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

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 Added by Cristian Micheletti
 Publication date 2001
  fields Physics
and research's language is English




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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.



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We develop a theoretical approach to the protein folding problem based on out-of-equilibrium stochastic dynamics. Within this framework, the computational difficulties related to the existence of large time scale gaps in the protein folding problem are removed and simulating the entire reaction in atomistic details using existing computers becomes feasible. In addition, this formalism provides a natural framework to investigate the relationships between thermodynamical and kinetic aspects of the folding. For example, it is possible to show that, in order to have a large probability to remain unchanged under Langevin diffusion, the native state has to be characterized by a small conformational entropy. We discuss how to determine the most probable folding pathway, to identify configurations representative of the transition state and to compute the most probable transition time. We perform an illustrative application of these ideas, studying the conformational evolution of alanine di-peptide, within an all-atom model based on the empiric GROMOS96 force field.
Current all-atom potential based molecular dynamics (MD) allow the identification of a proteins 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.
A theoretical model for the folding of proteins containing disulfide bonds is introduced. The model exploits the knowledge of the native state to favour the progressive establishment of native interactions. At variance with traditional approaches based on native topology, not all native bonds are treated in the same way; in particular, a suitable energy term is introduced to account for the special strength of disulfide bonds (irrespective of whether they are native or not) as well as their ability to undergo intra-molecular reshuffling. The model thus possesses the minimal ingredients necessary to investigated the much debated issue of whether the re-folding process occurs through partially structured intermediates with native or non-native disulfide bonds. This strategy is applied to a context of particular interest, the re-folding process of Hirudin, a thrombin-specific protease inhibitor, for which conflicting folding pathways have been proposed. We show that the only two parameters in the model (temperature and disulfide strength) can be tuned to reproduce well a set of experimental transitions between species with different number of formed disulfide. This model is then used to provide a characterisation of the folding process and a detailed description of the species involved in the rate-limiting step of Hirudin refolding.
An exactly solvable model based on the topology of a protein native state is applied to identify bottlenecks and key-sites for the folding of HIV-1 Protease. The predicted sites are found to correlate well with clinical data on resistance to FDA-approved drugs. It has been observed that the effects of drug therapy are to induce multiple mutations on the protease. The sites where such mutations occur correlate well with those involved in folding bottlenecks identified through the deterministic procedure proposed in this study. The high statistical significance of the observed correlations suggests that the approach may be promisingly used in conjunction with traditional techniques to identify candidate locations for drug attacks.
The dynamics of dissipative soft-sphere gases obeys Newtons equation of motion which are commonly solved numerically by (force-based) Molecular Dynamics schemes. With the assumption of instantaneous, pairwise collisions, the simulation can be accelerated considerably using event-driven Molecular Dynamics, where the coefficient of restitution is derived from the interaction force between particles. Recently it was shown, however, that this approach may fail dramatically, that is, the obtained trajectories deviate significantly from the ones predicted by Newtons equations. In this paper, we generalize the concept of the coefficient of restitution and derive a numerical scheme which, in the case of dilute systems and frictionless interaction, allows us to perform highly efficient event-driven Molecular Dynamics simulations even for non-instantaneous collisions. We show that the particle trajectories predicted by the new scheme agree perfectly with the corresponding (force-based) Molecular Dynamics, except for a short transient period whose duration corresponds to the duration of the contact. Thus, the new algorithm solves Newtons equations of motion like force-based MD while preserving the advantages of event-driven simulations.
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