Publication

De novo protein design by inversion of the AlphaFold structure prediction network

Related publications (116)

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The field of protein design has made remarkable progress over the past decade. Historically, the low reliability of purely structure-based design methods limited their application, but recent strategies that combine structure-based and sequence-based calcu ...

Nature Portfolio2024

Investigating the intra-molecular and inter-molecular effects of post-translational modifications on intrinsically disordered protein regions and structured protein regions

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Post-translational modifications (PTMs) play a pivotal role in regulating protein structure, interaction, and function. Aberrant PTM patterns are associated with diseases. Moreover, individual PTMs have a complex interaction with each other, known as PTM c ...

EPFL2024

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In the domain of computational structural biology, predicting protein interactions based on molecular structure remains a pivotal challenge. This thesis delves into this challenge through a series of interconnected studies.The first chapter introduces the ...

EPFL2024

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Proteins are foundational biomolecules of life playing a crucial role in a myriad of biological processes. Their function often requires interplay with other biomolecules, including proteins themselves. Protein-protein interactions (PPIs) are essential for ...

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Synergetic Support of Cartilage Homeostasis via Coupled Thermal-Hydrostatic Pressure Stimuli

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Cartilage homeostasis, crucial for musculoskeletal function, is orchestrated by interconnected biophysical cues. In healthy cartilage, repetitive compressive loading not only elicits a range of mechanical stimuli but also induces a gradual transient temper ...

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Borrowing some quotes from Harper Lee's novel "To Kill A Mockingbird" to help frame our manuscript, we discuss methods to profile local proteomes. We initially focus on chemical biology regimens that function in live organisms and use reactive biotin speci ...

Wiley-V C H Verlag Gmbh2024

A new age in protein design empowered by deep learning

Bruno Emanuel Ferreira De Sousa Correia, Michael Bronstein, Hamed Khakzad, Casper Alexander Goverde, Arne Schneuing, Ilia Igashov

The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of ...

Cambridge2023

Generative power of a protein language model trained on multiple sequence alignments

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Computational models starting from large ensembles of evolutionarily related protein sequences capture a representation of protein families and learn constraints associated to protein structure and function. They thus open the possibility for generating no ...

eLIFE SCIENCES PUBL LTD2023

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Proteins, the central building blocks of life, play pivotal roles in nearly every biological function. To do so, these macromolecular structures interact with their surrounding environment in complex ways, leading to diverse functional behaviors. The predi ...

EPFL2023

De novo designed proteins: a study in engineering novel folds and functions

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Proteins control nearly every facet of life on a molecular level. Proteins are formed from linear strings of amino acids, which fold into three-dimensional structures that can enact functions. Evolution has created highly efficient proteins in diverse fold ...

EPFL2023

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