Conformational dynamics data bank: a database for conformational dynamics of proteins and supramolecular protein assemblies

Understanding the Impacts of Conformational Dynamics on the Regulation of Protein-Protein Association by a Multiscale Simulation Method

Complexes formed among diverse proteins carry out versatile functions in nearly all physiological processes. Association rates which measure how fast proteins form various complexes are of fundamental importance to characterize their functions. The association rates are not only determined by the energetic features at binding interfaces of a protein complex but also influenced by the intrinsic conformational dynamics of each protein in the complex. Unfortunately, how this conformational effect regulates protein association has never been calibrated on a systematic level. To tackle this problem, we developed a multiscale strategy to incorporate the information on protein conformational variations from Langevin dynamic simulations into a kinetic Monte Carlo algorithm of protein-protein association. By systematically testing this approach against a large-scale benchmark set, we found the association of a protein complex with a relatively rigid structure tends to be reduced by its conformational fluctuations. With specific examples, we further show that higher degrees of structural flexibility in various protein complexes can facilitate the searching and formation of intermolecular interactions and thereby accelerate their associations. In general, the integration of conformational dynamics can improve the correlation between experimentally measured association rates and computationally derived association probabilities. Finally, we analyzed the statistical distributions of different secondary structural types on protein-protein binding interfaces and their preference to the change of association rates. Our study, to the best of our knowledge, is the first computational method that systematically estimates the impacts of protein conformational dynamics on protein-protein association. It throws lights on the molecular mechanisms of how protein-protein recognition is kinetically modulated.

A critical assessment of finite element modeling approach for protein dynamics

Finite element (FE) modeling approach has emerged as an efficient way of calculating the dynamic properties of supramolecular protein structures and their complexes. Its efficiency mainly stems from the fact that the complexity of three-dimensional shape of a molecular surface dominates the computational cost rather than the molecular size or the number of atoms. However, no critical evaluation of the method has been made yet particularly for its sensitivity to the parameters used in model construction. Here, we make a close investigation on the effect of FE model parameters by analyzing 135 representative protein structures whose normal modes calculated using all-atom normal mode analysis are publicly accessible online. Results demonstrate that it is more beneficial to use a contour surface of electron densities as the molecular surface, in general, rather than to employ a solvent excluded surface, and that the solution accuracy is almost insensitive to the model parameters unless we avoid extreme values leading to an inaccurate depiction of the characteristic shapes.

Toward Modular Analysis of Supramolecular Protein Assemblies

Despite recent advances in molecular simulation technologies, analysis of high-molecular-weight structures is still challenging. Here, we propose an automated model reduction procedure aiming to enable modular analysis of these structures. It employs a component mode synthesis for the reduction of finite element protein models. Reduced models may consist of real biological subunits or artificial partitions whose dynamics is described using the degrees of freedom at the substructural interfaces and a small set of dominant vibrational modes only. Notably, the proper number of dominant modes is automatically determined using a novel estimator for eigenvalue errors without calculating the reference eigensolutions of the full model. The performance of the proposed approach is thoroughly investigated by analyzing 50 representative structures including a crystal structure of GroEL and an electron density map of a ribosome.

In pursuit of an accurate spatial and temporal model of biomolecules at the atomistic level: a perspective on computer simulation

Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.

Translational bioinformatics approaches for systems and dynamical medicine

The exponential growth of experimental and clinical data generated from systematic studies, the complexity in health and diseases, and the request for the establishment of systems models are bringing bioinformatics to the center stage of pharmacogenomics and systems biology. Bioinformatics plays an essential role in bridging the gap among different knowledge domains for the translation of the voluminous data into better diagnosis, prognosis, prevention, and treatment. Bioinformatics is essential in finding the spatiotemporal patterns in pharmacogenomics, including the time-series analyses of the associations between genetic structural variations and functional alterations such as drug responses. The elucidation of the cross talks among different systems levels and time scales can contribute to the discovery of accurate and robust biomarkers at various diseases stages for the development of systems and dynamical medicine. Various resources are available for such purposes, including databases and tools supporting "omics" studies such as genomics, proteomics, epigenomics, transcriptomics, metabolomics, lipidomics, pharmacogenomics, and chronomics. The combination of bioinformatics and health informatics methods would provide powerful decision support in both scientific and clinical environments. Data integration, data mining, and knowledge discovery (KD) methods would enable the simulation of complex systems and dynamical networks to establish predictive models for achieving predictive, preventive, and personalized medicine.

3DEM Loupe: Analysis of macromolecular dynamics using structures from electron microscopy

Electron microscopy (EM) provides access to structural information of macromolecular complexes in the 3-20 Å resolution range. Normal mode analysis has been extensively used with atomic resolution structures and successfully applied to EM structures. The major application of normal modes is the identification of possible conformational changes in proteins. The analysis can throw light on the mechanism following ligand binding, protein-protein interactions, channel opening and other functional macromolecular movements. In this article, we present a new web server, 3DEM Loupe, which allows normal mode analysis of any uploaded EM volume using a user-friendly interface and an intuitive workflow. Results can be fully explored in 3D through animations and movies generated by the server. The application is freely available at http://3demloupe.cnb.csic.es.

Virtual interface substructure synthesis method for normal mode analysis of super-large molecular complexes at atomic resolution

Normal mode analysis of large biomolecular complexes at atomic resolution remains challenging in computational structure biology due to the requirement of large amount of memory space and central processing unit time. In this paper, we present a method called virtual interface substructure synthesis method or VISSM to calculate approximate normal modes of large biomolecular complexes at atomic resolution. VISSM introduces the subunit interfaces as independent substructures that join contacting molecules so as to keep the integrity of the system. Compared with other approximate methods, VISSM delivers atomic modes with no need of a coarse-graining-then-projection procedure. The method was examined for 54 protein-complexes with the conventional all-atom normal mode analysis using CHARMM simulation program and the overlap of the first 100 low-frequency modes is greater than 0.7 for 49 complexes, indicating its accuracy and reliability. We then applied VISSM to the satellite panicum mosaic virus (SPMV, 78,300 atoms) and to F-actin filament structures of up to 39-mer, 228,813 atoms and found that VISSM calculations capture functionally important conformational changes accessible to these structures at atomic resolution. Our results support the idea that the dynamics of a large biomolecular complex might be understood based on the motions of its component subunits and the way in which subunits bind one another.

The 2011 Nucleic Acids Research Database Issue and the online Molecular Biology Database Collection

The current 18th Database Issue of Nucleic Acids Research features descriptions of 96 new and 83 updated online databases covering various areas of molecular biology. It includes two editorials, one that discusses COMBREX, a new exciting project aimed at figuring out the functions of the ‘conserved hypothetical’ proteins, and one concerning BioDBcore, a proposed description of the ‘minimal information about a biological database’. Papers from the members of the International Nucleotide Sequence Database collaboration (INSDC) describe each of the participating databases, DDBJ, ENA and GenBank, principles of data exchange within the collaboration, and the recently established Sequence Read Archive. A testament to the longevity of databases, this issue includes updates on the RNA modification database, Definition of Secondary Structure of Proteins (DSSP) and Homology-derived Secondary Structure of Proteins (HSSP) databases, which have not been featured here in >12 years. There is also a block of papers describing recent progress in protein structure databases, such as Protein DataBank (PDB), PDB in Europe (PDBe), CATH, SUPERFAMILY and others, as well as databases on protein structure modeling, protein–protein interactions and the organization of inter-protein contact sites. Other highlights include updates of the popular gene expression databases, GEO and ArrayExpress, several cancer gene databases and a detailed description of the UK PubMed Central project. The Nucleic Acids Research online Database Collection, available at: http://www.oxfordjournals.org/nar/database/a/, now lists 1330 carefully selected molecular biology databases. The full content of the Database Issue is freely available online at the Nucleic Acids Research web site (http://nar.oxfordjournals.org/).