Optimal prediction of folding rates and transition state placement from native state geometry

A variety of experimental and theoretical studies have established that the folding process of monomeric proteins is strongly influenced by the topology of the native state. In particular, folding times have been shown to correlate well with the contact order, a measure of contact locality. Our investigation focuses on identifying additional topologic properties that correlate with experimentally measurable quantities, such as folding rates and transition state placement, for both two- and three-state folders. The validation against data from forty experiments shows that a particular topologic property which measures the interdepedence of contacts, termed cliquishness or clustering coefficient, can account with significant accuracy both for the transition state placement and especially for folding rates, the linear correlation coefficient being $r=0.71$. This result can be further improved to $r=0.74$, by optimally combining the distinct topologic information captured by cliquishness and contact order.Comment: Revtex, 15 pages, 8 figure

Probing the entanglement and locating knots in ring polymers: a comparative study of different arc closure schemes

The interplay between the topological and geometrical properties of a polymer ring can be clarified by establishing the entanglement trapped in any portion (arc) of the ring. The task requires to close the open arcs into a ring, and the resulting topological state may depend on the specific closure scheme that is followed. To understand the impact of this ambiguity in contexts of practical interest, such as knot localization in a ring with non trivial topology, we apply various closure schemes to model ring polymers. The rings have the same length and topological state (a trefoil knot) but have different degree of compactness. The comparison suggests that a novel method, termed the minimally-interfering closure, can be profitably used to characterize the arc entanglement in a robust and computationally-efficient way. This closure method is finally applied to the knot localization problem which is tackled using two different localization schemes based on top-down or bottom-up searches.Comment: 9 pages, 7 figures. Submitted to Progress of Theoretical Physic

Accurate and efficient description of protein vibrational dynamics: comparing molecular dynamics and Gaussian models

Current all-atom potential based molecular dynamics (MD) allow the identification of a protein's functional motions on a wide-range of time-scales, up to few tens of ns. However, functional large scale motions of proteins may occur on a time-scale currently not accessible by all-atom potential based molecular dynamics. To avoid the massive computational effort required by this approach several simplified schemes have been introduced. One of the most satisfactory is the Gaussian Network approach based on the energy expansion in terms of the deviation of the protein backbone from its native configuration. Here we consider an extension of this model which captures in a more realistic way the distribution of native interactions due to the introduction of effective sidechain centroids. Since their location is entirely determined by the protein backbone, the model is amenable to the same exact and computationally efficient treatment as previous simpler models. The ability of the model to describe the correlated motion of protein residues in thermodynamic equilibrium is established through a series of successful comparisons with an extensive (14 ns) MD simulation based on the AMBER potential of HIV-1 protease in complex with a peptide substrate. Thus, the model presented here emerges as a powerful tool to provide preliminary, fast yet accurate characterizations of proteins near-native motion.Comment: 14 pages 7 figure

Recurrent oligomers in proteins - an optimal scheme reconciling accurate and concise backbone representations in automated folding and design studies

A novel scheme is introduced to capture the spatial correlations of consecutive amino acids in naturally occurring proteins. This knowledge-based strategy is able to carry out optimally automated subdivisions of protein fragments into classes of similarity. The goal is to provide the minimal set of protein oligomers (termed ``oligons'' for brevity) that is able to represent any other fragment. At variance with previous studies where recurrent local motifs were classified, our concern is to provide simplified protein representations that have been optimised for use in automated folding and/or design attempts. In such contexts it is paramount to limit the number of degrees of freedom per amino acid without incurring in loss of accuracy of structural representations. The suggested method finds, by construction, the optimal compromise between these needs. Several possible oligon lengths are considered. It is shown that meaningful classifications cannot be done for lengths greater than 6 or smaller than 4. Different contexts are considered were oligons of length 5 or 6 are recommendable. With only a few dozen of oligons of such length, virtually any protein can be reproduced within typical experimental uncertainties. Structural data for the oligons is made publicly available.Comment: 19 pages, 13 postscript figure

Convergent dynamics in the protease enzymatic superfamily

Proteases regulate various aspects of the life cycle in all organisms by cleaving specific peptide bonds. Their action is so central for biochemical processes that at least 2% of any known genome encodes for proteolytic enzymes. Here we show that selected proteases pairs, despite differences in oligomeric state, catalytic residues and fold, share a common structural organization of functionally relevant regions which are further shown to undergo similar concerted movements. The structural and dynamical similarities found pervasively across evolutionarily distant clans point to common mechanisms for peptide hydrolysis.Comment: 13 pages, 6 figure

Molecular Dynamics Studies on HIV-1 Protease: Drug Resistance and Folding Pathways

Drug resistance to HIV-1 Protease involves accumulation of multiple mutations in the protein. Here we investigate the role of these mutations by using molecular dynamics simulations which exploit the influence of the native-state topology in the folding process. Our calculations show that sites contributing to phenotypic resistance of FDA-approved drugs are among the most sensitive positions for the stability of partially folded states and should play a relevant role in the folding process. Furthermore, associations between amino acid sites mutating under drug treatment are shown to be statistically correlated. The striking correlation between clinical data and our calculations suggest a novel approach to the design of drugs tailored to bind regions crucial not only for protein function but also for folding.Comment: Revtex, 14 pages, 7 eps figures. Proteins, Structure Function and Genetics, in press (2001

Variational approach to protein design and extraction of interaction potentials

We present and discuss a novel approach to the direct and inverse protein folding problem. The proposed strategy is based on a variational approach that allows the simultaneous extraction of amino acid interactions and the low-temperature free energy of sequences of amino acids. The knowledge-based technique is simple and straightforward to implement even for realistic off-lattice proteins because it does not entail threading-like procedures. Its validity is assessed in the context of a lattice model by means of a variety of stringent checks.Comment: 5 pages, 3 figure