting in a possible entropy-driven hydrophobic interaction and hydrogen bonds in the binding pocket. Altogether, these biophysical studies reveal important insights into the binding interactions of PKC-ι and its inhibitors ICA-1S/1T.

BiophysicaVol. 5(3)
University of South Florida (US), Moffitt Cancer Center (US), NanoTemper Technologies (Germany) (DE)
William and Ella Owens Medical Research Foundation, Leo and Anne Albert Charitable Trust
Openalex Percentile: Top 78%
Computational Drug Discovery Methods
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