タンパク質の化学と構造を操作する新しいワークフローを開発(Scientists Develop a New Workflow for Manipulating Protein Chemistry and Structure)

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2024-01-02 パシフィック・ノースウェスト国立研究所(PNNL)

◆PTM-Psiワークフローは、プロテオミクスデータセットから分子的な洞察を引き出すための新しい手法です。既存のオープンソースソフトウェアを統合し、ユーザーに関連情報を整理して提示することで、タンパク質の構造推定や自由エネルギー計算などが効率的に行えます。データ解析の効率向上と複数ソフトの学習・使用リソースの削減が期待されます。

<関連情報>

PTM-Psi: PTM-Psi:タンパク質の翻訳後修飾による構造変化とそのダイナミクスや機能への影響を計算機的に調べるためのPythonパッケージ PTM-Psi: A python package to facilitate the computational investigation of post-translational modification on protein structures and their impacts on dynamics and functions

Daniel Mejia-Rodriguez, Hoshin Kim, Natalie Sadler, Xiaolu Li, Pavlo Bohutskyi, Marat Valiev, Wei-Jun Qian, Margaret S. Cheung
Protein Science  Published: 30 October 2023
DOI:https://doi.org/10.1002/pro.4822

タンパク質の化学と構造を操作する新しいワークフローを開発(Scientists Develop a New Workflow for Manipulating Protein Chemistry and Structure)

Abstract

Post-translational modification (PTM) of a protein occurs after it has been synthesized from its genetic template, and involves chemical modifications of the protein’s specific amino acid residues. Despite of the central role played by PTM in regulating molecular interactions, particularly those driven by reversible redox reactions, it remains challenging to interpret PTMs in terms of protein dynamics and function because there are numerous combinatorially enormous means for modifying amino acids in response to changes in the protein environment. In this study, we provide a workflow that allows users to interpret how perturbations caused by PTMs affect a protein’s properties, dynamics, and interactions with its binding partners based on inferred or experimentally determined protein structure. This Python-based workflow, called PTM-Psi, integrates several established open-source software packages, thereby enabling the user to infer protein structure from sequence, develop force fields for non-standard amino acids using quantum mechanics, calculate free energy perturbations through molecular dynamics simulations, and score the bound complexes via docking algorithms. Using the S-nitrosylation of several cysteines on the GAP2 protein as an example, we demonstrated the utility of PTM-Psi for interpreting sequence–structure–function relationships derived from thiol redox proteomics data. We demonstrate that the S-nitrosylated cysteine that is exposed to the solvent indirectly affects the catalytic reaction of another buried cysteine over a distance in GAP2 protein through the movement of the two ligands. Our workflow tracks the PTMs on residues that are responsive to changes in the redox environment and lays the foundation for the automation of molecular and systems biology modeling.

細胞遺伝子工学
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