SPEDEN: Reconstructing single particles from their diffraction patterns

Speden is a computer program that reconstructs the electron density of single particles from their x-ray diffraction patterns, using a single-particle adaptation of the Holographic Method in crystallography. (Szoke, A., Szoke, H., and Somoza, J.R., 1997. Acta Cryst. A53, 291-313.) The method, like its parent, is unique that it does not rely on ``back'' transformation from the diffraction pattern into real space and on interpolation within measured data. It is designed to deal successfully with sparse, irregular, incomplete and noisy data. It is also designed to use prior information for ensuring sensible results and for reliable convergence. This article describes the theoretical basis for the reconstruction algorithm, its implementation and quantitative results of tests on synthetic and experimentally obtained data. The program could be used for determining the structure of radiation tolerant samples and, eventually, of large biological molecular structures without the need for crystallization.Comment: 12 pages, 10 figure

Two decades of Martini:Better beads, broader scope

The Martini model, a coarse-grained force field for molecular dynamics simulations, has been around for nearly two decades. Originally developed for lipid-based systems by the groups of Marrink and Tieleman, the Martini model has over the years been extended as a community effort to the current level of a general-purpose force field. Apart from the obvious benefit of a reduction in computational cost, the popularity of the model is largely due to the systematic yet intuitive building-block approach that underlies the model, as well as the open nature of the development and its continuous validation. The easy implementation in the widely used Gromacs software suite has also been instrumental. Since its conception in 2002, the Martini model underwent a gradual refinement of the bead interactions and a widening scope of applications. In this review, we look back at this development, culminating with the release of the Martini 3 version in 2021. The power of the model is illustrated with key examples of recent important findings in biological and material sciences enabled with Martini, as well as examples from areas where coarse-grained resolution is essential, namely high-throughput applications, systems with large complexity, and simulations approaching the scale of whole cells. This article is categorized under: Software > Molecular Modeling Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods Structure and Mechanism > Computational Materials Science Structure and Mechanism > Computational Biochemistry and Biophysics

Dynamics of clusters: From elementary to biological structures

Between isolated atoms or molecules and bulk materials there lies a class of unique structures, known as clusters, that consist of a few to hundreds of atoms or molecules. Within this range of "nanophase," many physical and chemical properties of the materials evolve as a function of cluster size, and materials may exhibit novel properties due to quantum confinement effects. Understanding these phenomena is in its own rights fundamental, but clusters have the additional advantage of being controllable model systems for unraveling the complexity of condensed-phase and biological structures, not to mention their vanguard role in defining nanoscience and nanotechnology. Over the last two decades, much progress has been made, and this short overview highlights our own involvement in developing cluster dynamics, from the first experiments on elementary systems to model systems in the condensed phase, and on to biological structures

Containment and reciprocity in biological systems : a putative psychophysical organising principle

The stuff of life, the living substance that is common to all biological organisms, is the aqueous society of biochemical activity ongoing in every cell in every living body. The basic biochemical ‘reactions’ of life are largely similar with variations of a theme played out in different cells living in different environment, e.g. the core biochemical metabolic processes of all life likely stem from an ancient, early-earth ancestor (Smith & Morowitz, 2004). However, even more common to life than shared biochemistry are the basic structural properties of all cells and all living organisms into complexes of compartmentalised units. In this paper, I will argue there are common feelings driving the generation of these ubiquitous structures in nature and that these feelings may constitute one of several primary forms of feeling in living systems

Brownian motion: a paradigm of soft matter and biological physics

This is a pedagogical introduction to Brownian motion on the occasion of the 100th anniversary of Einstein's 1905 paper on the subject. After briefly reviewing Einstein's work in its contemporary context, we pursue some lines of further developments and applications in soft condensed matter and biology. Over the last century Brownian motion became promoted from an odd curiosity of marginal scientific interest to a guiding theme pervading all of the modern (live) sciences.Comment: 30 pages, revie

Structural basis for Cul3 protein assembly with the BTB-Kelch family of E3 ubiquitin ligases

Cullin-RING ligases are multisubunit E3 ubiquitin ligases that recruit substrate-specific adaptors to catalyze protein ubiquitylation. Cul3-based Cullin-RING ligases are uniquely associated with BTB adaptors that incorporate homodimerization, Cul3 assembly, and substrate recognition into a single multidomain protein, of which the best known are BTB-BACK-Kelch domain proteins, including KEAP1. Cul3 assembly requires a BTB protein "3-box" motif, analogous to the F-box and SOCS box motifs of other Cullin-based E3s. To define the molecular basis for this assembly and the overall architecture of the E3, we determined the crystal structures of the BTB-BACK domains of KLHL11 both alone and in complex with Cul3, along with the Kelch domain structures of KLHL2 (Mayven), KLHL7, KLHL12, and KBTBD5. We show that Cul3 interaction is dependent on a unique N-terminal extension sequence that packs against the 3-box in a hydrophobic groove centrally located between the BTB and BACK domains. Deletion of this N-terminal region results in a 30-fold loss in affinity. The presented data offer a model for the quaternary assembly of this E3 class that supports the bivalent capture of Nrf2 and reveals potential new sites for E3 inhibitor design

Accurate Determination of Conformational Transitions in Oligomeric Membrane Proteins

The structural dynamics governing collective motions in oligomeric membrane proteins play key roles in vital biomolecular processes at cellular membranes. In this study, we present a structural refinement approach that combines solid-state NMR experiments and molecular simulations to accurately describe concerted conformational transitions identifying the overall structural, dynamical, and topological states of oligomeric membrane proteins. The accuracy of the structural ensembles generated with this method is shown to reach the statistical error limit, and is further demonstrated by correctly reproducing orthogonal NMR data. We demonstrate the accuracy of this approach by characterising the pentameric state of phospholamban, a key player in the regulation of calcium uptake in the sarcoplasmic reticulum, and by probing its dynamical activation upon phosphorylation. Our results underline the importance of using an ensemble approach to characterise the conformational transitions that are often responsible for the biological function of oligomeric membrane protein states

The EVA spectral descriptor

The EVA descriptor is derived from fundamental IR- and Raman range molecular vibrational frequencies. EVA is sensitive to 3D structure but has an advantage over field-based 3D-QSAR methods inasmuch as it is invariant to both translation and rotation of the structures concerned and thus structural superposition is not required. The latter property and the demonstration of the effectiveness of the descriptor for QSAR means that EVA has been the subject of a great deal of interest from the modelling community. This review describes the derivation of the descriptor, details its main parameters and how to apply them, and provides an overview of the validation that has been done with the descriptor. A recent enhancement to the technique is described which involves the localised adjustment of variance in such a way that enhanced internal and external predictivity may be obtained. Despite the statistical quality of EVA QSAR models the main draw-back to the descriptor at present is the difficulty associated with back-tracking from a PLS model to an EVA pharmacophore. Brief comment is made on the use of the EVA descriptor for diversity studies and the similarity searching of chemical structure databases