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Michele Vendruscolo

Publications and source records attributed to Michele Vendruscolo.

51 records · Page 3Linked to original sources
PubMed2004

Inhibition of protein crystallization by evolutionary negative design.

Why are proteins so hard to crystallize? We propose an 'evolutionary negative design' principle to explain this difficulty. Proteins have evolved to avoid crystallization because crystallization compromises the viability of the cell. Evolutionary negative design is supported by much evidence in the literature, including the effect of mutations on the crystallizability of a protein, the correlations found in the properties of crystal contacts in bioinformatics databases, and the positive use of protein crystallization by bacteria and viruses.

Biophysical Phenomena↗
PubMed2003

Rare fluctuations of native proteins sampled by equilibrium hydrogen exchange.

We present a method for determining the ensembles of native protein structures that result from the large fluctuations of low probability revealed by hydrogen-exchange experiments. The measured protection factors are used to bias Monte Carlo simulations to sample the structures of the exchange competent species. The approach is illustrated by its application to the case of alpha-lactalbumin.

Humans↗
PubMed2003

Structures and relative free energies of partially folded states of proteins.

The ability of proteins to fold to well defined compact structures is one of the most remarkable examples of the effect of natural selection on biological molecules. To understand their properties, including the stability, the mechanism of folding, and the possibilities of misfolding and association, it is necessary to know the protein free energy landscape. We use NMR data as restraints in a Monte Carlo sampling procedure to determine the ensemble of structures populated by human alpha-lactalbumin in the presence of increasing concentrations of urea. The ensembles of structures that represent the partially folded states of the protein show that two structural cores, corresponding to portions of the alpha and beta domains of the native protein, are preserved even when the native-like interactions that define their existence are substantially weakened. Analysis of the network of residual contacts reveals the presence of a complex interface region between the two structural cores and indicates that the development of specific interactions within this interface is the key step in achieving the native structure. The relative probabilities of the conformations determined from the NMR data are used to construct a coarse-grained free energy landscape for alpha-lactalbumin in the absence of urea. The form of the landscape, together with the existence of distinct cores, supports the concept that robustness and modularity are the properties that make possible the folding of complex proteins.

Humans↗
PubMed2003

Analysis of the distributed computing approach applied to the folding of a small beta peptide.

In the recently proposed distributed computing approach to protein folding a very large number of short independent simulations is performed. Using this method, folding events on a time scale orders of magnitude shorter than the experimental one have been reported. However, it has also been observed that the folding process is not an elementary kinetic step and that the presence of initial lag phases can bias short simulations toward atypical pathways. We study here a 20-residue three-stranded antiparallel beta-sheet peptide whose equilibrium properties can be characterized by atomistic molecular dynamics simulations. We found that the folding rate of this peptide is estimated correctly by the distributed computing approach when trajectories > approximately 1/100 of the equilibrium folding time are considered. We also found that the fastest folding events occur through high-energy pathways, which are unlikely under equilibrium conditions. These very fast folding pathways do not relax within the equilibrium denatured state that is stabilized by the transient presence of both native and non-native interactions, and they are characterized by the nearly simultaneous formation of the two beta-hairpins and a very small number of non-native contacts.

Computer Simulation↗
PubMed2003

Protein folding and misfolding: a paradigm of self-assembly and regulation in complex biological systems.

Understanding biological complexity is one of the grand scientific challenges for the future. A living organism is a highly evolved system made up of a large number of interwoven molecular networks. These networks primarily involve proteins, the macromolecules that enable and control virtually every chemical process that takes place in the cell. Proteins are also key elements in the essential characteristic of living systems, their ability to function and replicate themselves through controlled molecular interactions. Recent progress in understanding the most fundamental aspect of polypeptide self-organization, the process by which proteins fold to attain their active conformations, provides a global platform to gain knowledge about the function of biological systems and the regulatory mechanisms that underpin their ability to adapt to changing conditions. In order to exploit such progress effectively, we are developing a variety of approaches, including procedures that use experimental data to restrain the properties of complex systems in computer simulations, to describe their behaviour under a wide variety of conditions. We believe that such approaches can lead to significant advances in understanding biological complexity, in general, and protein folding and misfolding in particular. These advances would contribute to: a more effective exploitation of the information from genome sequences; more rational therapeutic approaches to diseases, particularly those associated with ageing; the responsible control of our own evolution; and the development of new technologies based on mimicking the principles of biological self-assembly, for instance in nanotechnology. More fundamentally, we believe that this research will result in a more coherent understanding of the origin, evolution and functional properties of living systems.

Alzheimer Disease↗
PubMed2003

Self-consistent determination of the transition state for protein folding: application to a fibronectin type III domain.

We present a general approach in which theory and experiments are combined in an iterative manner to provide a detailed description of the transition state ensemble (TSE) for folding. The method is illustrated by applying it to TNfn3, a fibronectin type III domain protein. In the first iteration, a coarse-grained determination of the TSE is carried out by using a limited set of experimental phi values as constraints in a molecular dynamics sampling simulation. The resulting model of the TSE is used to determine the additional residues whose phi value measurement would provide the most information for refining the TSE. Successive iterations with an increasing number of phi value measurements are carried out until no further changes in the properties of the TSE are detected or there are no additional residues whose phi values can be measured. In the study of TNfn3 three iterations were necessary to achieve self-consistency. A retrospective application of the method can be used to determine the accuracy of the TSE results and to find "key residues" for folding, i.e., those that are most important for the formation of the TSE. The approach reported here is an efficient method for finding the structures that make up the TSEs for protein folding. Its use will improve future efforts for their experimental determination and refinement.

Fibronectins↗
PubMed2003

Statistical properties of neutral evolution.

Neutral evolution is the simplest model of molecular evolution and thus it is most amenable to a comprehensive theoretical investigation. In this paper, we characterize the statistical properties of neutral evolution of proteins under the requirement that the native state remains thermodynamically stable, and compare them to the ones of Kimura's model of neutral evolution. Our study is based on the Structurally Constrained Neutral (SCN) model which we recently proposed. We show that, in the SCN model, the substitution rate decreases as longer time intervals are considered. Fluctuations from one branch of the evolutionary tree to another are strong, leading to a non-Poissonian statistics for the substitution process. Such strong fluctuations are in part due to the fact that neutral substitution rates for individual residues are strongly correlated for most residue pairs. Interestingly, structurally conserved residues, characterized by a much below average substitution rate, are also much less correlated to other residues and evolve in a much more regular way. Our results can improve methods aimed at distinguishing between neutral and adaptive substitutions as well as methods for computing the expected number of substitutions occurred since the divergence of two protein sequences. In particular, we compute the minimal sequence similarity below which no information about the evolutionary divergence of the compared sequences can be obtained.

Amino Acid Substitution↗
PubMed2003

Calculation of mutational free energy changes in transition states for protein folding.

Recent advances in experimental and computational methods have made it possible to determine with considerable accuracy the structures whose formation is rate limiting for the folding of some small proteins-the transition state ensemble, or TSE. We present a method to analyze and validate all-atom models of such structures. The method is based on the comparison of experimental data with the computation of the change in free energy of the TSE resulting from specific mutations. Each mutation is modeled individually in all members of an ensemble of transition state structures using a method originally developed to predict mutational changes in the stability of native proteins. We first apply this method to six proteins for which we have determined the TSEs with a technique that uses experimental mutational data (Phi-values) as restraints in the structure determination and find a highly significant correlation between the calculated free energy changes and those derived from experimental kinetic data. We then use the procedure to analyze transition state structures determined by molecular dynamics simulations of unfolding, again finding a high correlation. Finally, we use the method to estimate changes in folding rates of several hydrophobic core mutants of Fyn SH3. Taken together, these results show that the procedure developed here is a tool of general validity for analyzing, assessing, and improving the quality of the structures of transition states for protein folding.

Amino Acid Sequence↗
PubMed2003

Protein folding: bringing theory and experiment closer together.

The ability to perform enzymatic function by harnessing random molecular motion into self-organized protein structures is one of the most fascinating results of evolution. A close interplay between theory and experiment is driving the progress in understanding the principles that determine the behaviour of proteins. New techniques that significantly increase the amount of information obtainable from experimental data have been recently proposed; it is now becoming possible to describe at atomic resolution the events that take place during the folding process. Successful predictions of these events are being reported at an increasing rate and general principles are being outlined.

Computer Simulation↗
PubMed2002

Determination of a transition state at atomic resolution from protein engineering data.

We present a method for determining the structure of the transition state ensemble (TSE) of a protein by using phi values derived from protein engineering experiments as restraints in molecular dynamics simulations employing a realistic all-atom molecular mechanics energy function. The method uses a biasing potential to select an ensemble of structures having phi values in agreement with the experimental data set. An application to acylphosphatase (AcP), a protein for which phi values have been measured for 24 out of 98 residues, illustrates the approach. The properties of the TSE determined in this way are compared with those of a coarse-grained model obtained using a Monte Carlo (MC) sampling method based on a C(alpha) representation of the structure. The two TSEs determined at different structural resolution are consistent and complementary. While the C(alpha) model allows better sampling of the conformation space occupied by the transition state, the all-atom model offers a more detailed description of the structural and energetic properties of the conformations included in the TSE. The combination of low-resolution C(alpha) results with all-atom molecular dynamics simulations provides a powerful and general method for determining the nature of TSEs from protein engineering data.

Acid Anhydride Hydrolases↗
PubMed2002

Lack of self-averaging in neutral evolution of proteins.

We simulate neutral evolution of proteins imposing conservation of the thermodynamic stability of the native state in the framework of an effective model of folding thermodynamics. This procedure generates evolutionary trajectories in sequence space which share two universal features for all of the examined proteins. First, the number of neutral mutations fluctuates broadly from one sequence to another, leading to a non-Poissonian substitution process. Second, the number of neutral mutations displays strong correlations along the trajectory, thus causing the breakdown of self-averaging of the resulting evolutionary substitution process.

Cytochrome c Group↗
PubMed2002

Native and non-native interactions along protein folding and unfolding pathways.

Gō-type models, which include only native contact interactions in the energy function, are being used increasingly to describe the protein folding reaction. To investigate the validity of such models, we determine the role of native and non-native interactions along folding and unfolding pathways. For this purpose, we use a molecular mechanics energy function with an implicit solvation model (an effective energy function or potential of mean force) that can be expressed in a pairwise decomposable form. We find that for the native state and a wide range of other configurations, the contact energy is an accurate description, in part due to the cancellation of non-zero contributions from more distant residues. However, significant errors in the energy are introduced for non-native structures if the energy is calculated from the native contacts alone. Non-native contacts tend to make a significant contribution, particularly for molten globules and collapsed states along the unfolding pathways. The implication of these results for the use of Gō-type models in studies of protein folding are discussed.

Amino Acids↗
PubMed2002

Automated assignment of SCOP and CATH protein structure classifications from FSSP scores.

We present an automated procedure to assign CATH and SCOP classifications to proteins whose FSSP score is available. CATH classification is assigned down to the topology level, and SCOP classification is assigned to the fold level. Because the FSSP database is updated weekly, this method makes it possible to update also CATH and SCOP with the same frequency. Our predictions have a nearly perfect success rate when ambiguous cases are discarded. These ambiguous cases are intrinsic in any protein structure classification that relies on structural information alone. Hence, we introduce the "twilight zone for structure classification." We further suggest that to resolve these ambiguous cases, other criteria of classification, based also on information about sequence and function, must be used.

Algorithms↗
PubMed2002

Validity of Gō models: comparison with a solvent-shielded empirical energy decomposition.

Do Gō-type model potentials provide a valid approach for studying protein folding? They have been widely used for this purpose because of their simplicity and the speed of simulations based on their use. The essential assumption in such models is that only contact interactions existing in the native state determine the energy surface of a polypeptide chain, even for non-native configurations sampled along folding trajectories. Here we use an all-atom molecular mechanics energy function to investigate the adequacy of Gō-type potentials. We show that, although the contact approximation is accurate, non-native contributions to the energy can be significant. The assumed relation between residue-residue interaction energies and the number of contacts between them is found to be only approximate. By contrast, individual residue energies correlate very well with the number of contacts. The results demonstrate that models based on the latter should give meaningful results (e.g., as used to interpret phi values), whereas those that depend on the former are only qualitative, at best.

Computer Simulation↗