Can molecular dynamics simulations help in discriminating correct from erroneous protein 3D models?

Influence of the single-strand linker composition on the structural/dynamical properties of a truncated octahedral DNA nano-cage family

The structural/dynamical properties of three truncated octahedral DNA nano-cages composed by identical double helices but single strand linkers with different composition, namely 7 thymidines, 7 adenines, and 7 alternated thymidines and adenines, have been investigated through classical molecular dynamics simulations. Trajectories have been analyzed to investigate the role of the linkers in defining nano-cages stability and flexibility, including possible influence on the internal cages motions. The data indicate that the cages behavior is almost identical and that the structural/dynamical parameters measured along the trajectories are not particularly affected by the presence of different bases. These results demonstrate that the constraints imposed by the nano-structure geometry are the main factor in modulating these properties

Partial unfolding and refolding for structure refinement: A unified approach of geometric simulations and molecular dynamics

The most successful protein structure prediction methods to date have been template-based modeling (TBM) or homology modeling, which predicts protein structure based on experimental structures. These high accuracy predictions sometimes retain structural errors due to incorrect templates or a lack of accurate templates in the case of low sequence similarity, making these structures inadequate in drug-design studies or molecular dynamics simulations. We have developed a new physics based approach to the protein refinement problem by mimicking the mechanism of chaperons that rehabilitate misfolded proteins. The template structure is unfolded by selectively (targeted) pulling on different portions of the protein using the geometric based technique FRODA, and then refolded using hierarchically restrained replica exchange molecular dynamics simulations (hr-REMD). FRODA unfolding is used to create a diverse set of topologies for surveying near native-like structures from a template and to provide a set of persistent contacts to be employed during re-folding. We have tested our approach on 13 previous CASP targets and observed that this method of folding an ensemble of partially unfolded structures, through the hierarchical addition of contact restraints (that is, first local and then nonlocal interactions), leads to a refolding of the structure along with refinement in most cases (12/13). Although this approach yields refined models through advancement in sampling, the task of blind selection of the best refined models still needs to be solved. Overall, the method can be useful for improved sampling for low resolution models where certain of the portions of the structure are incorrectly modeled.

Understanding the mechanism of atovaquone drug resistance in Plasmodium falciparum cytochrome b mutation Y268S using computational methods

The rapid appearance of resistant malarial parasites after introduction of atovaquone (ATQ) drug has prompted the search for new drugs as even single point mutations in the active site of Cytochrome b protein can rapidly render ATQ ineffective. The presence of Y268 mutations in the Cytochrome b (Cyt b) protein is previously suggested to be responsible for the ATQ resistance in Plasmodium falciparum (P. falciparum). In this study, we examined the resistance mechanism against ATQ in P. falciparum through computational methods. Here, we reported a reliable protein model of Cyt bc1 complex containing Cyt b and the Iron-Sulphur Protein (ISP) of P. falciparum using composite modeling method by combining threading, ab initio modeling and atomic-level structure refinement approaches. The molecular dynamics simulations suggest that Y268S mutation causes ATQ resistance by reducing hydrophobic interactions between Cyt bc1 protein complex and ATQ. Moreover, the important histidine contact of ATQ with the ISP chain is also lost due to Y268S mutation. We noticed the induced mutation alters the arrangement of active site residues in a fashion that enforces ATQ to find its new stable binding site far away from the wild-type binding pocket. The MM-PBSA calculations also shows that the binding affinity of ATQ with Cyt bc1 complex is enough to hold it at this new site that ultimately leads to the ATQ resistance.

Solution and crystallographic structures of the central region of the phosphoprotein from human metapneumovirus

Human metapneumovirus (HMPV) of the family Paramyxoviridae is a major cause of respiratory illness worldwide. Phosphoproteins (P) from Paramyxoviridae are essential co-factors of the viral RNA polymerase that form tetramers and possess long intrinsically disordered regions (IDRs). We located the central region of HMPV P (P(ced)) which is involved in tetramerization using disorder analysis and modeled its 3D structure ab initio using Rosetta fold-and-dock. We characterized the solution-structure of P(ced) using small angle X-ray scattering (SAXS) and carried out direct fitting to the scattering data to filter out incorrect models. Molecular dynamics simulations (MDS) and ensemble optimization were employed to select correct models and capture the dynamic character of P(ced). Our analysis revealed that oligomerization involves a compact central core located between residues 169-194 (P(core)), that is surrounded by flexible regions with α-helical propensity. We crystallized this fragment and solved its structure at 3.1 Å resolution by molecular replacement, using the folded core from our SAXS-validated ab initio model. The RMSD between modeled and experimental tetramers is as low as 0.9 Å, demonstrating the accuracy of the approach. A comparison of the structure of HMPV P to existing mononegavirales P(ced) structures suggests that P(ced) evolved under weak selective pressure. Finally, we discuss the advantages of using SAXS in combination with ab initio modeling and MDS to solve the structure of small, homo-oligomeric protein complexes.

Statistical significance of threading scores

We present a general method for assessing threading score significance. The threading score of a protein sequence, thread onto a given structure, should be compared with the threading score distribution of a random amino-acid sequence, of the same length, thread on the same structure; small p-values point significantly high scores. We claim that, due to general protein contact map properties, this reference distribution is a Weibull extreme value distribution whose parameters depend on the threading method, the structure, the length of the query and the random sequence simulation model used. These parameters can be estimated off-line with simulated sequence samples, for different sequence lengths. They can further be interpolated at the exact length of a query, enabling the quick computation of the p-value.

Smoothing protein energy landscapes by integrating folding models with structure prediction

Decades of work has investigated the energy landscapes of simple protein models, but what do the landscapes of real, large, atomically detailed proteins look like? We explore an approach to this problem that systematically extracts simple funnel models of actual proteins using ensembles of structure predictions and physics-based atomic force fields and sampling. Central to our effort are calculations of a quantity called the relative entropy, which quantifies the extent to which a given set of structure decoys and a putative native structure can be projected onto a theoretical funnel description. We examine 86 structure prediction targets and one coupled folding-binding system, and find that in a majority of cases the relative entropy robustly signals which structures are nearest to native (i.e., which appear to lie closest to a funnel bottom). Importantly, the landscape model improves substantially upon purely energetic measures in scoring decoys. Our results suggest that physics-based models-including both folding theories and all-atom force fields-may be successfully integrated with structure prediction efforts. Conversely, detailed predictions of structures and the relative entropy approach enable one to extract coarse topographic features of protein landscapes that may enhance the development and application of simpler folding models.

STRIKE: evaluation of protein MSAs using a single 3D structure

MOTIVATION

Evaluating alternative multiple protein sequence alignments is an important unsolved problem in Biology. The most accurate way of doing this is to use structural information. Unfortunately, most methods require at least two structures to be embedded in the alignment, a condition rarely met when dealing with standard datasets.

RESULT

We developed STRIKE, a method that determines the relative accuracy of two alternative alignments of the same sequences using a single structure. We validated our methodology on three commonly used reference datasets (BAliBASE, Homestrad and Prefab). Given two alignments, STRIKE manages to identify the most accurate one in 70% of the cases on average. This figure increases to 79% when considering very challenging datasets like the RV11 category of BAliBASE. This discrimination capacity is significantly higher than that reported for other metrics such as Contact Accepted mutation or Blosum. We show that this increased performance results both from a refined definition of the contacts and from the use of an improved contact substitution score.

CONTACT

cedric.notredame@crg.eu

AVAILABILITY

STRIKE is an open source freeware available from www.tcoffee.org

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Weighted relative entropy for alignment-free sequence comparison based on Markov model

In this paper, we introduce a probabilistic measure for computing the similarity between two biological sequences without alignment. The computation of the similarity measure is based on the Kullback-Leibler divergence of two constructed Markov models. We firstly validate the method on clustering nine chromosomes from three species. Secondly, we give the result of similarity search based on our new method. We lastly apply the measure to the construction of phylogenetic tree of 48 HEV genome sequences. Our results indicate that the weighted relative entropy is an efficient and powerful alignment-free measure for the analysis of sequences in the genomic scale.

Toward a consensus model of the HERG potassium channel

Malfunction of hERG potassium channels, due to inherited mutations or inhibition by drugs, can cause long QT syndrome, which can lead to life-threatening arrhythmias. A three-dimensional structure of hERG is a prerequisite to understand the molecular basis of hERG malfunction. To achieve a consensus model, we carried out an extensive analysis of hERG models based on various alignments of helix S5. We analyzed seven models using a combination of conventional geometry/packing/normality validation methods as well as molecular dynamics simulations and molecular docking. A synthetic test set with the X-ray crystal structure of K(v)1.2 with artificially shifted S5 sequences modeled into the structure served as a reference case. We docked the known hERG inhibitors (+)-cisapride, (S)-terfenadine, and MK-499 into the hERG models and simulation snapshots. None of the single analyses unambiguously identified a preferred model, but the combination of all three revealed that there is only one model that fulfils all quality criteria. This model is confirmed by a recent mutation scanning experiment (P. Ju, G. Pages, R. P. Riek, P. C. Chen, A. M. Torres, P. S. Bansal, S. Kuyucak, P. W. Kuchel, J. I. Vandenberg, J. Biol. Chem. 2009, 284, 1000-1008). We expect the modeled structure to be useful as a basis both for computational studies of channel function and kinetics as well as the design of experiments.

Symmetry-restrained molecular dynamics simulations improve homology models of potassium channels

Most crystallized homo-oligomeric ion channels are highly symmetric, which dramatically decreases conformational space and facilitates building homology models (HMs). However, in molecular dynamics (MD) simulations channels deviate from ideal symmetry and accumulate thermal defects, which complicate the refinement of HMs using MD. In this work we evaluate the ability of symmetry constrained MD simulations to improve HMs accuracy, using an approach conceptually similar to Critical Assessment of techniques for protein Structure Prediction (CASP) competition: build HMs of channels with known structure and evaluate the efficiency of proposed methods in improving HMs accuracy (measured as deviation from experimental structure). Results indicate that unrestrained MD does not improve the accuracy of HMs, instantaneous symmetrization improves accuracy but not stability of HMs during subsequent unrestrained MD, while gradually imposing symmetry constraints improves both accuracy (by 5-50%) and stability of HMs. Moreover, accuracy and stability are strongly correlated, making stability a reliable criterion in predicting the accuracy of new HMs. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

Non-Markovian noise mediated through anomalous diffusion within ion channels

It is evident from a wide range of experimental findings that ion channel gating is inherently stochastic. The issue of "memory effects" (diffusional retardation due to local changes in water viscosity) in ionic flow has been recently addressed using Brownian dynamics simulations. The results presented indicate such memory effects are negligible, unless the diffusional barrier is much higher than that of free solute. In this paper using differential stochastic methods we conclude that the Markovian property of exponential dwell times gives rise to a high barrier, resulting in diffusional memory effects that cannot be ignored in determining ionic flow through channels. We have addressed this question using a generalized Langevin equation that contains a combination of Markovian and non-Markovian processes with different time scales. This approach afforded the development of an algorithm that describes an oscillatory ionic diffusional sequence. The resulting oscillatory function behavior, with exponential decay, was obtained at the weak non-Markovian limit with two distinct time scales corresponding to the processes of ionic diffusion and drift. This will be analyzed further in future studies using molecular dynamics simulations. We propose that the rise of time scales and memory effects is related to differences of shear viscosity in the cytoplasm and extracellular matrix.