Computational protein design: a review

By Ivan Coluzza. 2017

45 citations recorded by the source corpus.

Subfields: Biomaterials, Ecology, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomaterials

1. Héctor García Martín
2. Zak Costello

In Ecology

1. Héctor García Martín
2. Zak Costello

In Molecular Biology

1. Bruno E. Correia
2. Che Yang
3. Chun-chao Lo
4. S. Rosset
5. Xiuwen Liu
6. Wei Wu
7. Jinfeng Zhang
8. Yang Chen

Citations in the corpus

• ProDCoNN: Protein design using a convolutional neural network (2019, background): “For the latest review articles on CPD and IPF problem see References 1, 25, 26.”
• How to Hallucinate Functional Proteins (2019, background): “Like directed evolution, this approach has enjoyed wide success and has resulted in useful proteins designed from physical principals (15; 6; 3; 16; 17).”
• Rosetta FunFolDes – A general framework for the computational design of functional proteins (2018, background): “Computational protein design is the rational and structure-based approach to solve the inverse folding problem, i.e. the search for the best putative sequence capable of fitting and stabilizing a given protein’s three-dimensional conformation (Coluzza, 2017).”