Experimental protein structure determination methods make up a fundamental part of our understanding of biological systems. Manual interpretation of the output from these methods has been made obsolete by the sheer size and complexity of the acquired data. Instead, computational methods are becoming essential for this task and with the advent of high-throughput methods the efficiency and robustness of these methods are a major concern. This work focuses on the computational challenge of efficiently extracting statistically supported information from noisy or significantly reduced experimental data.

Small-angle X-ray scattering (SAXS) is a method capable of probing structural information with many experimental benefits compared to alternative methods. However, the acquired data is a noisy reduction of a large set of structural features into a low-dimensional signal-mixture, which significantly limits its interpretability. Due to this SAXS has this far been limited to conclusions about large-scale structural features, like radius of gyration or the oligomeric state of the sample. In this thesis I present an approach where SAXS data is used to guide molecular dynamics simulations to explore experimentally relevant conformational states. The experimental data is fed into the simulations through a metadynamics protocol, which explores the experimental data through conformational sampling subject to thermodynamic restraints. I show how this approach makes it possible to use SAXS to produce atomic-resolution models and make further-reaching conclusions about the underlying biological system, in particular by showcasing de novo folding of a small protein.

Another experimental method that generates noisy and reduced data is cryogenic electron microscopy (cryo-EM). Due to recent development in the field, the computational burden has become a considerable bottleneck, which greatly limits the throughput of the method. I present computational techniques to alleviate this burden through the use of specialized algorithms capable of efficient execution on graphics processing units (GPUs). This work improves the computational efficiency of the entire pipeline by several orders of magnitude and significantly advances the overall efficiency and applicability of the method. I show how this enables the development of improved algorithms with increased capabilities for extracting relevant biological information form the data. Several such improvements are presented that significantly increase the resolution of the refinement results and provide additional information about the dynamics of the system. Additionally, I present an application of these methods to data collected on a biogenesis intermediate of the mitochondrial ribosome. The new structures provide insights into the timing of the rRNA folding and protein incorporation as well as the role of two previously unknown assembly factors during the final stages of ribosome maturation.

Macromolecular complexes that exhibit continuous forms of structural flexibility pose a challenge for many existing tools in cryo-EM single-particle analysis. We describe a new tool, called multi-body refinement, which models flexible complexes as a user-defined number of rigid bodies that move independently from each other. Using separate focused refinements with iteratively improved partial signal subtraction, the new tool generates improved reconstructions for each of the defined bodies in a fully automated manner. Moreover, using principal component analysis on the relative orientations of the bodies over all particle images in the data set, we generate movies that describe the most important motions in the data. Our results on two test cases, a cytoplasmic ribosome from Plasmodium falciparum, and the spliceosomal B-complex from yeast, illustrate how multi-body refinement can be useful to gain unique insights into the structure and dynamics of large and flexible macromolecular complexes.

Here, we describe the third major release of RELION. CPU-based vector acceleration has been added in addition to GPU support, which provides flexibility in use of resources and avoids memory limitations. Reference-free autopicking with Laplacian-of-Gaussian filtering and execution of jobs from python allows non-interactive processing during acquisition, including 2D-classification, de novo model generation and 3D-classification. Per-particle refinement of CTF parameters and correction of estimated beam tilt provides higher resolution reconstructions when particles are at different heights in the ice, and/or coma-free alignment has not been optimal. Ewald sphere curvature correction improves resolution for large particles. We illustrate these developments with publicly available data sets: together with a Bayesian approach to beam-induced motion correction it leads to resolution improvements of 0.2-0.7 angstrom compared to previous RELION versions.

Oxygenic photosynthesis produces oxygen and builds a variety of organic compounds, changing the chemistry of the air, the sea and fuelling the food chain on our planet. The photochemical reactions underpinning this process in plants take place in the chloroplast. Chloroplasts evolved ~1.2 billion years ago from an engulfed primordial diazotrophic cyanobacterium, and chlororibosomes are responsible for synthesis of the core proteins driving photochemical reactions. Chlororibosomal activity is spatiotemporally coupled to the synthesis and incorporation of functionally essential co-factors, implying the presence of chloroplast-specific regulatory mechanisms and structural adaptation of the chlororibosome^1,2. Despite recent structural information^3,4,5,6, some of these aspects remained elusive. To provide new insights into the structural specialities and evolution, we report a comprehensive analysis of the 2.9–3.1 Å resolution electron cryo-microscopy structure of the spinach chlororibosome in complex with its recycling factor and hibernation-promoting factor. The model reveals a prominent channel extending from the exit tunnel to the chlororibosome exterior, structural re-arrangements that lead to increased surface area for translocon binding, and experimental evidence for parallel and convergent evolution of chloro- and mitoribosomes.

The sugar transporter Lactose permease (LacY) of Escherichia coli has become a prototype to understand the underlying molecular details of membrane transport. Crystal structures have trapped the protein in sugar-bound states facing the periplasm, but with narrow openings unable to accommodate sugar. Therefore, the molecular details of sugar uptake remain elusive. In this work, we have used extended simulations and metadynamics sampling to explore a putative sugar-uptake pathway and associated free energy landscape. We found an entrance at helix-pair 2 and 11, which involved lipid head groups and residues Gln 241 and Gln 359. Furthermore, the protein displayed high flexibility on the periplasmic side of Phe 27, which is located at the narrowest section of the pathway. Interactions to Phe 27 enabled passage into the binding site, which was associated with a 24 +/- 4 kJ/mol binding free energy in excellent agreement with an independent binding free energy calculation and experimental data. Two free energy minima corresponding to the two possible binding poses of the lactose analog beta-D-galactopyranosyl-1-thio-beta-D-galactopyranoside (TDG) were aligned with the crystal structure-binding pocket. This work outlines the chemical environment of a putative periplasmic sugar pathway and paves way for understanding substrate affinity and specificity in LacY.

The introduction of direct detectors and the automation of data collection in cryo-EM have led to a surge in data, creating new opportunities for advancing computational processing. In particular, on-the-fly workflows that connect data collection with three-dimensional reconstruction would be valuable for more efficient use of cryo-EM and its application as a sample-screening tool. Here, accelerated on-the-fly analysis is reported with optimized organization of the data-processing tools, image acquisition and particle alignment that make it possible to reconstruct the three-dimensional density of the 70S chlororibosome to 3.2 angstrom resolution within 24 h of tissue harvesting. It is also shown that it is possible to achieve even faster processing at comparable quality by imposing some limits to data use, as illustrated by a 3.7 angstrom resolution map that was obtained in only 80 min on a desktop computer. These on-the-fly methods can be employed as an assessment of data quality from small samples and extended to high-throughput approaches.

Mammalian mitochondrial ribosomes (mitoribosomes) have less rRNA content and 36 additional proteins compared with the evolutionarily related bacterial ribosome. These differences make the assembly of mitoribosomes more complex than the assembly of bacterial ribosomes, but the molecular details of mitoribosomal biogenesis remain elusive. Here, we report the structures of two late-stage assembly intermediates of the human mitoribosomal large subunit (mt-LSU) isolated from a native pool within a human cell line and solved by cryo-EM to similar to 3-angstrom resolution. Comparison of the structures reveals insights into the timing of rRNA folding and protein incorporation during the final steps of ribosomal maturation and the evolutionary adaptations that are required to preserve biogenesis after the structural diversification of mitoribosomes. Furthermore, the structures redefine the ribosome silencing factor (RsfS) family as multifunctional biogenesis factors and identify two new assembly factors (L0R8F8 and mt-ACP) not previously implicated in mitoribosomal biogenesis.

By reaching near-atomic resolution for a wide range of specimens, single-particle cryo-EM structure determination is transforming structural biology. However, the necessary calculations come at large computational costs, which has introduced a bottleneck that is currently limiting throughput and the development of new methods. Here, we present an implementation of the RELION image processing software that uses graphics processors (GPUs) to address the most computationally intensive steps of its cryo-EM structure determination workflow. Both image classification and high-resolution refinement have been accelerated more than an order-of-magnitude, and template-based particle selection has been accelerated well over two orders-of-magnitude on desktop hardware. Memory requirements on GPUs have been reduced to fit widely available hardware, and we show that the use of single precision arithmetic does not adversely affect results. This enables high-resolution cryo-EM structure determination in a matter of days on a single workstation.

The small-angle X-ray scattering (SAXS) methodology enables structural characterization of biological macromolecules in solution. However, because SAXS provides low-dimensional information, several potential structural configurations can reproduce the experimental scattering profile, which severely complicates the structural refinement process. Here, we present a bias-exchange metadynamics refinement protocol that incorporates SAXS data as collective variables and therefore tags all possible configurations with their corresponding free energies, which allows identification of a unique structural solution. The method has been implemented in PLUMED and combined with the GROMACS simulation package, and as a proof of principle, we explore the Trp-cage protein folding landscape.