Protposer: The web server that readily proposes protein stabilizing mutations with high PPV.

TitleProtposer: The web server that readily proposes protein stabilizing mutations with high PPV.
Publication TypeJournal Article
Year of Publication2022
AuthorsGarcía-Cebollada H, López A, Sancho J
JournalComput Struct Biotechnol J
Date Published2022

Protein stability is a requisite for most biotechnological and medical applications of proteins. As natural proteins tend to suffer from a low conformational stability , great efforts have been devoted toward increasing their stability through rational design and engineering of appropriate mutations. Unfortunately, even the best currently used predictors fail to compute the stability of protein variants with sufficient accuracy and their usefulness as tools to guide the rational stabilisation of proteins is limited. We present here , a protein stabilising tool based on a different approach. Instead of quantifying changes in stability, uses structure- and sequence-based screening modules to nominate candidate mutations for subsequent evaluation by a logistic regression model, carefully trained to avoid overfitting. Thus, analyses PDB files in search for stabilization opportunities and provides a ranked list of promising mutations with their estimated success rates (eSR), their probabilities of being stabilising by at least 0.5 kcal/mol. The agreement between eSRs and actual positive predictive values (PPV) on external datasets of mutations is excellent. When is used with its Optimal kappa selection threshold, its PPV is above 0.7. Even with less stringent thresholds, largely outperforms FoldX, Rosetta and PoPMusiC. Indicating the PDB file of the protein suffices to obtain a ranked list of mutations, their eSRs and hints on the likely source of the stabilization expected. is a distinct, straightforward and highly successful tool to design protein stabilising mutations, and it is freely available for academic use at

Alternate JournalComput Struct Biotechnol J
PubMed ID35664235
PubMed Central IDPMC9133766