A brief history of macromolecular crystallography, illustrated by a family tree and its Nobel fruits

Emerging Topics in Protein Crystallography

Protein crystallography is the discipline concerned with the determination of the three-dimensional structure of biological macromolecules in a crystalline state [...].

Words of advice: teaching macromolecular crystallography

The ability to view structures of proteins at atomic resolution, facilitated by the rise of macromolecular crystallography, has had a tremendous impact in many areas of sciences, including molecular pharmacology, drug discovery and biotechnology. However, the teaching of macromolecular crystallography in universities across the globe has been less than optimal. This could be attributed to the interdisciplinary nature of this subject, making it appear esoteric and incomprehensible, at least at first glance, for students who have exclusive training in only one specific discipline. For the instructor, this problem is compounded further by the plethora of complex concepts and specialized terminologies that the science of macromolecular crystallography has accumulated over the course of its evolution. Moreover, the advent of robotics and several sophisticated software algorithms have reduced the incentive to understand the beautiful conceptual bedrock on which this subject is based. As a way of addressing some of the challenges delineated above, this Words of Advice article attempts to formulate the broad framework within which the teaching and learning of macromolecular crystallography should be approached. It advocates the acknowledgement that this is an interdisciplinary field, with substantial contributions from chemical, physical, biological and mathematical sciences, requiring the evolution of teaching approaches that acknowledge this reality. Moreover, it suggests the use of visual tools, use of computational resources and history to make the subject more relatable to students.

Advances in chaperone-assisted RNA crystallography using synthetic antibodies

RNA molecules play essential roles in many biological functions, from gene expression regulation, cellular growth, and metabolism to catalysis. They frequently fold into three-dimensional structures to perform their functions. Therefore, determining RNA structure represents a key step for understanding the structure-function relationships and developing RNA-targeted therapeutics. X-ray crystallography remains a method of choice for determining high-resolution RNA structures, but it has been challenging due to difficulties associated with RNA crystallization and phasing. Several natural and synthetic RNA binding proteins have been used to facilitate RNA crystallography. Having unique properties to help crystal packing and phasing, synthetic antibody fragments, specifically the Fabs, have emerged as promising RNA crystallization chaperones, and so far, over a dozen of RNA structures have been solved using this strategy. Nevertheless, multiple steps in this approach need to be improved, including the recombinant expression of these anti-RNA Fabs, to warrant the full potential of these synthetic Fabs as RNA crystallization chaperones. This review highlights the nuts and bolts and recent advances in the chaperone-assisted RNA crystallography approach, specifically emphasizing the Fab antibody fragments as RNA crystallization chaperones.

Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics

Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19.

Comparative In Silico Analysis and Functional Characterization of TANK-Binding Kinase 1–Binding Protein 1

Protein modelling plays a vital role in the drug discovery process. TANK-binding kinase 1–binding protein 1 is also called an adapter protein, which is encoded by gene TBK1 present in Homo sapiens. It is found in lungs, small intestine, leukocytes, heart, placenta, muscle, kidney, lower level of thymus, and brain. It has a number of protein-binding sites, to which TBK1 and IKBKE bind and perform different functions as immunomodulatory, antiproliferative, and antiviral innate immunity which release different types of interferons. Our study predicts the comparative model of 3-dimensional (3D) structure through different bioinformatics tools that will be helpful for further studies in future. The reactivity and stability of these proteins were evaluated physicochemically and through domain determination and prediction of secondary structure using bioinformatics methods such as ProtParam, Pfam, and SOPMA, respectively. Robetta, an ab initio approach, I-TASSER, and AlphaFold was used for 3D structure prediction, and the models were validated using the SAVESv6.0 (PROCHECK) server. Conclusively, the best 3D structure of TBK1-binding protein 1 was predicted using Robetta software. After unveiling the 3D structure of the novel protein, we concluded that this structure will help us to find out its role other than in antiviral innate immunity and by producing torsion in its 3D structure researchers will be able to detect either this protein is involved in any disease or not because according to previous studies it was not associated with any disease.

Vetinformatics from functional genomics to drug discovery: Insights into decoding complex molecular mechanisms of livestock systems in veterinary science

Having played important roles in human growth and development, livestock animals are regarded as integral parts of society. However, industrialization has depleted natural resources and exacerbated climate change worldwide, spurring the emergence of various diseases that reduce livestock productivity. Meanwhile, a growing human population demands sufficient food to meet their needs, necessitating innovations in veterinary sciences that increase productivity both quantitatively and qualitatively. We have been able to address various challenges facing veterinary and farm systems with new scientific and technological advances, which might open new opportunities for research. Recent breakthroughs in multi-omics platforms have produced a wealth of genetic and genomic data for livestock that must be converted into knowledge for breeding, disease prevention and management, productivity, and sustainability. Vetinformatics is regarded as a new bioinformatics research concept or approach that is revolutionizing the field of veterinary science. It employs an interdisciplinary approach to understand the complex molecular mechanisms of animal systems in order to expedite veterinary research, ensuring food and nutritional security. This review article highlights the background, recent advances, challenges, opportunities, and application of vetinformatics for quality veterinary services.

Implementation of level-2 biosafety for a macromolecular crystallography beamline at SSRF

Macromolecular crystallography is commonly used to determine the structure of biological macromolecules. Currently the beamlines at synchrotron radiation facilities play an important role in macromolecular crystallography, and have produced an enormous number of molecular structures to help solve scientific questions and support applications. Structure information makes significant contributions to the virus-related research as well. However, it is mandatory to be protected the operators under a compatible biosafety infrastructure when a pathological agent is set up in a beamline. Here a level-2 biosafety protection for a macromolecular crystallography beamline at Shanghai Synchrotron Radiation Facility (SSRF) is introduced. To fulfill the biosafety in a radioactive environment, a dedicated design is implemented. Since the beamline will be opened to the external users from nationwide research units, the management process and experimental method are also drawn up.

Ten things I `hate' about refinement

Macromolecular refinement is an optimization process that aims to produce the most likely macromolecular structural model in the light of experimental data. As such, macromolecular refinement is one of the most complex optimization problems in wide use. Macromolecular refinement programs have to deal with the complex relationship between the parameters of the atomic model and the experimental data, as well as a large number of types of prior knowledge about chemical structure. This paper draws attention to areas of unfinished business in the field of macromolecular refinement. In it, we describe ten refinement topics that we think deserve attention and discuss directions leading to macromolecular refinement software that would make the best use of modern computer resources to meet the needs of structural biologists of the twenty-first century.

Structure and function relationship of OqxB efflux pump from Klebsiella pneumoniae

OqxB is an RND (Resistance-Nodulation-Division) efflux pump that has emerged as a factor contributing to the antibiotic resistance in Klebsiella pneumoniae. OqxB underwent horizontal gene transfer and is now seen in other Gram-negative bacterial pathogens including Escherichia coli, Enterobacter cloacae and Salmonella spp., further disseminating multi-drug resistance. In this study, we describe crystal structure of OqxB with n-dodecyl-β-D-maltoside (DDM) molecules bound in its substrate-binding pocket, at 1.85 Å resolution. We utilize this structure in computational studies to predict the key amino acids contributing to the efflux of fluoroquinolones by OqxB, distinct from analogous residues in related transporters AcrB and MexB. Finally, our complementation assays with mutated OqxB and minimum inhibitory concentration (MIC) experiments with clinical isolates of E. coli provide further evidence that the predicted structural features are indeed involved in ciprofloxacin efflux.

Highly accurate protein structure prediction with AlphaFold

Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort1-4, the structures of around 100,000 unique proteins have been determined5, but this represents a small fraction of the billions of known protein sequences6,7. Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence-the structure prediction component of the 'protein folding problem'8-has been an important open research problem for more than 50 years9. Despite recent progress10-14, existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14)15, demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm.

Advancements in macromolecular crystallography: from past to present

Protein Crystallography or Macromolecular Crystallography (MX) started as a new discipline of science with the pioneering work on the determination of the protein crystal structures by John Kendrew in 1958 and Max Perutz in 1960. The incredible achievements in MX are attributed to the development of advanced tools, methodologies, and automation in every aspect of the structure determination process, which have reduced the time required for solving protein structures from years to a few days, as evident from the tens of thousands of crystal structures of macromolecules available in PDB. The advent of brilliant synchrotron sources, fast detectors, and novel sample delivery methods has shifted the paradigm from static structures to understanding the dynamic picture of macromolecules; further propelled by X-ray Free Electron Lasers (XFELs) that explore the femtosecond regime. The revival of the Laue diffraction has also enabled the understanding of macromolecules through time-resolved crystallography. In this review, we present some of the astonishing method-related and technological advancements that have contributed to the progress of MX. Even with the rapid evolution of several methods for structure determination, the developments in MX will keep this technique relevant and it will continue to play a pivotal role in gaining unprecedented atomic-level details as well as revealing the dynamics of biological macromolecules. With many exciting developments awaiting in the upcoming years, MX has the potential to contribute significantly to the growth of modern biology by unraveling the mechanisms of complex biological processes as well as impacting the area of drug designing.

How structural biology transformed studies of transcription regulation

The past 4 decades have seen remarkable advances in our understanding of the structural basis of gene regulation. Technological advances in protein expression, nucleic acid synthesis, and structural biology made it possible to study the proteins that regulate transcription in the context of ever larger complexes containing proteins bound to DNA. This review, written on the occasion of the 50th anniversary of the founding of the Protein Data Bank focuses on the insights gained from structural studies of protein-DNA complexes and the role the PDB has played in driving this research. I cover highlights in the field, beginning with X-ray crystal structures of the first DNA-binding domains to be studied, through recent cryo-EM structures of transcription factor binding to nucleosomal DNA.

Looking Back: A Short History of the Discovery of Enzymes and How They Became Powerful Chemical Tools

Enzymatic approaches to challenges in chemical synthesis are increasingly popular and very attractive to industry given their green nature and high efficiency compared to traditional methods. In this historical review we highlight the developments across several fields that were necessary to create the modern field of biocatalysis, with enzyme engineering and directed evolution at its core. We exemplify the modular, incremental, and highly unpredictable nature of scientific discovery, driven by curiosity, and showcase the resulting examples of cutting-edge enzymatic applications in industry.

Accurate crystal structures and chemical properties from NoSpherA2

The relationship between the structure and the properties of a drug or material is a key concept of chemistry. Knowledge of the three-dimensional structure is considered to be of such importance that almost every report of a new chemical compound is accompanied by an X-ray crystal structure – at least since the 1970s when diffraction equipment became widely available. Crystallographic software of that time was restricted to very limited computing power, and therefore drastic simplifications had to be made. It is these simplifications that make the determination of the correct structure, especially when it comes to hydrogen atoms, virtually impossible. We have devised a robust and fast system where modern chemical structure models replace the old assumptions, leading to correct structures from the model refinement against standard in-house diffraction data using no more than widely available software and desktop computing power. We call this system NoSpherA2 (Non-Spherical Atoms in Olex2). We explain the theoretical background of this technique and demonstrate the far-reaching effects that the improved structure quality that is now routinely available can have on the interpretation of chemical problems exemplified by five selected examples.

NoSpherA2 brings quantum crystallography to routine structure determination and to the analysis of chemical properties for any class of materials.

A Personal History of Using Crystals and Crystallography to Understand Biology and Advanced Drug Discovery

Over the past 60 years, the use of crystals to define structures of complexes using X-ray analysis has contributed to the discovery of new medicines in a very significant way. This has been in understanding not only small-molecule inhibitors of proteins, such as enzymes, but also protein or peptide hormones or growth factors that bind to cell surface receptors. Experimental structures from crystallography have also been exploited in software to allow prediction of structures of important targets based on knowledge of homologues. Crystals and crystallography continue to contribute to drug design and provide a successful example of academia–industry collaboration.

The Mutation of the "Nobel Prize in Chemistry" into the "Nobel Prize in Chemistry or Life Sciences": Several Decades of Transparent and Opaque Evidence of Change within the Nobel Prize Program

Over the past several decades, the Nobel Prize program has slowly but steadily been modified in both transparent and opaque ways. A transparent change has been the creation of the Nobel Prize in Economic Sciences, officially known as the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel. An opaque change has been the mutation of the Nobel Prize in Chemistry into what is effectively the "Nobel Prize in Chemistry or Life Sciences." This paper presents a detailed study of this opaque change, including evidence that the disciplines of chemistry and biochemistry cover, today, intellectually quite distinct and generally scientifically-unrelated intellectual territory. This paper supports the evolution of the Nobel Prizes, and encourages the Nobel Prize program to move from opaque to transparent change processes for the next generations of achievement in the sciences.

Stable sample delivery in viscous media via a capillary for serial crystallography

Serial crystallography (SX) is an innovative technology in structural biology that enables the visualization of the molecular dynamics of macromolecules at room temperature. SX experiments always require a considerable amount of effort to deliver a crystal sample to the X-ray interaction point continuously and reliably. Here, a sample-delivery method using a capillary and a delivery medium is introduced. The crystals embedded in the delivery medium can pass through the capillary tube, which is aligned with the X-ray beam, at very low flow rates without requiring elaborate delivery techniques, drastically reducing sample consumption. In serial millisecond crystallography using a viscous medium via a capillary, crystals of lysozyme embedded in agarose, which produce an unstable injection stream at atmospheric pressure, and crystals of glucose isomerase embedded in gelatin, which is known to be problematic for open-extruder operation, were stably delivered at a flow rate of 100 nl min−1. The room-temperature crystal structures of lysozyme and glucose isomerase were successfully determined at 1.85 and 1.70 Å resolutions, respectively. This simple but highly efficient sample-delivery method can allow researchers to deliver crystals precisely to an X-ray beam in SX experiments.

Fast and Accurate Quantum Crystallography: From Small to Large, from Light to Heavy

The coupling of the crystallographic refinement technique Hirshfeld atom refinement (HAR) with the recently constructed libraries of extremely localized molecular orbitals (ELMOs) gives rise to the new quantum-crystallographic method HAR-ELMO. This method is significantly faster than HAR but as accurate and precise, especially concerning the free refinement of hydrogen atoms from X-ray diffraction data, so that the first fully quantum-crystallographic refinement of a protein is presented here. However, the promise of HAR-ELMO exceeds large molecules and protein crystallography. In fact, it also renders possible electron-density investigations of heavy elements in small molecules and facilitates the detection and isolation of systematic errors from physical effects.

A simple and versatile microfluidic device for efficient biomacromolecule crystallization and structural analysis by serial crystallography

Determining optimal conditions for the production of well diffracting crystals is a key step in every biocrystallography project. Here, a microfluidic device is described that enables the production of crystals by counter-diffusion and their direct on-chip analysis by serial crystallography at room temperature. Nine 'non-model' and diverse biomacromolecules, including seven soluble proteins, a membrane protein and an RNA duplex, were crystallized and treated on-chip with a variety of standard techniques including micro-seeding, crystal soaking with ligands and crystal detection by fluorescence. Furthermore, the crystal structures of four proteins and an RNA were determined based on serial data collected on four synchrotron beamlines, demonstrating the general applicability of this multipurpose chip concept.

Sample Delivery Media for Serial Crystallography

X-ray crystallographic methods can be used to visualize macromolecules at high resolution. This provides an understanding of molecular mechanisms and an insight into drug development and rational engineering of enzymes used in the industry. Although conventional synchrotron-based X-ray crystallography remains a powerful tool for understanding molecular function, it has experimental limitations, including radiation damage, cryogenic temperature, and static structural information. Serial femtosecond crystallography (SFX) using X-ray free electron laser (XFEL) and serial millisecond crystallography (SMX) using synchrotron X-ray have recently gained attention as research methods for visualizing macromolecules at room temperature without causing or reducing radiation damage, respectively. These techniques provide more biologically relevant structures than traditional X-ray crystallography at cryogenic temperatures using a single crystal. Serial femtosecond crystallography techniques visualize the dynamics of macromolecules through time-resolved experiments. In serial crystallography (SX), one of the most important aspects is the delivery of crystal samples efficiently, reliably, and continuously to an X-ray interaction point. A viscous delivery medium, such as a carrier matrix, dramatically reduces sample consumption, contributing to the success of SX experiments. This review discusses the preparation and criteria for the selection and development of a sample delivery medium and its application for SX.

Fast and accurate data collection for macromolecular crystallography using the JUNGFRAU detector

The accuracy of X-ray diffraction data is directly related to how the X-ray detector records photons. Here we describe the application of a direct-detection charge-integrating pixel-array detector (JUNGFRAU) in macromolecular crystallography (MX). JUNGFRAU features a uniform response on the subpixel level, linear behavior toward high photon rates, and low-noise performance across the whole dynamic range. We demonstrate that these features allow accurate MX data to be recorded at unprecedented speed. We also demonstrate improvements over previous-generation detectors in terms of data quality, using native single-wavelength anomalous diffraction (SAD) phasing, for thaumatin, lysozyme, and aminopeptidase N. Our results suggest that the JUNGFRAU detector will substantially improve the performance of synchrotron MX beamlines and equip them for future synchrotron light sources.

A brief history of bioinformatics

It is easy for today’s students and researchers to believe that modern bioinformatics emerged recently to assist next-generation sequencing data analysis. However, the very beginnings of bioinformatics occurred more than 50 years ago, when desktop computers were still a hypothesis and DNA could not yet be sequenced. The foundations of bioinformatics were laid in the early 1960s with the application of computational methods to protein sequence analysis (notably, de novo sequence assembly, biological sequence databases and substitution models). Later on, DNA analysis also emerged due to parallel advances in (i) molecular biology methods, which allowed easier manipulation of DNA, as well as its sequencing, and (ii) computer science, which saw the rise of increasingly miniaturized and more powerful computers, as well as novel software better suited to handle bioinformatics tasks. In the 1990s through the 2000s, major improvements in sequencing technology, along with reduced costs, gave rise to an exponential increase of data. The arrival of ‘Big Data’ has laid out new challenges in terms of data mining and management, calling for more expertise from computer science into the field. Coupled with an ever-increasing amount of bioinformatics tools, biological Big Data had (and continues to have) profound implications on the predictive power and reproducibility of bioinformatics results. To overcome this issue, universities are now fully integrating this discipline into the curriculum of biology students. Recent subdisciplines such as synthetic biology, systems biology and whole-cell modeling have emerged from the ever-increasing complementarity between computer science and biology.

Prediction of DNA and RNA structure with the NARES-2P force field and conformational space annealing

A physics-based method for the prediction of the structures of nucleic acids, which is based on the physics-based 2-bead NARES-2P model of polynucleotides and global-optimization Conformational Space Annealing (CSA) algorithm has been proposed. The target structure is sought as the global-energy-minimum structure, which ignores the entropy component of the free energy but spares expensive multicanonical simulations necessary to find the conformational ensemble with the lowest free energy. The CSA algorithm has been modified to optimize its performance when treating both single and multi-chain nucleic acids. It was shown that the method finds the native fold for simple RNA molecules and DNA duplexes and with limited distance restraints, which can easily be obtained from the secondary-structure-prediction servers, complex RNA folds can be treated with using moderate computer resources.

Current Strategies and Applications for Precision Drug Design

Since Human Genome Project (HGP) revealed the heterogeneity of individuals, precision medicine that proposes the customized healthcare has become an intractable and hot research. Meanwhile, as the Precision Medicine Initiative launched, precision drug design which aims at maximizing therapeutic effects while minimizing undesired side effects for an individual patient has entered a new stage. One of the key strategies of precision drug design is target based drug design. Once a key pathogenic target is identified, rational drug design which constitutes the major part of precision drug design can be performed. Examples of rational drug design on novel druggable targets and protein-protein interaction surfaces are summarized in this review. Besides, various kinds of computational modeling and simulation approaches increasingly benefit for the drug discovery progress. Molecular dynamic simulation, drug target prediction and in silico clinical trials are discussed. Moreover, due to the powerful ability in handling high-dimensional data and complex system, deep learning has efficiently promoted the applications of artificial intelligence in drug discovery and design. In this review, deep learning methods that tailor to precision drug design are carefully discussed. When a drug molecule is discovered, the development of specific targeted drug delivery system becomes another key aspect of precision drug design. Therefore, state-of-the-art techniques of drug delivery system including antibody-drug conjugates (ADCs), and ligand-targeted conjugates are also included in this review.

Automated Protocols for Macromolecular Crystallization at the MRC Laboratory of Molecular Biology

When high quality crystals are obtained that diffract X-rays, the crystal structure may be solved at near atomic resolution. The conditions to crystallize proteins, DNAs, RNAs, and their complexes can however not be predicted. Employing a broad variety of conditions is a way to increase the yield of quality diffraction crystals. Two fully automated systems have been developed at the MRC Laboratory of Molecular Biology (Cambridge, England, MRC-LMB) that facilitate crystallization screening against 1,920 initial conditions by vapor diffusion in nanoliter droplets. Semi-automated protocols have also been developed to optimize conditions by changing the concentrations of reagents, the pH, or by introducing additives that potentially enhance properties of the resulting crystals. All the corresponding protocols will be described in detail and briefly discussed. Taken together, they enable convenient and highly efficient macromolecular crystallization in a multi-user facility, while giving the users control over key parameters of their experiments.

X-rays in the Cryo-Electron Microscopy Era: Structural Biology's Dynamic Future

Over the past several years, single-particle cryo-electron microscopy (cryo-EM) has emerged as a leading method for elucidating macromolecular structures at near-atomic resolution, rivaling even the established technique of X-ray crystallography. Cryo-EM is now able to probe proteins as small as hemoglobin (64 kDa) while avoiding the crystallization bottleneck entirely. The remarkable success of cryo-EM has called into question the continuing relevance of X-ray methods, particularly crystallography. To say that the future of structural biology is either cryo-EM or crystallography, however, would be misguided. Crystallography remains better suited to yield precise atomic coordinates of macromolecules under a few hundred kilodaltons in size, while the ability to probe larger, potentially more disordered assemblies is a distinct advantage of cryo-EM. Likewise, crystallography is better equipped to provide high-resolution dynamic information as a function of time, temperature, pressure, and other perturbations, whereas cryo-EM offers increasing insight into conformational and energy landscapes, particularly as algorithms to deconvolute conformational heterogeneity become more advanced. Ultimately, the future of both techniques depends on how their individual strengths are utilized to tackle questions at the frontiers of structural biology. Structure determination is just one piece of a much larger puzzle: a central challenge of modern structural biology is to relate structural information to biological function. In this perspective, we share insight from several leaders in the field and examine the unique and complementary ways in which X-ray methods and cryo-EM can shape the future of structural biology.

Combining X-Ray Crystallography with Small Angle X-Ray Scattering to Model Unstructured Regions of Nsa1 from S. Cerevisiae

Determination of the full-length structure of ribosome assembly factor Nsa1 from Saccharomyces cerevisiae (S. cerevisiae) is challenging because of the disordered and protease labile C-terminus of the protein. This manuscript describes the methods to purify recombinant Nsa1 from S. cerevisiae for structural analysis by both X-ray crystallography and SAXS. X-ray crystallography was utilized to solve the structure of the well-ordered N-terminal WD40 domain of Nsa1, and then SAXS was used to resolve the structure of the C-terminus of Nsa1 in solution. Solution scattering data was collected from full-length Nsa1 in solution. The theoretical scattering amplitudes were calculated from the high-resolution crystal structure of the WD40 domain, and then a combination of rigid body and ab initio modeling revealed the C-terminus of Nsa1. Through this hybrid approach the quaternary structure of the entire protein was reconstructed. The methods presented here should be generally applicable for the hybrid structural determination of other proteins composed of a mix of structured and unstructured domains.

Structure-based drug design: aiming for a perfect fit

Knowledge of the three-dimensional structure of therapeutically relevant targets has informed drug discovery since the first protein structures were determined using X-ray crystallography in the 1950s and 1960s. In this editorial we provide a brief overview of the powerful impact of structure-based drug design (SBDD), which has its roots in computational and structural biology, with major contributions from both academia and industry. We describe advances in the application of SBDD for integral membrane protein targets that have traditionally proved very challenging. We emphasize the major progress made in fragment-based approaches for which success has been exemplified by over 30 clinical drug candidates and importantly three FDA-approved drugs in oncology. We summarize the articles in this issue that provide an excellent snapshot of the current state of the field of SBDD and fragment-based drug design and which offer key insights into exciting new developments, such as the X-ray free-electron laser technology, cryo-electron microscopy, open science approaches and targeted protein degradation. We stress the value of SBDD in the design of high-quality chemical tools that are used to interrogate biology and disease pathology, and to inform target validation. We emphasize the need to maintain the scientific rigour that has been traditionally associated with structural biology and extend this to other methods used in drug discovery. This is particularly important because the quality and robustness of any form of contributory data determines its usefulness in accelerating drug design, and therefore ultimately in providing patient benefit.

Structural Biology and the Design of New Therapeutics: From HIV and Cancer to Mycobacterial Infections: A Paper Dedicated to John Kendrew

Interest in applications of protein crystallography to medicine was evident, as the first high-resolution structures emerged in the 50s and 60s. In Cambridge, Max Perutz and John Kendrew sought to understand mutations in sickle cell and other genetic diseases related to hemoglobin, while in Oxford, the group of Dorothy Hodgkin became interested in long-lasting zinc-insulin crystals for treatment of diabetes and later considered insulin redesign, as synthetic insulins became possible. The use of protein crystallography in structure-guided drug discovery emerged as enzyme structures allowed the identification of potential inhibitor-binding sites and optimization of interactions of hits using the structure of the target protein. Early examples of this approach were the use of the structure of renin to design antihypertensives and the structure of HIV protease in design of AIDS antivirals. More recently, use of structure-guided design with fragment-based drug discovery, which reduces the size of screening libraries by decreasing complexity, has improved ligand efficiency in drug design and has been used to progress three oncology drugs through clinical trials to FDA approval. We exemplify current developments in structure-guided target identification and fragment-based lead discovery with efforts to develop new antimicrobials for mycobacterial infections.

Protein crystallography and drug discovery: recollections of knowledge exchange between academia and industry

The development of structure-guided drug discovery is a story of knowledge exchange where new ideas originate from all parts of the research ecosystem. Dorothy Crowfoot Hodgkin obtained insulin from Boots Pure Drug Company in the 1930s and insulin crystallization was optimized in the company Novo in the 1950s, allowing the structure to be determined at Oxford University. The structure of renin was developed in academia, on this occasion in London, in response to a need to develop antihypertensives in pharma. The idea of a dimeric aspartic protease came from an international academic team and was discovered in HIV; it eventually led to new HIV antivirals being developed in industry. Structure-guided fragment-based discovery was developed in large pharma and biotechs, but has been exploited in academia for the development of new inhibitors targeting protein-protein interactions and also antimicrobials to combat mycobacterial infections such as tuberculosis. These observations provide a strong argument against the so-called 'linear model', where ideas flow only in one direction from academic institutions to industry. Structure-guided drug discovery is a story of applications of protein crystallography and knowledge exhange between academia and industry that has led to new drug approvals for cancer and other common medical conditions by the Food and Drug Administration in the USA, as well as hope for the treatment of rare genetic diseases and infectious diseases that are a particular challenge in the developing world.

The "Sticky Patch" Model of Crystallization and Modification of Proteins for Enhanced Crystallizability

Crystallization of macromolecules has long been perceived as a stochastic process, which cannot be predicted or controlled. This is consistent with another popular notion that the interactions of molecules within the crystal, i.e., crystal contacts, are essentially random and devoid of specific physicochemical features. In contrast, functionally relevant surfaces, such as oligomerization interfaces and specific protein-protein interaction sites, are under evolutionary pressures so their amino acid composition, structure, and topology are distinct. However, current theoretical and experimental studies are significantly changing our understanding of the nature of crystallization. The increasingly popular "sticky patch" model, derived from soft matter physics, describes crystallization as a process driven by interactions between select, specific surface patches, with properties thermodynamically favorable for cohesive interactions. Independent support for this model comes from various sources including structural studies and bioinformatics. Proteins that are recalcitrant to crystallization can be modified for enhanced crystallizability through chemical or mutational modification of their surface to effectively engineer "sticky patches" which would drive crystallization. Here, we discuss the current state of knowledge of the relationship between the microscopic properties of the target macromolecule and its crystallizability, focusing on the "sticky patch" model. We discuss state-of-the-art in silico methods that evaluate the propensity of a given target protein to form crystals based on these relationships, with the objective to design variants with modified molecular surface properties and enhanced crystallization propensity. We illustrate this discussion with specific cases where these approaches allowed to generate crystals suitable for structural analysis.

Application of advanced X-ray methods in life sciences

BACKGROUND

Synchrotron radiation (SR) sources provide diverse X-ray methods for the investigation of structure-function relationships in biological macromolecules.

SCOPE OF REVIEW

Recent developments in SR sources and in the X-ray tools they offer for life sciences are reviewed. Specifically, advances in macromolecular crystallography, small angle X-ray solution scattering, X-ray absorption and fluorescence spectroscopy, and imaging are discussed with examples.

MAJOR CONCLUSIONS

SR sources offer a range of X-ray techniques that can be used in a complementary fashion in studies of biological systems at a wide range of resolutions from atomic to cellular scale. Emerging applications of X-ray techniques include the characterization of disordered proteins, noncrystalline and nonequilibrium systems, elemental imaging of tissues, cells and organs, and detection of time-resolved changes in molecular structures.

GENERAL SIGNIFICANCE

X-ray techniques are in the center of hybrid approaches that are used to gain insight into complex problems relating to biomolecular mechanisms, disease and possible therapeutic solutions. This article is part of a Special Issue entitled "Science for Life". Guest Editors: Dr. Austen Angell, Dr. Salvatore Magazù and Dr. Federica Migliardo.

Revealing the Mechanisms of Protein Disorder and N-Glycosylation in CD44-Hyaluronan Binding Using Molecular Simulation

The extracellular N-terminal hyaluronan binding domain (HABD) of CD44 is a small globular domain that confers hyaluronan (HA) binding functionality to this large transmembrane glycoprotein. When recombinantly expressed by itself, HABD exists as a globular water-soluble protein that retains the capacity to bind HA. This has enabled atomic-resolution structural biology experiments that have revealed the structure of HABD and its binding mode with oligomeric HA. Such experiments have also pointed to an order-to-disorder transition in HABD that is associated with HA binding. However, it had remained unclear how this structural transition was involved in binding since it occurs in a region of HABD distant from the HA-binding site. Furthermore, HABD is known to be N-glycosylated, and such glycosylation can diminish HA binding when the associated N-glycans are capped with sialic acid residues. The intrinsic flexibility of disordered proteins and of N-glycans makes it difficult to apply experimental structural biology approaches to probe the molecular mechanisms of how the order-to-disorder transition and N-glycosylation can modulate HA binding by HABD. We review recent results from molecular dynamics simulations that provide atomic-resolution mechanistic understanding of such modulation to help bridge gaps between existing experimental binding and structural biology data. Findings from these simulations include: Tyr42 may function as a molecular switch that converts the HA-binding site from a low affinity to a high affinity state; in the partially disordered form of HABD, basic amino acids in the C-terminal region can gain sufficient mobility to form direct contacts with bound HA to further stabilize binding; and terminal sialic acids on covalently attached N-glycans can form charge-paired hydrogen bonding interactions with basic amino acids that could otherwise bind to HA, thereby blocking HA binding to glycosylated CD44 HABD.

Bioinformatic analysis of a PLP-dependent enzyme superfamily suitable for biocatalytic applications

In this review we analyse structure/sequence-function relationships for the superfamily of PLP-dependent enzymes with special emphasis on class III transaminases. Amine transaminases are highly important for applications in biocatalysis in the synthesis of chiral amines. In addition, other enzyme activities such as racemases or decarboxylases are also discussed. The substrate scope and the ability to accept chemically different types of substrates are shown to be reflected in conserved patterns of amino acids around the active site. These findings are condensed in a sequence-function matrix, which facilitates annotation and identification of biocatalytically relevant enzymes and protein engineering thereof.

Concepts in bio-molecular spectroscopy: vibrational case studies on metalloenzymes

Challenges and chances in bio-molecular spectroscopy are exemplified by vibrational case studies on metalloenzymes.

Protein Crystallography from the Perspective of Technology Developments

Early on, crystallography was a domain of mineralogy and mathematics and dealt mostly with symmetry properties and imaginary crystal lattices. This changed when Wilhelm Conrad Röntgen discovered X-rays in 1895, and in 1912 Max von Laue and his associates discovered X-ray irradiated salt crystals would produce diffraction patterns that could reveal the internal atomic periodicity of the crystals. In the same year the father-and-son team, Henry and Lawrence Bragg successfully solved the first crystal structure of sodium chloride and the era of modern crystallography began. Protein crystallography (PX) started some 20 years later with the pioneering work of British crystallographers. In the past 50-60 years, the achievements of modern crystallography and particularly those in protein crystallography have been due to breakthroughs in theoretical and technical advancements such as phasing and direct methods; to more powerful X-ray sources such as synchrotron radiation (SR); to more sensitive and efficient X-ray detectors; to ever faster computers and to improvements in software. The exponential development of protein crystallography has been accelerated by the invention and applications of recombinant DNA technology that can yield nearly any protein of interest in large amounts and with relative ease. Novel methods, informatics platforms, and technologies for automation and high-throughput have allowed the development of large-scale, high efficiency macromolecular crystallography efforts in the field of structural genomics (SG). Very recently, the X-ray free-electron laser (XFEL) sources and its applications in protein crystallography have shown great potential for revolutionizing the whole field again in the near future.

Improved reproducibility of unit-cell parameters in macromolecular cryocrystallography by limiting dehydration during crystal mounting

In macromolecular cryocrystallography unit-cell parameters can have low reproducibility, limiting the effectiveness of combining data sets from multiple crystals and inhibiting the development of defined repeatable cooling protocols. Here, potential sources of unit-cell variation are investigated and crystal dehydration during loop-mounting is found to be an important factor. The amount of water lost by the unit cell depends on the crystal size, the loop size, the ambient relative humidity and the transfer distance to the cooling medium. To limit water loss during crystal mounting, a threefold strategy has been implemented. Firstly, crystal manipulations are performed in a humid environment similar to the humidity of the crystal-growth or soaking solution. Secondly, the looped crystal is transferred to a vial containing a small amount of the crystal soaking solution. Upon loop transfer, the vial is sealed, which allows transport of the crystal at its equilibrated humidity. Thirdly, the crystal loop is directly mounted from the vial into the cold gas stream. This strategy minimizes the exposure of the crystal to relatively low humidity ambient air, improves the reproducibility of low-temperature unit-cell parameters and offers some new approaches to crystal handling and cryoprotection.

Missed opportunities in crystallography

Scrutinized from the perspective of time, the giants in the history of crystallography more than once missed a nearly obvious chance to make another great discovery, or went in the wrong direction. This review analyzes such missed opportunities focusing on macromolecular crystallographers (using Perutz, Pauling, Franklin as examples), although cases of particular historical (Kepler), methodological (Laue, Patterson) or structural (Pauling, Ramachandran) relevance are also described. Linus Pauling, in particular, is presented several times in different circumstances, as a man of vision, oversight, or even blindness. His example underscores the simple truth that also in science incessant creativity is inevitably connected with some probability of fault.

Disruptive photon technologies for chemical dynamics

A perspective of new and emerging technologies for chemical dynamics is given, with an emphasis on the use of X-ray sources that generate sub-picosecond pulses. The two classes of experimental techniques used for time-resolved measurements of chemical processes and their effects are spectroscopy and imaging, where the latter includes microscopy, diffractive imaging, and crystallography. X-Ray free-electron lasers have brought new impetus to the field, allowing not only temporal and spatial resolution at atomic time and length scales, but also bringing a new way to overcome limitations due to perturbation of the sample by the X-ray probe by out-running radiation damage. Associated instrumentation and methods are being developed to take advantage of the new opportunities of these sources. Once these methods of observational science have been mastered it should be possible to use the new tools to directly control those chemical processes.