New developments in crystallography: exploring its technology, methods and scope in the molecular biosciences

X-Ray Crystallography for Macromolecular Complexes

X-ray crystallography has for most of the last century been the standard technique to determine the high-resolution structure of biological macromolecules, including multi-subunit protein-protein and protein-nucleic acids as large as the ribosome and viruses. As such, the successful application of X-ray crystallography to many biological problems revolutionized biology and biomedicine by solving the structures of small molecules and vitamins, peptides and proteins, DNA and RNA molecules, and many complexes-affording a detailed knowledge of the structures that clarified biological and chemical mechanisms, conformational changes, interactions, catalysis and the biological processes underlying DNA replication, translation, and protein synthesis. Now reaching well into the first quarter of the twenty-first century, X-ray crystallography shares the structural biology stage with cryo-electron microscopy and other innovative structure determination methods, as relevant and central to our understanding of biological function and structure as ever. In this chapter, we provide an overview of modern X-ray crystallography and how it interfaces with other mainstream structural biology techniques, with an emphasis on macromolecular complexes.

Interaction of Vanadium Complexes with Proteins: Revisiting the Reported Structures in the Protein Data Bank (PDB) since 2015

The structural determination and characterization of molecules, namely proteins and enzymes, is crucial to gaining a better understanding of their role in different chemical and biological processes. The continuous technical developments in the experimental and computational resources of X-ray diffraction (XRD) and, more recently, cryogenic Electron Microscopy (cryo-EM) led to an enormous growth in the number of structures deposited in the Protein Data Bank (PDB). Bioinorganic chemistry arose as a relevant discipline in biology and therapeutics, with a massive number of studies reporting the effects of metal complexes on biological systems, with vanadium complexes being one of the relevant systems addressed. In this review, we focus on the interactions of vanadium compounds (VCs) with proteins. Several types of binding are established between VCs and proteins/enzymes. Considering that the V-species that bind may differ from those initially added, the mentioned structural techniques are pivotal to clarifying the nature and variety of interactions of VCs with proteins and to proposing the mechanisms involved either in enzymatic inhibition or catalysis. As such, we provide an account of the available structural information of VCs bound to proteins obtained by both XRD and/or cryo-EM, mainly exploring the more recent structures, particularly those containing organic-based vanadium complexes.

Behind the Optimization of the Sensor Film: Bioconjugation of Triangular Gold Nanoparticles with Hemoproteins for Sensitivity Enhancement of Enzymatic Biosensors

Electrochemical biosensors are widely used in a multitude of applications, such as medical, nutrition, research, among other fields. These sensors have been historically used and have not undergone many changes in terms of the involved electrochemical processes. In this work, we propose a new approach on the immobilization and enhancement of the electrochemical properties of the sensing layers through the control and bioconjugation of hemoproteins (hemoglobin, myoglobin, and cytochrome C) on anisotropic gold nanoparticles (gold nanotriangles (AuNTs)). The hemeproteins and the AuNTs are mixed in a solution, resulting in stable bioconjugates that are deposited onto the electrode surface to obtain the biosensors. All the systems proposed herein exhibited direct well-defined redox responses, highlighting the key role of the AuNTs acting as mediators of such electron transfers. Several protein layers surrounding the AuNTs are electroactive, as demonstrated from the charge measured by cyclic voltammetry. The retention of the stability of the hemeproteins once they are part of the bioconjugates is evidenced towards the electrocatalytic reduction of hydrogen peroxide, oxygen, and nitrite. The parameters obtained for the proposed biosensors are similar or even lower than those previously reported for similar systems based on nanomaterials, and they exhibit attractive properties that make them potential candidates for the latest developments in the field of sensing devices.

Fundamental Redesign of the TIGER2hs Kernel to Address Severe Parameter Sensitivity

Replica exchange molecular dynamics simulations are one of the most popular approaches to enhance conformational sampling of molecular systems. Applications range from protein folding to protein-protein or other host-guest interactions, as well as binding free energy calculations. While these methods are computationally expensive, highly accurate results can be obtained. We recently developed TIGER2hs, an improved version of the temperature intervals with global exchange of replicas (TIGER2) algorithm. This method combines the replica-based enhanced sampling in an explicit solvent with a hybrid solvent energy evaluation. During the exchange attempts, bulk water is replaced by an implicit solvent model, allowing sampling with significantly less replicas than parallel tempering (REMD). This enables accurate enhanced sampling calculations with only a fraction of computational resources compared to REMD. Our latest results highlight several issues with sampling imbalance and parameter sensitivity within the original TIGER2 exchange algorithms that affect the overall state populations. A high sensitivity on replica number and maximum temperature is eliminated by changing to a pairwise exchange kernel (PE) without additional sorting. Simulations are controlled by adjusting the average temperature change per exchange ⟨ΔT/χ⟩ to below 30 K to mimic a controlled temperature mixing of replicas similar to REMD. Thus, this parameter provides an applicable property for selecting combinations of replica number and maximum temperature to adjust simulations for best accuracy, with flexible resource investment. This increases the robustness of the method and ensures results in excellent agreement with REMD, as demonstrated for three different peptides.

Extended-ensemble docking to probe dynamic variation of ligand binding sites during large-scale structural changes of proteins

Proteins can sample a broad landscape as they undergo conformational transition between different functional states. At the same time, as key players in almost all cellular processes, proteins are important drug targets. Considering the different conformational states of a protein is therefore central for a successful drug-design strategy. Here we introduce a novel docking protocol, termed extended-ensemble docking, pertaining to proteins that undergo large-scale (global) conformational changes during their function. In its application to multidrug ABC-transporter P-glycoprotein (Pgp), extensive non-equilibrium molecular dynamics simulations employing system-specific collective variables are first used to describe the transition cycle of the transporter. An extended set of conformations (extended ensemble) representing the full transition cycle between the inward- and the outward-facing states is then used to seed high-throughput docking calculations of known substrates, non-substrates, and modulators of the transporter. Large differences are predicted in the binding affinities to different conformations, with compounds showing stronger binding affinities to intermediate conformations compared to the starting crystal structure. Hierarchical clustering of the binding modes shows all ligands preferably bind to the large central cavity of the protein, formed at the apex of the transmembrane domain (TMD), whereas only small binding populations are observed in the previously described R and H sites present within the individual TMD leaflets. Based on the results, the central cavity is further divided into two major subsites, first preferably binding smaller substrates and high-affinity inhibitors, whereas the second one shows preference for larger substrates and low-affinity modulators. These central subsites along with the low-affinity interaction sites present within the individual TMD leaflets may respectively correspond to the proposed high- and low-affinity binding sites in Pgp. We propose further an optimization strategy for developing more potent inhibitors of Pgp, based on increasing its specificity to the extended ensemble of the protein, instead of using a single protein structure, as well as its selectivity for the high-affinity binding site. In contrast to earlier in silico studies using single static structures of Pgp, our results show better agreement with experimental studies, pointing to the importance of incorporating the global conformational flexibility of proteins in future drug-discovery endeavors.

Visualizing RNA Structures by SAXS-Driven MD Simulations

The biological role of biomolecules is intimately linked to their structural dynamics. Experimental or computational techniques alone are often insufficient to determine accurate structural ensembles in atomic detail. We use all-atom molecular dynamics (MD) simulations and couple it to small-angle X-ray scattering (SAXS) experiments to resolve the structural dynamics of RNA molecules. To accomplish this task, we utilize a set of re-weighting and biasing techniques tailored for RNA molecules. To showcase our approach, we study two RNA molecules: a riboswitch that shows structural variations upon ligand binding, and a two-way junction RNA that displays structural heterogeneity and sensitivity to salt conditions. Integration of MD simulations and experiments allows the accurate construction of conformational ensembles of RNA molecules. We observe a dynamic change of the SAM-I riboswitch conformations depending on its binding partners. The binding of SAM and Mg2+ cations stabilizes the compact state. The absence of Mg2+ or SAM leads to the loss of tertiary contacts, resulting in a dramatic expansion of the riboswitch conformations. The sensitivity of RNA structures to the ionic strength demonstrates itself in the helix junction helix (HJH). The HJH shows non-monotonic compaction as the ionic strength increases. The physics-based picture derived from the experimentally guided MD simulations allows biophysical characterization of RNA molecules. All in all, SAXS-guided MD simulations offer great prospects for studying RNA structural dynamics.

Novel Device and Strategy for Growing Large, High-Quality Protein Crystals by Controlling Crystallization Conditions

Neutron diffraction experiments are informative for determining the locations of hydrogen atoms in protein molecules; however, much larger crystals are needed than those required for X-ray diffraction. Thus, additional techniques are required to grow larger crystals. Here, a unique crystallization device and strategy for growing large protein crystals are introduced. The device uses two micropumps to control crystal growth by altering the precipitant concentration and regulating the pinpoint injection of dry air flow to the crystallization cell. Furthermore, the crystal growth can be observed in real time. Preliminary microbatch crystallization experiments at various concentration ranges of polyethylene glycol (PEG) 4000 and sodium chloride were first performed to elucidate optimized crystallization conditions. Based on these results, a device to precisely control the sodium chloride and PEG concentrations and the supply of dry air to the crystallization cell was used, and 1.8 mm lysozyme and 1.5 mm alpha-amylase crystals with good reproducibility were obtained. X-ray data sets of both crystals were collected at room temperature at BL2S1 of the Aichi Synchrotron Radiation Center and confirmed that these crystals were of high quality. Therefore, this crystallization device and strategy were effective for growing large, high-quality protein crystals.

Deep Learning in Virtual Screening: Recent Applications and Developments

Drug discovery is a cost and time-intensive process that is often assisted by computational methods, such as virtual screening, to speed up and guide the design of new compounds. For many years, machine learning methods have been successfully applied in the context of computer-aided drug discovery. Recently, thanks to the rise of novel technologies as well as the increasing amount of available chemical and bioactivity data, deep learning has gained a tremendous impact in rational active compound discovery. Herein, recent applications and developments of machine learning, with a focus on deep learning, in virtual screening for active compound design are reviewed. This includes introducing different compound and protein encodings, deep learning techniques as well as frequently used bioactivity and benchmark data sets for model training and testing. Finally, the present state-of-the-art, including the current challenges and emerging problems, are examined and discussed.

IceBear: an intuitive and versatile web application for research-data tracking from crystallization experiment to PDB deposition

The web-based IceBear software is a versatile tool to monitor the results of crystallization experiments and is designed to facilitate supervisor and student communications. It also records and tracks all relevant information from crystallization setup to PDB deposition in protein crystallography projects. Fully automated data collection is now possible at several synchrotrons, which means that the number of samples tested at the synchrotron is currently increasing rapidly. Therefore, the protein crystallography research communities at the University of Oulu, Weizmann Institute of Science and Diamond Light Source have joined forces to automate the uploading of sample metadata to the synchrotron. In IceBear, each crystal selected for data collection is given a unique sample name and a crystal page is generated. Subsequently, the metadata required for data collection are uploaded directly to the ISPyB synchrotron database by a shipment module, and for each sample a link to the relevant ISPyB page is stored. IceBear allows notes to be made for each sample during cryocooling treatment and during data collection, as well as in later steps of the structure determination. Protocols are also available to aid the recycling of pins, pucks and dewars when the dewar returns from the synchrotron. The IceBear database is organized around projects, and project members can easily access the crystallization and diffraction metadata for each sample, as well as any additional information that has been provided via the notes. The crystal page for each sample connects the crystallization, diffraction and structural information by providing links to the IceBear drop-viewer page and to the ISPyB data-collection page, as well as to the structure deposited in the Protein Data Bank.

Semi-empirical model to estimate ideal conditions for the growth of large protein crystals

A large high-quality crystal is required to specify the positions of H atoms in neutron structural analysis. Consequently, several methods have been proposed for obtaining such large crystals, and theoretical considerations for growing them have been presented. However, further investigation is required to obtain a numerical model that can provide quantitative experimental conditions for obtaining a single large crystal. In the case of protein crystallization experiments, the amount of sample is often limited. Therefore, it is more realistic to make a rough estimation from a small number of experiments. This paper proposes a method of estimating the optimum experimental conditions for the growth of large protein crystals by performing a small number of experiments using a micro-batch method and reporting a numerical model based on nucleation theory and a linear approximation of the crystal-growth rate. Specifically, micro-batch experiments are performed to provide the empirical parameters for the model and to help to estimate the conditions for the growth of a crystal of a predetermined size using a certain sample concentration and volume. This method is offered as a step on the path towards efficiently and rationally producing large crystals that can be subjected to neutron diffraction without depending on luck or on performing many experiments. It is expected to contribute to drug design and the elucidation of protein molecular functions and mechanisms by obtaining positional information on H atoms in the protein molecule, which is an advantage of neutron diffraction.

Recent Progress in the Discovery and Development of 2-Nitroimidazooxazines and 6-Nitroimidazooxazoles to Treat Tuberculosis and Neglected Tropical Diseases

Nitroimidazole drugs have a long history as therapeutic agents to treat bacterial and parasitic diseases. The discovery in 1989 of a bicyclic nitroimidazole lead, displaying in vitro and in vivo antitubercular activity, spurred intensive exploration of this and related scaffolds, which led to the regulatory approval of pretomanid and delamanid as a new class of tuberculosis drugs. Much of the discovery work related to this took place over a 20-year period ending in 2010, which is covered in a number of cited reviews. This review highlights subsequent research published over the 2011–August 2020 timeframe, and captures detailed structure–activity relationship studies and synthetic strategies directed towards uncovering newer generation drugs for both tuberculosis and selected neglected tropical diseases. Additionally, this review presents in silico calculations relating to the drug-like properties of lead compounds and clinical agents, as well as chemical development and manufacturing processes toward providing bulk drug supplies.

Collision-Induced Unfolding Studies of Proteins and Protein Complexes using Drift Tube Ion Mobility-Mass Spectrometer

Elucidating the structures and stabilities of proteins and their complexes is paramount to understanding their biological functions in cellular processes. Native mass spectrometry (MS) coupled with ion mobility spectrometry (IMS) is emerging as an important biophysical technique owing to its high sensitivity, rapid analysis time, and ability to interrogate sample complexity or heterogeneity and the ability to probe protein structure dynamics. Here, a commercial IMS-MS platform has been modified for static native ESI emitters and an extended mass-to-charge range (20 kDa m/z) and its performance capabilities and limits were explored for a range of protein and protein complexes. The results show new potential for this instrument platform for studies of large protein and protein complexes and provides a roadmap for extending the performance metrics for studies of even larger, more complex systems, namely, membrane protein complexes and their interactions with ligands.

Seeing is believing: structures and functions of biological molecules

The ability to elucidate the structure and function of biological molecules holds great importance in a variety of domains. This includes prospects to tackle public health concerns, identification of new drug targets and therapeutic agents. In this issue of Tech News, Nawsheen Boodhun explores techniques used to understand macromolecules.

Characterizing metal-binding sites in proteins with X-ray crystallography

Metals have crucial roles in many physiological, pathological, toxicological, pharmaceutical, and diagnostic processes. Proper handling of metal-containing macromolecule samples for structural studies is not trivial, and failure to handle them properly is often a source of irreproducibility caused by issues such as pH changes, incorporation of unexpected metals, or oxidization/reduction of the metal. This protocol outlines the guidelines and best practices for characterizing metal-binding sites in protein structures and alerts experimenters to potential pitfalls during the preparation and handling of metal-containing protein samples for X-ray crystallography studies. The protocol features strategies for controlling the sample pH and the metal oxidation state, recording X-ray fluorescence (XRF) spectra, and collecting diffraction data sets above and below the corresponding metal absorption edges. This protocol should allow experimenters to gather sufficient evidence to unambiguously determine the identity and location of the metal of interest, as well as to accurately characterize the coordinating ligands in the metal binding environment within the protein. Meticulous handling of metal-containing macromolecule samples as described in this protocol should enhance experimental reproducibility in biomedical sciences, especially in X-ray macromolecular crystallography. For most samples, the protocol can be completed within a period of 7-190 d, most of which (2-180 d) is devoted to growing the crystal. The protocol should be readily understandable to structural biologists, particularly protein crystallographers with an intermediate level of experience.

X-ray data processing

The method of molecular structure determination by X-ray crystallography is a little over a century old. The history is described briefly, along with developments in X-ray sources and detectors. The fundamental processes involved in measuring diffraction patterns on area detectors, i.e. autoindexing, refining crystal and detector parameters, integrating the reflections themselves and putting the resultant measurements on to a common scale are discussed, with particular reference to the most commonly used software in the field.