Recent advances in de novo protein design: Principles, methods, and applications

By Xingjie Pan, Tanja Kortemme. 2021

194 citations recorded by the source corpus.

The computational de novo protein design is increasingly applied to address a number of key challenges in biomedicine and biological engineering. Successes in expanding applications are driven by advances in design principles and methods over several decades. Here, we review recent innovations in major aspects of the de novo protein design and include how these advances were informed by principles of protein architecture and interactions derived from the wealth of structures in the Protein Data Bank. We describe developments in de novo generation of designable backbone structures, optimization of sequences, design scoring functions, and the design of the function. The advances not only highlight design goals reachable now but also point to the challenges and opportunities for the future of the field.

Subfields: Biotechnology, Molecular Biology

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Citations in the corpus

AlphaFold2 and its applications in the fields of biology and medicine (2023, background): “109 It is a complex and challenging task, which is mainly hindered by the dif ﬁ culty in reliable prediction of protein 3D structures from amino acid sequences.”
AlphaDesign: A de novo protein design framework based on AlphaFold (2021, background): “More recently, computational design approaches have enabled de novo protein design, encompassing a full suite of functionalities ranging from rules for topology selection, protein backbone construction, sequence optimisation as well combinations of these approaches [37, 44].”
Identifying well-folded de novo proteins in the new era of accurate structure prediction (2022, background): “The success rate highly depends on the complexity of the protein fold, which tends to increase with β-sheet content, contact order and size (Marcos and Silva, 2018; Pan and Kortemme, 2021).”