PACSAB Server: A Web-Based Tool for the Study of Aggregation and the Conformational Ensemble of Disordered and Folded Proteins.

We present in this article the PACSAB server, which is designed to provide information about the structural ensemble and interactions of both stable and disordered proteins to researchers in the field of molecular biology. The use of this tool does not require any computational skills as the user just needs to upload the structure of the protein to be studied; the server runs a simulation with the PACSAB model, a highly accurate coarse-grained model that is much more efficient than standard molecular dynamics for the exploration of the conformational space of multiprotein systems. The trajectories generated by the simulations based on this model reveal the propensity of the protein under study for aggregation, identify the residues playing a central role in the aggregation process, and reproduce the whole conformational space of disordered proteins. All of this information is shown and can be downloaded from the web page.

Universal ion-transport descriptors and classes of inorganic solid-state electrolytes.

Solid-state electrolytes (SSEs) with high ion conductivity are pivotal for the development and large-scale adoption of green-energy conversion and storage technologies such as fuel cells, electrocatalysts and solid-state batteries. Yet, SSEs are extremely complex materials for which general rational design principles remain indeterminate. Here, we combine first-principles materials modelling, computational power and modern data analysis techniques to advance towards the solution of such a fundamental and technologically pressing problem. Our data-driven survey reveals that the correlations between ion diffusivity and other materials descriptors in general are monotonic, although not necessarily linear, and largest when the latter are of vibrational nature and explicitly incorporate anharmonic effects. Surprisingly, principal component and k-means clustering analyses show that elastic and vibrational descriptors, rather than the usual ones related to chemical composition and ion mobility, are best suited for reducing the high complexity of SSEs and classifying them into universal classes. Our findings highlight the need for considering databases that incorporate temperature effects to improve our understanding of SSEs and point towards a generalized approach to the design of energy materials.

Accurate Description of Protein-Protein Recognition and Protein Aggregation with the Implicit-Solvent-Based PACSAB Protein Model.

We used the PACSAB protein model, based on the implicit solvation approach, to simulate protein-protein recognition and study the effect of helical structure on the association of aggregating peptides. After optimization, the PACSAB force field was able to reproduce correctly both the correct binding interface in ubiquitin dimerization and the conformational ensemble of the disordered protein activator for hormone and retinoid receptor (ACTR). The PACSAB model allowed us to predict the native binding of ACTR with its binding partner, reproducing the refolding upon binding mechanism of the disordered protein.

Effect of the Water Model in Simulations of Protein-Protein Recognition and Association.

We study self-association of ubiquitin and the disordered protein ACTR using the most commonly used water models. We find that dissociation events are found only with TIP4P-EW and TIP4P/2005, while the widely used TIP3P water model produces straightforward aggregation of the molecules due to the absence of dissociation events. We also find that TIP4P/2005 is the only water model that reproduces the fast association/dissociation dynamics of ubiquitin and best identifies its binding surface. Our results show the critical role of the water model in the description of protein-protein interactions and binding.

Discrete Molecular Dynamics Approach to the Study of Disordered and Aggregating Proteins.

We present a refinement of the Coarse Grained PACSAB force field for Discrete Molecular Dynamics (DMD) simulations of proteins in aqueous conditions. As the original version, the refined method provides good representation of the structure and dynamics of folded proteins but provides much better representations of a variety of unfolded proteins, including some very large, impossible to analyze by atomistic simulation methods. The PACSAB/DMD method also reproduces accurately aggregation properties, providing good pictures of the structural ensembles of proteins showing a folded core and an intrinsically disordered region. The combination of accuracy and speed makes the method presented here a good alternative for the exploration of unstructured protein systems.

Residues Coevolution Guides the Systematic Identification of Alternative Functional Conformations in Proteins.

We present here a new approach for the systematic identification of functionally relevant conformations in proteins. Our fully automated pipeline, based on discrete molecular dynamics enriched with coevolutionary information, is able to capture alternative conformational states in 76% of the proteins studied, providing key atomic details for understanding their function and mechanism of action. We also demonstrate that, given its sampling speed, our method is well suited to explore structural transitions in a high-throughput manner, and can be used to determine functional conformational transitions at the entire proteome level.

PACSAB: Coarse-Grained Force Field for the Study of Protein-Protein Interactions and Conformational Sampling in Multiprotein Systems.

Molecular dynamics simulations of proteins are usually performed on a single molecule, and coarse-grained protein models are calibrated using single-molecule simulations, therefore ignoring intermolecular interactions. We present here a new coarse-grained force field for the study of many protein systems. The force field, which is implemented in the context of the discrete molecular dynamics algorithm, is able to reproduce the properties of folded and unfolded proteins, in both isolation, complexed forming well-defined quaternary structures, or aggregated, thanks to its proper evaluation of protein-protein interactions. The accuracy and computational efficiency of the method makes it a universal tool for the study of the structure, dynamics, and association/dissociation of proteins.

Exploration of conformational transition pathways from coarse-grained simulations.

MOTIVATION: A new algorithm to trace conformational transitions in proteins is presented. The method uses discrete molecular dynamics as engine to sample protein conformational space. A multiple minima Go-like potential energy function is used in combination with several enhancing sampling strategies, such as metadynamics, Maxwell Demon molecular dynamics and essential dynamics. The method, which shows an unprecedented computational efficiency, is able to trace a wide range of known experimental transitions. Contrary to simpler methods our strategy does not introduce distortions in the chemical structure of the protein and is able to reproduce well complex non-linear conformational transitions. The method, called GOdMD, can easily introduce additional restraints to the transition (presence of ligand, known intermediate, known maintained contacts, …) and is freely distributed to the community through the Spanish National Bioinformatics Institute (http://mmb.irbbarcelona.org/GOdMD). AVAILABILITY: Freely available on the web at http://mmb.irbbarcelona.org/GOdMD.

Efficient Relaxation of Protein-Protein Interfaces by Discrete Molecular Dynamics Simulations.

Protein-protein interactions are responsible for the transfer of information inside the cell and represent one of the most interesting research fields in structural biology. Unfortunately, after decades of intense research, experimental approaches still have difficulties in providing 3D structures for the hundreds of thousands of interactions formed between the different proteins in a living organism. The use of theoretical approaches like docking aims to complement experimental efforts to represent the structure of the protein interactome. However, we cannot ignore that current methods have limitations due to problems of sampling of the protein-protein conformational space and the lack of accuracy of available force fields. Cases that are especially difficult for prediction are those in which complex formation implies a non-negligible change in the conformation of the interacting proteins, i.e., those cases where protein flexibility plays a key role in protein-protein docking. In this work, we present a new approach to treat flexibility in docking by global structural relaxation based on ultrafast discrete molecular dynamics. On a standard benchmark of protein complexes, the method provides a general improvement over the results obtained by rigid docking. The method is especially efficient in cases with large conformational changes upon binding, in which structure relaxation with discrete molecular dynamics leads to a predictive success rate double that obtained with state-of-the-art rigid-body docking.

Finding Conformational Transition Pathways from Discrete Molecular Dynamics Simulations.

We present a new method for estimating pathways for conformational transitions in macromolecules from the use of discrete molecular dynamics and biasing techniques based on a combination of essential dynamics and Maxwell-Demon sampling techniques. The method can work with high efficiency at different levels of resolution, including the atomistic one, and can help to define initial pathways for further exploration by means of more accurate atomistic molecular dynamics simulations. The method is implemented in a freely available Web-based application accessible at http://mmb.irbbarcelona.org/MDdMD .

Coarse-grained representation of protein flexibility. Foundations, successes, and shortcomings.

Flexibility is the key magnitude to understand the variety of functions of proteins. Unfortunately, its experimental study is quite difficult, and in fact, most experimental procedures are designed to reduce flexibility and allow a better definition of the structure. Theoretical approaches have become then the alternative but face serious timescale problems, since many biologically relevant deformation movements happen in a timescale that is far beyond the possibility of current atomistic models. In this complex scenario, coarse-grained simulation methods have emerged as a powerful and inexpensive alternative. Along this chapter, we will review these coarse-grained methods, and explain their physical foundations and their range of applicability.

Protein flexibility from discrete molecular dynamics simulations using quasi-physical potentials.

We have applied all atoms discrete molecular dynamics (DMD) based on a quasi-physical potential to study the flexibility of an extended set of proteins for which atomistic MD simulations are available. The method uses pure physical potentials supplemented by information on secondary structure and despite its simplicity is able to reproduce with good accuracy the dynamics of proteins in solution. The method presents a clear improvement with respect to coarse-grained methods based on structure potentials and opens the possibility to explore dynamics of proteins out from the equilibrium and to trace conformational changes induced by interaction of proteins with both small and macromolecular ligands.

FlexServ: an integrated tool for the analysis of protein flexibility.

SUMMARY: FlexServ is a web-based tool for the analysis of protein flexibility. The server incorporates powerful protocols for the coarse-grained determination of protein dynamics using different versions of Normal Mode Analysis (NMA), Brownian dynamics (BD) and Discrete Dynamics (DMD). It can also analyze user provided trajectories. The server allows a complete analysis of flexibility using a large variety of metrics, including basic geometrical analysis, B-factors, essential dynamics, stiffness analysis, collectivity measures, Lindemann's indexes, residue correlation, chain-correlations, dynamic domain determination, hinge point detections, etc. Data is presented through a web interface as plain text, 2D and 3D graphics. AVAILABILITY: http://mmb.pcb.ub.es/FlexServ; http://www.inab.org

Exploring the suitability of coarse-grained techniques for the representation of protein dynamics.

A systematic study of two coarse-grained techniques for the description of protein dynamics is presented. The two techniques exploit either Brownian or discrete molecular dynamics algorithms applied in the context of simple C(alpha)-C(alpha) potentials, like those used in coarse-grained normal mode analysis. Coarse-grained simulations of the flexibility of protein metafolds are compared to those computed with fully atomistic molecular dynamics simulations using state-of-the-art physical potentials and explicit solvent. Both coarse-grained models efficiently capture critical features of the protein dynamics.

United-Atom Discrete Molecular Dynamics of Proteins Using Physics-Based Potentials.

We present a method for the efficient simulation of the equilibrium dynamics of proteins based on the well established discrete molecular dynamics algorithm, which avoids integration of Newton equations of motion at short time steps, allowing then the derivation of very large trajectories for proteins with a reduced computational cost. In the presented implementation we used an all heavy-atoms description of proteins, with simple potentials describing the conformational region around the experimental structure based on local physical interactions (covalent structure, hydrogen bonds, hydrophobic contacts, solvation, steric hindrance, and bulk dispersion interactions). The method shows a good ability to describe the flexibility of 33 diverse proteins in water as determined by atomistic molecular dynamics simulation and can be useful for massive simulation of proteins in crowded environments or for refinement of protein structure in large complexes.