タンパク質のポケットオームをマッピング(Protein pocketome mapped)

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2025-09-17 マックス・プランク研究所

マックス・プランク分子植物生理学研究所の研究者らは、AIによるタンパク質構造予測(AlphaFold)を活用し、11種の生物にわたる22万種のタンパク質から約10万の結合ポケットを同定した「ポケットーム(pocketome)」マップを構築した。対象にはヒト、マウス、酵母、大腸菌、線虫、イネやトウモロコシなど主要作物も含まれる。解析の結果、進化に伴いタンパク質数は増加するものの、結合部位の多様性はそれほど比例して増えず、分子相互作用の革新には限界がある可能性が示唆された。この成果は創薬や安全な農薬開発に応用できると期待される。

タンパク質のポケットオームをマッピング(Protein pocketome mapped)Protein structure of human phosphodiesterase. Colored in teal is the binding pocket into which the small molecule, GMP (stick-model), binds. Exploiting AlphaFold, an AI-based structure prediction method, the study by Zillmer & Walther systematically identified and characterized all such binding pockets across eleven species from different kingdoms of life.

<関連情報>

ポケットオーム宇宙の包括的理解に向けて―生物学的意義とアルゴリズム的課題 Towards a comprehensive view of the pocketome universe—biological implications and algorithmic challenges

Hanne Zillmer,Dirk Walther
PLOS Computational Biology  Published: July 24, 2025
DOI:https://doi.org/10.1371/journal.pcbi.1013298

Abstract

With the availability of reliably predicted 3D-structures for essentially all known proteins, characterizing the entirety of compound-binding sites (binding pockets on proteins) has become a possibility. The aim of this study was to identify and analyze all compound-binding sites, i.e., the pocketomes, of eleven species from different kingdoms of life to discern evolutionary trends as well as to arrive at a global cross-species view of the pocketome universe. Computational binding site prediction was performed on all protein structures in each species as available from the AlphaFold database. The resulting set of potential binding sites was inspected for overlaps with known pockets and annotated with regard to the protein domains in which they are located. 2D-projection plots of all pockets embedded in a 128-dimensional feature space, and characterizing them with regard to selected physicochemical properties, provide informative, global pocketome maps that unveil differentiating features between pockets. Our study revealed a sub-linear scaling law of the number of unique binding sites relative to the number of unique protein structures per species. Thus, as proteomes increased in size during evolution and therefore potentially diversified, the number of distinct binding sites, reflecting potentially diversifying functions, grew less than proportionally. We discuss the biological significance of this finding as well as identify critical and unmet algorithmic challenges.

Author summary

The function of proteins is governed by specific interactions with other molecules, notably small molecules (compounds, such as metabolites). The precise nature of the protein-compound interaction, and thus, the associated function, is determined by the stereochemical and physicochemical properties of the sites at which the interaction occurs (binding pockets). Thus, novel functions (binding of novel compounds) generally require the emergence of new binding sites. With the recent breakthroughs in protein structure prediction, the complete set of protein structures has become available. This allowed us to apply computational binding site predictions and to investigate the entirety of all pockets (the “pocketome”) across eleven species from different kingdoms of life, and to study the relationship between the emergence of novel binding sites in relation to increasing sizes of proteomes, i.e., the set of all protein structures in a given species. Our analysis uncovered a sub-linear relationship between the numbers of unique pockets and unique protein structures, suggesting that during evolution, functional diversity shows signs of saturation, which is consistent with other reports, but approached here from the perspective of compound-binding specificities. Our study constitutes the first large-scale investigation of pocketomes based on the now available high-confidence protein structures.

 

生物化学工学
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