Overview
K-Pro is a collection of numerical data of kinetic parameters such as the logarithm of folding and unfolding rates (ln(kf), ln(ku)),
the folding and unfolding slopes of the Chevron plot (mf, mu) and the Tanford’s β and the φ values etc. for wild-type and mutant proteins.
When available, thermodynamic parameters obtained from kinetic experiments are also collected.
K-Pro also contains information about secondary structure and accessibility of wild type
residues, experimental conditions (pH, temperature, buffer, ion and protein concentration) and measurements and methods used for each data.
K-Pro is cross-linked with protein sequence (UniProt)
and structure (PDB) database and literature databases
(PubMed).
The web interface enables users to search data based on various terms.
Statistics
The K-Pro database contains 1,529 entries from 62 proteins which correspond to 65 unique structures.
The mapping between protein sequences and structures always exhibits some exceptions. The discrepancy in the numbers arises from the presence of multiple domains belonging to the same protein and mutants linked to different protein structures.
The mapping between protein sequences and structures always presents some exceptions.
Indeed the discrepancy in the numbers is due to the presence of: i) multiple domains belonging to the same protein; ii) protein mutants linked to different structures.
The majority of the kinetic data records are from single-point mutants, accounting for approximately 88%
of the database, with the remaining 12% split between wild-type (~6%) and multiple-point (~6%) mutations.
For the 1,341 single-point mutants, a structural analysis shows that 44% of the mutated residues were in a
helical conformation, 29% were in beta regions, and 27% were in a coil conformation.
Based on the fraction of the surface of the wild-type residue exposed to solvent (RSA), the mutated sites were
then divided into three groups: buried (RSA≤10), intermediate (10
To assess the impact of single amino acid substitutions on protein folding kinetics, the distribution of the
variations in the logarithms of folding and unfolding rates was analyzed.
The data collected in K-Pro suggests that the majority of mutations slow down the folding process, decreasing
the average logarithm of kfH2O by approximately 0.6, and accelerate the unfolding process, increasing the logarithm
of kuH2O by approximately 2. In both cases, the standard deviation of the distribution is
similar to the mean, reaching 0.9 for Δln(kfH2O) and 1.9 for
Δln(kuH2O).
The difference between Δln(kfH2O) and Δln(kuH2O),
is proportional to the variation of Gibbs free energy change of the unfolding process upon mutation
(ΔΔGumut-wt<0).
In the whole database, that calculated free energy difference results on average in a negative value, in agreement with the
thermodynamic experiments showing that mutations mostly tend to have a destabilizing effect.
The tab-separated file collecting all the records of the database is available at this link.
Data Standardization
The data collected in K-Pro are reported, in their original publications, in a highly heterogeneous manner, regarding e.g.:
Sign convention for free energy change, and/or for variation of free energy change upon mutation, units of measure
(e.g. °T versus °K, kcal versus kJ, seconds versus milliseconds, etc.), sequence numbering, etc.
For the sake of easy comparison, in K-Pro the data were all converted, if needed, to a single standard.
Disclaimer
K-Pro database is a non-profit service to the scientific community. Curators are working to provide accurate and up-to-date information.
However, there is make no warranty that the provided information is complete. Maintainers have no responsibility for any damage
resulting from the use of this database.
References
K-Pro database also includes data from previously developed databases and published datasets.
Below are reported the references to the largest collection of folding kinetic data.
Fulton KF, et al. (2006). Protein Folding Database (PFD 2.0): an online environment for the International Foldeomics Consortium.
Nucleic Acids Res. 35(Database issue):D304-7.
PMID:17170010.
Bogatyreva NS, et al. (2009). KineticDB: a database of protein folding kinetics.
Nucleic Acids Res. 37, D342-346.
PMID:18842631.
Manavalan B, et al. (2019) PFDB: A standardized protein folding database with
temperature Sci Rep. 2019 9(1):1588.
PMID:30733462.
Chaudhary P, et al. (2015) Folding RaCe: a robust method for predicting changes in protein folding rates upon point mutations.
Bioinformatics. 31(13):2091-7.
PMID:25686635.
Naganathan AN, Muñoz V (2010) Insights into protein folding mechanisms from large scale analysis of mutational effects.
Proc. Natl Acad. Sci. U.S.A.,107,8611–8616.
PMID:20418505.
