Substrate dynamics contribute to enzymatic specificity in human and bacterial methionine adenosyltransferases

Gade, Madhuri; Tan, Li Lynn; Damry, Adam M.; Sandhu, Mahakaran; Brock, Jospeh S.; Delaney, Andie; Villar‐Briones, Alejandro; Jackson, C.J.; Laurino, Paola

doi:10.1101/2021.02.18.431797

Cited by 3 publications

(6 citation statements)

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“…We note that nearly every long adaptive trajectory beyond few mutations, includes multiple mutations at positions distal to the active site. Despite the importance of these so‐called third shell mutations their contribution to the emergence of new protein function remains poorly understood 96,97 …”

Section: Evolutionary Rates Of Proteinsmentioning

confidence: 99%

Mechanisms of protein evolution

et al. 2022

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How do proteins evolve? How do changes in sequence mediate changes in protein structure, and in turn in function? This question has multiple angles, ranging from biochemistry and biophysics to evolutionary biology. This review provides a brief integrated view of some key mechanistic aspects of protein evolution. First, we explain how protein evolution is primarily driven by randomly acquired genetic mutations and selection for function, and how these mutations can even give rise to completely new folds. Then, we also comment on how phenotypic protein variability, including promiscuity, transcriptional and translational errors, may also accelerate this process, possibly via "plasticity-first" mechanisms. Finally, we highlight open questions in the field of protein evolution, with respect to the emergence of more sophisticated protein systems such as protein complexes, pathways, and the emergence of pre-LUCA enzymes.

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Section: Evolutionary Rates Of Proteinsmentioning

confidence: 99%

Mechanisms of protein evolution

et al. 2022

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“…. , ℓ NC 𝑖 , ΔΔ𝐺 𝑖 , where Δ𝐺 C is the optimum binding a nity of the cognate ligand, and ΔΔ𝐺 𝑖 is the required minimal binding energy gap between the cognate ligand ℓ C and noncognate ligand 𝑖, ℓ NC 𝑖 ; the degree of speci city required for each non-cognate ligand depends on the in vivo concentration, 58 and the cost of incorrect binding.…”

Section: Discussionmentioning

confidence: 99%

“…76 Proteins need to be just flexible enough for the cognate ligand to bind, but not the non-cognate ligand. Too much flexibility (reduces deformation energy) and both will bind; 58 too rigid and either both will partially bind with negligible deformation.…”

Section: Discussionmentioning

confidence: 99%

“…g ., proteolysis) challenging depending on how similar the product is to the substrate. In principle, the difficulty, Ψ , can be expressed as a function of the set of ligands, {Λ}, and the required degree of specificity, where Δ G C is the optimum binding affinity of the cognate ligand, and ΔΔ G i is the required minimal binding energy gap between the cognate ligand Λ C and non-cognate ligand i , ; the degree of specificity required for each non-cognate ligand depends on the in vivo concentration, 70 and the cost of incorrect binding.…”

Section: Discussionmentioning

confidence: 99%

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General theory of specific binding: insights from a genetic-mechano-chemical protein model

McBride

Eckmann

Tlusty³

2022

Preprint

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Proteins need to selectively interact with specific targets among a multitude of similar molecules in the cell. Despite a firm physical understanding of binding interactions, we lack a general theory of how proteins evolve high specificity. Here, we present a model that combines chemistry, mechanics and genetics, and explains how their interplay governs the evolution of specific protein-ligand interactions. The model shows that there are many routes to achieving discrimination -- by varying degrees of flexibility and shape/chemistry complementarity -- but the key ingredient is precision. Harder discrimination tasks require more collective and precise coaction of structure, forces and movements. Proteins can achieve this through correlated mutations extending far from a binding site, which fine tune the localized interaction with the ligand. Thus, the solution of more complicated tasks is aided by increasing the protein, and proteins become more evolvable and robust when they are larger than the bare minimum required for discrimination. Our model makes testable, specific predictions about the role of flexibility in discrimination, and how to independently tune affinity and specificity. Thus, the proposed theory of molecular discrimination addresses the natural question ``why are proteins so big?'' A possible answer is that molecular discrimination is often a hard task best performed by adding more layers to the protein.

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“…Activity assay was performed as previously reported [ 73 ]. Briefly, ATP/GTP/CTP/UTP (5 m m ), methionine (10 m m ), HEPES (100 m m ), MgCl 2 (10 m m ), KCl (50 m m ), and MAT (20 µ m ) were mixed in water, following which the pH of the mixture was adjusted to 8.…”

Section: Methodsmentioning

confidence: 99%

Implications of divergence of methionine adenosyltransferase in archaea

et al. 2021

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Methionine adenosyltransferase (MAT) catalyzes the biosynthesis of S‐adenosyl methionine from l ‐methionine and ATP. MAT enzymes are ancient, believed to share a common ancestor, and are highly conserved in all three domains of life. However, the sequences of archaeal MATs show considerable divergence compared with their bacterial and eukaryotic counterparts. Furthermore, the structural significance and functional significance of this sequence divergence are not well understood. In the present study, we employed structural analysis and ancestral sequence reconstruction to investigate archaeal MAT divergence. We observed that the dimer interface containing the active site (which is usually well conserved) diverged considerably between the bacterial/eukaryotic MATs and archaeal MAT. A detailed investigation of the available structures supports the sequence analysis outcome: The protein domains and subdomains of bacterial and eukaryotic MAT are more similar than those of archaea. Finally, we resurrected archaeal MAT ancestors. Interestingly, archaeal MAT ancestors show substrate specificity, which is lost during evolution. This observation supports the hypothesis of a common MAT ancestor for the three domains of life. In conclusion, we have demonstrated that archaeal MAT is an ideal system for studying an enzyme family that evolved differently in one domain compared with others while maintaining the same catalytic activity.

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Substrate dynamics contribute to enzymatic specificity in human and bacterial methionine adenosyltransferases

Cited by 3 publications

References 70 publications

Mechanisms of protein evolution

Mechanisms of protein evolution

General theory of specific binding: insights from a genetic-mechano-chemical protein model

Implications of divergence of methionine adenosyltransferase in archaea

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