Natural Fatty Acids as Dual ACE2-Inflammatory Modulators: Integrated Computational Framework for Pandemic Preparedness

The COVID-19 pandemic exposed critical vulnerabilities in single-target antiviral strategies, highlighting the urgent need for multi-mechanism therapeutic approaches against emerging viral threats. Here, we present an integrated computational framework systematically evaluating natural fatty acids as potential dual ACE2 (Angiotension Converting Enzyme 2)-inflammatory modulators; compounds simultaneously disrupting SARS-CoV-2 viral entry through allosteric ACE2 binding while suppressing host inflammatory cascades; through allosteric binding mechanisms rather than conventional competitive inhibition. Using molecular docking across eight ACE2 regions, 100 ns molecular dynamics simulations, MM/PBSA free energy calculations, and multivariate statistical analysis (PCA/LDA), we computationally assessed nine naturally occurring fatty acids representing saturated, monounsaturated, and polyunsaturated classes. Hierarchical dynamics analysis identified three distinct binding regimes spanning fast (τ < 50 ns) to slow (τ > 150 ns) timescales, with unsaturated fatty acids demonstrating superior binding affinities (ΔG = -6.85 ± 0.27 kcal/mol vs. -6.65 ± 0.25 kcal/mol for saturated analogs, <i>p</i> = 0.002). Arachidonic acid achieved optimal SwissDock affinity (-7.28 kcal/mol), while oleic acid exhibited top-ranked predicted binding affinity within the computational hierarchy (ΔG<sub>bind</sub> = -24.12 ± 7.42 kcal/mol), establishing relative prioritization for experimental validation rather than absolute affinity quantification. Energetic decomposition identified van der Waals interactions as primary binding drivers (65-80% contribution), complemented by hydrogen bonds as transient directional anchors. Comprehensive ADMET profiling predicted favorable safety profiles compared to synthetic antivirals, with ω-3 fatty acids showing minimal nephrotoxicity risks while maintaining excellent intestinal absorption (>91%). Multi-platform bioactivity analysis identified convergent anti-inflammatory mechanisms through eicosanoid pathway modulation and kinase inhibition. This computational investigation positions natural fatty acids as promising candidates for experimental validation in next-generation pandemic preparedness strategies, integrating potential therapeutic efficacy with sustainable sourcing. The framework is generalizable to fatty acids from diverse biological origins.

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Journal
International Journal of Molecular Sciences
Published
2025-12-30
DOI
https://doi.org/10.3390/ijms27010402
Primary Topic
Computational Drug Discovery Methods
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article
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article

Natural Fatty Acids as Dual ACE2-Inflammatory Modulators: Integrated Computational Framework for Pandemic Preparedness

Santiago Ballaz, J. M. Sasikumar, Tanishque Verma, Shanmugamurthy Lakshmanan et al.
International Journal of Molecular Sciences
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article

Natural Fatty Acids as Dual ACE2-Inflammatory Modulators: Integrated Computational Framework for Pandemic Preparedness

Santiago Ballaz, J. M. Sasikumar, Tanishque Verma, Shanmugamurthy Lakshmanan, William D. Lituma-González
article en

Abstract

The COVID-19 pandemic exposed critical vulnerabilities in single-target antiviral strategies, highlighting the urgent need for multi-mechanism therapeutic approaches against emerging viral threats. Here, we present an integrated computational framework systematically evaluating natural fatty acids as potential dual ACE2 (Angiotension Converting Enzyme 2)-inflammatory modulators; compounds simultaneously disrupting SARS-CoV-2 viral entry through allosteric ACE2 binding while suppressing host inflammatory cascades; through allosteric binding mechanisms rather than conventional competitive inhibition. Using molecular docking across eight ACE2 regions, 100 ns molecular dynamics simulations, MM/PBSA free energy calculations, and multivariate statistical analysis (PCA/LDA), we computationally assessed nine naturally occurring fatty acids representing saturated, monounsaturated, and polyunsaturated classes. Hierarchical dynamics analysis identified three distinct binding regimes spanning fast (τ < 50 ns) to slow (τ > 150 ns) timescales, with unsaturated fatty acids demonstrating superior binding affinities (ΔG = -6.85 ± 0.27 kcal/mol vs. -6.65 ± 0.25 kcal/mol for saturated analogs, <i>p</i> = 0.002). Arachidonic acid achieved optimal SwissDock affinity (-7.28 kcal/mol), while oleic acid exhibited top-ranked predicted binding affinity within the computational hierarchy (ΔG<sub>bind</sub> = -24.12 ± 7.42 kcal/mol), establishing relative prioritization for experimental validation rather than absolute affinity quantification. Energetic decomposition identified van der Waals interactions as primary binding drivers (65-80% contribution), complemented by hydrogen bonds as transient directional anchors. Comprehensive ADMET profiling predicted favorable safety profiles compared to synthetic antivirals, with ω-3 fatty acids showing minimal nephrotoxicity risks while maintaining excellent intestinal absorption (>91%). Multi-platform bioactivity analysis identified convergent anti-inflammatory mechanisms through eicosanoid pathway modulation and kinase inhibition. This computational investigation positions natural fatty acids as promising candidates for experimental validation in next-generation pandemic preparedness strategies, integrating potential therapeutic efficacy with sustainable sourcing. The framework is generalizable to fatty acids from diverse biological origins.

International Journal of Molecular SciencesVol. 27(1)
University Hospital, Newark (US), Universidad Espíritu Santo (EC), Karpagam Academy of Higher Education (IN)
Good health and well-being
Openalex Percentile: Top 26%
Computational Drug Discovery Methods
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