The CCP4 suite: integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.

Local structuring of diketopyrrolopyrrole (DPP)-based oligomers from molecular dynamics simulations

The microscopic structure of high mobility semiconducting polymers is known to be essential for their performance but it cannot be easily deduced from the available experimental data. A series of short oligomers of diketopyrrolopyrrole (DPP)-based materials that display high charge mobility are studied by molecular dynamics simulations to understand their local structuring at an atomic level. Different analyses are proposed to compare the ability of different oligomers to form large aggregates and their driving force. The simulations show that the tendency for this class of materials to form aggregates is driven by the interaction between DPP fragments, but this is modulated by the other conjugated fragments of the materials which affect the rigidity of the polymer and, ultimately, the size of the aggregates that are formed. The main structural features and the electronic structure of the oligomers are fairly similar above the glass transition temperature and at room temperature.

Molecular Dynamics of Janus Nanodimers Dispersed in Lamellar Phases of a Block Copolymer

We investigate structural and dynamical properties of Janus nanodimers (NDs) dispersed in lamellar phases of a diblock copolymer. By performing molecular dynamics simulations, we show that an accurate tuning of the interactions between NDs and copolymer blocks can lead to a close control of NDs' space distribution and orientation. In particular, NDs are preferentially found within the lamellae if enthalpy-driven forces offset their entropic counterpart. By contrast, when enthalpy-driven forces are not significant, the distribution of NDs, preferentially observed within the inter-lamellar spacing, is mostly driven by excluded-volume effects. Not only does the degree of affinity between host and guest species drive the NDs' distribution in the polymer matrix, but it also determines their space orientation. In turn, these key structural properties influence the long-time dynamics and the ability of NDs to diffuse through the polymer matrix.

In silico prediction of structure and function for a large family of transmembrane proteins that includes human Tmem41b

Background: Recent strides in computational structural biology have opened up an opportunity to understand previously uncharacterised proteins.  The under-representation of transmembrane proteins in the Protein Data Bank highlights the need to apply new and advanced bioinformatics methods to shed light on their structure and function.  This study focuses on a family of transmembrane proteins containing the Pfam domain PF09335 ('SNARE_ASSOC'/ 'VTT '/'Tvp38'/'DedA'). One prominent member, Tmem41b, has been shown to be involved in early stages of autophagosome formation and is vital in mouse embryonic development as well as being identified as a viral host factor of SARS-CoV-2. Methods: We used evolutionary covariance-derived information to construct and validate ab initio models, make domain boundary predictions and infer local structural features.  Results: The results from the structural bioinformatics analysis of Tmem41b and its homologues showed that they contain a tandem repeat that is clearly visible in evolutionary covariance data but much less so by sequence analysis.  Furthermore, cross-referencing of other prediction data with covariance analysis showed that the internal repeat features two-fold rotational symmetry.  Ab initio modelling of Tmem41b and homologues reinforces these structural predictions.  Local structural features predicted to be present in Tmem41b were also present in Cl ^-/H ⁺ antiporters.  Conclusions: The results of this study strongly point to Tmem41b and its homologues being transporters for an as-yet uncharacterised substrate and possibly using H ⁺ antiporter activity as its mechanism for transport.

In silico prediction of structure and function for a large family of transmembrane proteins that includes human Tmem41b

Background: Recent strides in computational structural biology have opened up an opportunity to understand previously uncharacterised proteins.  The under-representation of transmembrane proteins in the Protein Data Bank highlights the need to apply new and advanced bioinformatics methods to shed light on their structure and function.  This study focuses on a family of transmembrane proteins containing the Pfam domain PF09335 ('SNARE_ASSOC'/ 'VTT '/'Tvp38'). One prominent member, Tmem41b, has been shown to be involved in early stages of autophagosome formation and is vital in mouse embryonic development as well as being identified as a viral host factor of SARS-CoV-2. Methods: We used evolutionary covariance-derived information to construct and validate ab initio models, make domain boundary predictions and infer local structural features.  Results: The results from the structural bioinformatics analysis of Tmem41b and its homologues showed that they contain a tandem repeat that is clearly visible in evolutionary covariance data but much less so by sequence analysis.  Furthermore, cross-referencing of other prediction data with covariance analysis showed that the internal repeat features two-fold rotational symmetry.  Ab initio modelling of Tmem41b and homologues reinforces these structural predictions.  Local structural features predicted to be present in Tmem41b were also present in Cl ^-/H ⁺ antiporters.  Conclusions: The results of this study strongly point to Tmem41b and its homologues being transporters for an as-yet uncharacterised substrate and possibly using H ⁺ antiporter activity as its mechanism for transport.

ConPlot: Web-based application for the visualisation of protein contact maps integrated with other data

Summary

Covariance-based predictions of residue contacts and inter-residue distances are an increasingly popular data type in protein bioinformatics. Here we present ConPlot, a web-based application for convenient display and analysis of contact maps and distograms. Integration of predicted contact data with other predictions is often required to facilitate inference of structural features. ConPlot can therefore use the empty space near the contact map diagonal to display multiple coloured tracks representing other sequence-based predictions. Popular file formats are natively read and bespoke data can also be flexibly displayed. This novel visualization will enable easier interpretation of predicted contact maps.

Availability and implementation

available online at www.conplot.org, along with documentation and examples. Alternatively, ConPlot can be installed and used locally using the docker image from the project’s Docker Hub repository. ConPlot is licensed under the BSD 3-Clause.

Supplementary information

Supplementary data are available at Bioinformatics online.

Modeling the Effect of Polymer Chain Stiffness on the Behavior of Polymer Nanocomposites

Due to their central role in industrial formulations spanning from food packaging to smart coatings, polymer nanocomposites have been the object of remarkable attention over the last two decades. Incorporating nanoparticles (NPs) into a polymer matrix modifies the conformation and mobility of the polymer chains at the NP-polymer interface and can potentially provide materials with enhanced properties as compared to pristine polymers. To this end, it is crucial to predict and control the ability of NPs to diffuse and achieve a good dispersion in the polymer matrix. Understanding how to control the NPs' dispersion is a challenging task controlled by the delicate balance between enthalpic and entropic contributions, such as NP-polymer interaction, NP size and shape, and polymer chain conformation. By performing molecular dynamics (MD) simulations, we investigate the effect of polymer chains' stiffness on the mobility of spherical NPs that establish weak or strong interactions with the polymer. Our results show a sound dependence of the NPs' diffusivity on the long-range order of the polymer melt, which undergoes an isotropic-to-nematic phase transition upon increasing chain stiffness. This phase transition induces a dynamical anisotropy in the nematic phase, with the NPs preferentially diffusing along the nematic director rather than in the directions perpendicular to it. Not only does this tendency determine the NPs' mobility and degree of dispersion in the polymer matrix, but it also influences the resistance to flow of the polymer nanocomposite when a shear is applied. In particular, to assess the role of the chains' conformation on the macroscopic response of our model PNC, we employ reverse nonequilibrium MD to calculate the zero-shear viscosity in both the isotropic and nematic phases, and unveil a plasticizing effect at increasing chain stiffness when the shear is applied along the nematic axis.

Effective short-range Coulomb correction to model the aggregation behavior of ionic surfactants

We present a short-range correction to the Coulomb potential to investigate the aggregation of amphiphilic molecules in aqueous solutions. The proposed modification allows to quantitatively reproduce the distribution of counterions above the critical micelle concentration (CMC) or, equivalently, the degree of ionization, α, of the micellar clusters. In particular, our theoretical framework has been applied to unveil the behavior of the cationic surfactant C24H49N2O2 (+) CH3SO4 (-), which offers a wide range of applications in the thriving and growing personal care market. A reliable and unambiguous estimation of α is essential to correctly understand many crucial features of the micellar solutions, such as their viscoelastic behavior and transport properties, in order to provide sound formulations for the above mentioned personal care solutions. We have validated our theory by performing extensive lattice Monte Carlo simulations, which show an excellent agreement with experimental observations. More specifically, our coarse-grained model is able to reproduce and predict the complex morphology of the micelles observed at equilibrium. Additionally, our simulation results disclose the existence of a transition from a monodisperse to a bidisperse size distribution of aggregates, unveiling the intriguing existence of a second CMC.