✦ LIBER ✦

NeEMO: a method using residue interaction networks to improve prediction of protein stability upon mutation

✍ Scribed by Giollo, Manuel; Martin, Alberto JM; Walsh, Ian; Ferrari, Carlo; Tosatto, Silvio CE

Book ID: 125397504
Publisher: BioMed Central
Year: 2014
Tongue: English
Weight: 640 KB
Volume: 15
Category: Article
ISSN: 1471-2164
DOI: 10.1186/1471-2164-15-S4-S7

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Can one predict protein stability? An at

Can one predict protein stability? An attempt to do so for residue 133 of T4 lysozyme using a combination of free energy derivatives, PROFEC, and free energy perturbation methods

✍ Lu Wang; David L. Veenstra; Randall J. Radmer; Peter A. Kollman 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 373 KB 👁 2 views

Free energy derivatives, pictorial representation of free energy changes (PROFEC) and free energy perturbation methods were employed to suggest the modifications that may improve the stability of a mutant T4 lysozyme with a S-2-amino-3-cyclopentylpropanoic acid residue (Cpe) at position 133. The fre

[IEEE 2003 IEEE XIII Workshop on Neural

[IEEE 2003 IEEE XIII Workshop on Neural Networks for Signal Processing - Toulouse, France (17-19 Sept. 2003)] 2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718) - A neural network method to improve prediction of protein-protein interaction sites in heterocomplexes

✍ Fariselli, P.; Zauli, A.; Rossi, I.; Finelli, M.; Martelli, P.L.; Casadio, R. 📂 Article 📅 2003 🏛 IEEE 🌐 English ⚖ 335 KB