Machine learning for functional protein design
Recent breakthroughs in AI coupled with the rapid accumulation of protein sequence and
structure data have radically transformed computational protein design. New methods …
structure data have radically transformed computational protein design. New methods …
New Insights into the Cooperativity and Dynamics of Dimeric Enzymes
KW Chen, TY Sun, YD Wu - Chemical Reviews, 2023 - ACS Publications
A survey of protein databases indicates that the majority of enzymes exist in oligomeric
forms, with about half of those found in the UniProt database being homodimeric …
forms, with about half of those found in the UniProt database being homodimeric …
A DNA turbine powered by a transmembrane potential across a nanopore
Rotary motors play key roles in energy transduction, from macroscale windmills to
nanoscale turbines such as ATP synthase in cells. Despite our abilities to construct engines …
nanoscale turbines such as ATP synthase in cells. Despite our abilities to construct engines …
[HTML][HTML] De novo protein design—From new structures to programmable functions
T Kortemme - Cell, 2024 - cell.com
Methods from artificial intelligence (AI) trained on large datasets of sequences and
structures can now" write" proteins with new shapes and molecular functions de novo …
structures can now" write" proteins with new shapes and molecular functions de novo …
Motility of an autonomous protein-based artificial motor that operates via a burnt-bridge principle
Inspired by biology, great progress has been made in creating artificial molecular motors.
However, the dream of harnessing proteins–the building blocks selected by nature–to …
However, the dream of harnessing proteins–the building blocks selected by nature–to …
Small-angle X-ray scattering studies of enzymes
Enzyme function requires conformational changes to achieve substrate binding, domain
rearrangements, and interactions with partner proteins, but these movements are difficult to …
rearrangements, and interactions with partner proteins, but these movements are difficult to …
[HTML][HTML] From sequence to function through structure: Deep learning for protein design
The process of designing biomolecules, in particular proteins, is witnessing a rapid change
in available tooling and approaches, moving from design through physicochemical force …
in available tooling and approaches, moving from design through physicochemical force …
Leveraging deep learning to improve vaccine design
AP Hederman, ME Ackerman - Trends in immunology, 2023 - cell.com
Deep learning has led to incredible breakthroughs in areas of research, from self-driving
vehicles to solutions, to formal mathematical proofs. In the biomedical sciences, however …
vehicles to solutions, to formal mathematical proofs. In the biomedical sciences, however …
Sterically driven current reversal in a molecular motor model
Simulations can help unravel the complicated ways in which molecular structure determines
function. Here, we use molecular simulations to show how slight alterations of a molecular …
function. Here, we use molecular simulations to show how slight alterations of a molecular …
De novo design of modular protein hydrogels with programmable intra-and extracellular viscoelasticity
R Mout, RC Bretherton, J Decarreau… - Proceedings of the …, 2024 - National Acad Sciences
Relating the macroscopic properties of protein-based materials to their underlying
component microstructure is an outstanding challenge. Here, we exploit computational …
component microstructure is an outstanding challenge. Here, we exploit computational …