Knowledge-Based Optimization of Molecular Geometries Using Crystal Structures.

This paper describes a novel way to use the structural information contained in the Cambridge Structural Database (CSD) to drive geometry optimization of organic molecules. We describe how CSD structural information is transformed into objective functions for gradient-based optimization to provide good quality geometries for a large variety of organic molecules. Performance is assessed by minimizing different sets of organic molecules reporting RMSD movements for bond lengths, valence angles, torsion angles, and heavy atom positions.

A crystallographic perspective on sharing data and knowledge.

The crystallographic community is in many ways an exemplar of the benefits and practices of sharing data. Since the inception of the technique, virtually every published crystal structure has been made available to others. This has been achieved through the establishment of several specialist data centres, including the Cambridge Crystallographic Data Centre, which produces the Cambridge Structural Database. Containing curated structures of small organic molecules, some containing a metal, the database has been produced for almost 50 years. This has required the development of complex informatics tools and an environment allowing expert human curation. As importantly, a financial model has evolved which has, to date, ensured the sustainability of the resource. However, the opportunities afforded by technological changes and changing attitudes to sharing data make it an opportune moment to review current practices.

The Cambridge Structural Database in retrospect and prospect.

The Cambridge Crystallographic Data Centre (CCDC) was established in 1965 to record numerical, chemical and bibliographic data relating to published organic and metal-organic crystal structures. The Cambridge Structural Database (CSD) now stores data for nearly 700,000 structures and is a comprehensive and fully retrospective historical archive of small-molecule crystallography. Nearly 40,000 new structures are added each year. As X-ray crystallography celebrates its centenary as a subject, and the CCDC approaches its own 50th year, this article traces the origins of the CCDC as a publicly funded organization and its onward development into a self-financing charitable institution. Principally, however, we describe the growth of the CSD and its extensive associated software system, and summarize its impact and value as a basis for research in structural chemistry, materials science and the life sciences, including drug discovery and drug development. Finally, the article considers the CCDC's funding model in relation to open access and open data paradigms.

The hydrogen bond environments of 1H-tetrazole and tetrazolate rings: the structural basis for tetrazole-carboxylic acid bioisosterism.

Bioisosterism involving replacement of a carboxylic acid substituent by 1H-tetrazole, yielding deprotonated carboxylate and tetrazolate under physiological conditions, is a well-known synthetic strategy in medicinal chemistry. To improve our overall understanding of bioisosterism, we have used this example to study the geometrical and energetic aspects of the functional group replacement. Specifically, we use crystal structure informatics and high-level ab initio calculations to study the hydrogen bond (H-bond) energy landscapes of the protonated and deprotonated bioisosteric pairs. Each pair exhibits very similar H-bond environments in crystal structures retrieved from the CSD, and the attractive energies of these H-bonds are also very similar. However, by comparison with -COOH and -COO(-), the H-bond environments around 1H-tetrazole and tetrazolate substituents extend further, by about 1.2 Å, from the core of the connected molecule. Analysis of pairs of PDB structures containing ligands which differ only in having a tetrazole or a carboxyl substituent and which are bound to the same protein indicates that the protein binding site must flex sufficiently to form strong H-bonds to either substituent. A survey of DrugBank shows a rather small number of tetrazole-containing drugs in the 'approved' and 'experimental' drug sections of that database.

The good, the bad and the twisted: a survey of ligand geometry in protein crystal structures.

The protein databank now contains the structures of over 11,000 ligands bound to proteins. These structures are invaluable in applied areas such as structure-based drug design, but are also the substrate for understanding the energetics of intermolecular interactions with proteins. Despite their obvious importance, the careful analysis of ligands bound to protein structures lags behind the analysis of the protein structures themselves. We present an analysis of the geometry of ligands bound to proteins and highlight the role of small molecule crystal structures in enabling molecular modellers to critically evaluate a ligand model's quality and investigate protein-induced strain.

IRAK-4 inhibitors. Part II: a structure-based assessment of imidazo[1,2-a]pyridine binding.

A potent IRAK-4 inhibitor was identified through routine project cross screening. The binding mode was inferred using a combination of in silico docking into an IRAK-4 homology model, surrogate crystal structure analysis and chemical analogue SAR.

The druggable genome.

An assessment of the number of molecular targets that represent an opportunity for therapeutic intervention is crucial to the development of post-genomic research strategies within the pharmaceutical industry. Now that we know the size of the human genome, it is interesting to consider just how many molecular targets this opportunity represents. We start from the position that we understand the properties that are required for a good drug, and therefore must be able to understand what makes a good drug target.

The use of small-molecule structures to complement protein-ligand crystal structures in drug discovery.

Many ligand-discovery stories tell of the use of structures of protein-ligand complexes, but the contribution of structural chemistry is such a core part of finding and improving ligands that it is often overlooked. More than 800 000 crystal structures are available to the community through the Cambridge Structural Database (CSD). Individually, these structures can be of tremendous value and the collection of crystal structures is even more helpful. This article provides examples of how small-molecule crystal structures have been used to complement those of protein-ligand complexes to address challenges ranging from affinity, selectivity and bioavailability though to solubility.

Using more than 801†296 small-molecule crystal structures to aid in protein structure refinement and analysis. Addendum.

An addendum to the Introduction of Cole et al. [(2017), Acta Cryst. D73, 234-239] is made to recognize the work of Bricogne, Smart and others in the development of methods to make use of Cambridge Structural Database data in protein structure solution.

Using more than 801†296 small-molecule crystal structures to aid in protein structure refinement and analysis.

The Cambridge Structural Database (CSD) is the worldwide resource for the dissemination of all published three-dimensional structures of small-molecule organic and metal-organic compounds. This paper briefly describes how this collection of crystal structures can be used en masse in the context of macromolecular crystallography. Examples highlight how the CSD and associated software aid protein-ligand complex validation, and show how the CSD could be further used in the generation of geometrical restraints for protein structure refinement.

The Cambridge Structural Database.

The Cambridge Structural Database (CSD) contains a complete record of all published organic and metal-organic small-molecule crystal structures. The database has been in operation for over 50 years and continues to be the primary means of sharing structural chemistry data and knowledge across disciplines. As well as structures that are made public to support scientific articles, it includes many structures published directly as CSD Communications. All structures are processed both computationally and by expert structural chemistry editors prior to entering the database. A key component of this processing is the reliable association of the chemical identity of the structure studied with the experimental data. This important step helps ensure that data is widely discoverable and readily reusable. Content is further enriched through selective inclusion of additional experimental data. Entries are available to anyone through free CSD community web services. Linking services developed and maintained by the CCDC, combined with the use of standard identifiers, facilitate discovery from other resources. Data can also be accessed through CCDC and third party software applications and through an application programming interface.

Capturing neon - the first experimental structure of neon trapped within a metal-organic environment.

Despite being the fifth most abundant element in the atmosphere, neon has never been observed in an organic or metal-organic environment. This study shows the adsorption of this highly unreactive element within such an environment and reveals the first crystallographic observation of an interaction between neon and a transition metal.

Identifying Interactions that Determine Fragment Binding at Protein Hotspots.

Locating a ligand-binding site is an important first step in structure-guided drug discovery, but current methods do little to suggest which interactions within a pocket are the most important for binding. Here we illustrate a method that samples atomic hotspots with simple molecular probes to produce fragment hotspot maps. These maps specifically highlight fragment-binding sites and their corresponding pharmacophores. For ligand-bound structures, they provide an intuitive visual guide within the binding site, directing medicinal chemists where to grow the molecule and alerting them to suboptimal interactions within the original hit. The fragment hotspot map calculation is validated using experimental binding positions of 21 fragments and subsequent lead molecules. The ligands are found in high scoring areas of the fragment hotspot maps, with fragment atoms having a median percentage rank of 97%. Protein kinase B and pantothenate synthetase are examined in detail. In each case, the fragment hotspot maps are able to rationalize a Free-Wilson analysis of SAR data from a fragment-based drug design project.

Hydrogen bonding at C=Se acceptors in selenoureas, selenoamides and selones.

In recent years there has been considerable interest in chalcogen and hydrogen bonding involving Se atoms, but a general understanding of their nature and behaviour has yet to emerge. In the present work, the hydrogen-bonding ability and nature of Se atoms in selenourea derivatives, selenoamides and selones has been explored using analysis of the Cambridge Structural Database and ab initio calculations. In the CSD there are 70 C=Se structures forming hydrogen bonds, all of them selenourea derivatives or selenoamides. Analysis of intramolecular geometries and ab initio partial charges show that this bonding stems from resonance-induced C(δ+)=Se(δ-) dipoles, much like hydrogen bonding to C=S acceptors. C=Se acceptors are in many respects similar to C=S acceptors, with similar vdW-normalized hydrogen-bond lengths and calculated interaction strengths. The similarity between the C=S and C=Se acceptors for hydrogen bonding should inform and guide the use of C=Se in crystal engineering.

Generation of crystal structures using known crystal structures as analogues.

This analysis attempts to answer the question of whether similar molecules crystallize in a similar manner. An analysis of structures in the Cambridge Structural Database shows that the answer is yes - sometimes they do, particularly for single-component structures. However, one does need to define what we mean by similar in both cases. Building on this observation we then demonstrate how this correlation between shape similarity and packing similarity can be used to generate potential lattices for molecules with no known crystal structure. Simple intermolecular interaction potentials can be used to minimize these potential lattices. Finally we discuss the many limitations of this approach.

Outcome of the First wwPDB/CCDC/D3R Ligand Validation Workshop.

Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) represent an important source of information concerning drug-target interactions, providing atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. Of the more than 115,000 entries extant in the Protein Data Bank (PDB) archive, ∼75% include at least one non-polymeric ligand. Ligand geometrical and stereochemical quality, the suitability of ligand models for in silico drug discovery and design, and the goodness-of-fit of ligand models to electron-density maps vary widely across the archive. We describe the proceedings and conclusions from the first Worldwide PDB/Cambridge Crystallographic Data Center/Drug Design Data Resource (wwPDB/CCDC/D3R) Ligand Validation Workshop held at the Research Collaboratory for Structural Bioinformatics at Rutgers University on July 30-31, 2015. Experts in protein crystallography from academe and industry came together with non-profit and for-profit software providers for crystallography and with experts in computational chemistry and data archiving to discuss and make recommendations on best practices, as framed by a series of questions central to structural studies of macromolecule-ligand complexes. What data concerning bound ligands should be archived in the PDB? How should the ligands be best represented? How should structural models of macromolecule-ligand complexes be validated? What supplementary information should accompany publications of structural studies of biological macromolecules? Consensus recommendations on best practices developed in response to each of these questions are provided, together with some details regarding implementation. Important issues addressed but not resolved at the workshop are also enumerated.

Data to knowledge: how to get meaning from your result.

Structural and functional studies require the development of sophisticated 'Big Data' technologies and software to increase the knowledge derived and ensure reproducibility of the data. This paper presents summaries of the Structural Biology Knowledge Base, the VIPERdb Virus Structure Database, evaluation of homology modeling by the Protein Model Portal, the ProSMART tool for conformation-independent structure comparison, the LabDB 'super' laboratory information management system and the Cambridge Structural Database. These techniques and technologies represent important tools for the transformation of crystallographic data into knowledge and information, in an effort to address the problem of non-reproducibility of experimental results.

Proteases as drug targets.

The effective management of AIDS with HIV protease inhibitors, or the use of angiotensin-converting enzyme inhibitors to treat hypertension, indicates that proteases do make good drug targets. On the other hand, matrix metalloproteinase (MMP) inhibitors from several companies have failed in both cancer and rheumatoid arthritis clinical trials. Mindful of the MMP inhibitor experience, this chapter explores how tractable proteases are as drug targets from a chemistry perspective. It examines the recent success of other classes of drug for the treatment of rheumatoid arthritis, and highlights the need to consider where putative targets lie on pathophysiological pathways--regardless of what kind of therapeutic entity would be required to target them. With genome research yielding many possible new drug targets, it explores the likelihood of discovering proteolytic enzymes that are causally responsible for disease processes and that might therefore make better targets, especially if they lead to the development of drugs that can be administered orally. It also considers the impact that biologics are having on drug discovery, and in particular whether biologically derived therapeutics such as antibodies are likely to significantly alter the way we view proteases as targets and the methods used to discover therapeutic inhibitors.

Sixth blind test of organic crystal-structure prediction methods.

Over the past 15 years progress in predicting crystal structures of small organic molecules has been charted by a series of blind tests hosted by the Cambridge Crystallographic Data Centre. This letter announces a sixth blind test to take place between September 2014 and August 2015, giving details of the target systems and the revised procedure. We hope that as many methods as possible will be assessed and benchmarked in this new blind test.