Locating interaction sites on proteins: The crystal structure of thermolysin soaked in 2% to 100% isopropanol

Fragment screening libraries for the identification of protein hot spots and their minimal binding pharmacophores

Fragment-based drug design relies heavily on structural information for the elaboration and optimisation of hits. The ability to identify neighbouring binding hot spots, energetically favourable interactions and conserved binding motifs in protein structures through X-ray crystallography can inform the evolution of fragments into lead-like compounds through structure-based design. The composition of fragment libraries can be designed and curated to fit this purpose and herein, we describe and compare screening libraries containing compounds comprising between 2 and 18 heavy atoms. We evaluate the properties of the compounds in these libraries and assess their ability to probe protein surfaces for binding hot spots.

A unifying Bayesian framework for merging X-ray diffraction data

Novel X-ray methods are transforming the study of the functional dynamics of biomolecules. Key to this revolution is detection of often subtle conformational changes from diffraction data. Diffraction data contain patterns of bright spots known as reflections. To compute the electron density of a molecule, the intensity of each reflection must be estimated, and redundant observations reduced to consensus intensities. Systematic effects, however, lead to the measurement of equivalent reflections on different scales, corrupting observation of changes in electron density. Here, we present a modern Bayesian solution to this problem, which uses deep learning and variational inference to simultaneously rescale and merge reflection observations. We successfully apply this method to monochromatic and polychromatic single-crystal diffraction data, as well as serial femtosecond crystallography data. We find that this approach is applicable to the analysis of many types of diffraction experiments, while accurately and sensitively detecting subtle dynamics and anomalous scattering.

MBTPS2, a membrane bound protease, underlying several distinct skin and bone disorders

The MBTPS2 gene on the X-chromosome encodes the membrane-bound transcription factor protease, site-2 (MBTPS2) or site-2 protease (S2P) which cleaves and activates several signaling and regulatory proteins from the membrane. The MBTPS2 is critical for a myriad of cellular processes, ranging from the regulation of cholesterol homeostasis to unfolded protein responses. While its functional role has become much clearer in the recent years, how mutations in the MBTPS2 gene lead to several human disorders with different phenotypes including Ichthyosis Follicularis, Atrichia and Photophobia syndrome (IFAP) with or without BRESHECK syndrome, Keratosis Follicularis Spinulosa Decalvans (KFSD), Olmsted syndrome, and Osteogenesis Imperfecta type XIX remains obscure. This review presents the biological role of MBTPS2 in development, summarizes its mutations and implicated disorders, and discusses outstanding unanswered questions.

Benchmark Sets for Binding Hot Spot Identification in Fragment-Based Ligand Discovery

Binding hot spots are regions of proteins that, due to their potentially high contribution to the binding free energy, have high propensity to bind small molecules. We present benchmark sets for testing computational methods for the identification of binding hot spots with emphasis on fragment-based ligand discovery. Each protein structure in the set binds a fragment, which is extended into larger ligands in other structures without substantial change in its binding mode. Structures of the same proteins without any bound ligand are also collected to form an unbound benchmark. We also discuss a set developed by Astex Pharmaceuticals for the validation of hot and warm spots for fragment binding. The set is based on the assumption that a fragment that occurs in diverse ligands in the same subpocket identifies a binding hot spot. Since this set includes only ligand-bound proteins, we added a set with unbound structures. All four sets were tested using FTMap, a computational analogue of fragment screening experiments to form a baseline for testing other prediction methods, and differences among the sets are discussed.

Applied Biophysical Methods in Fragment-Based Drug Discovery

Fragment-based drug discovery (FBDD) has come of age in the last decade with the FDA approval of four fragment-derived drugs. Biophysical methods are at the heart of hit discovery and validation in FBDD campaigns. The three most commonly used methods, thermal shift, surface plasmon resonance, and nuclear magnetic resonance, can be daunting for the novice user. We aim here to provide the nonexpert user of these methods with a summary of problems and challenges that might be faced, but also highlight the potential gains that each method can contribute to an FBDD project. While our view on FBDD is slightly biased toward enabling structure-guided drug discovery, most of the points we address in this review are also valid for non-structure-focused FBDD.

Scaling diffraction data in the DIALS software package: algorithms and new approaches for multi-crystal scaling

In processing X-ray diffraction data, the intensities obtained from integration of the diffraction images must be corrected for experimental effects in order to place all intensities on a common scale both within and between data collections. Scaling corrects for effects such as changes in sample illumination, absorption and, to some extent, global radiation damage that cause the measured intensities of symmetry-equivalent observations to differ throughout a data set. This necessarily requires a prior evaluation of the point-group symmetry of the crystal. This paper describes and evaluates the scaling algorithms implemented within the DIALS data-processing package and demonstrates the effectiveness and key features of the implementation on example macromolecular crystallographic rotation data. In particular, the scaling algorithms enable new workflows for the scaling of multi-crystal or multi-sweep data sets, providing the analysis required to support current trends towards collecting data from ever-smaller samples. In addition, the implementation of a free-set validation method is discussed, which allows the quantification of the suitability of scaling-model and algorithm choices.

Protein-protein interactions: a structural view of inhibition strategies and the IL-23/IL-17 axis

Protein-protein interactions are central to biology and provide opportunities to modulate disease with small-molecule or protein therapeutics. Recent developments in the understanding of the tractability of protein-protein interactions are discussed with a focus on the ligandable nature of protein-protein interaction surfaces. General principles of inhibiting protein-protein interactions are illustrated with structural biology examples from six members of the IL-23/IL-17 signaling family (IL-1, IL-6, IL-17, IL-23 RORγT and TNFα). These examples illustrate the different approaches to discover protein-protein interaction inhibitors on a target-specific basis that has proven fruitful in terms of discovering both small molecule and biologic based protein-protein interaction inhibitors.

Solving a new R2lox protein structure by microcrystal electron diffraction

Microcrystal electron diffraction (MicroED) has recently shown potential for structural biology. It enables the study of biomolecules from micrometer-sized 3D crystals that are too small to be studied by conventional x-ray crystallography. However, to date, MicroED has only been applied to redetermine protein structures that had already been solved previously by x-ray diffraction. Here, we present the first new protein structure-an R2lox enzyme-solved using MicroED. The structure was phased by molecular replacement using a search model of 35% sequence identity. The resulting electrostatic scattering potential map at 3.0-Å resolution was of sufficient quality to allow accurate model building and refinement. The dinuclear metal cofactor could be located in the map and was modeled as a heterodinuclear Mn/Fe center based on previous studies. Our results demonstrate that MicroED has the potential to become a widely applicable tool for revealing novel insights into protein structure and function.

Two-domain aminopeptidase of M1 family: Structural features for substrate binding and gating in absence of C-terminal domain

Zinc metallopeptidases of the M1 family (M1 peptidases) with unique metal binding motif HEXXH(X)₁₈E regulate many important biological processes such as tumor growth, angiogenesis, hormone regulation, and immune cell development. Typically, these enzymes exist in three-domain [N-terminal domain (N-domain), catalytic domain, and C-terminal domain (C-domain)] or four-domain (N-domain, catalytic domain, middle domain, and C-domain) format in which N-domain and catalytic domain are more conserved. The C-domain plays important roles in substrate binding and gating. In this study we report the first structure of a two-domain (N-domain and catalytic domain) M1 peptidase at 2.05 Å resolution. Despite the lack of C-domain, the enzyme is active and prefers peptide substrates with large hydrophobic N-terminal residues. Its substrate-bound structure was determined at 1.9 Å resolution. Structural analyses supported by site directed mutagenesis and molecular dynamics simulations reveal structural features that could compensate for the lack of C-domain. A unique loop insertion (loop A) in the N-domain has important roles in gating and desolvation of active site. Three Arg residues of the catalytic domain are involved in substrate-binding roles typically played by positively charged residues of C-domain in other M1 peptidases. Further, its unique exopeptidase sequence motif, LALET, creates a more hydrophobic environment at the S1 subsite (which binds N-terminal residue of the substrate in aminopeptidases) than the more common GXMEN motif in the family. This leads to high affinity for large hydrophobic residues in the S1 subsite, which contributes towards efficient substrate binding in absence of C-domain.

DRoP: Automated detection of conserved solvent-binding sites on proteins

Water and ligand binding play critical roles in the structure and function of proteins, yet their binding sites and significance are difficult to predict a priori. Multiple solvent crystal structures (MSCS) is a method where several X-ray crystal structures are solved, each in a unique solvent environment, with organic molecules that serve as probes of the protein surface for sites evolved to bind ligands, while the first hydration shell is essentially maintained. When superimposed, these structures contain a vast amount of information regarding hot spots of protein-protein or protein-ligand interactions, as well as conserved water-binding sites retained with the change in solvent properties. Optimized mining of this information requires reliable structural data and a consistent, objective analysis tool. Detection of related solvent positions (DRoP) was developed to automatically organize and rank the water or small organic molecule binding sites within a given set of structures. It is a flexible tool that can also be used in conserved water analysis given multiple structures of any protein independent of the MSCS method. The DRoP output is an HTML format list of the solvent sites ordered by conservation rank in its population within the set of structures, along with renumbered and recolored PDB files for visualization and facile analysis. Here, we present a previously unpublished set of MSCS structures of bovine pancreatic ribonuclease A (RNase A) and use it together with published structures to illustrate the capabilities of DRoP.

Site-Resolved and Quantitative Characterization of Very Weak Protein-Ligand Interactions

Very weak interactions between small organic molecules and proteins have long been predicted and are expected to have dissociation constants of hundreds of millimolar and above. Unfortunately, quantitative evaluation of binding in a high-resolution structural context for this affinity regime is particularly difficult and often impossible using existing experimental approaches. Here, we show that nanoscale encapsulation of single protein molecules within the water core of reverse micelles enables the detection and evaluation of weak binding interactions at atomic resolution using solution NMR spectroscopy. This strategy is used to survey the interactions of a set of small molecules with the cytokine interleukin-1β (IL-1β). The interaction of IL-1β with these molecules is found to vary from more diffuse and weak binding modes to more specific and with a relatively higher affinity. The interactions detected here cover a large portion of the protein surface and have dissociation constants mostly in the low molar range. These results illustrate the ability of a protein to interact productively with a variety of small molecule functional groups and point to a broader potential to target even relatively featureless protein surfaces for applications in chemical biology and drug discovery.

On-chip crystallization for serial crystallography experiments and on-chip ligand-binding studies

Efficient and reliable sample delivery has remained one of the bottlenecks for serial crystallography experiments. Compared with other methods, fixed-target sample delivery offers the advantage of significantly reduced sample consumption and shorter data collection times owing to higher hit rates. Here, a new method of on-chip crystallization is reported which allows the efficient and reproducible growth of large numbers of protein crystals directly on micro-patterned silicon chips for in-situ serial crystallography experiments. Crystals are grown by sitting-drop vapor diffusion and previously established crystallization conditions can be directly applied. By reducing the number of crystal-handling steps, the method is particularly well suited for sensitive crystal systems. Excessive mother liquor can be efficiently removed from the crystals by blotting, and no sealing of the fixed-target sample holders is required to prevent the crystals from dehydrating. As a consequence, 'naked' crystals are obtained on the chip, resulting in very low background scattering levels and making the crystals highly accessible for external manipulation such as the application of ligand solutions. Serial diffraction experiments carried out at cryogenic temperatures at a synchrotron and at room temperature at an X-ray free-electron laser yielded high-quality X-ray structures of the human membrane protein aquaporin 2 and two new ligand-bound structures of thermolysin and the human kinase DRAK2. The results highlight the applicability of the method for future high-throughput on-chip screening of pharmaceutical compounds.

Crystallographic screening using ultra-low-molecular-weight ligands to guide drug design

We present a novel crystallographic screening methodology (MiniFrags) that employs high-concentration aqueous soaks with a chemically diverse and ultra-low-molecular-weight library (heavy atom count 5-7) to identify ligand-binding hot and warm spots on proteins. We propose that MiniFrag screening represents a highly effective method for guiding optimisation of fragment-derived lead compounds or chemical tools and that the high screening hit rates reflect enhanced sampling of chemical space.

Solvents to Fragments to Drugs: MD Applications in Drug Design

Simulations of molecular dynamics (MD) are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: Binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals solvent structures and preferential interaction sites (hot spots) on the protein surface. The information provided by water and its cosolvents can be used very effectively to understand protein ligand recognition and to improve the predictive capability of well-established methods such as molecular docking. The application of MD simulations to the study of the association of proteins with drug-like compounds is currently only possible for specific cases, as it remains computationally very expensive and labor intensive. MDmix simulations on the other hand, can be used systematically to address some of the common tasks in SBDD. With the advent of new tools and faster computers we expect to see an increase in the application of mixed solvent MD simulations to a plethora of protein targets to identify new drug candidates.

High resolution crystal structure of substrate-free human neprilysin

Neprilysin is a transmembrane M13 zinc metalloprotease responsible for the degradation of several biologically active peptides including insulin, enkephalin, substance P, bradykinin, endothelin-1, neurotensin and amyloid-β. The protein has received attention for its role in modulating blood pressure responses with its inhibition producing an antihypertensive response. To date, several inhibitor bound crystal structures of the human neprilysin extracellular domain have been determined, but, a structure free of bound inhibitor or substrate has yet to be reported. Here, we report the first crystal structure free of substrate or inhibitor for the extracellular catalytic domain of human neprilysin at 1.9 Å resolution. This structure will provide a reference point for comparisons to future inhibitor or substrate bound structures. The neprilysin structure also reveals that a closed protein conformation can be adopted in protein crystals absent of bound substrate or inhibitor.

Improved protein-crystal identification by using 2,2,2-trichloroethanol as a fluorescence enhancer

The identification of initial lead conditions for successful protein crystallization is crucial for structural studies using X-ray crystallography. In order to reduce the number of false-negative conditions, an emerging number of fluorescence-based methods have been developed which allow more efficient identification of protein crystals and help to distinguish them from salt crystals. Detection of the native tryptophan fluorescence of protein crystals is one of the most widely used methods. However, this method can fail owing to the properties of the crystallized protein or the chemical composition of the crystallization trials. Here, a simple, fast and cost-efficient method employing 2,2,2-trichloroethanol (TCE) has been developed. It can be performed with a standard UV-light microscope and can be applied to cases in which detection of native tryptophan fluorescence fails. In four test cases this method had no effect on the diffraction properties of the crystals and no structural changes were observed. Further evidence is provided that TCE can be added to crystallization trials during their preparation, making this method compatible with high-throughput approaches.

DIALS: implementation and evaluation of a new integration package

The DIALS project is a collaboration between Diamond Light Source, Lawrence Berkeley National Laboratory and CCP4 to develop a new software suite for the analysis of crystallographic X-ray diffraction data, initially encompassing spot finding, indexing, refinement and integration. The design, core algorithms and structure of the software are introduced, alongside results from the analysis of data from biological and chemical crystallography experiments.

Large scale analysis of protein conformational transitions from aqueous to non-aqueous media

Background

Biocatalysis in organic solvents is nowadays a common practice with a large potential in Biotechnology. Several studies report that proteins which are co-crystallized or soaked in organic solvents preserve their fold integrity showing almost identical arrangements when compared to their aqueous forms. However, it is well established that the catalytic activity of proteins in organic solvents is much lower than in water. In order to explain this diminished activity and to further characterize the behaviour of proteins in non-aqueous environments, we performed a large-scale analysis (1737 proteins) of the conformational diversity of proteins crystallized in aqueous and co-crystallized or soaked in non-aqueous media.

Results

Using proteins’ experimentally determined conformational diversity taken from CoDNaS database, we found that proteins in non-aqueous media display much lower conformational diversity when compared to the corresponding conformers obtained in water. When conformational diversity is compared between conformers obtained in different non-aqueous media, their structural differences are larger and mostly independent of the presence of cognate ligands. We also found that conformers corresponding to non-aqueous media have larger but less flexible cavities, lower number of disordered regions and lower active-site residue mobility.

Conclusions

Our results show that non-aqueous media conformers have specific structural features and that they do not adopt extreme conformations found in aqueous media. This makes them clearly different from their corresponding aqueous conformers.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2044-2) contains supplementary material, which is available to authorized users.

Current perspectives in fragment-based lead discovery (FBLD)

It is over 20 years since the first fragment-based discovery projects were disclosed. The methods are now mature for most ‘conventional’ targets in drug discovery such as enzymes (kinases and proteases) but there has also been growing success on more challenging targets, such as disruption of protein–protein interactions. The main application is to identify tractable chemical startpoints that non-covalently modulate the activity of a biological molecule. In this essay, we overview current practice in the methods and discuss how they have had an impact in lead discovery – generating a large number of fragment-derived compounds that are in clinical trials and two medicines treating patients. In addition, we discuss some of the more recent applications of the methods in chemical biology – providing chemical tools to investigate biological molecules, mechanisms and systems.

Atomic-resolution structures from fragmented protein crystals with the cryoEM method MicroED

Crystallographic analysis of macromolecules depends on large, well-ordered crystals, which often require significant effort to obtain. Even sizable crystals sometimes suffer from pathologies that render them inappropriate for high-resolution structure determination. Here we show that fragmentation of large, imperfect crystals can provide a simple path for high-resolution structure determination by serial femtosecond crystallography or the cryoEM method MicroED.

Antibacterial Properties of Metallocenyl-7-ADCA Derivatives and Structure in Complex with CTX-M β-Lactamase

A series of six novel metallocenyl-7-ADCA (metallocenyl = ferrocenyl or ruthenocenyl; 7-ADCA = 7-aminodesacetoxycephalosporanic acid) conjugates were synthesized and their antibacterial properties evaluated by biochemical and microbiological assays. The ruthenocene derivatives showed a higher level of inhibition of DD-carboxypeptidase 64-575, a Penicillin Binding Protein (PBP), than the ferrocene derivatives and the reference compound penicillin G. Protein X-ray crystallographic analysis revealed a covalent acyl-enzyme complex of a ruthenocenyl compound with CTX-M β-lactamase E166A mutant, corresponding to a similar complex with PBPs responsible for the bactericidal activities of these compounds. Most interestingly, an intact compound was captured at the crystal-packing interface, elucidating for the first time the structure of a metallocenyl β-lactam compound that previously eluded small molecule crystallography. We propose that protein crystals, even from biologically unrelated molecules, can be utilized to determine structures of small molecules.

Driving Structure-Based Drug Discovery through Cosolvent Molecular Dynamics

Identifying binding hotspots on protein surfaces is of prime interest in structure-based drug discovery, either to assess the tractability of pursuing a protein target or to drive improved potency of lead compounds. Computational approaches to detect such regions have traditionally relied on energy minimization of probe molecules onto static protein conformations in the absence of the natural aqueous environment. Advances in high performance computing now allow us to assess hotspots using molecular dynamics (MD) simulations. MD simulations integrate protein flexibility and the complicated role of water, thereby providing a more realistic assessment of the complex kinetics and thermodynamics at play. In this review, we describe the evolution of various cosolvent-based MD techniques and highlight a myriad of potential applications for such technologies in computational drug development.

Computational solvent mapping in structure-based drug design

Over the past two decades, solvent mapping has emerged as a useful tool for identifying hot spots within binding sites on proteins for drug-like molecules and suggesting properties of potential binders. While the experimental technique requires solving multiple crystal structures of a protein in different solvents, computational solvent mapping allows for fast analysis of a protein for potential binding sites and their druggability. Recent advances in genomics, systems biology and interactomics provide a multitude of potential targets for drug development and solvent mapping can provide useful information to help prioritize targets for drug discovery projects. Here, we review various approaches to computational solvent mapping, highlight some key advances and provide our opinion on future directions in the field.

Lessons from Hot Spot Analysis for Fragment-Based Drug Discovery

Analysis of binding energy hot spots at protein surfaces can provide crucial insights into the prospects for successful application of fragment-based drug discovery (FBDD), and whether a fragment hit can be advanced into a high-affinity, drug-like ligand. The key factor is the strength of the top ranking hot spot, and how well a given fragment complements it. We show that published data are sufficient to provide a sophisticated and quantitative understanding of how hot spots derive from a protein 3D structure, and how their strength, number, and spatial arrangement govern the potential for a surface site to bind to fragment-sized and larger ligands. This improved understanding provides important guidance for the effective application of FBDD in drug discovery.

The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins

FTMap is a computational mapping server that identifies binding hot spots of macromolecules-i.e., regions of the surface with major contributions to the ligand-binding free energy. To use FTMap, users submit a protein, DNA or RNA structure in PDB (Protein Data Bank) format. FTMap samples billions of positions of small organic molecules used as probes, and it scores the probe poses using a detailed energy expression. Regions that bind clusters of multiple probe types identify the binding hot spots in good agreement with experimental data. FTMap serves as the basis for other servers, namely FTSite, which is used to predict ligand-binding sites, FTFlex, which is used to account for side chain flexibility, FTMap/param, used to parameterize additional probes and FTDyn, for mapping ensembles of protein structures. Applications include determining the druggability of proteins, identifying ligand moieties that are most important for binding, finding the most bound-like conformation in ensembles of unliganded protein structures and providing input for fragment-based drug design. FTMap is more accurate than classical mapping methods such as GRID and MCSS, and it is much faster than the more-recent approaches to protein mapping based on mixed molecular dynamics. By using 16 probe molecules, the FTMap server finds the hot spots of an average-size protein in <1 h. As FTFlex performs mapping for all low-energy conformers of side chains in the binding site, its completion time is proportionately longer.

Fragment screening by SPR and advanced application to GPCRs

Surface plasmon resonance (SPR) is one of the primary biophysical methods for the screening of low molecular weight 'fragment' libraries, due to its low protein consumption and 'label-free' methodology. SPR biosensor interaction analysis is employed to both screen and confirm the binding of compounds in fragment screening experiments, as it provides accurate information on the affinity and kinetics of molecular interactions. The most advanced application of the use of SPR for fragment screening is against membrane protein drug targets, such G-protein coupled receptors (GPCRs). Biophysical GPCR assays using SPR have been validated with pharmacological measurements approximate to cell-based methods, yet provide the advantage of biophysical methods in their ability to measure the weak affinities of low molecular weight fragments. A number of SPR fragment screens against GPCRs have now been disclosed in the literature. SPR fragment screening is proving versatile to screen both thermostabilised GPCRs and solubilised wild type receptors. In this chapter, we discuss the state-of-the-art in GPCR fragment screening by SPR and the technical considerations in performing such experiments.

Advantages of crystallographic fragment screening: functional and mechanistic insights from a powerful platform for efficient drug discovery

X-ray crystallography has been an under-appreciated screening tool for fragment-based drug discovery due to the perception of low throughput and technical difficulty. Investigators in industry and academia have overcome these challenges by taking advantage of key factors that contribute to a successful crystallographic screening campaign. Efficient cocktail design and soaking methodologies have evolved to maximize throughput while minimizing false positives/negatives. In addition, technical improvements at synchrotron beamlines have dramatically increased data collection rates thus enabling screening on a timescale comparable to other techniques. The combination of available resources and efficient experimental design has resulted in many successful crystallographic screening campaigns. The three-dimensional crystal structure of the bound fragment complexed to its target, a direct result of the screening effort, enables structure-based drug design while revealing insights regarding protein dynamics and function not readily obtained through other experimental approaches. Furthermore, this "chemical interrogation" of the target protein crystals can lead to the identification of useful reagents for improving diffraction resolution or compound solubility.

Taking snapshots of photosynthetic water oxidation using femtosecond X-ray diffraction and spectroscopy

The dioxygen we breathe is formed by light-induced oxidation of water in photosystem II. O2 formation takes place at a catalytic manganese cluster within milliseconds after the photosystem II reaction centre is excited by three single-turnover flashes. Here we present combined X-ray emission spectra and diffraction data of 2-flash (2F) and 3-flash (3F) photosystem II samples, and of a transient 3F' state (250 μs after the third flash), collected under functional conditions using an X-ray free electron laser. The spectra show that the initial O-O bond formation, coupled to Mn reduction, does not yet occur within 250 μs after the third flash. Diffraction data of all states studied exhibit an anomalous scattering signal from Mn but show no significant structural changes at the present resolution of 4.5 Å. This study represents the initial frames in a molecular movie of the structural changes during the catalytic reaction in photosystem II.

Inhibitory Effects of Alcohols on the Activity of Human Matrix Metalloproteinase 7 (Matrilysin)

Aliphatic alcohols inhibited the activity of human matrix metalloproteinase 7 (matrilysin) competitively with K(i) of 6.1-19.4% (v/v) or 0.66-4.80 M. From the relationship between the structures of alcohols and their K(i) values, alcohols are considered to bind the hydrophobic S1' subsite most plausibly, and the size of the pocket was estimated to be large enough to accommodate the length of 1-butanol (4-carbon chain) and the bulk of tertiary alcohols. Alcohols might be suitable probes for exploring the active-site geometry of enzymes.

Accurate macromolecular structures using minimal measurements from X-ray free-electron lasers

X-ray free-electron laser (XFEL) sources enable the use of crystallography to solve three-dimensional macromolecular structures under native conditions and without radiation damage. Results to date, however, have been limited by the challenge of deriving accurate Bragg intensities from a heterogeneous population of microcrystals, while at the same time modeling the X-ray spectrum and detector geometry. Here we present a computational approach designed to extract meaningful high-resolution signals from fewer diffraction measurements.

Improving protocols for protein mapping through proper comparison to crystallography data

Computational approaches to fragment-based drug design (FBDD) can complement experiments and facilitate the identification of potential hot spots along the protein surface. However, the evaluation of computational methods for mapping binding sites frequently focuses upon the ability to reproduce crystallographic coordinates to within a low RMSD threshold. This dependency on the deposited coordinate data overlooks the original electron density from the experiment, thus techniques may be developed based upon subjective-or even erroneous-atomic coordinates. This can become a significant drawback in applications to systems where the location of hot spots is unknown. On the basis of comparison to crystallographic density, we previously showed that mixed-solvent molecular dynamics (MixMD) accurately identifies the active site for HEWL, with acetonitrile as an organic solvent. Here, we concentrated on the influence of protic solvent on simulation and refined the optimal MixMD approach for extrapolation of the method to systems without established sites. Our results establish an accurate approach for comparing simulations to experiment. We have outlined the most efficient strategy for MixMD, based on simulation length and number of runs. The development outlined here makes MixMD a robust method which should prove useful across a broad range of target structures. Lastly, our results with MixMD match experimental data so well that consistency between simulations and density may be a useful way to aid the identification of probes vs waters during the refinement of future multiple solvent crystallographic structures.

Structure of gentlyase, the neutral metalloprotease of Paenibacillus polymyxa

Gentlyase is a bacterial extracellular metalloprotease that is widely applied in cell culture and for tissue dissociation and that belongs to the family of thermolysin-like proteases. The structure of thermolysin has been known since 1972 and that of Bacillus cereus neutral protease since 1992. However, the structure determination of other Bacillus neutral proteases has been hindered by their tendency to cannibalistic autolysis. High calcium conditions that allow the concentration and crystallization of the active Gentlyase metalloprotease without autoproteolysis were identified using thermal fluorescent shift assays. X-ray structures of the protease were solved in the absence and in the presence of the inhibitor phosphoramidon at 1.59 and 1.76 Å resolution, respectively. No domain movement was observed upon inhibitor binding, although such movement is thought to be a general feature of the thermolysin-like protease family. Further analysis of the structure shows that the observed calcium dependency of Gentlyase stability may arise from a partly degenerated calcium site Ca1-2 and a deletion near site Ca3.

Fragment-based screening by protein crystallography: successes and pitfalls

Fragment-based drug discovery (FBDD) concerns the screening of low-molecular weight compounds against macromolecular targets of clinical relevance. These compounds act as starting points for the development of drugs. FBDD has evolved and grown in popularity over the past 15 years. In this paper, the rationale and technology behind the use of X-ray crystallography in fragment based screening (FBS) will be described, including fragment library design and use of synchrotron radiation and robotics for high-throughput X-ray data collection. Some recent uses of crystallography in FBS will be described in detail, including interrogation of the drug targets β-secretase, phenylethanolamine N-methyltransferase, phosphodiesterase 4A and Hsp90. These examples provide illustrations of projects where crystallography is straightforward or difficult, and where other screening methods can help overcome the limitations of crystallography necessitated by diffraction quality.

Protein flexibility in docking and surface mapping

Structure-based drug design has become an essential tool for rapid lead discovery and optimization. As available structural information has increased, researchers have become increasingly aware of the importance of protein flexibility for accurate description of the native state. Typical protein-ligand docking efforts still rely on a single rigid receptor, which is an incomplete representation of potential binding conformations of the protein. These rigid docking efforts typically show the best performance rates between 50 and 75%, while fully flexible docking methods can enhance pose prediction up to 80-95%. This review examines the current toolbox for flexible protein-ligand docking and receptor surface mapping. Present limitations and possibilities for future development are discussed.

Relationship between hot spot residues and ligand binding hot spots in protein-protein interfaces

In the context of protein-protein interactions, the term "hot spot" refers to a residue or cluster of residues that makes a major contribution to the binding free energy, as determined by alanine scanning mutagenesis. In contrast, in pharmaceutical research, a hot spot is a site on a target protein that has high propensity for ligand binding and hence is potentially important for drug discovery. Here we examine the relationship between these two hot spot concepts by comparing alanine scanning data for a set of 15 proteins with results from mapping the protein surfaces for sites that can bind fragment-sized small molecules. We find the two types of hot spots are largely complementary; the residues protruding into hot spot regions identified by computational mapping or experimental fragment screening are almost always themselves hot spot residues as defined by alanine scanning experiments. Conversely, a residue that is found by alanine scanning to contribute little to binding rarely interacts with hot spot regions on the partner protein identified by fragment mapping. In spite of the strong correlation between the two hot spot concepts, they fundamentally differ, however. In particular, while identification of a hot spot by alanine scanning establishes the potential to generate substantial interaction energy with a binding partner, there are additional topological requirements to be a hot spot for small molecule binding. Hence, only a minority of hot spots identified by alanine scanning represent sites that are potentially useful for small inhibitor binding, and it is this subset that is identified by experimental or computational fragment screening.

Emerging role of surface plasmon resonance in fragment-based drug discovery

Surface plasmon resonance (SPR) offers a method of biophysical fragment screening that is fast, efficient, cost effective and accurate. SPR is increasingly being adopted as a secondary assay to validate fragment hits. Recently, technical advances have resulted in the emergence of SPR as a primary screening methodology for fragment-based drug discovery. Moreover, SPR biosensor assays can be developed for a wide range of proteins, including membrane proteins, such as G-protein-coupled receptors. In this review, we discuss the advantages and limitations of SPR fragment screening including experimental consideration of reducing false positive and false negative rates to a minimum. We discuss how ligand efficiency can be used both as a method to eliminate false positives and to understand which fragments in a library may be a source of false negatives.

Analyzing the molecular basis of enzyme stability in ethanol/water mixtures using molecular dynamics simulations

One of the drawbacks of nonaqueous enzymology is the fact that enzymes tend to be less stable in organic solvents than in water. There are, however, some enzymes that display very high stabilities in nonaqueous media. In order to take full advantage of the use of nonaqueous solvents in enzyme catalysis, it is essential to elucidate the molecular basis of enzyme stability in these media. Toward this end, we performed μs-long molecular dynamics simulations using two homologous proteases, pseudolysin, and thermolysin, which are known to have considerably different stabilities in solutions containing ethanol. The analysis of the simulations indicates that pseudolysin is more stable than thermolysin in ethanol/water mixtures and that the disulfide bridge between C30 and C58 is important for the stability of the former enzyme, which is consistent with previous experimental observations. Our results indicate that thermolysin has a higher tendency to interact with ethanol molecules (especially through van der Waals contacts) than pseudolysin, which can lead to the disruption of intraprotein hydrophobic interactions and ultimately result in protein unfolding. In the absence of the C30-C58 disulfide bridge, pseudolysin undergoes larger conformational changes, becoming more open and more permeable to ethanol molecules which accumulate in its interior and form hydrophobic interactions with the enzyme, destroying its structure. Our observations are not only in good agreement with several previous experimental findings on the stability of the enzymes studied in ethanol/water mixtures but also give an insight on the molecular determinants of this stability. Our findings may, therefore, be useful in the rational development of enzymes with increased stability in these media.

Analysis of protein binding sites by computational solvent mapping

Computational solvent mapping globally samples the surface of target proteins using molecular probes-small molecules or functional groups-to identify potentially favorable binding positions. The method is based on X-ray and NMR screening studies showing that the binding sites of proteins also bind a large variety of fragment-sized molecules. We have developed the multistage mapping algorithm FTMap (available as a server at http://ftmap.bu.edu/ ) based on the fast Fourier transform (FFT) correlation approach. Identifying regions of low free energy rather than individual low energy conformations, FTMap reproduces the available experimental mapping results. Applications to a variety of proteins show that the probes always cluster in important subsites of the binding site, and the amino acid residues that interact with many probes also bind the specific ligands of the protein. The "consensus" sites at which a number of different probes cluster are likely to be "druggable" sites, capable of binding drug-size ligands with high affinity. Due to its sensitivity to conformational changes, the method can also be used for comparing the binding sites in different structures of a protein.

Optimal fine φ-slicing for single-photon-counting pixel detectors

The data-collection parameters used in a macromolecular diffraction experiment have a strong impact on data quality. A careful choice of parameters leads to better data and can make the difference between success and failure in phasing attempts, and will also result in a more accurate atomic model. The selection of parameters has to account for the application of the data in various phasing methods or high-resolution refinement. Furthermore, experimental factors such as crystal characteristics, available experiment time and the properties of the X-ray source and detector have to be considered. For many years, CCD detectors have been the prevalent type of detectors used in macromolecular crystallography. Recently, hybrid pixel X-ray detectors that operate in single-photon-counting mode have become available. These detectors have fundamentally different characteristics compared with CCD detectors and different data-collection strategies should be applied. Fine φ-slicing is a strategy that is particularly well suited to hybrid pixel detectors because of the fast readout time and the absence of readout noise. A large number of data sets were systematically collected from crystals of four different proteins in order to investigate the benefit of fine φ-slicing on data quality with a noise-free detector. The results show that fine φ-slicing can substantially improve scaling statistics and anomalous signal provided that the rotation angle is comparable to half the crystal mosaicity.

Experimental and computational active site mapping as a starting point to fragment-based lead discovery

Small highly soluble probe molecules such as aniline, urea, N-methylurea, 2-bromoacetate, 1,2-propanediol, nitrous oxide, benzamidine, and phenol were soaked into crystals of various proteins to map their binding pockets and to detect hot spots of binding with respect to hydrophobic and hydrophilic properties. The selected probe molecules were first tested at the zinc protease thermolysin. They were then applied to a wider range of proteins such as protein kinase A, D-xylose isomerase, 4-diphosphocytidyl-2C-methyl-D-erythritol synthase, endothiapepsin, and secreted aspartic protease 2. The crystal structures obtained clearly show that the probe molecules populate the protein binding pockets in an ordered fashion. The thus characterized, experimentally observed hot spots of binding were subjected to computational active site mapping using HotspotsX. This approach uses knowledge-based pair potentials to detect favorable binding positions for various atom types. Good agreement between the in silico hot spot predictions and the experimentally observed positions of the polar hydrogen bond forming functional groups and hydrophobic portions was obtained. Finally, we compared the observed poses of the small-molecule probes with those of much larger structurally related ligands. They coincide remarkably well with the larger ligands, considering their spatial orientation and the experienced interaction patterns. This observation confirms the fundamental hypothesis of fragment-based lead discovery: that binding poses, even of very small molecular probes, do not significantly deviate or move once a ligand is grown further into the binding site. This underscores the fact that these probes populate given hot spots and can be regarded as relevant seeds for further design.

Hot spot analysis for driving the development of hits into leads in fragment-based drug discovery

Fragment-based drug design (FBDD) starts with finding fragment-sized compounds that are highly ligand efficient and can serve as a core moiety for developing high-affinity leads. Although the core-bound structure of a protein facilitates the construction of leads, effective design is far from straightforward. We show that protein mapping, a computational method developed to find binding hot spots and implemented as the FTMap server, provides information that complements the fragment screening results and can drive the evolution of core fragments into larger leads with a minimal loss or, in some cases, even a gain in ligand efficiency. The method places small molecular probes, the size of organic solvents, on a dense grid around the protein and identifies the hot spots as consensus clusters formed by clusters of several probes. The hot spots are ranked based on the number of probe clusters, which predicts the binding propensity of the subsites and hence their importance for drug design. Accordingly, with a single exception the main hot spot identified by FTMap binds the core compound found by fragment screening. The most useful information is provided by the neighboring secondary hot spots, indicating the regions where the core can be extended to increase its affinity. To quantify this information, we calculate the density of probes from mapping, which describes the binding propensity at each point, and show that the change in the correlation between a ligand position and the probe density upon extending or repositioning the core moiety predicts the expected change in ligand efficiency.

Robust identification of binding hot spots using continuum electrostatics: application to hen egg-white lysozyme

Binding hot spots, protein regions with high binding affinity, can be identified by using X-ray crystallography or NMR spectroscopy to screen libraries of small organic molecules that tend to cluster at such hot spots. FTMap, a direct computational analogue of the experimental screening approaches, uses 16 different probe molecules for global sampling of the surface of a target protein on a dense grid and evaluates the energy of interaction using an empirical energy function that includes a continuum electrostatic term. Energy evaluation is based on the fast Fourier transform correlation approach, which allows for the sampling of billions of probe positions. The grid sampling is followed by off-grid minimization that uses a more detailed energy expression with a continuum electrostatics term. FTMap identifies the hot spots as consensus clusters formed by overlapping clusters of several probes. The hot spots are ranked on the basis of the number of probe clusters, which predicts their binding propensity. We applied FTMap to nine structures of hen egg-white lysozyme (HEWL), whose hot spots have been extensively studied by both experimental and computational methods. FTMap found the primary hot spot in site C of all nine structures, in spite of conformational differences. In addition, secondary hot spots in sites B and D that are known to be important for the binding of polysaccharide substrates were found. The predicted probe–protein interactions agree well with those seen in the complexes of HEWL with various ligands and also agree with an NMR-based study of HEWL in aqueous solutions of eight organic solvents. We argue that FTMap provides more complete information on the HEWL binding site than previous computational methods and yields fewer false-positive binding locations than the X-ray structures of HEWL from crystals soaked in organic solvents.

Biophysical studies of an NAD(P)(+)-dependent aldehyde dehydrogenase from Bacillus licheniformis

Aldehyde dehydrogenase (ALDH) catalyzes the conversion of aldehydes to the corresponding acids by means of an NAD(P)(+)-dependent virtually irreversible reaction. In this investigation, the biophysical properties of a recombinant Bacillus licheniformis ALDH (BlALDH) were characterized in detail by analytical ultracentrifuge (AUC) and various spectroscopic techniques. The oligomeric state of BlALDH in solution was determined to be tetrameric by AUC. Far-UV circular dichroism analysis revealed that the secondary structures of BlALDH were not altered in the presence of acetone and ethanol, whereas SDS had a detrimental effect on the folding of the enzyme. Thermal unfolding of this enzyme was found to be highly irreversible. The native enzyme started to unfold beyond ~0.2 M guanidine hydrochloride (GdnHCl) and reached an unfolded intermediate, [GdnHCl](05, N-U), at 0.93 M. BlALDH was active at concentrations of urea below 2 M, but it experienced an irreversible unfolding under 8 M denaturant. Taken together, this study provides a foundation for the future structural investigation of BlALDH, a typical member of ALDH superfamily enzymes.