Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

Antimicrobial activity is being increasingly linked to amyloid fibril formation, suggesting physiological roles for some human amyloids, which have historically been viewed as strictly pathological agents. This work reports on formation of functional cross-α amyloid fibrils of the amphibian antimicrobial peptide uperin 3.5 at atomic resolution, an architecture initially discovered in the bacterial PSMα3 cytotoxin. The fibrils of uperin 3.5 and PSMα3 comprised antiparallel and parallel helical sheets, respectively, recapitulating properties of β-sheets. Uperin 3.5 demonstrated chameleon properties of a secondary structure switch, forming mostly cross-β fibrils in the absence of lipids. Uperin 3.5 helical fibril formation was largely induced by, and formed on, bacterial cells or membrane mimetics, and led to membrane damage and cell death. These findings suggest a regulation mechanism, which includes storage of inactive peptides as well as environmentally induced activation of uperin 3.5, via chameleon cross-α/β amyloid fibrils.

Performance in the template-based modeling (TBM) category of CASP13 is assessed here, using a variety of metrics. Performance of the predictor groups that participated is ranked using the primary ranking score that was developed by the assessors for CASP12. This reveals that the best results are obtained by groups that include contact predictions or inter-residue distance predictions derived from deep multiple sequence alignments. In cases where there is a good homologue in the wwPDB (TBM-easy category), the best results are obtained by modifying a template. However, for cases with poorer homologues (TBM-hard), very good results can be obtained without using an explicit template, by deep learning algorithms trained on the wwPDB. Alternative metrics are introduced, to allow testing of aspects of structural models that are not addressed by traditional CASP metrics. These include comparisons to the main-chain and side-chain torsion angles of the target, and the utility of models for solving crystal structures by the molecular replacement method. The alternative metrics are poorly correlated with the traditional metrics, and it is proposed that modeling has reached a sufficient level of maturity that the best models should be expected to satisfy this wider range of criteria.

We describe an algorithm for phasing protein crystal X-ray diffraction data that identifies, retrieves, refines and exploits general tertiary structural information from small fragments available in the Protein Data Bank. The algorithm successfully phased, through unspecific molecular replacement combined with density modification, all-helical, mixed alpha-beta, and all-beta protein structures. The method is available as a software implementation: Borges.

Since its release in September 2009, the structure-solution program ARCIMBOLDO, based on the combination of locating small model fragments such as polyalanine -helices with density modification with the program SHELXE in a multisolution frame, has evolved to incorporate other sources of stereochemical or experimental information. Fragments that are more sophisticated than the ubiquitous main-chain -helix can be proposed by modelling side chains onto the main chain or extracted from low-homology models, as locally their structure may be similar enough to the unknown one even if the conventional molecular-replacement approach has been unsuccessful. In such cases, the program may test a set of alternative models in parallel against a specified figure of merit and proceed with the selected one(s). Experimental information can be incorporated in three ways: searching within ARCIMBOLDO for an anomalous fragment against anomalous differences or MAD data or finding model fragments when an anomalous substructure has been determined with another program such as SHELXD or is subsequently located in the anomalous Fourier map calculated from the partial fragment phases. Both sources of information may be combined in the expansion process. In all these cases the key is to control the workflow to maximize the chances of success whilst avoiding the creation of an intractable number of parallel processes. A GUI has been implemented to aid the setup of suitable strategies within the various typical scenarios. In the present work, the practical application of ARCIM-BOLDO within each of these scenarios is described through the distributed test cases.

The AlphaFold2 results in the 14th edition of Critical Assessment of Structure Prediction (CASP14) showed that accurate (low root-mean-square deviation) in silico models of protein structure domains are on the horizon, whether or not the protein is related to known structures through high-coverage sequence similarity. As highly accurate models become available, generated by harnessing the power of correlated mutations and deep learning, one of the aspects of structural biology to be impacted will be methods of phasing in crystallography. Here, the data from CASP14 are used to explore the prospects for changes in phasing methods, and in particular to explore the prospects for molecular-replacement phasing using in silico models.

Molecular replacement, one of the general methods used to solve the crystallographic phase problem, relies on the availability of suitable models for placement in the unit cell of the unknown structure in order to provide initial phases. ARCIMBOLDO, originally conceived for ab initio phasing, operates at the limit of this approach, using small, very accurate fragments such as polyalanine α‐helices. A distant homolog may contain accurate building blocks, but it may not be evident which sub‐structure is the most suitable purely from the degree of conservation. Trying out all alternative possibilities in a systematic way is computationally expensive, even if effective. In the present study, the solution of the previously unknown structure of MltE, an outer membrane‐anchored endolytic peptidoglycan lytic transglycosylase from Escherichia coli, is described. The asymmetric unit contains a dimer of this 194 amino acid protein. The closest available homolog was the catalytic domain of Slt70 (PDB code http://www.rcsb.org/pdb/search/structidSearch.do?structureId=1QTE). Originally, this template was used omitting contiguous spans of aminoacids and setting as many ARCIMBOLDO runs as models, each aiming to locate two copies sequentially with PHASER. Fragment trimming against the correlation coefficient prior to expansion through density modification and autotracing in SHELXE was essential. Analysis of the figures of merit led to the strategy to optimize the search model against the experimental data now implemented within ARCIMBOLDO‐SHREDDER (http://chango.ibmb.csic.es/SHREDDER). In this strategy, the initial template is systematically shredded, and fragments are scored against each unique solution of the rotation function. Results are combined into a score per residue and the template is trimmed accordingly.

ARCIMBOLDO solves the phase problem at resolutions of around 2 Å or better through massive combination of small fragments and density modification. For complex structures, this imposes a need for a powerful grid where calculations can be distributed, but for structures with up to 200 amino acids in the asymmetric unit a single workstation may suffice. The use and performance of the single-workstation implementation, ARCIMBOLDO_LITE, on a pool of test structures with 40-120 amino acids and resolutions between 0.54 and 2.2 Å is described. Inbuilt polyalanine helices and iron cofactors are used as search fragments. ARCIMBOLDO_BORGES can also run on a single workstation to solve structures in this test set using precomputed libraries of local folds. The results of this study have been incorporated into an automated, resolution- and hardware-dependent parameterization. ARCIMBOLDO has been thoroughly rewritten and three binaries are now available: ARCIMBOLDO_LITE, ARCIMBOLDO_SHREDDER and ARCIMBOLDO_BORGES. The programs and libraries can be downloaded from http://chango.ibmb.csic.es/ARCIMBOLDO_LITE.