Introduction to the BioChemical Library (BCL): An Application-Based Open-Source Toolkit for Integrated Cheminformatics and Machine Learning in Computer-Aided Drug Discovery.

The BioChemical Library (BCL) cheminformatics toolkit is an application-based academic open-source software package designed to integrate traditional small molecule cheminformatics tools with machine learning-based quantitative structure-activity/property relationship (QSAR/QSPR) modeling. In this pedagogical article we provide a detailed introduction to core BCL cheminformatics functionality, showing how traditional tasks (e.g., computing chemical properties, estimating druglikeness) can be readily combined with machine learning. In addition, we have included multiple examples covering areas of advanced use, such as reaction-based library design. We anticipate that this manuscript will be a valuable resource for researchers in computer-aided drug discovery looking to integrate modular cheminformatics and machine learning tools into their pipelines.

High-Throughput Screening Assay Datasets from the PubChem Database.

Availability of high-throughput screening (HTS) data in the public domain offers great potential to foster development of ligand-based computer-aided drug discovery (LB-CADD) methods crucial for drug discovery efforts in academia and industry. LB-CADD method development depends on high-quality HTS assay data, i.e., datasets that contain both active and inactive compounds. These active compounds are hits from primary screens that have been tested in concentration-response experiments and where the target-specificity of the hits has been validated through suitable secondary screening experiments. Publicly available HTS repositories such as PubChem often provide such data in a convoluted way: compounds that are classified as inactive need to be extracted from the primary screening record. However, compounds classified as active in the primary screening record are not suitable as a set of active compounds for LB-CADD experiments due to high false-positive rate. A suitable set of actives can be derived by carefully analysing results in often up to five or more assays that are used to confirm and classify the activity of compounds. These assays, in part, build on each other. However, often not all hit compounds from the previous screen have been tested. Sometimes a compound can be classified as 'active', though its meaning is 'inactive' on the target of interest as it is 'active' on a different target protein. Here, a curation process of hierarchically related confirmatory screens is illustrated based on two specifically chosen protein use-cases. The subsequent re-upload procedure into PubChem is described for the findings of those two scenarios. Further, we provide nine publicly accessible high quality datasets for future LB-CADD method development that provide a common baseline for comparison of future methods to the scientific community. We also provide a protocol researchers can follow to upload additional datasets for benchmarking.

Inactivation of peptidylglycine α-hydroxylating monooxygenase by cinnamic acid analogs.

Peptidylglycine α-amidating monooxygenase (PAM) is a bifunctional enzyme that catalyzes the final reaction in the maturation of α-amidated peptide hormones. Peptidylglycine α-hydroxylating monooxygenase (PHM) is the PAM domain responsible for the copper-, ascorbate- and O2-dependent hydroxylation of a glycine-extended peptide. Peptidylamidoglycolate lyase is the PAM domain responsible for the Zn(II)-dependent dealkylation of the α-hydroxyglycine-containing precursor to the final α-amidated peptide. We report herein that cinnamic acid and cinnamic acid analogs are inhibitors or inactivators of PHM. The inactivation chemistry exhibited by the cinnamates exhibits all the attributes of a suicide-substrate. However, we find no evidence for the formation of an irreversible linkage between cinnamate and PHM in the inactivated enzyme. Our data support the reversible formation of a Michael adduct between an active site nucleophile and cinnamate that leads to inactive enzyme. Our data are of significance given that cinnamates are found in foods, perfumes, cosmetics and pharmaceuticals.

Mechanistic studies of the tyrosinase-catalyzed oxidative cyclocondensation of 2-aminophenol to 2-aminophenoxazin-3-one.

Tyrosinase (EC 1.14.18.1) catalyzes the monophenolase and diphenolase reaction associated with vertebrate pigmentation and fruit/vegetable browning. Tyrosinase is an oxygen-dependent, dicopper enzyme that has three states: Emet, Eoxy, and Edeoxy. The diphenolase activity can be carried out by both the met and the oxy states of the enzyme while neither mono- nor diphenolase activity results from the deoxy state. In this study, the oxidative cyclocondensation of 2-aminophenol (OAP) to the corresponding 2-aminophenoxazin-3-one (APX) by mushroom tyrosinase was investigated. Using a combination of various steady- and pre-steady state methodologies, we have investigated the kinetic and chemical mechanism of this reaction. The kcat for OAP is 75 ± 2s(-1), K(OAP)M = 1.8 ± 0.2mM, K(O2)M =25 ± 4 µM with substrates binding in a steady-state preferred fashion. Stopped flow and global analysis support a model where OAP preferentially binds to the oxy form over the met (k7 ≫ k1). For the met form, His269 and His61 are the proposed bases, while the oxy form uses the copper-peroxide and His61 for the sequential deprotonation of anilinic and phenolic hydrogens. Solvent KIEs show proton transfer to be increasingly rate limiting for kcat/K(OAP)M as [O2] → 0 µM (1.38 ± 0.06) decreasing to 0.83 ± 0.03 as [O2] → ∞ reflecting a partially rate limiting µ-OH bond cleavage (E met) and formation (E oxy) following protonation in the transition state. The coupling and cyclization reactions of o-quinone imine and OAP pass through a phenyliminocyclohexadione intermediate to APX, forming at a rate of 6.91 ± 0.03 µM(-1)s(-1) and 2.59E-2 ± 5.31E-4s(-1). Differences in reactivity attributed to the anilinic moiety of OAP with o-diphenols are discussed.

BCL::SAXS: GPU accelerated Debye method for computation of small angle X-ray scattering profiles.

Small angle X-ray scattering (SAXS) is an experimental technique used for structural characterization of macromolecules in solution. Here, we introduce BCL::SAXS--an algorithm designed to replicate SAXS profiles from rigid protein models at different levels of detail. We first show our derivation of BCL::SAXS and compare our results with the experimental scattering profile of hen egg white lysozyme. Using this protein we show how to generate SAXS profiles representing: (1) complete models, (2) models with approximated side chain coordinates, and (3) models with approximated side chain and loop region coordinates. We evaluated the ability of SAXS profiles to identify a correct protein topology from a non-redundant benchmark set of proteins. We find that complete SAXS profiles can be used to identify the correct protein by receiver operating characteristic (ROC) analysis with an area under the curve (AUC) > 99%. We show how our approximation of loop coordinates between secondary structure elements improves protein recognition by SAχS for protein models without loop regions and side chains. Agreement with SAXS data is a necessary but not sufficient condition for structure determination. We conclude that experimental SAXS data can be used as a filter to exclude protein models with large structural differences from the native.

Discoidin domain receptor 1 (DDR1) kinase as target for structure-based drug discovery.

Discoidin domain receptor (DDR) 1 and 2 are transmembrane receptors that belong to the family of receptor tyrosine kinases (RTK). Upon collagen binding, DDRs transduce cellular signaling involved in various cell functions, including cell adhesion, proliferation, differentiation, migration, and matrix homeostasis. Altered DDR function resulting from either mutations or overexpression has been implicated in several types of disease, including atherosclerosis, inflammation, cancer, and tissue fibrosis. Several established inhibitors, such as imatinib, dasatinib, and nilotinib, originally developed as Abelson murine leukemia (Abl) kinase inhibitors, have been found to inhibit DDR kinase activity. As we review here, recent discoveries of novel inhibitors and their co-crystal structure with the DDR1 kinase domain have made structure-based drug discovery for DDR1 amenable.

Cellular manganese content is developmentally regulated in human dopaminergic neurons.

Manganese (Mn) is both an essential biological cofactor and neurotoxicant. Disruption of Mn biology in the basal ganglia has been implicated in the pathogenesis of neurodegenerative disorders, such as parkinsonism and Huntington's disease. Handling of other essential metals (e.g. iron and zinc) occurs via complex intracellular signaling networks that link metal detection and transport systems. However, beyond several non-selective transporters, little is known about the intracellular processes regulating neuronal Mn homeostasis. We hypothesized that small molecules that modulate intracellular Mn could provide insight into cell-level Mn regulatory mechanisms. We performed a high throughput screen of 40,167 small molecules for modifiers of cellular Mn content in a mouse striatal neuron cell line. Following stringent validation assays and chemical informatics, we obtained a chemical 'toolbox' of 41 small molecules with diverse structure-activity relationships that can alter intracellular Mn levels under biologically relevant Mn exposures. We utilized this toolbox to test for differential regulation of Mn handling in human floor-plate lineage dopaminergic neurons, a lineage especially vulnerable to environmental Mn exposure. We report differential Mn accumulation between developmental stages and stage-specific differences in the Mn-altering activity of individual small molecules. This work demonstrates cell-level regulation of Mn content across neuronal differentiation.

Computational methods in drug discovery.

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature.

Benchmarking ligand-based virtual High-Throughput Screening with the PubChem database.

With the rapidly increasing availability of High-Throughput Screening (HTS) data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD) have the potential to accelerate and reduce the cost of probe development and drug discovery efforts in academia. We assemble nine data sets from realistic HTS campaigns representing major families of drug target proteins for benchmarking LB-CADD methods. Each data set is public domain through PubChem and carefully collated through confirmation screens validating active compounds. These data sets provide the foundation for benchmarking a new cheminformatics framework BCL::ChemInfo, which is freely available for non-commercial use. Quantitative structure activity relationship (QSAR) models are built using Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Decision Trees (DTs), and Kohonen networks (KNs). Problem-specific descriptor optimization protocols are assessed including Sequential Feature Forward Selection (SFFS) and various information content measures. Measures of predictive power and confidence are evaluated through cross-validation, and a consensus prediction scheme is tested that combines orthogonal machine learning algorithms into a single predictor. Enrichments ranging from 15 to 101 for a TPR cutoff of 25% are observed.

Reconstruction of SAXS Profiles from Protein Structures.

Small angle X-ray scattering (SAXS) is used for low resolution structural characterization of proteins often in combination with other experimental techniques. After briefly reviewing the theory of SAXS we discuss computational methods based on 1) the Debye equation and 2) Spherical Harmonics to compute intensity profiles from a particular macromolecular structure. Further, we review how these formulas are parameterized for solvent density and hydration shell adjustment. Finally we introduce our solution to compute SAXS profiles utilizing GPU acceleration.

BCL::EMAS--enantioselective molecular asymmetry descriptor for 3D-QSAR.

Stereochemistry is an important determinant of a molecule's biological activity. Stereoisomers can have different degrees of efficacy or even opposing effects when interacting with a target protein. Stereochemistry is a molecular property difficult to represent in 2D-QSAR as it is an inherently three-dimensional phenomenon. A major drawback of most proposed descriptors for 3D-QSAR that encode stereochemistry is that they require a heuristic for defining all stereocenters and rank-ordering its substituents. Here we propose a novel 3D-QSAR descriptor termed Enantioselective Molecular ASymmetry (EMAS) that is capable of distinguishing between enantiomers in the absence of such heuristics. The descriptor aims to measure the deviation from an overall symmetric shape of the molecule. A radial-distribution function (RDF) determines a signed volume of tetrahedrons of all triplets of atoms and the molecule center. The descriptor can be enriched with atom-centric properties such as partial charge. This descriptor showed good predictability when tested with a dataset of thirty-one steroids commonly used to benchmark stereochemistry descriptors (r² = 0.89, q² = 0.78). Additionally, EMAS improved enrichment of 4.38 versus 3.94 without EMAS in a simulated virtual high-throughput screening (vHTS) for inhibitors and substrates of cytochrome P450 (PUBCHEM AID891).

N-acylethanolamines as novel alcohol dehydrogenase 3 substrates.

N-acylethanolamines (NAEs) are members of the fatty acid amide family. The NAEs have been proposed to serve as metabolic precursors to N-acylglycines (NAGs). The sequential oxidation of the NAEs by an alcohol dehydrogenase and an aldehyde dehydrogenase would yield the N-acylglycinals and/or the NAGs. Alcohol dehydrogenase 3 (ADH3) is one enzyme that might catalyze this reaction. To define a potential role for ADH3 in NAE catabolism, we synthesized a set of NAEs and evaluated these as ADH3 substrates. NAEs were oxidized by ADH3, yielding the N-acylglycinals as the product. The (V/K)(app) values for the NAEs included here were low relative to cinnamyl alcohol. Our data show that the NAEs can serve as alcohol dehydrogenase substrates.

Evidence for substrate preorganization in the peptidylglycine α-amidating monooxygenase reaction describing the contribution of ground state structure to hydrogen tunneling.

Peptidylglycine α-amidating monooxygenase (PAM) is a bifunctional enzyme which catalyzes the post-translational modification of inactive C-terminal glycine-extended peptide precursors to the corresponding bioactive α-amidated peptide hormone. This conversion involves two sequential reactions both of which are catalyzed by the separate catalytic domains of PAM. The first step, the copper-, ascorbate-, and O(2)-dependent stereospecific hydroxylation at the α-carbon of the C-terminal glycine, is catalyzed by peptidylglycine α-hydroxylating monooxygenase (PHM). The second step, the zinc-dependent dealkylation of the carbinolamide intermediate, is catalyzed by peptidylglycine amidoglycolate lyase. Quantum mechanical tunneling dominates PHM-dependent C(α)-H bond activation. This study probes the substrate structure dependence of this chemistry using a set of N-acylglycine substrates of varying hydrophobicity. Primary deuterium kinetic isotope effects (KIEs), molecular mechanical docking, alchemical free energy perturbation, and equilibrium molecular dynamics were used to study the role played by ground-state substrate structure on PHM catalysis. Our data show that all Ν-acylglycines bind sequentially to PHM in an equilibrium-ordered fashion. The primary deuterium KIE displays a linear decrease with respect to acyl chain length for straight-chain N-acylglycine substrates. Docking orientation of these substrates displayed increased dissociation energy proportional to hydrophobic pocket interaction. The decrease in KIE with hydrophobicity was attributed to a preorganization event which decreased reorganization energy by decreasing the conformational sampling associated with ground state substrate binding. This is the first example of preorganization in the family of noncoupled copper monooxygenases.

3D-QSAR CoMFA study of benzoxazepine derivatives as mGluR5 positive allosteric modulators.

Positive allosteric modulation of the metabotropic glutamate receptor subtype 5 was studied by conducting a comparative molecular field analysis on 118 benzoxazepine derivatives. The model with the best predictive ability retained significant cross-validated correlation coefficients of q(2) = 0.58 (r(2) = 0.81) yielding a standard error of 0.20 in pEC(50) for this class of compounds. The subsequent contour maps highlight the structural features pertinent to the bioactivity values of benzoxazepines.

Imino-oxy acetic acid dealkylation as evidence for an inner-sphere alcohol intermediate in the reaction catalyzed by peptidylglycine alpha-hydroxylating monooxygenase.

Peptidylglycine alpha-hydroxylating monooxygenase (PHM, EC 1.14.17.3) catalyzes the stereospecific hydroxylation of a glycyl alpha-carbon in a reaction that requires O(2) and ascorbate. Subsequent dealkylation of the alpha-hydroxyglycine by another enzyme, peptidylamidoglycolate lyase (PAL. EC 4.3.2.5), yields a bioactive amide and glyoxylate. PHM is a noncoupled, type II dicopper monooxygenase which activates O(2) at only a single copper atom, Cu(M). In this study, the PHM mechanism was probed using a non-natural substrate, benzaldehyde imino-oxy acetic acid (BIAA). PHM catalyzes the O-oxidative dealkylation of BIAA to benzaldoxime and glyoxylate with no involvement of PAL. The minimal kinetic mechanism for BIAA was shown to be steady-state ordered using primary deuterium kinetic isotope effects. The (D)(V/K)(APPARENT, BIAA) decreased from 14.7 +/- 1.0 as [O(2)] --> 0 to 1.0 +/- 0.2 as [O(2)] --> infinity suggesting the dissociation rate constant from the PHM x BIAA complex decreases as [O(2)] increases; thereby, reducing the steady-state concentration of [PHM](free). BIAA was further used to differentiate between potential oxidative Cu/O species using a QM/MM reaction coordinate simulation to determine which species could yield product O-dealkylation that matched our experimental data. The results of this study provided compelling evidence for the presence of a covalently linked Cu(II)-alkoxide intermediate with a quartet spin state responsible BIAA oxidation.

Substituted hippurates and hippurate analogs as substrates and inhibitors of peptidylglycine alpha-hydroxylating monooxygenase (PHM).

Peptidyl alpha-hydroxylating monooxygenase (PHM) functions in vivo towards the biosynthesis of alpha-amidated peptide hormones in mammals and insects. PHM is a potential target for the development of inhibitors as drugs for the treatment of human disease and as insecticides for the management of insect pests. We show here that relatively simple ground state analogs of the PHM substrate hippuric acid (C(6)H(5)-CO-NH-CH(2)-COOH) inhibit the enzyme with K(i) values as low as 0.5microM. Substitution of sulfur atom(s) into the hippuric acid analog increases the affinity of PHM for the inhibitor. Replacement of the acetylglycine moiety, -CO-NH-CH(2)-COOH with an S-(thioacetyl)thioglycolic acid moiety, -CS-S-CH(2)-COOH, yields compounds with the highest PHM affinity. Both S-(2-phenylthioacetyl)thioglycolate and S-(4-ethylthiobenzoyl)thioglycolic acid inhibit the proliferation of cultured human prostate cancer cells at concentrations >100-fold excess of their respective K(i) values. Comparison of K(i) values between mammalian PHM and insect PHM shows differences in potency suggesting that a PHM-based insecticide with limited human toxicity can be developed.

Thiorphan, tiopronin, and related analogs as substrates and inhibitors of peptidylglycine alpha-amidating monooxygenase (PAM).

Peptidyglycine alpha-amidating monooxygenase is a copper- and zinc-dependent, bifunctional enzyme that catalyzes the cleavage of glycine-extended peptides or N-acylglycines to the corresponding amides and glyoxylate. This reaction is a key step in the biosynthesis of bioactive alpha-amidated peptides and, perhaps, the primary fatty acids amides also. Two clinically useful N-acylglycines are thiorphan and tiopronin, each with a thiol moiety attached to the acyl group. We report here that thiorphan and tiopronin are substrates for PAM, exhibiting relatively low K(M,app) and V(MAX,app) values. The low V(MAX,app) values result, most likely, from a decrease in active PAM.2Cu(II) as the enzyme competes ineffectively with thiorphan and tiopronin for free copper.