Using iterative fragment assembly and progressive sequence truncation to facilitate phasing and crystal structure determination of distantly related proteins

Integrative Structural Biology in the Era of Accurate Structure Prediction

Characterizing the three-dimensional structure of macromolecules is central to understanding their function. Traditionally, structures of proteins and their complexes have been determined using experimental techniques such as X-ray crystallography, NMR, or cryo-electron microscopy-applied individually or in an integrative manner. Meanwhile, however, computational methods for protein structure prediction have been improving their accuracy, gradually, then suddenly, with the breakthrough advance by AlphaFold2, whose models of monomeric proteins are often as accurate as experimental structures. This breakthrough foreshadows a new era of computational methods that can build accurate models for most monomeric proteins. Here, we envision how such accurate modeling methods can combine with experimental structural biology techniques, enhancing integrative structural biology. We highlight the challenges that arise when considering multiple structural conformations, protein complexes, and polymorphic assemblies. These challenges will motivate further developments, both in modeling programs and in methods to solve experimental structures, towards better and quicker investigation of structure-function relationships.

Molecular-replacement phasing using predicted protein structures from AWSEM-Suite

The phase problem in X-ray crystallography arises from the fact that only the intensities, and not the phases, of the diffracting electromagnetic waves are measured directly. Molecular replacement can often estimate the relative phases of reflections starting with those derived from a template structure, which is usually a previously solved structure of a similar protein. The key factor in the success of molecular replacement is finding a good template structure. When no good solved template exists, predicted structures based partially on templates can sometimes be used to generate models for molecular replacement, thereby extending the lower bound of structural and sequence similarity required for successful structure determination. Here, the effectiveness is examined of structures predicted by a state-of-the-art prediction algorithm, the Associative memory, Water-mediated, Structure and Energy Model Suite (AWSEM-Suite), which has been shown to perform well in predicting protein structures in CASP13 when there is no significant sequence similarity to a solved protein or only very low sequence similarity to known templates. The performance of AWSEM-Suite structures in molecular replacement is discussed and the results show that AWSEM-Suite performs well in providing useful phase information, often performing better than I-TASSER-MR and the previous algorithm AWSEM-Template.

I-TASSER-MR: automated molecular replacement for distant-homology proteins using iterative fragment assembly and progressive sequence truncation

Molecular replacement (MR) is one of the most common techniques used for solving the phase problem in X-ray crystal diffraction. The success rate of MR however drops quickly when the sequence identity between query and templates is reduced, while the I-TASSER-MR server is designed to solve the phase problem for proteins that lack close homologous templates. Starting from a sequence, it first generates full-length models using I-TASSER by iterative structural fragment reassembly. A progressive sequence truncation procedure is then used for editing the models based on local variations of the structural assembly simulations. Next, the edited models are submitted to MR-REX to search for optimal placements in the crystal unit-cells through replica-exchange Monte Carlo simulations, with the phasing results used by CNS for final atomic model refinement and selection. The I-TASSER-MR algorithm was tested in large-scale benchmark datasets and solved 36% more targets compared to using the best threading templates. The server takes primary sequence and raw crystal diffraction data as input, with output containing annotated phase information and refined structure models. It also allows users to choose between different methods for setting B-factors and the number of models used for phasing. The online server is freely available at http://zhanglab.ccmb.med.umich.edu/I-TASSER-MR.

Characteristics and Expression Analysis of FmTCP15 under Abiotic Stresses and Hormones and Interact with DELLA Protein in Fraxinus mandshurica Rupr

The TEOSINTE BRANCHED1, CYCLOIDEA, and PROLIFERATION CELL FACTOR (TCP) transcription factor is a plant-specific gene family and acts on multiple functional genes in controlling growth, development, stress response, and the circadian clock. In this study, a class I member of the TCP family from Fraxinus mandshurica Rupr. was isolated and named FmTCP15, which encoded a protein of 362 amino acids. Protein structures were analyzed and five ligand binding sites were predicted. The phylogenetic relationship showed that FmTCP15 was most closely related to Solanaceae and Plantaginaceae. FmTCP15 was localized in the nuclei of F. mandshurica protoplast cells and highly expressed in cotyledons. The expression pattern revealed the FmTCP15 response to multiple abiotic stresses and hormone signals. Downstream genes for transient overexpression of FmTCP15 in seedlings were also investigated. A yeast two-hybrid assay confirmed that FmTCP15 could interact with DELLA proteins. FmTCP15 participated in the GA-signaling pathway, responded to abiotic stresses and hormone signals, and regulated multiple genes in these biological processes. Our study revealed the potential value of FmTCP15 for understanding the molecular mechanisms of stress and hormone signal responses.

MR-REX: molecular replacement by cooperative conformational search and occupancy optimization on low-accuracy protein models

Molecular replacement (MR) has commonly been employed to derive the phase information in protein crystal X-ray diffraction, but its success rate decreases rapidly when the search model is dissimilar to the target. MR-REX has been developed to perform an MR search by replica-exchange Monte Carlo simulations, which enables cooperative rotation and translation searches and simultaneous clash and occupancy optimization. MR-REX was tested on a set of 1303 protein structures of different accuracies and successfully placed 699 structures at positions that have an r.m.s.d. of below 2 Å to the target position, which is 10% higher than was obtained by Phaser. However, cases studies show that many of the models for which Phaser failed and MR-REX succeeded can be solved by Phaser by pruning them and using nondefault parameters. The factors effecting success and the parts of the methodology which lead to success are studied. The results demonstrate a new avenue for molecular replacement which outperforms (and has results that are complementary to) the state-of-the-art MR methods, in particular for distantly homologous proteins.

Fragon: rapid high-resolution structure determination from ideal protein fragments

Correctly positioning ideal protein fragments by molecular replacement presents an attractive method for obtaining preliminary phases when no template structure for molecular replacement is available. This has been exploited in several existing pipelines. This paper presents a new pipeline, named Fragon, in which fragments (ideal α-helices or β-strands) are placed using Phaser and the phases calculated from these coordinates are then improved by the density-modification methods provided by ACORN. The reliable scoring algorithm provided by ACORN identifies success. In these cases, the resulting phases are usually of sufficient quality to enable automated model building of the entire structure. Fragon was evaluated against two test sets comprising mixed α/β folds and all-β folds at resolutions between 1.0 and 1.7 Å. Success rates of 61% for the mixed α/β test set and 30% for the all-β test set were achieved. In almost 70% of successful runs, fragment placement and density modification took less than 30 min on relatively modest four-core desktop computers. In all successful runs the best set of phases enabled automated model building with ARP/wARP to complete the structure.

Approaches to ab initio molecular replacement of α-helical transmembrane proteins

α-Helical transmembrane proteins are a ubiquitous and important class of proteins, but present difficulties for crystallographic structure solution. Here, the effectiveness of the AMPLE molecular replacement pipeline in solving α-helical transmembrane-protein structures is assessed using a small library of eight ideal helices, as well as search models derived from ab initio models generated both with and without evolutionary contact information. The ideal helices prove to be surprisingly effective at solving higher resolution structures, but ab initio-derived search models are able to solve structures that could not be solved with the ideal helices. The addition of evolutionary contact information results in a marked improvement in the modelling and makes additional solutions possible.