Alberto Perez

A consensus view of protein dynamics

The dynamics of proteins in aqueous solution has been investigated through a massive approach based on “state of the art” molecular dynamics simulations performed for all protein metafolds using the four most popular force fields (OPLS, CHARMM, AMBER, and GROMOS). A detailed analysis of the massive database of trajectories (>1.5 terabytes of data obtained using ≈50 years of CPU) allowed us to obtain a robust-consensus picture of protein dynamics in aqueous solution.

Essential Dynamics: A Tool for Efficient Trajectory Compression and Management

We present a simple method for compression and management of very large molecular dynamics trajectories. The approach is based on the projection of the Cartesian snapshots collected along the trajectory into an orthogonal space defined by the eigenvectors obtained by diagonalization of the covariance matrix. The transformation is mathematically exact when the number of eigenvectors equals 3N-6 (N being the number of atoms), and in practice very accurate even when the number of eigenvectors is much smaller, permitting a dramatic reduction in the size of trajectory files. In addition, we have examined the ability of the method, when combined with interpolation, to recover dense samplings (snapshots collected at a high frequency) from more sparse (lower frequency) data as a method for further data compression. Finally, we have investigated the possibility of using the approach when extrapolating the behavior of the system to times longer than the original simulation period. Overall our results suggest that the method is an attractive alternative to current approaches for including dynamic information in static structure files such as those deposited in the Protein Data Bank.

MoDEL (Molecular Dynamics Extended Library): A Database of Atomistic Molecular Dynamics Trajectories

More than 1700 trajectories of proteins representative of monomeric soluble structures in the protein data bank (PDB) have been obtained by means of state-of-the-art atomistic molecular dynamics simulations in near-physiological conditions. The trajectories and analyses are stored in a large data warehouse, which can be queried for dynamic information on proteins, including interactions. Here, we describe the project and the structure and contents of our database, and provide examples of how it can be used to describe the global flexibility properties of proteins. Basic analyses and trajectories stripped of solvent molecules at a reduced resolution level are available from our web server.

Assessment of protein structure refinement in CASP9.

We assess performance in the structure refinement category in CASP9. Two years after CASP8, the performance of the best groups has not improved. There are few groups that improve any of our assessment scores with statistical significance. Some predictors, however, are able to consistently improve the physicality of the models. Although we cannot identify any clear bottleneck in improving refinement, several points arise: (1) The refinement portion of CASP has too few targets to make many statistically meaningful conclusions. (2) Predictors are usually very conservative, limiting the possibility of large improvements in models. (3) No group is actually able to correctly rank their five submissions—indicating that potentially better models may be discarded. (4) Different sampling strategies work better for different refinement problems; there is no single strategy that works on all targets. In general, conservative strategies do better, while the greatest improvements come from more adventurous sampling—at the cost of consistency. Comparison with experimental data reveals aspects not captured by comparison to a single structure. In particular, we show that improvement in backbone geometry does not always mean better agreement with experimental data. Finally, we demonstrate that even given the current challenges facing refinement, the refined models are useful for solving the crystallographic phase problem through molecular replacement. Proteins 2011;.

Impact of Methylation on the Physical Properties of DNA

There is increasing evidence for the presence of an alternative code imprinted in the genome that might contribute to gene expression regulation through an indirect reading mechanism. In mammals, components of this coarse-grained regulatory mechanism include chromatin structure and epigenetic signatures, where d(CpG) nucleotide steps are key players. We report a comprehensive experimental and theoretical study of d(CpG) steps that provides a detailed description of their physical characteristics and the impact of cytosine methylation on these properties. We observed that methylation changes the physical properties of d(CpG) steps, having a dramatic effect on enriched CpG segments, such as CpG islands. We demonstrate that methylation reduces the affinity of DNA to assemble into nucleosomes, and can affect nucleosome positioning around transcription start sites. Overall, our results suggest a mechanism by which the basic physical properties of the DNA fiber can explain parts of the cellular epigenetic regulatory mechanisms.

Exploring polymorphisms in B-DNA helical conformations

The traditional mesoscopic paradigm represents DNA as a series of base-pair steps whose energy response to equilibrium perturbations is elastic, with harmonic oscillations (defining local stiffness) around a single equilibrium conformation. In addition, base sequence effects are often analysed as a succession of independent XpY base-pair steps (i.e. a nearest-neighbour (NN) model with only 10 unique cases). Unfortunately, recent massive simulations carried out by the ABC consortium suggest that the real picture of DNA flexibility may be much more complex. The paradigm of DNA flexibility therefore needs to be revisited. In this article, we explore in detail one of the most obvious violations of the elastic NN model of flexibility: the bimodal distributions of some helical parameters. We perform here an in-depth statistical analysis of a very large set of MD trajectories and also of experimental structures, which lead to very solid evidence of bimodality. We then suggest ways to improve mesoscopic models to account for this deviation from the elastic regime.

Advances in free-energy-based simulations of protein folding and ligand binding.

Free-energy-based simulations are increasingly providing the narratives about the structures, dynamics and biological mechanisms that constitute the fabric of protein science. Here, we review two recent successes. It is becoming practical: first, to fold small proteins with free-energy methods without knowing substructures and second, to compute ligand-protein binding affinities, not just their binding poses. Over the past 40 years, the timescales that can be simulated by atomistic MD are doubling every 1.3 years--which is faster than Moores law. Thus, these advances are not simply due to the availability of faster computers. Force fields, solvation models and simulation methodology have kept pace with computing advancements, and are now quite good. At the tip of the spear recently are GPU-based computing, improved fast-solvation methods, continued advances in force fields, and conformational sampling methods that harness external information.

8-Amino guanine accelerates tetramolecular G-quadruplex formation

We demonstrate here that 8-amino guanine () strongly accelerates quadruplex formation, which makes this nucleobase the most attractive replacement for guanine in the context of tetramolecular parallel quadruplexes.

Determining protein structures by combining semireliable data with atomistic physical models by Bayesian inference.

Significance Modeling Employing Limited Data (MELD) is a method of integrative structural biology. It serves to determine protein structures by a Bayesian approach combining physical models with experimental data that are only semireliable, by virtue of being either too sparse, too ambiguous, or too uncertain. For eight proteins for which both the correct native structure and semireliable data were available, MELD gives excellent structures. More than 100,000 protein structures are now known at atomic detail. However, far more are not yet known, particularly among large or complex proteins. Often, experimental information is only semireliable because it is uncertain, limited, or confusing in important ways. Some experiments give sparse information, some give ambiguous or nonspecific information, and others give uncertain information—where some is right, some is wrong, but we don’t know which. We describe a method called Modeling Employing Limited Data (MELD) that can harness such problematic information in a physics-based, Bayesian framework for improved structure determination. We apply MELD to eight proteins of known structure for which such problematic structural data are available, including a sparse NMR dataset, two ambiguous EPR datasets, and four uncertain datasets taken from sequence evolution data. MELD gives excellent structures, indicating its promise for experimental biomolecule structure determination where only semireliable data are available.

DNAlive: a tool for the physical analysis of DNA at the genomic scale.

SUMMARYnDNAlive is a tool for the analysis and graphical display of structural and physical characteristics of genomic DNA. The web server implements a wide repertoire of metrics to derive physical information from DNA sequences with a powerful interface to derive 3D information on large sequences of both naked and protein-bound DNAs. Furthermore, it implements a mesoscopic Metropolis code which allows the inexpensive study of the dynamic properties of chromatin fibers. In addition, our server also surveys other protein and genomic databases allowing the user to combine and explore the physical properties of selected DNA in the context of functional features annotated on those regions.nnnAVAILABILITYnhttp://mmb.pcb.ub.es/DNAlive/ ; http://www.inab.org/