This Review is aimed at synthetic organic chemists who may be familiar with organometallic
catalysis but have no experience with biocatalysis, and seeks to provide an answer to the …

Molecular self-assembly has received considerable attention in biomedical fields as a
simple and effective method for develo** biomolecular nanostructures. Self-assembled …

We report two generative deep-learning models that predict amino acid sequences and 3D
protein structures on the basis of secondary-structure design objectives via either the overall …

Through evolution, nature has presented a set of remarkable protein materials, including
elastins, silks, keratins and collagens with superior mechanical performances that play …

Owing to their outstanding performances in molecular recognition, antibodies are
extensively used in research and applications in molecular biology, biotechnology and …

Sequence-controlled polymers are an emerging class of synthetic polymers with a regulated
sequence of monomers. In the past decade, tremendous progress has been made in the …

Vaccines play an essential role in controlling the rates of fatality and morbidity. Vaccines not
only arrest the beginning of different diseases but also assign a gateway for its elimination …

The recent emergence of deep learning to characterize complex patterns of protein big data
reveals its potential to address the classic challenges in the field of protein data mining …

Proteins are some of the most fascinating and challenging molecules in the universe, and
they pose a big challenge for artificial intelligence. The implementation of machine …

We report the use of a deep learning model to design de novo proteins, based on the
interplay of elementary building blocks via hierarchical patterns. The deep neural network …