Investigating the Nature of PRM:SH3 Interactions Using Artificial Intelligence and Molecular Dynamics

Understanding the binding interactions within protein-peptide complexes is crucial for elucidating key physicochemical phenomena in biological systems. Among the outcomes of these interactions, biomolecular condensates have recently emerged as vital players in various cellular functions including signaling. Complexes such as PRM:SH3 are known to undergo condensation, yet the chemical interactions and governing factors driving these behaviors remain poorly understood. In this study, we combine AlphaFold2 and molecular dynamics simulations to investigate the binding nature of PRM:SH3. Our findings reveal that proline-to-alanine mutations enhance flexibility, weakening the binding affinity, while charge-altering mutations modify the binding mode and influence the binding strength. Notably, the PRM(H) series shows that binding is primarily driven by local flexibility and the hydrophobic effect. Furthermore, we demonstrate that the root-mean-square deviation and dendrogram height are correlated to experimental dissociation constants. These insights provide a framework for understanding the binding behaviors of protein-peptide complexes and offer an effective approach for studying similar systems.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2025-05-19
DOI
https://doi.org/10.1021/acs.jcim.5c00342
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Investigating the Nature of PRM:SH3 Interactions Using Artificial Intelligence and Molecular Dynamics

Sejun Kim, Jeong‐Mo Choi, Hyungjun Kim, Da‐Eun Hwang
Journal of Chemical Information and Modeling
Protein Structure and Dynamics
article

Investigating the Nature of PRM:SH3 Interactions Using Artificial Intelligence and Molecular Dynamics

Sejun Kim, Jeong‐Mo Choi, Hyungjun Kim, Da‐Eun Hwang
article en

Abstract

Understanding the binding interactions within protein-peptide complexes is crucial for elucidating key physicochemical phenomena in biological systems. Among the outcomes of these interactions, biomolecular condensates have recently emerged as vital players in various cellular functions including signaling. Complexes such as PRM:SH3 are known to undergo condensation, yet the chemical interactions and governing factors driving these behaviors remain poorly understood. In this study, we combine AlphaFold2 and molecular dynamics simulations to investigate the binding nature of PRM:SH3. Our findings reveal that proline-to-alanine mutations enhance flexibility, weakening the binding affinity, while charge-altering mutations modify the binding mode and influence the binding strength. Notably, the PRM(H) series shows that binding is primarily driven by local flexibility and the hydrophobic effect. Furthermore, we demonstrate that the root-mean-square deviation and dendrogram height are correlated to experimental dissociation constants. These insights provide a framework for understanding the binding behaviors of protein-peptide complexes and offer an effective approach for studying similar systems.

Journal of Chemical Information and ModelingVol. 65(11)
Korea Advanced Institute of Science and Technology (KR), Pusan National University (KR)
POSCO TJ Park Foundation, Korea Toray Science Foundation, National Research Foundation of Korea
Openalex Percentile: Top 90%
Protein Structure and Dynamics
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Investigating the Nature of PRM:SH3 Interactions Using Artificial Intelligence and Molecular Dynamics — Sejun Kim, Jeong‐Mo Choi, et al. · Journal of Chemical Information and Modeling (2025) | TGRS Research Map | TGRS