17 research outputs found
Carbohydrate structure: : the rocky road to automation
With the introduction of intuitive graphical software, structural biologists who are not experts in crystallography are now able to build complete protein or nucleic acid models rapidly. In contrast, carbohydrates are in a wholly different situation: scant automation exists, with manual building attempts being sometimes toppled by incorrect dictionaries or refinement problems. Sugars are the most stereochemically complex family of biomolecules and, as pyranose rings, have clear conformational preferences. Despite this, all refinement programs may produce high-energy conformations at medium to low resolution, without any support from the electron density. This problem renders the affected structures unusable in glyco-chemical terms. Bringing structural glycobiology up to ‘protein standards’ will require a total overhaul of the methodology. Time is of the essence, as the community is steadily increasing the production rate of glycoproteins, and electron cryo-microscopy has just started to image them in precisely that resolution range where crystallographic methods falter most
ModelCraft : an advanced automated model-building pipeline using Buccaneer
Interactive model building can be a difficult and time-consuming step in the structure-solution process. Automated model-building programs such as Buccaneer often make it quicker and easier by completing most of the model in advance. However, they may fail to do so with low-resolution data or a poor initial model or map. The Buccaneer pipeline is a relatively simple program that iterates Buccaneer with REFMAC to refine the model and update the map. A new pipeline called ModelCraft has been developed that expands on this to include shift-field refinement, machine-learned pruning of incorrect residues, classical density modification, addition of water and dummy atoms, building of nucleic acids and final rebuilding of side chains. Testing was performed on 1180 structures solved by experimental phasing, 1338 structures solved by molecular replacement using homologues and 2030 structures solved by molecular replacement using predicted AlphaFold models. Compared with the previous Buccaneer pipeline, ModelCraft increased the mean completeness of the protein models in the experimental phasing cases from 91% to 95%, the molecular-replacement cases from 50% to 78% and the AlphaFold cases from 82% to 91%
Overview of the CCP4 suite and current developments.
The CCP4 (Collaborative Computational Project, Number 4) software suite is a collection of programs and associated data and software libraries which can be used for macromolecular structure determination by X-ray crystallography. The suite is designed to be flexible, allowing users a number of methods of achieving their aims. The programs are from a wide variety of sources but are connected by a common infrastructure provided by standard file formats, data objects and graphical interfaces. Structure solution by macromolecular crystallography is becoming increasingly automated and the CCP4 suite includes several automation pipelines. After giving a brief description of the evolution of CCP4 over the last 30 years, an overview of the current suite is given. While detailed descriptions are given in the accompanying articles, here it is shown how the individual programs contribute to a complete software package
Host-parasite co-metabolic activation of antitrypanosomal aminomethyl-benzoxaboroles
<div><p>Recent development of benzoxaborole-based chemistry gave rise to a collection of compounds with great potential in targeting diverse infectious diseases, including human African Trypanosomiasis (HAT), a devastating neglected tropical disease. However, further medicinal development is largely restricted by a lack of insight into mechanism of action (MoA) in pathogenic kinetoplastids. We adopted a multidisciplinary approach, combining a high-throughput forward genetic screen with functional group focused chemical biological, structural biology and biochemical analyses, to tackle the complex MoAs of benzoxaboroles in <i>Trypanosoma brucei</i>. We describe an oxidative enzymatic pathway composed of host semicarbazide-sensitive amine oxidase and a trypanosomal aldehyde dehydrogenase TbALDH3. Two sequential reactions through this pathway serve as the key underlying mechanism for activating a series of 4-aminomethylphenoxy-benzoxaboroles as potent trypanocides; the methylamine parental compounds as pro-drugs are transformed first into intermediate aldehyde metabolites, and further into the carboxylate metabolites as effective forms. Moreover, comparative biochemical and crystallographic analyses elucidated the catalytic specificity of TbALDH3 towards the benzaldehyde benzoxaborole metabolites as xenogeneic substrates. Overall, this work proposes a novel drug activation mechanism dependent on both host and parasite metabolism of primary amine containing molecules, which contributes a new perspective to our understanding of the benzoxaborole MoA, and could be further exploited to improve the therapeutic index of antimicrobial compounds.</p></div
Recommended from our members
Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge
This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Ã…). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density
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
Atomic model validation using the CCP-EM software suite
Recently, there has been a dramatic improvement in the quality and quantity of data derived using cryogenic electron microscopy (cryo-EM). This is also associated with a large increase in the number of atomic models built. Although the best resolutions that are achievable are improving, often the local resolution is variable, and a significant majority of data are still resolved at resolutions worse than 3 Å. Model building and refinement is often challenging at these resolutions, and hence atomic model validation becomes even more crucial to identify less reliable regions of the model. Here, a graphical user interface for atomic model validation, implemented in the CCP-EM software suite, is presented. It is aimed to develop this into a platform where users can access multiple complementary validation metrics that work across a range of resolutions and obtain a summary of evaluations. Based on the validation estimates from atomic models associated with cryo-EM structures from SARS-CoV-2, it was observed that models typically favor adopting the most common conformations over fitting the observations when compared with the model agreement with data. At low resolutions, the stereochemical quality may be favored over data fit, but care should be taken to ensure that the model agrees with the data in terms of resolvable features. It is demonstrated that further re-refinement can lead to improvement of the agreement with data without the loss of geometric quality. This also highlights the need for improved resolution-dependent weight optimization in model refinement and an effective test for overfitting that would help to guide the refinement process
Recommended from our members
Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures
The level of agreement between climate model simulations and observed surface temperature change is a topic of scientific and policy concern. While the Earth system continues to accumulate energy due to anthropogenic and other radiative forcings, estimates of recent surface temperature evolution fall at the lower end of climate model projections. Global mean temperatures from climate model simulations are typically calculated using surface air temperatures, while the corresponding observations are based on a blend of air and sea surface temperatures. This work quantifies a systematic bias in model-observation comparisons arising from differential warming rates between sea surface temperatures and surface air temperatures over oceans. A further bias arises from the treatment of temperatures in regions where the sea ice boundary has changed. Applying the methodology of the HadCRUT4 record to climate model temperature fields accounts for 38% of the discrepancy in trend between models and observations over the period 1975–2014