Impact of ancestral sequence reconstruction on mechanistic and structural enzymology

Nicoll, Callum R.; Massari, Marta; Fraaije, Marco W.; Mascotti, María Laura; Mattevi, Andrea

doi:10.1016/j.sbi.2023.102669

Cited by 10 publications

(3 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A compelling question related to enzyme design principles is how nature evolved enzymes to achieve the remarkable catalytic capabilities found in modern enzymes. ,,,,,,,,, To address this question, ancestral sequence reconstruction (ASR) algorithms , can be combined with protein structure prediction algorithms to test evolutionary design principles, such as those governing their catalytic activities and thermal adaptation, and to rapidly evaluate hypotheses. ,,, This idea has already been adopted, where the high accuracy of proteins structure predictions such as AlphaFold2 and RoseTTAFold2 have been used to evaluate the structures of the ASR-generated sequences, followed by biochemical/biophysical characterization and structural elucidation. − Notable examples of such studies include the study of monooxygenases’ functional diversification, which revealed relatively few mutations could be sufficient to induce diversification of the catalytic function of the enzyme, and the development of multiple xylulose isomerases by combining big data, ASR, and adaptive laboratory evolution techniques for biotechnology . We expect that this combined approach will be used more frequently to provide new opportunities for researchers.…”

Section: De Novo Enzyme Design and Evolutionmentioning

confidence: 99%

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Nam,

Shao,

Major

et al. 2024

ACS Omega

View full text Add to dashboard Cite

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

show abstract

Section: De Novo Enzyme Design and Evolutionmentioning

confidence: 99%

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Nam,

Shao,

Major

et al. 2024

ACS Omega

View full text Add to dashboard Cite

show abstract

“…They concluded that ancestral proteins should be routinely considered a protein crystallization tool. Furthermore, the recently published review by Nicoll et al [46] depicts the impact of ancestral enzymes on unveiling catalytic mechanisms. Haloalkane dehalogenases (subfamily HLD-II) AncHLD2 (6Y9E) AncHLD3 (6Y9F) AncHLD5 (6Y9G)…”

Section: Directions Of Developmentmentioning

confidence: 99%

Deciphering Enzyme Mechanisms with Engineered Ancestors and Substrate Analogues

Gao,

Damborsky,

Janin

et al. 2023

ChemCatChem

View full text Add to dashboard Cite

Environmentally friendly industrial and biotech processes greatly benefit from enzyme‐based technologies. Their use is often possible only when the enzyme‐catalytic mechanism is thoroughly known. Thus, atomic‐level knowledge of a Michaelis enzyme‐substrate complex, revealing molecular details of substrate recognition and catalytic chemistry, is crucial for understanding and then rationally extending or improving enzyme‐catalyzed reactions. However, many known enzymes sample huge protein conformational space, often preventing complete structural characterization by X‐ray crystallography. Moreover, using a cognate substrate is problematic since its conversion into a reaction product in the presence of the enzyme will prevent the capture of the enzyme‐substrate conformation in an activated state. Here, we outlined how to deal with such obstacles, focusing on the recent discovery of a Renilla‐type bioluminescence reaction mechanism facilitated by a combination of engineered ancestral enzyme and the availability of a non‐oxidizable luciferin analogue. The automated ancestral sequence reconstructions using FireProtASR provided a thermostable enzyme suited for structural studies, and a stable luciferin analogue azacoelenterazine provided a structurally cognate chemical incapable of catalyzed oxidation. We suggest that an analogous strategy can be applied to various enzymes with unknown catalytic mechanisms and poor crystallizability.

show abstract

“…[16] Many proteins encoded by reconstructed ancestral sequences ("resurrected" ancestral proteins, in jargon) have been prepared and characterized in the last ~25 years. [17][18][19][20][21][22][23][24][25] They have often been found to display interesting properties from both the evolutionary and biophysical viewpoints. In fact, in a substantial number of cases resurrected ancestral proteins have shown enhanced promiscuity.…”

mentioning

confidence: 99%

Ancestral versus Modern Substrate Scope in Family-1 Glycosidases

Gutierrez-Rus,

Petrovic,

Schneider

et al. 2024

Preprint

View full text Add to dashboard Cite

Promiscuity, the capability of catalyzing a diversity of chemical reactions, is a desirable feature in many enzymes intended for biotechnological applications. Promiscuous activities, however, are typically depressed in specialized modern enzymes. On the other hand, several ancestral reconstruction studies have reported enzymes with enhanced promiscuity. Glycosidases catalyze the hydrolysis of glycosidic bonds in all living cells but find practical applications in the synthesis of glycoconjugates as catalysts of the reverse reaction. Here, we use a library of about 500 possible substrates to compare the catalytic scope of the modern family-1 glycosidase from Halothermothrix orenii with that of a putative ancestral family-1 glycosidase derived from sequence reconstruction at a bacterial-eukaryotic common ancestor. The modern enzyme is the better catalyst for the hydrolysis of small substrates typically used to assess the activity of family-1 glycosidases. We identify, however, a trend for the modern enzyme to become less catalytically efficient with increasing substrate size. Such trend is not apparent in the conformationally-flexible ancestral glycosidase, which is in fact the better catalyst for the hydrolysis of flavonoid glycosides. Our results support that ancestral sequence reconstruction may provide a basis for enzyme engineering for the synthesis of glycoconjugates with large glycosyl acceptors.

show abstract

Impact of ancestral sequence reconstruction on mechanistic and structural enzymology

Cited by 10 publications

References 51 publications

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Deciphering Enzyme Mechanisms with Engineered Ancestors and Substrate Analogues

Ancestral versus Modern Substrate Scope in Family-1 Glycosidases

Contact Info

Product

Resources

About