An overview of descriptors to capture protein properties – Tools and perspectives in the context of QSAR modeling
- Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative.
Author: | Jessica EmontsORCiD, Johannes Felix Buyel |
---|---|
DOI: | https://doi.org/10.1016/j.csbj.2023.05.022 |
ISSN: | 2001-0370 (online-ressource) |
Parent Title (English): | Computational and Structural Biotechnology Journal |
Publisher: | Research Network of Computational and Structural Biotechnology |
Place of publication: | Gotenburg |
Document Type: | Article |
Language: | English |
Year of Completion: | 2023 |
Tag: | Prediction of molecular features; Protein structure complexity; Quantitative structure activity relationship; Scalar parameters; Shape and surface properties |
Issue: | 21 |
First Page: | 3234 |
Last Page: | 3247 |
Link: | https://doi.org/10.1016/j.csbj.2023.05.022 |
Zugriffsart: | weltweit |
Institutes: | FH Aachen / Fachbereich Maschinenbau und Mechatronik |
collections: | Verlag / Research Network of Computational and Structural Biotechnology (RNCSB) |