Biomedical subjects

Francesco Rao

Publications and source records attributed to Francesco Rao.

5 recordsLinked to original sources

PubMed2007

Estimation of folding probabilities and phi values from molecular dynamics simulations of reversible Peptide folding.

Molecular dynamics simulations with an implicit model of the solvent have allowed to investigate the reversible folding of structured peptides. For a 20-residue antiparallel beta-sheet peptide, the simulation results have revealed multiple folding pathways. Moreover, the conformational heterogeneity of the denatured state has been shown to originate from high enthalpy, high entropy basins with fluctuating non-native secondary structure, as well as low enthalpy, low entropy traps. An efficient and simple approach to estimate folding probabilities from molecular dynamics simulations has allowed to isolate conformations in the transition state ensemble and to evaluate Phi values, i.e., the effects of mutations on the folding kinetics and thermodynamic stability. These molecular dynamics studies have provided evidence that, if interpreted by neglecting the non-native interactions, Phi values overestimate the amount of native-like structure in the transition state.

Computer Simulation↗

PubMed2005

Local modularity measure for network clusterizations.

Many complex networks have an underlying modular structure, i.e., structural subunits (communities or clusters) characterized by highly interconnected nodes. The modularity has been introduced as a measure to assess the quality of clusterizations. has a global view, while in many real-world networks clusters are linked mainly locally among each other (local cluster connectivity). Here we introduce a measure of localized modularity , which reflects local cluster structure. Optimization of and on the clusterization of two biological networks shows that the localized modularity identifies more cohesive clusters, yielding a complementary view of higher granularity.

Journal Article↗

PubMed2005

Estimation of protein folding probability from equilibrium simulations.

The assumption that similar structures have similar folding probabilities (p(fold)) leads naturally to a procedure to evaluate p(fold) for every snapshot saved along an equilibrium folding-unfolding trajectory of a structured peptide or protein. The procedure utilizes a structurally homogeneous clustering and does not require any additional simulation. It can be used to detect multiple folding pathways as shown for a three-stranded antiparallel beta-sheet peptide investigated by implicit solvent molecular dynamics simulations.

Biophysics↗

PubMed2005

Phi-value analysis by molecular dynamics simulations of reversible folding.

In Phi-value analysis, the effects of mutations on the folding kinetics are compared with the corresponding effects on thermodynamic stability to investigate the structure of the protein-folding transition state (TS). Here, molecular dynamics (MD) simulations (totaling 0.65 ms) have been performed for a large set of single-point mutants of a 20-residue three-stranded antiparallel beta-sheet peptide. Between 57 and 120 folding events were sampled at near equilibrium for each mutant, allowing for accurate estimates of folding/unfolding rates and stability changes. The Phi values calculated from folding and unfolding rates extracted from the MD trajectories are reliable if the stability loss upon mutation is larger than approximately 0.6 kcal/mol, which is observed for 8 of the 32 single-point mutants. The same heterogeneity of the TS of the wild type was found in the mutated peptides, showing two possible pathways for folding. Single-point mutations can induce significant TS shifts not always detected by Phi-value analysis. Specific nonnative interactions at the TS were observed in most of the peptides studied here. The interpretation of Phi values based on the ratio of atomic contacts at the TS over the native state, which has been used in the past in MD and Monte Carlo simulations, is in agreement with the TS structures of wild-type peptide. However, Phi values tend to overestimate the nativeness of the TS ensemble, when interpreted neglecting the nonnative interactions.

Computer Simulation↗

PubMed2004

The protein folding network.

The conformation space of a 20 residue antiparallel beta-sheet peptide, sampled by molecular dynamics simulations, is mapped to a network. Snapshots saved along the trajectory are grouped according to secondary structure into nodes of the network and the transitions between them are links. The conformation space network describes the significant free energy minima and their dynamic connectivity without requiring arbitrarily chosen reaction coordinates. As previously found for the Internet and the World-Wide Web as well as for social and biological networks, the conformation space network is scale-free and contains highly connected hubs like the native state which is the most populated free energy basin. Furthermore, the native basin exhibits a hierarchical organization, which is not found for a random heteropolymer lacking a predominant free-energy minimum. The network topology is used to identify conformations in the folding transition state (TS) ensemble, and provides a basis for understanding the heterogeneity of the TS and denatured state ensemble as well as the existence of multiple pathways.

Models, Molecular↗