Unveiling Antibody-Mediated Allostery in Interleukin-1ß Via Conformational Sampling and Machine Learning

Yıl 2025, Cilt: 8 Sayı: 5, 1440 - 1449, 15.09.2025

Arzu Uyar

https://doi.org/10.34248/bsengineering.1664037

Öz

Human interleukin-1β (IL-1β), a pivotal proinflammatory cytokine, is a therapeutic target in autoimmune and inflammatory diseases. While antibodies blocking IL-1β signaling are effective, their allosteric mechanisms remain poorly understood. This study investigates how four distinct antibodies induce long-range allosteric effects in IL-1β, leveraging computational approaches to map allosteric communication and identify critical sites. Ensembles of apo and antibody-bound IL-1β states were generated using the enhanced conformational sampling technique ClustENMD, followed by the application of two different dimensionality reduction methods in machine learning (principal component analysis, PCA; linear discriminant analysis, LDA) to the generated conformers. PCA highlighted how diverse ensembles ClustENMD generated, while LDA revealed antibody-specific allosteric effects on the human IL-1β. By integrating conformational dynamics with machine learning, this work advances a predictive framework for engineering antibodies with tailored allosteric properties. The discovery of binding sites on IL-1β might further open avenues for drug design.

Anahtar Kelimeler

Antibody , Allostery , Conformational sampling , ClustENMD , Machine learning

Etik Beyan

Ethics committee approval was not required for this study because there was no study on animals or humans.

Destekleyen Kurum

İzmir Institute of Technology

Proje Numarası

AUDP-2022-İYTE-3-0041

Teşekkür

AU acknowledges the financial support from the projects at İzmir Institute of Technology (Project no: AUDP-2022-İYTE-3-0041). Google Colab free computing resources are also used in this study.

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