Biology subjects

Fabrizio Pucci

Publications and source records attributed to Fabrizio Pucci.

4 recordsLinked to original sources

bioRxiv2016

Improved insights into protein thermal stability: from the molecular to the structurome scale

Despite the intense efforts of the last decades to understand the thermal stability of proteins, the mechanisms responsible for its modulation still remain debated. In this investigation, we tackle this issue by showing how a multi-scale perspective can yield new insights. With the help of temperature-dependent statistical potentials, we analyzed some amino acid interactions at the molecular level, which are suggested to be relevant for the enhancement of thermal resistance. We then investigated the thermal stability at the protein level by quantifying its modification upon amino acid substitutions. Finally, a large scale analysis of protein stability - at the structurome level - contributed to the clarification of the relation between stability and natural evolution, thereby showing that the mutational profile of thermostable and mesostable proteins differ. Some final considerations on how the multi-scale approach could help unraveling the protein stability mechanisms are briefly discussed.

Bioinformatics↗

bioRxiv2016

A little walk from physical to biological complexity: protein folding and stability

As an example of topic where biology and physics meet, we present the issue of protein folding and stability, and the development of thermodynamics-based bioinformatics tools that predict the stability and thermal resistance of proteins and the change of these quantities upon amino acid substitutions. These methods are based on knowledge-driven statistical potentials, derived from experimental protein structures using the inverse Boltzmann law. We also describe an application of these predictors, which contributed to the understanding of the mechanisms of aggregation of a particular protein known to cause a neuronal disease.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC=\"FIGDIR/small/043737_ufig1.gif\" ALT=\"Figure 1000\">\nView larger version (98K):\norg.highwire.dtl.DTLVardef@1fb262borg.highwire.dtl.DTLVardef@186eaaforg.highwire.dtl.DTLVardef@99b828org.highwire.dtl.DTLVardef@953a2_HPS_FORMAT_FIGEXP M_FIG C_FIG

Bioinformatics↗

bioRxiv2016

Predicting protein thermal stability changes upon point mutations using statistical potentials: Introducing HoTMuSiC

The accurate prediction of the impact of an amino acid substitution on the thermal stability of a protein is a central issue in protein science, and is of key relevance for the rational optimization of various bioprocesses that use enzymes in unusual conditions. Here we present one of the first computational tools to predict the change in melting temperature {Delta}Tm upon point mutations, given the protein structure and, when available, the melting temperature Tm of the wild-type protein. The key ingredients of our model structure are standard and temperature-dependent statistical potentials, which are combined with the help of an artificial neural network. The model structure was chosen on the basis of a detailed thermodynamic analysis of the system. The parameters of the model were identified on a set of more than 1,600 mutations with experimentally measured {Delta}Tm. The performance of our method was tested using a strict 5-fold cross-validation procedure, and was found to be significantly superior to that of competing methods. We obtained a root mean square deviation between predicted and experimental {Delta}Tm values of 4.2{degrees}C that reduces to 2.9{degrees}C when ten percent outliers are removed. A webserver-based tool is freely available for non-commercial use at soft.dezyme.com.

Bioinformatics↗

bioRxiv2016

High-quality thermodynamic data on the stability changes of proteins upon single-site mutations

We have set up and manually curated a dataset containing experimental information on the impact of amino acid substitutions in a protein on its thermal stability. It consists of a repository of experimentally measured melting temperatures (Tm) and their changes upon point mutations ({Delta}Tm) for proteins having a well-resolved X-ray structure. This high-quality dataset is designed for being used for the training or benchmarking of in silico thermal stability prediction methods. It also reports other experimentally measured thermodynamic quantities when available, i.e. the folding enthalpy ({Delta}H) and heat capacity ({Delta}CP) of the wild type proteins and their changes upon mutations ({Delta}{Delta}H and {Delta}{Delta}CP), as well as the change in folding free energy ({Delta}{Delta}G) at a reference temperature. These data are analyzed in view of improving our insights into the correlation between thermal and thermodynamic stabilities, the asymmetry between the number of stabilizing and destabilizing mutations, and the difference in stabilization potential of thermostable versus mesostable proteins.

Bioinformatics↗