Targeting the Crosstalk Between Metabolism and Chronic Inflammation: In Silico Multitargeting Drug Design Approach for Cardiometabolic Syndrome

Petsas, Errikos; Siasos, Gerasimos; Mavromoustakos, Thomas; Chasapis, Christos T.

doi:10.3390/biomedicines14061213

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Targeting the Crosstalk Between Metabolism and Chronic Inflammation: In Silico Multitargeting Drug Design Approach for Cardiometabolic Syndrome

¹

Laboratory of Organic Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, 15771 Athens, Greece

²

3rd Department of Cardiology, Thoracic Diseases General Hospital Sotiria, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece

^*

Author to whom correspondence should be addressed.

Biomedicines 2026, 14(6), 1213; https://doi.org/10.3390/biomedicines14061213

Submission received: 3 May 2026 / Revised: 18 May 2026 / Accepted: 25 May 2026 / Published: 27 May 2026

(This article belongs to the Section Drug Discovery, Development and Delivery)

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Abstract

Βackround/Objectives: The rising global burden of cardiometabolic disorders and chronic low-grade inflammation underscores the need for therapies capable of modulating multiple interconnected pathways. Methods: In this work, a ligand-based virtual screening campaign centered on a previously reported scaffold (compound 1a) was combined with molecular docking, 200 ns molecular dynamics simulations and ADMET prediction to identify and prioritize small-molecule multitarget candidates against PCSK9, GLP1R, FGFR1, GIPR, NF-κB and NLRP3. Results: Among the screened analogs, D4Z emerged as the most balanced lead, displaying consistently favorable binding profiles, stable interactions within functionally relevant pockets and a drug-like physicochemical and pharmacokinetic profile with high predicted oral absorption. Conclusions: Although these findings remain purely computational, they support D4Z as a prioritized multitarget lead for synthesis and experimental validation and illustrate the potential of rational multitarget design for addressing the cardiometabolic–inflammatory axis.

Keywords: multitarget drug design; medicinal chemistry; molecular docking; molecular dynamics; cardiometabolic syndrome; type 2 diabetes; cholesterol; obesity; inflammation; in silico ADMET

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MDPI and ACS Style

Petsas, E.; Siasos, G.; Mavromoustakos, T.; Chasapis, C.T. Targeting the Crosstalk Between Metabolism and Chronic Inflammation: In Silico Multitargeting Drug Design Approach for Cardiometabolic Syndrome. Biomedicines 2026, 14, 1213. https://doi.org/10.3390/biomedicines14061213

AMA Style

Petsas E, Siasos G, Mavromoustakos T, Chasapis CT. Targeting the Crosstalk Between Metabolism and Chronic Inflammation: In Silico Multitargeting Drug Design Approach for Cardiometabolic Syndrome. Biomedicines. 2026; 14(6):1213. https://doi.org/10.3390/biomedicines14061213

Chicago/Turabian Style

Petsas, Errikos, Gerasimos Siasos, Thomas Mavromoustakos, and Christos T. Chasapis. 2026. "Targeting the Crosstalk Between Metabolism and Chronic Inflammation: In Silico Multitargeting Drug Design Approach for Cardiometabolic Syndrome" Biomedicines 14, no. 6: 1213. https://doi.org/10.3390/biomedicines14061213

APA Style

Petsas, E., Siasos, G., Mavromoustakos, T., & Chasapis, C. T. (2026). Targeting the Crosstalk Between Metabolism and Chronic Inflammation: In Silico Multitargeting Drug Design Approach for Cardiometabolic Syndrome. Biomedicines, 14(6), 1213. https://doi.org/10.3390/biomedicines14061213

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Targeting the Crosstalk Between Metabolism and Chronic Inflammation: In Silico Multitargeting Drug Design Approach for Cardiometabolic Syndrome

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