From electron microscopy maps to atomic structures using normal mode-based fitting

Local Normal Mode Analysis for Fast Loop Conformational Sampling

We propose and validate a novel method to efficiently explore local protein loop conformations based on a new formalism for constrained normal mode analysis (NMA) in internal coordinates. The manifold of possible loop configurations imposed by the position and orientation of the fixed loop ends is reduced to an orthogonal set of motions (or modes) encoding concerted rotations of all the backbone dihedral angles. We validate the sampling power on a set of protein loops with highly variable experimental structures and demonstrate that our approach can efficiently explore the conformational space of closed loops. We also show an acceptable resemblance of the ensembles around equilibrium conformations generated by long molecular simulations and constrained NMA on a set of exposed and diverse loops. In comparison with other methods, the main advantage is the lack of restrictions on the number of dihedrals that can be altered simultaneously. Furthermore, the method is computationally efficient since it only requires the diagonalization of a tiny matrix, and the modes of motions are energetically contextualized by the elastic network model, which includes both the loop and the neighboring residues.

New generation of elastic network models

The intrinsic flexibility of proteins and nucleic acids can be grasped from remarkably simple mechanical models of particles connected by springs. In recent decades, Elastic Network Models (ENMs) combined with Normal Model Analysis widely confirmed their ability to predict biologically relevant motions of biomolecules and soon became a popular methodology to reveal large-scale dynamics in multiple structural biology scenarios. The simplicity, robustness, low computational cost, and relatively high accuracy are the reasons behind the success of ENMs. This review focuses on recent advances in the development and application of ENMs, paying particular attention to combinations with experimental data. Successful application scenarios include large macromolecular machines, structural refinement, docking, and evolutionary conservation.

Construction and validation of an atomic model for bacterial TSPO from electron microscopy density, evolutionary constraints, and biochemical and biophysical data

The 18 kDa protein TSPO is a highly conserved transmembrane protein found in bacteria, yeast, animals and plants. TSPO is involved in a wide range of physiological functions, among which the transport of several molecules. The atomic structure of monomeric ligand-bound mouse TSPO in detergent has been published recently. A previously published low-resolution structure of Rhodobacter sphaeroides TSPO, obtained from tubular crystals with lipids and observed in cryo-electron microscopy, revealed an oligomeric structure without any ligand. We analyze this electron microscopy density in view of available biochemical and biophysical data, building a matching atomic model for the monomer and then the entire crystal. We compare its intra- and inter-molecular contacts with those predicted by amino acid covariation in TSPO proteins from evolutionary sequence analysis. The arrangement of the five transmembrane helices in a monomer of our model is different from that observed for the mouse TSPO. We analyze possible ligand binding sites for protoporphyrin, for the high-affinity ligand PK 11195, and for cholesterol in TSPO monomers and/or oligomers, and we discuss possible functional implications.

Developing advanced X-ray scattering methods combined with crystallography and computation

The extensive use of small angle X-ray scattering (SAXS) over the last few years is rapidly providing new insights into protein interactions, complex formation and conformational states in solution. This SAXS methodology allows for detailed biophysical quantification of samples of interest. Initial analyses provide a judgment of sample quality, revealing the potential presence of aggregation, the overall extent of folding or disorder, the radius of gyration, maximum particle dimensions and oligomerization state. Structural characterizations include ab initio approaches from SAXS data alone, and when combined with previously determined crystal/NMR, atomistic modeling can further enhance structural solutions and assess validity. This combination can provide definitions of architectures, spatial organizations of protein domains within a complex, including those not determined by crystallography or NMR, as well as defining key conformational states of a protein interaction. SAXS is not generally constrained by macromolecule size, and the rapid collection of data in a 96-well plate format provides methods to screen sample conditions. This includes screening for co-factors, substrates, differing protein or nucleotide partners or small molecule inhibitors, to more fully characterize the variations within assembly states and key conformational changes. Such analyses may be useful for screening constructs and conditions to determine those most likely to promote crystal growth of a complex under study. Moreover, these high throughput structural determinations can be leveraged to define how polymorphisms affect assembly formations and activities. This is in addition to potentially providing architectural characterizations of complexes and interactions for systems biology-based research, and distinctions in assemblies and interactions in comparative genomics. Thus, SAXS combined with crystallography/NMR and computation provides a unique set of tools that should be considered as being part of one's repertoire of biophysical analyses, when conducting characterizations of protein and other macromolecular interactions.

Macromolecular assembly structures by comparative modeling and electron microscopy

Advances in electron microscopy allow for structure determination of large biological machines at increasingly higher resolutions. A key step in this process is fitting component structures into the electron microscopy-derived density map of their assembly. Comparative modeling can contribute by providing atomic models of the components, via fold assignment, sequence-structure alignment, model building, and model assessment. All four stages of comparative modeling can also benefit from consideration of the density map. In this chapter, we describe numerous types of modeling problems restrained by a density map and available protocols for finding solutions. In particular, we provide detailed instructions for density map-guided modeling using the Integrative Modeling Platform (IMP), MODELLER, and UCSF Chimera.

iMod: multipurpose normal mode analysis in internal coordinates

MOTIVATION

Dynamic simulations of systems with biologically relevant sizes and time scales are critical for understanding macromolecular functioning. Coarse-grained representations combined with normal mode analysis (NMA) have been established as an alternative to atomistic simulations. The versatility and efficiency of current approaches normally based on Cartesian coordinates can be greatly enhanced with internal coordinates (IC).

RESULTS

Here, we present a new versatile tool chest to explore conformational flexibility of both protein and nucleic acid structures using NMA in IC. Consideration of dihedral angles as variables reduces the computational cost and non-physical distortions of classical Cartesian NMA methods. Our proposed framework operates at different coarse-grained levels and offers an efficient framework to conduct NMA-based conformational studies, including standard vibrational analysis, Monte-Carlo simulations or pathway exploration. Examples of these approaches are shown to demonstrate its applicability, robustness and efficiency.

CONTACT

pablo@chaconlab.org

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.