Challenges in the determination of the binding modes of non-standard ligands in X-ray crystal complexes

Study of SQ109 analogs binding to mycobacterium MmpL3 transporter using MD simulations and alchemical relative binding free energy calculations

N-geranyl-N΄-(2-adamantyl)ethane-1,2-diamine (SQ109) is a tuberculosis drug that has high potency against Mycobacterium tuberculosis (Mtb) and may function by blocking cell wall biosynthesis. After the crystal structure of MmpL3 from Mycobacterium smegmatis in complex with SQ109 became available, it was suggested that SQ109 inhibits Mmpl3 mycolic acid transporter. Here, we showed using molecular dynamics (MD) simulations that the binding profile of nine SQ109 analogs with inhibitory potency against Mtb and alkyl or aryl adducts at C-2 or C-1 adamantyl carbon to MmpL3 was consistent with the X-ray structure of MmpL3 - SQ109 complex. We showed that rotation of SQ109 around carbon-carbon bond in the monoprotonated ethylenediamine unit favors two gauche conformations as minima in water and lipophilic solvent using DFT calculations as well as inside the transporter's binding area using MD simulations. The binding assays in micelles suggested that the binding affinity of the SQ109 analogs was increased for the larger, more hydrophobic adducts, which was consistent with our results from MD simulations of the SQ109 analogues suggesting that sizeable C-2 adamantyl adducts of SQ109 can fill a lipophilic region between Y257, Y646, F260 and F649 in MmpL3. This was confirmed quantitatively by our calculations of the relative binding free energies using the thermodynamic integration coupled with MD simulations method with a mean assigned error of 0.74 kcal mol^-1 compared to the experimental values.

GlycoTorch Vina: Docking Designed and Tested for Glycosaminoglycans

Glycosaminoglycans (GAGs) are a family of anionic carbohydrates that play an essential role in the physiology and pathology of all eukaryotic life forms. Experimental determination of GAG-protein complexes is challenging due to their difficult isolation from biological sources, natural heterogeneity, and conformational flexibility-including possible ring puckering of sulfated iduronic acid from ¹C₄ to ²S_O conformation. To overcome these challenges, we present GlycoTorch Vina (GTV), a molecular docking tool based on the carbohydrate docking program VinaCarb (VC). Our program is unique in that it contains parameters to model ²S_O sugars while also supporting glycosidic linkages specific to GAGs. We discuss how crystallographic models of carbohydrates can be biased by the choice of refinement software and structural dictionaries. To overcome these variations, we carefully curated 12 of the best available GAG and GAG-like crystal structures (ranging from tetra- to octasaccharides or longer) obtained from the PDB-REDO server and refined using the same protocol. Both GTV and VC produced pose predictions with a mean root-mean-square deviation (RMSD) of 3.1 Å from the native crystal structure-a statistically significant improvement when compared to AutoDock Vina (4.5 Å) and the commercial software Glide (5.9 Å). Examples of how real-space correlation coefficients can be used to better assess the accuracy of docking pose predictions are given. Comparisons between statistical distributions of empirical "salt bridge" interactions, relevant to GAGs, were compared to density functional theory (DFT) studies of model salt bridges, and water-mediated salt bridges; however, there was generally a poor agreement between these data. Water bridges appear to play an important, yet poorly understood, role in the structures of GAG-protein complexes. To aid in the rapid prototyping of future pose scoring functions, we include a module that allows users to include their own torsional and nonbonded parameters.

High-throughput quantum-mechanics/molecular-mechanics (ONIOM) macromolecular crystallographic refinement with PHENIX/DivCon: the impact of mixed Hamiltonian methods on ligand and protein structure

Conventional macromolecular crystallographic refinement relies on often dubious stereochemical restraints, the preparation of which often requires human validation for unusual species, and on rudimentary energy functionals that are devoid of nonbonding effects owing to electrostatics, polarization, charge transfer or even hydrogen bonding. While this approach has served the crystallographic community for decades, as structure-based drug design/discovery (SBDD) has grown in prominence it has become clear that these conventional methods are less rigorous than they need to be in order to produce properly predictive protein-ligand models, and that the human intervention that is required to successfully treat ligands and other unusual chemistries found in SBDD often precludes high-throughput, automated refinement. Recently, plugins to the Python-based Hierarchical ENvironment for Integrated Xtallography (PHENIX) crystallographic platform have been developed to augment conventional methods with the in situ use of quantum mechanics (QM) applied to ligand(s) along with the surrounding active site(s) at each step of refinement [Borbulevych et al. (2014), Acta Cryst D70, 1233-1247]. This method (Region-QM) significantly increases the accuracy of the X-ray refinement process, and this approach is now used, coupled with experimental density, to accurately determine protonation states, binding modes, ring-flip states, water positions and so on. In the present work, this approach is expanded to include a more rigorous treatment of the entire structure, including the ligand(s), the associated active site(s) and the entire protein, using a fully automated, mixed quantum-mechanics/molecular-mechanics (QM/MM) Hamiltonian recently implemented in the DivCon package. This approach was validated through the automatic treatment of a population of 80 protein-ligand structures chosen from the Astex Diverse Set. Across the entire population, this method results in an average 3.5-fold reduction in ligand strain and a 4.5-fold improvement in MolProbity clashscore, as well as improvements in Ramachandran and rotamer outlier analyses. Overall, these results demonstrate that the use of a structure-wide QM/MM Hamiltonian exhibits improvements in the local structural chemistry of the ligand similar to Region-QM refinement but with significant improvements in the overall structure beyond the active site.

Predicting the Prevalence of Alternative Warfarin Tautomers in Solution

Warfarin, a widely used oral anticoagulant, is prescribed as a racemic mixture. Each enantiomer of neutral Warfarin can exist in 20 possible tautomeric states leading to complex pharmacokinetics and uncertainty as to the relevant species under different conditions. Here, the ability of alternative computational approaches to predict the preferred tautomeric form(s) of neutral Warfarin in different solvents is examined. It is shown that varying the method used to estimate the heat of formation in vacuum (direct or via homodesmic reactions), whether entropic corrections were included, and the method used to estimate the free enthalpy of solvation (i.e., PCM, COSMO, or SMD implicit models or explicit solvent) lead to large differences in the predicted rank and relative populations of the tautomers. In this case, only a combination of the enthalpy of formation using homodesmic reactions and explicit solvent to estimate the free enthalpy of solvation yielded results compatible with the available experimental data. The work also suggests that a small but significant subset of the possible Warfarin tautomers are likely to be physiologically relevant.

Assigning crystallographic electron densities with free energy calculations-The case of the fluoride channel Fluc

Approximately 90% of the structures in the Protein Data Bank (PDB) were obtained by X-ray crystallography or electron microscopy. Whereas the overall quality of structure is considered high, thanks to a wide range of tools for structure validation, uncertainties may arise from density maps of small molecules, such as organic ligands, ions or water, which are non-covalently bound to the biomolecules. Even with some experience and chemical intuition, the assignment of such disconnected electron densities is often far from obvious. In this study, we suggest the use of molecular dynamics (MD) simulations and free energy calculations, which are well-established computational methods, to aid in the assignment of ambiguous disconnected electron densities. Specifically, estimates of (i) relative binding affinities, for instance between an ion and water, (ii) absolute binding free energies, i.e., free energies for transferring a solute from bulk solvent to a binding site, and (iii) stability assessments during equilibrium simulations may reveal the most plausible assignments. We illustrate this strategy using the crystal structure of the fluoride specific channel (Fluc), which contains five disconnected electron densities previously interpreted as four fluoride and one sodium ion. The simulations support the assignment of the sodium ion. In contrast, calculations of relative and absolute binding free energies as well as stability assessments during free MD simulations suggest that four of the densities represent water molecules instead of fluoride. The assignment of water is compatible with the loss of these densities in the non-conductive F82I/F85I mutant of Fluc. We critically discuss the role of the ion force fields for the calculations presented here. Overall, these findings indicate that MD simulations and free energy calculations are helpful tools for modeling water and ions into crystallographic density maps.

Conformational energy range of ligands in protein crystal structures: The difficult quest for accurate understanding

In this review, we address a fundamental question: What is the range of conformational energies seen in ligands in protein-ligand crystal structures? This value is important biophysically, for better understanding the protein-ligand binding process; and practically, for providing a parameter to be used in many computational drug design methods such as docking and pharmacophore searches. We synthesize a selection of previously reported conflicting results from computational studies of this issue and conclude that high ligand conformational energies really are present in some crystal structures. The main source of disagreement between different analyses appears to be due to divergent treatments of electrostatics and solvation. At the same time, however, for many ligands, a high conformational energy is in error, due to either crystal structure inaccuracies or incorrect determination of the reference state. Aside from simple chemistry mistakes, we argue that crystal structure error may mainly be because of the heuristic weighting of ligand stereochemical restraints relative to the fit of the structure to the electron density. This problem cannot be fixed with improvements to electron density fitting or with simple ligand geometry checks, though better metrics are needed for evaluating ligand and binding site chemistry in addition to geometry during structure refinement. The ultimate solution for accurately determining ligand conformational energies lies in ultrahigh-resolution crystal structures that can be refined without restraints.

Molecular dynamics simulations reveal structural insights into inhibitor binding modes and functionality in human Group IIA phospholipase A2

Human Group IIA phospholipase A₂ (hGIIA) promotes inflammation in immune-mediated pathologies by regulating the arachidonic acid pathway through both catalysis-dependent and -independent mechanisms. The hGIIA crystal structure, both alone and inhibitor-bound, together with structures of closely related snake-venom-derived secreted phospholipase enzymes has been well described. However, differentiation of biological and nonbiological contacts and the relevance of structures determined from snake venom enzymes to human enzymes are not clear. We employed molecular dynamics (MD) and docking approaches to understand the binding of inhibitors that selectively or nonselectively block the catalysis-independent mechanism of hGIIA. Our results indicate that hGIIA behaves as a monomer in the solution environment rather than a dimer arrangement that is in the asymmetric unit of some crystal structures. The binding mode of a nonselective inhibitor, KH064, was validated by a combination of the experimental electron density and MD simulations. The binding mode of the selective pentapeptide inhibitor FLSYK to hGIIA was stipulated to be different to that of the snake venom phospholipases A₂ of Daboia russelli pulchella (svPLA₂ ). Our data suggest that the application of MD approaches to crystal structure data is beneficial in evaluating the robustness of conclusions drawn based on crystal structure data alone. Proteins 2017; 85:827-842. © 2016 Wiley Periodicals, Inc.

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.

XModeScore: a novel method for accurate protonation/tautomer-state determination using quantum-mechanically driven macromolecular X-ray crystallographic refinement

Gaining an understanding of the protein-ligand complex structure along with the proper protonation and explicit solvent effects can be important in obtaining meaningful results in structure-guided drug discovery and structure-based drug discovery. Unfortunately, protonation and tautomerism are difficult to establish with conventional methods because of difficulties in the experimental detection of H atoms owing to the well known limitations of X-ray crystallography. In the present work, it is demonstrated that semiempirical, quantum-mechanics-based macromolecular crystallographic refinement is sensitive to the choice of a protonation-state/tautomer form of ligands and residues, and can therefore be used to explore potential states. A novel scoring method, called XModeScore, is described which enumerates the possible protomeric/tautomeric modes, refines each mode against X-ray diffraction data with the semiempirical quantum-mechanics (PM6) Hamiltonian and scores each mode using a combination of energetic strain (or ligand strain) and rigorous statistical analysis of the difference electron-density distribution. It is shown that using XModeScore it is possible to consistently distinguish the correct bound protomeric/tautomeric modes based on routine X-ray data, even at lower resolutions of around 3 Å. These X-ray results are compared with the results obtained from much more expensive and laborious neutron diffraction studies for three different examples: tautomerism in the acetazolamide ligand of human carbonic anhydrase II (PDB entries 3hs4 and 4k0s), tautomerism in the 8HX ligand of urate oxidase (PDB entries 4n9s and 4n9m) and the protonation states of the catalytic aspartic acid found within the active site of an aspartic protease (PDB entry 2jjj). In each case, XModeScore applied to the X-ray diffraction data is able to determine the correct protonation state as defined by the neutron diffraction data. The impact of QM-based refinement versus conventional refinement on XModeScore is also discussed.

The future of crystallography in drug discovery

INTRODUCTION

X-ray crystallography plays an important role in structure-based drug design (SBDD), and accurate analysis of crystal structures of target macromolecules and macromolecule-ligand complexes is critical at all stages. However, whereas there has been significant progress in improving methods of structural biology, particularly in X-ray crystallography, corresponding progress in the development of computational methods (such as in silico high-throughput screening) is still on the horizon. Crystal structures can be overinterpreted and thus bias hypotheses and follow-up experiments. As in any experimental science, the models of macromolecular structures derived from X-ray diffraction data have their limitations, which need to be critically evaluated and well understood for structure-based drug discovery.

AREAS COVERED

This review describes how the validity, accuracy and precision of a protein or nucleic acid structure determined by X-ray crystallography can be evaluated from three different perspectives: i) the nature of the diffraction experiment; ii) the interpretation of an electron density map; and iii) the interpretation of the structural model in terms of function and mechanism. The strategies to optimally exploit a macromolecular structure are also discussed in the context of 'Big Data' analysis, biochemical experimental design and structure-based drug discovery.

EXPERT OPINION

Although X-ray crystallography is one of the most detailed 'microscopes' available today for examining macromolecular structures, the authors would like to re-emphasize that such structures are only simplified models of the target macromolecules. The authors also wish to reinforce the idea that a structure should not be thought of as a set of precise coordinates but rather as a framework for generating hypotheses to be explored. Numerous biochemical and biophysical experiments, including new diffraction experiments, can and should be performed to verify or falsify these hypotheses. X-ray crystallography will find its future application in drug discovery by the development of specific tools that would allow realistic interpretation of the outcome coordinates and/or support testing of these hypotheses.

The quality and validation of structures from structural genomics

Quality control of three-dimensional structures of macromolecules is a critical step to ensure the integrity of structural biology data, especially those produced by structural genomics centers. Whereas the Protein Data Bank (PDB) has proven to be a remarkable success overall, the inconsistent quality of structures reveals a lack of universal standards for structure/deposit validation. Here, we review the state-of-the-art methods used in macromolecular structure validation, focusing on validation of structures determined by X-ray crystallography. We describe some general protocols used in the rebuilding and re-refinement of problematic structural models. We also briefly discuss some frontier areas of structure validation, including refinement of protein-ligand complexes, automation of structure redetermination, and the use of NMR structures and computational models to solve X-ray crystal structures by molecular replacement.

Conformational properties of cholic acid, a lead compound at the crossroads of bile acid inspired drug discovery

DFT and NMR spectroscopy studies unveil three major minima conformations of cholic acid that may affect its biological properties.

Metformin impairs glucose consumption and survival in Calu-1 cells by direct inhibition of hexokinase-II

The anti-hyperglycaemic drug metformin has important anticancer properties as shown by the direct inhibition of cancer cells proliferation. Tumor cells avidly use glucose as a source for energy production and cell building blocks. Critical to this phenotype is the production of glucose-6-phosphate (G6P), catalysed by hexokinases (HK) I and II, whose role in glucose retention and metabolism is highly advantageous for cell survival and proliferation. Here we show that metformin impairs the enzymatic function of HKI and II in Calu-1 cells. This inhibition virtually abolishes cell glucose uptake and phosphorylation as documented by the reduced entrapment of ¹⁸F-fluorodeoxyglucose. In-silico models indicate that this action is due to metformin capability to mimic G6P features by steadily binding its pocket in HKII. The impairment of this energy source results in mitochondrial depolarization and subsequent cell death. These results could represent a starting point to open effective strategies in cancer prevention and treatment.

Learning from our mistakes: the 'unknown knowns' in fragment screening

In the past 15 years, fragment-based lead discovery (FBLD) has been adopted widely throughout academia and industry. The approach entails discovering very small molecular fragments and growing, merging, or linking them to produce drug leads. Because the affinities of the initial fragments are often low, detection methods are pushed to their limits, leading to a variety of artifacts, false positives, and false negatives that too often go unrecognized. This Digest discusses some of these problems and offers suggestions to avoid them. Although the primary focus is on FBLD, many of the lessons also apply to more established approaches such as high-throughput screening.

Mechanism of the ABC transporter ATPase domains: catalytic models and the biochemical and biophysical record

ABC transporters comprise a large, diverse, and ubiquitous superfamily of membrane active transporters. Their core architecture is a dimer of dimers, comprising two transmembrane domains that bind substrate and form the channel, and two ATP-binding cassettes, which bind and hydrolyze ATP to energize the translocase function. The prevailing paradigm for the ABC transport mechanism is the Switch Model, in which the nucleotide binding domains are proposed to dimerise upon binding of two ATP molecules, and thence dissociate upon sequential hydrolysis of the ATP. This idea appears consistent with crystal structures of both isolated subunits and whole transporters, as well as with a significant body of biochemical data. Nonetheless, an alternative Constant Contact Model has been proposed, in which the nucleotide binding domains do not fully dissociate, and ATP hydrolysis occurs alternately at each of the two active sites. Here, we review the biochemical and biophysical data relating to the ABC catalytic mechanism, to show how they may be construed as consistent with a Constant Contact Model, and to assess to what extent they support the Switch Model.

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.

Thermodynamics of transport through the ammonium transporter Amt-1 investigated with free energy calculations

Amt-1 from Archaeoglobus fulgidus (AfAmt-1) belongs to the Amt/Rh family of ammonium/ammonia transporting membrane proteins. The transport mode and the precise microscopic permeation mechanism utilized by these proteins are intensely debated. Open questions concern the identity of the transported substrate (ammonia and/or ammonium) and whether the transport is passive or active. To address these questions, we studied the overall thermodynamics of the different transport modes as a function of the environmental conditions. Then, we investigated the thermodynamics of the underlying microscopic transport mechanisms with free energy calculations within a continuum electrostatics model. The formalism developed for this purpose is of general utility in the calculation of binding free energies for ligands with multiple protonation forms or other binding forms. The results of our calculations are compared to the available experimental and theoretical data on Amt/Rh proteins and discussed in light of the current knowledge on the physiological conditions experienced by microorganisms and plants. We found that microscopic models of electroneutral and electrogenic transport modes are in principle thermodynamically viable. However, only the electrogenic variants have a net thermodynamic driving force under the physiological conditions experienced by microorganisms and plants. Thus, the transport mechanism of AfAmt-1 is most likely electrogenic.

Evaluating the enthalpic contribution to ligand binding using QM calculations: effect of methodology on geometries and interaction energies

As a result of research on ligand efficiency in the pharmaceutical industry, there is greater focus on optimizing the strength of polar interactions within receptors, so that the contribution of overall size and lipophilicity to binding can be decreased. A number of quantum mechanical (QM) methods involving simple probes are available to assess the H-bonding potential of different heterocycles or functional groups. However, in most receptors, multiple features are present, and these have distinct directionality, meaning very minimalist models may not be so ideal to describe the interactions. We describe how the use of gas phase QM models of kinase protein-ligand complex, which can more closely mimic the polar features of the active site region, can prove useful in assessing alterations to a core template, or different substituents. We investigate some practical issues surrounding the use of QM cluster models in structure based design (SBD). These include the choice of the method; semi-empirical, density functional theory or ab-initio, the choice of the basis set, whether to include implicit or explicit solvation, whether BSSE should be included, etc. We find a combination of the M06-2X method and the 6-31G* basis set is sufficiently rapid, and accurate, for the computation of structural and energetic parameters for this system.

Missing fragments: detecting cooperative binding in fragment-based drug design

The aim of fragment-based drug design (FBDD) is to identify molecular fragments that bind to alternate subsites within a given binding pocket leading to cooperative binding when linked. In this study, the binding of fragments to human phenylethanolamine N-methyltransferase is used to illustrate how (a) current protocols may fail to detect fragments that bind cooperatively, (b) theoretical approaches can be used to validate potential hits, and (c) apparent false positives obtained when screening against cocktails of fragments may in fact indicate promising leads.

PDB ligand conformational energies calculated quantum-mechanically

We present here a greatly updated version of an earlier study on the conformational energies of protein-ligand complexes in the Protein Data Bank (PDB) [Nicklaus et al. Bioorg. Med. Chem. 1995, 3, 411-428], with the goal of improving on all possible aspects such as number and selection of ligand instances, energy calculations performed, and additional analyses conducted. Starting from about 357,000 ligand instances deposited in the 2008 version of the Ligand Expo database of the experimental 3D coordinates of all small-molecule instances in the PDB, we created a "high-quality" subset of ligand instances by various filtering steps including application of crystallographic quality criteria and structural unambiguousness. Submission of 640 Gaussian 03 jobs yielded a set of about 415 successfully concluded runs. We used a stepwise optimization of internal degrees of freedom at the DFT level of theory with the B3LYP/6-31G(d) basis set and a single-point energy calculation at B3LYP/6-311++G(3df,2p) after each round of (partial) optimization to separate energy changes due to bond length stretches vs bond angle changes vs torsion changes. Even for the most "conservative" choice of all the possible conformational energies-the energy difference between the conformation in which all internal degrees of freedom except torsions have been optimized and the fully optimized conformer-significant energy values were found. The range of 0 to ~25 kcal/mol was populated quite evenly and independently of the crystallographic resolution. A smaller number of "outliers" of yet higher energies were seen only at resolutions above 1.3 Å. The energies showed some correlation with molecular size and flexibility but not with crystallographic quality metrics such as the Cruickshank diffraction-component precision index (DPI) and R(free)-R, or with the ligand instance-specific metrics such as occupancy-weighted B-factor (OWAB), real-space R factor (RSR), and real-space correlation coefficient (RSCC). We repeated these calculations with the solvent model IEFPCM, which yielded energy differences that were generally somewhat lower than the corresponding vacuum results but did not produce a qualitatively different picture. Torsional sampling around the crystal conformation at the molecular mechanics level using the MMFF94s force field typically led to an increase in energy.

X-ray crystallography: Assessment and validation of protein-small molecule complexes for drug discovery

INTRODUCTION: Crystallography is the key initial component for structure-based and fragment-based drug design and can often generate leads that can be developed into high potency drugs. Therefore, huge sums of money are committed based on the outcome of crystallography experiments and their interpretation. AREAS COVERED: This review discusses how to evaluate the correctness of an X-ray structure, focusing on the validation of small molecule-protein complexes. Various types of inaccuracies found within the PDB are identified and the ramifications of these errors are discussed. The reader will gain an understanding of the key parameters that need to be inspected before a structure can be used in drug discovery efforts, as well as an appreciation of the difficulties of correctly interpreting electron density for small molecules. The reader will also be introduced to methods for validating small molecules within the context of a macromolecular structure. EXPERT OPINION: One of the reasons that ligand identification and positioning, within a macromolecular crystal structure, is so difficult is that the quality of small molecules widely varies in the PDB. For this reason, the PDB can not always be considered a reliable repository of structural information pertaining to small molecules, and this makes the derivation of general principles that govern small molecule-protein interactions more difficult.