TY - JOUR
T1 - Reused Protein Segments Linked to Functional Dynamics
AU - Kutlu, Yiǧit
AU - Axel, Gabriel
AU - Kolodny, Rachel
AU - Ben-Tal, Nir
AU - Haliloglu, Turkan
N1 - Publisher Copyright:
© 2024 The Author(s).
PY - 2024/9/1
Y1 - 2024/9/1
N2 - Protein space is characterized by extensive recurrence, or "reuse,"of parts, suggesting that new proteins and domains can evolve by mixing-and-matching of existing segments. From an evolutionary perspective, for a given combination to persist, the protein segments should presumably not only match geometrically but also dynamically communicate with each other to allow concerted motions that are key to function. Evidence from protein space supports the premise that domains indeed combine in this manner; we explore whether a similar phenomenon can be observed at the sub-domain level. To this end, we use Gaussian Network Models (GNMs) to calculate the so-called soft modes, or low-frequency modes of motion for a dataset of 150 protein domains. Modes of motion can be used to decompose a domain into segments of consecutive amino acids that we call "dynamic elements", each of which belongs to one of two parts that move in opposite senses. We find that, in many cases, the dynamic elements, detected based on GNM analysis, correspond to established "themes": Sub-domain-level segments that have been shown to recur in protein space, and which were detected in previous research using sequence similarity alone (i.e. completely independently of the GNM analysis). This statistically significant correlation hints at the importance of dynamics in evolution. Overall, the results are consistent with an evolutionary scenario where proteins have emerged from themes that need to match each other both geometrically and dynamically, e.g. to facilitate allosteric regulation.
AB - Protein space is characterized by extensive recurrence, or "reuse,"of parts, suggesting that new proteins and domains can evolve by mixing-and-matching of existing segments. From an evolutionary perspective, for a given combination to persist, the protein segments should presumably not only match geometrically but also dynamically communicate with each other to allow concerted motions that are key to function. Evidence from protein space supports the premise that domains indeed combine in this manner; we explore whether a similar phenomenon can be observed at the sub-domain level. To this end, we use Gaussian Network Models (GNMs) to calculate the so-called soft modes, or low-frequency modes of motion for a dataset of 150 protein domains. Modes of motion can be used to decompose a domain into segments of consecutive amino acids that we call "dynamic elements", each of which belongs to one of two parts that move in opposite senses. We find that, in many cases, the dynamic elements, detected based on GNM analysis, correspond to established "themes": Sub-domain-level segments that have been shown to recur in protein space, and which were detected in previous research using sequence similarity alone (i.e. completely independently of the GNM analysis). This statistically significant correlation hints at the importance of dynamics in evolution. Overall, the results are consistent with an evolutionary scenario where proteins have emerged from themes that need to match each other both geometrically and dynamically, e.g. to facilitate allosteric regulation.
KW - domains
KW - dynamic elements
KW - elastic network models
KW - evolution
KW - structural dynamics
KW - themes
UR - http://www.scopus.com/inward/record.url?scp=85204660743&partnerID=8YFLogxK
U2 - 10.1093/molbev/msae184
DO - 10.1093/molbev/msae184
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C2 - 39226145
AN - SCOPUS:85204660743
SN - 0737-4038
VL - 41
JO - Molecular Biology and Evolution
JF - Molecular Biology and Evolution
IS - 9
M1 - msae184
ER -