In Silico Characterization of Structural Distinctions between Isoforms of

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Computational Biochemistry

In silico Characterization of Structural Distinctions Between Isoforms of Human and Mouse Sphingosine Kinases for Accelerating Drug Discovery Brittney L Worrell, Anne M. Brown, Webster L Santos, and David R. Bevan J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.8b00931 • Publication Date (Web): 07 Mar 2019 Downloaded from http://pubs.acs.org on March 18, 2019

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Journal of Chemical Information and Modeling

In silico Characterization of Structural Distinctions Between Isoforms of Human and Mouse Sphingosine Kinases for Accelerating Drug Discovery Brittney L. Worrell1, Anne M. Brown1,2,4, Webster L. Santos3,4, and David R. Bevan*1,4 Department of Biochemistry1, Virginia Tech, Blacksburg, VA, 24061, University Libraries2, Virginia Tech, Blacksburg, VA, 24061, Department of Chemistry3, Virginia Tech, Blacksburg, VA, 24061 and Virginia Tech Center for Drug Discovery4, Virginia Tech, Blacksburg, VA, 24061

*Corresponding author Email: [email protected] Address: 201 Engel Hall (0308) 340 West Campus Drive Blacksburg, VA 24061 Phone: (540) 231-9080

KEYWORDS: sphingosine kinases, molecular docking, enzyme-inhibitor interactions, in silico drug design, cancer

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ABSTRACT

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Alterations in cellular signaling pathways are associated with multiple disease states including

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cancers and fibrosis. Current research efforts to attenuate cancers, specifically lymphatic cancer,

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focus on inhibition of two sphingosine kinase isoforms, sphingosine kinase 1 (SphK1) and

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sphingosine kinase 2 (SphK2). Determining differences in structural and physicochemical binding

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site properties of SphKs is attractive to refine inhibitor potency and isoform selectivity. This study

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utilizes a predictive in silico approach to determine key differences in binding sites in SphK

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isoforms in human and mouse species. Homology modeling, molecular docking of inhibitors,

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analysis of binding pocket residue positions, development of pharmacophore models, and analysis

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of binding cavity volume were performed to determine isoform- and species-selective

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characteristics of the binding site and generate a system to rank potential inhibitors. Interestingly,

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docking studies showed compounds bound to mouse SphK1 in a manner more similar to human

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SphK2 than to human SphK1, indicating that SphKs in mice have structural properties distinct

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from human that confounds prediction of ligand selectivity in mice. Our studies aid in the

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development and production of new compound classes by highlighting structural distinctions and

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identifying the role of key residues that cause observable, functional differences in isoforms and

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between orthologues.

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Introduction According to the National Cancer Institute, approximately 600,000 Americans died of

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cancer in 2017.1 Cancer has been the second leading cause of death in the U.S. for years2 with

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treatments for cancers including surgery, hormone therapy, immunotherapy, radiation therapy, and

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chemotherapy, encompassing more than 200 molecular targeting drugs, most of which are specific

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to certain cancer types.3

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chemotherapeutic agents, a need still exists for drugs with novel mechanisms of action that target

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pathways influencing cell growth, survival, and migration. Controlling the production of

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endogenous regulatory molecules is an attractive approach to disrupting cellular signaling and

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proliferation/differentiation pathways in cancer cells.4 Among these regulatory signaling

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molecules is sphingosine-1-phosphate (S1P), which has been implicated as a potent cell growth-

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signaling lipid.5

Despite the relatively large number of molecular target and

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S1P is a pleiotropic lipid mediator that is generated by phosphorylation of sphingosine

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(Sph) by one of two isoforms of sphingosine kinase (SphK): sphingosine kinase 1 (SphK1) or

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sphingosine kinase 2 (SphK2).4, 6 S1P controls cell proliferation and survival7, with S1P levels

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being highly regulated through SphK phosphorylation and subsequent degradation that occurs

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through cleavage by S1P lyase or dephosphorylation by S1P phosphatases.6 S1P binds as an

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extracellular ligand to five G protein-coupled receptors (GPCRs)8 and acts as a second messenger

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to regulate calcium mobilization and cell growth.9

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deacetylases, TNS receptor-associated factor 2, prohibitin 2, protein kinase C delta, and BACE1,

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indicating an extensive role for S1P in regulatory and immune response pathways.10 SphKs are

Intracellular targets include histone

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being examined as drug targets to control in vivo levels of S1P, as SphK1 and SphK2 have been

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found to express S1P at elevated levels in certain cancers.5, 11 Therefore, inhibiting SphKs by

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utilizing small molecule-based treatments is an attractive avenue for development in therapeutic

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design for cancers and other associated diseases. 12, 13

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S1P is found in higher levels in the blood and lymphatic system than in tissues such as

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muscle and the epithelium.14 Within cells, SphK1 is localized in the cytoplasm whereas SphK2 is

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localized in the nucleus, leading to different roles for SphK isoforms in S1P production.11, 14 In

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mice, the knock-out of SphK1 alleles results in ~50% reduction of S1P levels in the blood

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compared to wild-type mice.14 In contrast, knock-out of SphK2 alleles in mice results in no

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significant change in the level of blood S1P relative to wild-type mice, and SphK2 selective

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inhibitors result in substantially increased (~133%) levels of S1P in blood of wild type mice and

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rats.14 The same SphK2 selective inhibitors have the opposite effect in a cultured human cell line

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(U937), where SphK2 inhibition decreases the amount of cell-associated S1P compared to cells

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cultured in the absence of inhibitor.14

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Isoform-selective and dual SphK inhibitors are reported to decrease S1P levels in vitro.15

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Currently, the most successful inhibitors contain a guanidine-based, oxadiazole-containing

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scaffold with a variety of moieties extending from the lipid tail region of the inhibitor.4 These

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compounds have good pharmacokinetic properties that track well with a pharmacodynamic

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marker, S1P concentration, in mice.16 While these compounds are potent and selective, more

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development is needed to enhance potency and isoform selectivity. Inhibitor studies performed

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on human and rat sphingosine kinases demonstrate isoform selectivity with Ki values exhibiting

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>20-fold selectivity towards SphK2 over SphK1 in mice17. However, these inhibitors had varying

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inhibitor activity when mouse or rat versus human homologues were used in these assays. For

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example, compound SLC5091592 shows 20-fold selectivity for human SphK2 (hSphK2) but is a

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nonselective inhibitor in rat and mouse.17 This difference in potency between mouse and human

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SphKs has been observed with a number of experimental inhibitors.14

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In this work, we assessed differences in the Sph binding pockets of human (hSphK) and

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mouse (mSphK) using computational techniques in order to generate a predictive model for

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compound selectivity and potency, as well as provide further understanding of the role of in silico

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and computational chemistry methods in isoform and orthologue specific inhibitor development.

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To elucidate structural variations between isoforms and orthologues, techniques including

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homology modeling, molecular docking of known dual and isoform-selective inhibitors (Table

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S1), and pharmacophore modeling were performed. To date, one crystal structure of human SphK1

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with ADP bound and four crystal structures of hSphK1 in complex with either Sph or inhibitors

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have been solved,18-20 but no x-ray structures of hSphK2, mSphK1, or mSphK2 are currently

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available. Sequence comparisons of the Sph binding pocket of SphK1 and SphK2 reveal several

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residue differences that may affect inhibitor selectivity and that can be studied in more depth using

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homology models of these other isoforms and orthologues (Figure 1, Supporting Information,

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Figure S1-S3, Tables S2-S3). Collectively, this work seeks to identify and assess structural features

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of homology models for both SphK1 and SphK2 of human and mouse variants, in order to

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rationalize experimental results of isoform-selective inhibitors and determine exploitable features

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for future drug discovery. By focusing on the structural comparison of model structures and

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docking known, experimentally confirmed inhibitors with identified isoform selectivity, we can

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also infer differences observed between species and isoforms. From these results, we investigated

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the possibility of designing compounds that improve the potency and selectivity in mice and

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human isoforms, enhancing the scope and potential for more inhibitor development for SphKs that

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can be effectively tested in vivo.

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METHODS

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Generating Homology Models for Human SphK2, Mouse SphK1, and Mouse SphK2

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The homology models for human SphK2 (hSphK2), mouse SphK1 (mSphK1), and mouse

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SphK2 (mSphK2) were generated with Molecular Operating Environment (MOE)21 using the

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crystal structure (SK1a splice variant, accession 3VZB_A from GenBank) of hSphK1 PDB ID:

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3VZB20 as the template. ADP was co-crystallized in the hSphK1 crystal structure 3VZD.20

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Structures were overlaid and ADP and Mg2+ were superimposed into each homology model based

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on the coordinates in the crystal structure. The structures were energy minimized using MOE and

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the AmberEHT force field 22 with ADP and Mg2+ present. The co-substrate, ATP, was positioned

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in the binding site by adding a phosphate group to ADP in MOE and subsequently energy

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minimizing the protein, ATP, and Mg2+ using the same methods as above. Structures with ADP or

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ATP were then analyzed for model quality using online servers including SWISS-MODEL23, 24,

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ProSA25, and Verify 3D.26, 27 These servers evaluated the backbone favorability, comparison to

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known experimentally solved structures, local side chain environment and position, and 3D

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structure environment. The three homology models and hSphK1 structure with ATP showed

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favorable free energy scores, phi/psi angles, and 3D local side chain structure environments and

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were deemed to fall into acceptable ranges based on these metrics, which allowed for confidence

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in using the models in our studies (Supporting Information, Figures S4-S7).

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Figure 1. Structural orientation of the Sph binding cavity and multiple sequence alignment of isoforms and orthologues. (A) Orientation of Sph and ATP binding cavity in hSphK1, with regions marked as head, hydrophobic core, and tail region of the Sph binding cavity. Sphingosine is shown as blue sticks colored by element, with ATP shown as wheat sticks colored by element. Mg2+ is shown as green sphere. (B) Multiple Sequence Alignment of hSphK1, hSphK2, mSphK1, and mSphK2 SK1a splice variant. Sequences are displayed by single letter amino acid code and are labeled by kinase isoform and orthologue on the left. Variation in residues are highlighted in different colors as a gradient depending on the amino acid type (hydrophobic - green, polar - blue, charged – red/purple, aromatic – orange, cysteine - yellow). Key residues in the sphingosine binding pocket are highlighted in magenta. Percent identity of hSphK2, mSphK1, and mSphK2 as compared to hSphK1 are shown on the right as percentages.

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After validating the homology models, we resolved the issue of mismatched residue

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numbers across the four models. For each model, the residue numbering began at different starting

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residue numbers based on model output and total length of the protein so that the same residue in

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the sequence alignment had four different numbers based on the kinase to which it belonged. A

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multiple sequence alignment (MSA) was performed with Schrödinger Maestro Multiple Sequence 7 ACS Paragon Plus Environment

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Viewer.28 The MSA positioned extra residues of SphK2 in the core (central) domain of the

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structure, with gaps created in the sequence of SphK1, rather than the extra residues being at the

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N-terminus as previously suggested.29 Additionally, the literature cites Asp 81 in hSphK1 as an

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essential residue, with this residue aligning with Asp 135, Asp 211, and Asp 212 in mSphK1,

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hSphK1, and hSphK2, respectively, in the sequence alignment (Figure 1, Supporting Information,

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Figure S1-S3). To adjust the numbering of the MSA to match literature residue numbering, the

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starting residue number was changed to five in hSphK2, mSphK1, and mSphK2 so that the key

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residues would match the numbering in the literature for hSphK1. With the adjusted numbering

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system, the corresponding residue in each enzyme is labeled as Asp 81. Similarly, other key

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residues in each isoform also were renumbered to simplify the discussion of conserved residues in

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the sphingosine binding cavity (Table 1, Supporting Information, Figure S7). Key residues were

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also confirmed after molecular docking studies utilizing ligand fingerprinting (Supporting

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Information, Figures S10-S13).

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Table 1. Key residues in the sphingosine binding pockets of four isoforms of SphK with the original numbering from the enzyme sequence accessions and our adjusted numbering system based on the MSA. These key residues were the basis for the position of the grid box for docking and were used for distance measurements to the ligand for quantitative comparisons. The residues in the same column match spatial positioning in the binding pocket of the four kinases.

Enzyme Human SphK1 Mouse SphK1 Human SphK2 Mouse SphK2 Enzyme Human SphK1 Mouse SphK1 Human SphK2 Mouse SphK2

Key Residues in Binding Pocket – Original Numbering Asp81 Asp178 Ser168 Ile174 Phe303 Phe288 Tyr321 Asp135 Asp232 Ser222 Val228 Phe356 Phe341 His374 Asp211 Asp308 Ser298 Val304 Phe548 Cys533 Tyr566 Asp212 Asp309 Ser299 Leu305 Leu548 Cys533 Tyr566 Key Residues in Binding Pocket – Adjusted Numbering Asp81 Asp178 Ser168 Ile174 Phe419 Phe404 Tyr437 Asp81 Asp178 Ser168 Val174 Phe419 Phe404 His437 Asp81 Asp178 Ser168 Val174 Phe419 Cys404 Tyr437 Asp81 Asp178 Ser168 Leu174 Leu419 Cys404 Tyr437

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Pharmacophore Generation and Analysis

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His311 His364 His556 His556 His427 His427 His427 His427

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The Schrödinger Maestro28 Pharmacophore Hypothesis tool was used for receptor-based

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pharmacophore analysis. Receptor-only PDB files, as well as PDB files of docked poses of the

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ligands in the receptors, were loaded into Maestro, and the receptor-only method of the

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pharmacophore hypothesis was employed. This tool allowed us to identify hydrogen bond donor

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atoms, hydrogen bond acceptor atoms, aromatic regions, and hydrophobic regions within each

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binding cavity (Supporting Information, Figures S8-S9).

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Volume Calculations of Sphingosine Binding Cavities

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The Epock cavity detector plugin,30 implemented in the Visual Molecular Dynamics

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(VMD) program,31 was used to analyze the binding pockets of all four enzymes. The Epock

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program calculates the volume of a targeted binding pocket, visually represented as spheres, based

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on residues in the binding pocket (Table 2, Supporting Information, Tables S4-S5). The analysis

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was performed on enzyme structures that included ATP and had been energy minimized. The

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eight key binding pocket residues (Table 1) were specified for each isoenzyme so that the software

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correctly targeted the active site. The configuration options were specified as follows: contiguous

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opt. false, profile opt. true, and contrib opt. true. The box size and parameters were optimized for

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each enzyme such that the spheres that represent the calculated pocket volume were inclusive of

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only the pocket of interest, and spheres outside of the binding pocket were not included in the

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volume calculation. hSphK1 had a box size of 20 Å x 15 Å x 15 Å, hSphK2 had a box size of 20

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Å x 20 Å x 28 Å, mSphK1 had a box size of 24 Å x 20 Å x 14 Å, and mSphK2 had a box size of

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16 Å x 20 Å x 20 Å.

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Molecular Docking of Isoform Selective and Dual Inhibitor Compounds

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AutoDock Tools version 1.5.6

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was used to edit the structure files to include partial

charges and atom types (PDBQT files) for the receptors and ligands. AutoDock Vina33 software

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was used to dock ligands into the enzymes. Configuration files containing parameters necessary

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for docking were generated based on the docking grid box for the structures, which was centered

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on the binding site based on the location and proximity of the eight key residues (Table 1). Key

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binding pocket residues were based on previous mutagenesis studies of Asp81,34 crystallographic

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studies,20 and our prior docking studies.5 Structures were overlaid and the same configuration file

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was used for all four isoforms to maintain consistency in grid box position and size. The grid box

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encompassed the active site and key residues and was centered on the coordinates (50.0, 61.5, 6.8)

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and was sized 24 Å x 24 Å x 28 Å with 1.000 Å grid spacing. Using the same box size and position

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for all four enzymes allowed for consistency in the docking procedure as well as in overlaying the

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structures for docked poses in the sphingosine binding cavity. Each docking experiment resulted

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in up to nine poses (Supporting Information, Figures S14-S28, Tables S6-S13). The lowest energy

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pose with the polar and/or charged headgroup of the ligand facing the ATP binding cavity and

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Asp81/Asp178 was chosen for further analysis such as distance measurements and ligand

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positioning. This criterion was employed given that experimental results indicate the charged head

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group of the ligand should interact with the Asp81/Asp178 residues near the ATP binding cavity

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while the lipophilic tail of ligands should interact with the hydrophobic residues at the tail of the

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binding cavity (Figure 1B).34 To develop the assessment and docking protocol, we first probed and

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refined these methods using the guanidine-based, oxadiazole- containing inhibitors set. This

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refined or training criteria and we further added in other ligands in this study, which include

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experientially characterized inhibitors outside of the original training compound class.

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Sphingosine was redocked into hSphK1 and compared to the sphingosine position in the

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crystal structure 3VZB20 as a metric for validation of our docking protocol. A root-mean-square

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deviation (RMSD) value of 1.215 Å was calculated comparing the docked versus crystal structure

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position of sphingosine. We also utilized an inhibitor in this work, PF-543, that is co-crystallized

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with hSphK1 (PDB ID: 4V2419). A calculated RMSD of 2.694 Å was determined comparing the

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docked pose of PF-543 in hSphK1 with the co-crystal position. For both sphingosine and PF-543

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redocking, comparable distance measurements from key residues to sphingosine were observed in

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both docked and crystal structure ligand binding poses, as well as similar spatial occupancy in the

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binding cavity, validating the docking methodology (Supporting Information, Figure S14, S21).

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The Schrödinger Maestro28 Interaction Fingerprints tool was used to analyze and determine

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potential interactions between protein residues and docked ligands. Four individual residue-ligand

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interaction matrices were produced based on each of the four SphKs used in the study via the

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docked poses method (Supporting Information, Figures S10-S13). Distance measurements

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between residues and ligands fell into three different categories depending on the heavy atoms

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involved and distance: electrostatic interactions were 3.0 – 5.0 Å, hydrophobic interactions were

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3.0 – 5.0 Å, and hydrogen bonding was 2.8 – 4.0 Å. The docked poses were overlaid in PyMOL35

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molecular visualization software to assess differences in ligand positioning in the isoenzymes.

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Interactions between specific key residues and the ligands were ranked using strength of the

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interaction based on distance between heavy atoms and polarity. A shorter distance measurement

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between ligand and amino acid residue constituted a better ligand fit and better predicted inhibition

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capabilities. This knowledge-based ranking system allowed us to define isoform and orthologue

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selectivity based on distance measurements. Script files and input files are found on our public

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Open Science Framework page (https://osf.io/82n73/).

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Results and Discussion

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In silico methods for characterizing and categorizing structural properties of receptors and

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ligands is advantageous for determining essential atomistic features that contribute to biological

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activity.36 The inclusion of orthologue assessment and comparison in in vitro, in vivo, and in silico

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experiments is often overlooked, but recent observations show benefit to including orthologues in

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terms of novel target coverage37 and rationale for the difference in inhibitor selectivity.17, 38 Part

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of the challenge is that comparable data sets from mice and humans may not be available, and

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results from in vitro assays are sometimes at odds with in vivo studies in mice. This challenge is

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observed in SphKs, where inhibitors that are selective for hSphK2 decreased S1P production in in

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vitro assays but resulted in an increase in circulating S1P levels when administered to mice.14 A

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major hurdle in understanding the several roles of the enzymes is the interspecies difference, which

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plays an often-overlooked role in the beginning stages of drug discovery. SphK1 has four crystal

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structures currently available of the human orthologue, all deposited in the PDB in the last five

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years.18-20 The SphK2 structure has remained unresolved, mostly due to the predicted disordered

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loop region present in this isoform compared to SphK1. However, similarities in binding cavity

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sequence and catalytic reaction support homology modeling and in silico discovery as an alternate

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way to explore the potential influence of both isoform and orthologue selectivity on inhibitor

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activity. This work systematically characterizes the binding pocket of human and mouse SphKs

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using validated homology models as a starting point to better understand small, but influential,

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differences in the Sph binding pocket between isoforms and orthologues. Results from this work

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emphasize the need to explore multiple binding pocket analyses to rationalize inhibitor binding

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affinity and selectivity as well as provide directed guidelines towards next-step inhibitor design.

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Additionally, the difference in results between in vitro and in vivo assays for orthologues of each

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SphK isoform14 is unexpected but provides a pathway to rationalize current experimental results

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on inhibitor efficacy.39 Specifically, our investigation aimed to (1) interrogate how variation in key

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residues in the Sph binding cavities among isoforms and across orthologues affects the binding

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site shape, volume, and lipophilicity, and (2) identify intermolecular interactions that can be

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exploited to improve inhibitors as based on known experimental inhibitor selectivity and molecular

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docking results.

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Sequence Alignment, Homology Modeling, and Structural Comparisons Between Isoforms and Orthologues To generate homology models and rationalize utilization of hSphK1

as a template

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structure, a sequence alignment was performed using Schrödinger Maestro28 Multiple Sequence

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Viewer (Figure 1B, Supporting Information, Figures S1-S3). For clarity in naming residues in this

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work, see the residue numbers that were assigned according to our adjusted numbering system as

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described in Methods (Table 1). Based on percent identities of our alignment on the full sequence

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of the SphKs, the orthologous isoforms are more identical (83% for hSphK1 and mSphK1; 83%

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for hSphK2 and mSphK2) than the paralogous isoforms within species (39% for hSphK1 and

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hSphK2; 38% for mSphK1 and mSphK2) (Supporting Information, Figure S1). The relatively low

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sequence identity between paralogues is attributed to the additional 115 residues in SphK2

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compared to SphK1, which is confirmed by a pairwise sequence alignment between all SphKs

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with the proximal loop region (residues 216-349 in SphK2) removed (Supporting Information,

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Figures S2-S3, Tables S2-S3). Pairwise sequence alignments to the template HSphK1 sequence

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show 53% and 52% identity (hSphK2 and mSphK2, respectively) and 70% similarity when the

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additional SphK2-specific loop region is removed. Additionally, a high level of sequence identity

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between paralogues is observed in residues flanking the gap region inserted in our full sequence

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alignment (Supporting Information, Figure S1). All residues assessed experimentally through

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crystallography or mutagenesis that are considered necessary in substrate (Asp81, Asp178,

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Ser168)20,40 or ATP binding (Glu86, Arg185, Arg191)20 are conserved in our alignment (Figure

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1B, Supporting Information, Figures S1-S3).

312

In order to examine the binding cavity across both human and mouse variants of the two

313

sphingosine kinase isoforms, homology models of hSphK2, mSphK1, and mSphK2 were

314

generated based on the crystal structures of the hSphK1 SK1a variant (PDB ID: 3VZB, 3VZC, and

315

3VZD).20 For both hSphK1 and mSphK1, there are three splice variants, denoted SK1a, SK1b, and

316

SK1c,41 with primary differences in these splices being the length of the N-terminal sequence. This

317

hSphK1 structure template used was crystallized independently with either Sph (PDB ID:3VZB),

318

the known inhibitor 4-{[4-(4-chlorophenyl)thiazol-2-yl]amino}phenol (SKI–II, also known as

319

SKi) (PDB ID: 3VZB), and SKI-II with ADP (PDB ID: 3VZD). 20 The crystal structure of hSphK1

320

revealed a large, J-shaped pocket that positioned the conserved catalytic aspartate residue (Asp81)

321

near the ADP/ATP binding site (Figure 1A) and was the basis for our orientation of the Sph binding

322

pocket and structural assessment of isoforms and orthologues.34,40 Another key residue, Asp178,

323

further connects human and mouse experimental data, with site-directed mutagenesis of Asp178

324

in mSphK1 (D178N) showing minimal disruption to the ATP binding but significantly decreasing

325

kinase activity and increasing Km for Sph.42

326

The homology models were assessed for quality using SWISS-MODEL,23, 24 ProSA,25 and

327

Verify 3D,26,

27

328

environment, respectively. These analyses showed that the models had favorable structural

329

parameters (Supporting Information, Figures S4-S6). Moreover, the analysis metrics related to

330

structural features in the Sph binding pocket region all noted that side chain conformation and

331

positions were energetically favorable and in positions that were consistent with the

332

physicochemical properties of the surrounding environment. Collectively, these metrics for

which show the energy state, z-score and model quality, and 3D structure

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Journal of Chemical Information and Modeling

333

homology model generation and assessment confirm the utilization of the hSphK1 sequence and

334

structure as a template for homology models and reveal similar structural and sequence

335

conservation among isoforms and orthologues.

336

The sequence alignments and structural overlays revealed high similarity in the Sph

337

binding cavities across isoforms and orthologues while revealing a few key differences that can be

338

exploited for inhibitor development. The most notable differences in the Sph binding pocket

339

between isoforms and orthologues include Ile/Val/Leu174 and Phe/Leu419 in the hydrophobic

340

channel portion of the binding pocket, and Phe/Cys404 in the tail region of the Sph binding cavity

341

(Figure 1B). The differences in size and shape of these residues, with Val/Leu174 residue and the

342

Phe/Leu419 residue at the bottom of the Sph cavity, influenced the positioning of the Asp residues

343

at the head of the pocket (Figure 2). These residue position shifts are predicted to impart subtle

344

alterations in ligand binding in this Sph cavity, giving rise to exploitable features in inhibitor

345

design. Structural overlays of isoforms and orthologues showed that hSphK2 and mSphK1 were

346

more similar in residue positioning and type than hSphK2 and mSphK2 (Figure 2), providing a

347

rationale for the lack of congruence in activity between SphK2-selective inhibitors between human

348

and mouse.

349

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350 351 352 353 354 355 356 357 358

Figure 2. Overlay of human and mouse SphK structures reveal key differences to exploit in isoform and orthologue specific inhibitor design. Kinases are shown as cartoon and colored per orthologue, with key residues shown as sticks and colored by element. ATP is shown as sticks, colored wheat by element, for orientation. (A) Overlay of hSphK1 (grey) and mSphK1 (teal) Sph binding cavities. (B) Overlay of hSphK2 and mSphK2 Sph binding cavities. (C) Overlay of hSphK2 and mSphK1 Sph binding cavities. Purple stars represent differences in residues in the binding cavity predicted to strongly influence ligand binding.

359

The other residue variations at the tail of the binding cavity, Phe/Cys404 and Tyr/His437,

360

are not predicted to directly influence the shape of the binding cavity. These residues are distantly

361

positioned from the polar head region. As later discussed in the molecular docking results,

362

interactions between the tail of the ligand and those residues do not greatly affect overall ligand

363

binding, although Phe/Cys404 may aid in increasing isoform selectivity after inhibitor design is

364

tailored to the other features of the cavities. We confirm and validate our homology model

365

approach in that the Asp residues that interact with the polar head group of Sph remain necessary

366

for binding and stabilizing Sph and inhibitors in all isoforms and orthologues. The Val/Ile/Leu174

367

and Phe/Leu419 residue differences have the greatest effect on ligand/inhibitor binding given their

368

location in the hydrophobic core and their effect on positioning of the Asp residues.

369

Volumetric Analysis of Binding Cavities

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370

Volumetric analysis was performed for all hSphK1 crystal structures as well as the

371

homology models generated in this work (Tables 2, 3). All solved structures of hSphK1 were

372

included as a quality assessment metric to ensure that similar volumes were found among the

373

different hSphK1 structures while accounting for the presence of ligands or ADP (Table 2). The

374

pocket volumes varied by approximately 23% among these structures, with the volume being

375

related, in general, to the ligand volume, as will be discussed in more detail below.

376 377 378

Table 2. hSphK1 sphingosine binding cavity and ligand volume measurements based on solved structures. Five different crystallized structures of hSphK1 were analyzed using Epock software. For ligand volume calculations, each ligand was extracted from the PDB file and the volume was calculated with Chimera43.

Structure

Description

3VZB20

hSphK1 with sphingosine

3VZC20 3VZD20 4V2419 4L0218

Box Size

hSphK1 with inhibitor (SKIII) hSphK1 with inhibitor (SKIII) and ADP hSphK1 with inhibitor (PF543) hSphK1 with inhibitor (1V2)

Pocket Volume (Å3)

Sph/Inhibitor Volume (Å3)

545

317

452

239

433

239

511

418

500

399

16 x 16 x 20 16 x 16 x 20 16 x 16 x 20 16 x 16 x 20 16 x 16 x 20

379 380 381

Table 3. Binding cavity volume measurements of apo, energy minimized hSphK1 crystal structure and homology models.

Volume (Å3) 538 606 443 412

Structure hSphK1a mSphK1 hSphK2 mSphK2 382 383 384 385

a.The

structure of hSphK1 (PDB ID: 3VZB) was energy minimized prior to molecular docking. Energy minimization only slightly decreased the binding pocket volume (7 Å3) compared to the non-energy minimized structure (Table 2).

386

In comparing the binding cavity volumes for the isoforms and orthologues, the mSphK1

387

binding cavity (606 Å3) was the largest cavity, and the shape of the pocket showed space for

388

ligands in both the hydrophobic core and the head regions of the binding cavity. The energy 17 ACS Paragon Plus Environment

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389

minimized structure of hSphK1 had a binding cavity volume of 538 Å3, which was larger than that

390

of hSphK2 (443 Å). The observed difference in volume pocket between hSphK1 and hSphK2,

391

even though the model of hSphK2 is based on hSphK1, emphasizes the influence of the Ile/Val174

392

residue difference and provides rationale to design SphK1 selectivity by designing a larger ligand

393

that would be excluded from the hSphK2 binding cavity. mSphK2 had a notably smaller binding

394

cavity (412 Å3) than the other SphKs, as Leu residues in the hydrophobic core reduce the volume

395

(Figure 3).

396

397 398 399 400 401 402 403 404 405

Figure 3. Sph binding cavity volume and shape analysis. (A) hSphK1 Sph cavity rendered in light pink cartoon representation with spheres showing ligand-accessible areas of the pocket. (B) hSphK2 rendered as in (a) in purple. (C) mSphK1 pocket rendered in light teal with spheres showing ligand-accessible volume. (D) mSphK2 rendered as in (c) in dark blue. The key residues are shown as sticks and labeled. ATP is shown in sticks for reference in all panels. metaPocket2.0 binding cavity volume measurements were utilized for the shape analysis. The online server predicted the ligand binding site and ATP binding site for each enzyme tested; only the ligand binding sites are shown here. The volume and shape were then analyzed and shown in sphere representation using PyMOL.

406

The influence of Val/Ile/Leu174 was apparent from examination of the shapes of the

407

hydrophobic core (Figure 3). With hSphK1 and mSphK2, the presence of Ile/Leu174 caused an 18 ACS Paragon Plus Environment

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408

invagination (Figure 3A,D) that was not observed in hSphK2 and mSphK1 (Figure 3B,C), which

409

have a considerably smaller residue, valine, at this position. Additionally, Phe/Leu419 contributes

410

to the shape of the hydrophobic core of the SphK cavity, highlighted by the influence of Leu419

411

on the mSphK2 binding cavity shape (Figure 3D). While the volume of the hSphK2 and mSphK1

412

were not as similar, the shape, notably in the hydrophobic core, was more similar between these

413

kinases than the other kinases. Based on the dissimilarity in shape and size of the mSphK2 Sph

414

cavity as compared to the other isoforms, mSphK2 selective inhibitors should be smaller in size,

415

especially for the chemical moieties that occupy the hydrophobic core region.

416

To further support our hypothesis and protocol, ligand volume calculations were

417

performed. Ligand structures were extracted from the PDB files and their volumes were measured

418

using the surface analysis tool in UCSF Chimera43 (Supporting Information, Tables S4, S5). As

419

expected, all the ligand volumes were smaller than their respective crystal structure Sph binding

420

cavity (Table 2). Volumes of sphingosine and the inhibitors that were considered in this study were

421

also calculated to establish a connection between ligand size and isoform or orthologue selectivity

422

(Supporting Information, Table S5). The volume of sphingosine was among the smallest of these

423

compounds, which is consistent with it being the endogenous substrate that must be accommodated

424

by all of these kinases. Confirming our structure pocket volume results and conclusions, the largest

425

of the inhibitors, PF-543, is SphK1 selective and correlates with the larger binding cavities in

426

SphK1s relative to SphK2s. The SphK2 selective inhibitors were among the smallest of the

427

inhibitors, consistent with the smaller binding cavities in SphK2s relative to SphK1s. The dual

428

inhibitors were, in general, intermediate in size between the SphK1 and the SphK2 selective

429

inhibitors (Supporting Information, Table S5). The one exception to these general observations is

430

inhibitor SLC5091592, which is a SphK2 selective inhibitor but of a size similar to the dual

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431

inhibitors. In terms of utilization of these results, inhibitor design for hSphK1 should focus on

432

larger ligands that occupy more of the head region of the Sph cavity and approach or exceed the

433

calculated volume of the SphK2 cavity (443 Å3). These results suggest general principles regarding

434

volume that may be applied in designing inhibitors for SphKs.

435

Pharmacophore Models Highlight Isoform and Orthologue Selective Features

436

While designing more potent and selective inhibitors based on volume and shape of the

437

Sph binding cavity can be promising, combining such information with chemical characteristics

438

can further facilitate de novo design of inhibitors. Pharmacophore modeling has shown powerful

439

potential in determining new leads and hits in other studies,44 giving rise to its use in this work to

440

highlight chemical differences between isoforms and orthologues as well as determining essential

441

ligand properties known to elicit isoform selectivity. Pharmacophore models were created using

442

receptor-based methods, in which we combined knowledge of spatial distribution,

443

physicochemical characteristics, and size of residues in the Sph binding cavity. These

444

pharmacophore models were examined in light of the efficacy and selectivity of known

445

experimental inhibitors (Supporting Information, Table S1).

446

Receptor-based pharmacophore models were generated using the Schrödinger Maestro

447

suite28 with the receptor-only complex method. The receptor-only method was based on the

448

position of the key residues in the binding pocket of each kinase (Table 1). Each pharmacophore

449

model displayed a general “J” shape of the sphingosine binding cavity (Supporting Information,

450

Figures S6-S7), as was reported for the hSphK1 structure. Although the general J-shape of the

451

pharmacophores was similar across isoforms and orthologues, the number and placement of

452

hydrophobic and aromatic features varied across the receptor-based pharmacophores giving

453

further insight into the role of amino acid differences in the binding cavity and exploitable features

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454

for isoform and orthologue selectivity (Supporting Information, Figures S8-S9). In the head group

455

region of the pocket, hSphK2, mSphK1, and mSphK2 have two aromatic features compared to one

456

in hSphK1 (Supporting Information, Figures S8-S9). All four receptor-based pharmacophore

457

models had hydrophobic and aromatic groups near the tail of the binding cavity, with the order

458

and positioning of hydrophobic and aromatic moieties in the hydrophobic core varying among the

459

kinases, such as the difference in Ile/Leu174 in hSphK1 and mSphK2 (Supporting Information,

460

Figure S8). Typically, inhibitors that have been studied have a large aromatic substituent (phenyl

461

or naphthyl ring) in this portion of the ligand, with an additional methylene moiety between polar

462

and hydrophobic regions of the inhibitor that can “switch” selectivity (e.g. compound

463

SLP7111228) to be more hSphK1 selective relative to hSphK2.39 Further adding to the role of

464

residue 174 in selectivity, an internal phenyl ring with no additional methylene moiety was found

465

to be essential in hSphK2 selectivity.17 Given the lack of a hydrophobic characteristic in mSphK2

466

in the core of the sphingosine binding cavity, it is unsurprising that no inhibitors have currently

467

been generated that selectively target this orthologue based on our receptor-based pharmacophore

468

model for mSphK2. Comparisons of receptor-based pharmacophore models suggest that the

469

chemical characteristics of mSphK1 and hSphK2 are more similar than is evident from structural

470

overlays of the binding cavities (Figures 2-3, Supporting Information, Figures S8-9).

471

Another notable difference between the receptor-based pharmacophores focused on the

472

presence and positioning of hydrogen bond donors. hSphK1 and mSphK2 had an additional

473

hydrogen bond donor feature in the head group region as compared to hSphK2 and mSphK1. The

474

position of the second hydrogen bond donor in the mSphK2 pharmacophore model suggests that

475

mSphK2 inhibitors have a shorter hydrophobic region connecting head and tail group of inhibitors

476

in addition to having a second hydrogen bond acceptor as a substituent on an aromatic feature. A

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477

compound having a ligand headgroup that is more aromatic with one hydrogen bond donor feature

478

may confer hSphK2 and mSphK1 selectively.

479

Partnering chemical features as determined from the pharmacophore models rationalizes

480

the potency and selectivity of some of the best inhibitors to date and provides insights into inhibitor

481

features that are necessary for selectivity. Dual inhibitor design can also be informed from these

482

shapes, with mSphK1 and hSphK2 features revealing themselves as more similar than previously

483

expected, aiding future design.17 Given the differences between hSphK2 and mSphK2 in terms of

484

shape and positioning of chemical features, the few similar features such as size and chemical

485

features of the tail region will need to be exploited in future design for inhibitors to be selective

486

for both.

487

Molecular Docking of Dual and Isoform Selective Inhibitors

488

To further our analysis of the structural and pharmacophore models of the kinases,

489

molecular docking of known inhibitors to each isoform of SphK was used to (1) confirm the role

490

of the eight key residues and explore additional residues to add into protocol assessment as well

491

as (2) determine protocol for ranking compounds in future screening efforts and rational drug

492

design. The inhibitors used in this work are known to be competitive with Sph.45 For docking

493

studies, ATP and Mg2+ were included in the protocol and positioned based on the solved structure.

494

The docking protocol was validated by re-docking sphingosine and PF-453 into hSphK1 and

495

comparing docked poses to co-crystal substrate and inhibitor structures. Comparison of ligand

496

position for re-docked and co-crystal structure gave a RMSD of 1.215 Å and 2.694 Å for

497

sphingosine and PF-453, respectively, thereby demonstrating an ability of the chosen software,

498

parameters, and protocol to reproduce ligand and inhibitor position in the Sph binding cavity.

499

Calculated free energy scores and ligand orientation in the binding cavity (hydrophilic/polar end

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Journal of Chemical Information and Modeling

500

near the head of the sphingosine binding cavity and hydrophobic end interacting with the tail of

501

the binding cavity – Figure 1A) were used to select the best docked pose of each ligand (Supporting

502

Information, Tables S6-S13). These poses were then analyzed to identify factors that account for

503

the selectivity observed and to combine both computational and wet-lab data into workable

504

protocols for future experiment design. Docking free energies of binding as a ranking protocol to

505

determine inhibitor selectivity were less useful in our analysis given that the volume of the binding

506

cavities varied greatly across isoform and orthologue (38% different), influencing the sampling of

507

bond angles of inhibitor poses and allowing greater conformational freedom for SphK1 poses

508

(Figure 3, Table 3). As a result, SphK1 docking energies were consistently more negative than

509

SphK2 docking energies in the docking of all ligands regardless of experimentally known inhibitor

510

isoform selectivity.

511

Our analysis for predicting selectivity then focused on docked poses and number of key

512

residue interactions as demonstrated through fingerprinting analysis as well as measurement of

513

distances between atoms in the ligands and atoms in key residues to determine potential interaction

514

strength. Electrostatic and hydrogen bond interaction strength fall off gradually with distance and

515

atom type (1/r – charge-charge, 1/r2 - charge-dipole, 1/ r3 – dipole-dipole ) and represent a metric

516

to assess strength of interaction based on different binding poses as influenced by orthologue and

517

isoform differences in the Sph binding cavity. We rationalized the selectivity of each of the

518

inhibitors based on these interactions, as well as the orientation of the ligands in the binding

519

cavities, primarily in comparing hSphK2 and mSphK1 with regard docking results and known,

520

wet-lab experimental data.

521

Ligand fingerprinting analysis was used to examine the interactions between the ligands

522

and amino acid residues in or near the binding cavity (Supporting Information, Figures S10-S13).

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523

The eight key residues were frequently involved in interactions, though not with all ligands and in

524

all isoforms and orthologues. For example, Asp178 was found to interact with all ligands in all

525

isoforms and orthologues except for inhibitor K145 in mSphK1. Asp81, which has been previously

526

denoted as an essential residue in catalytic activity of these kinases, also did not interact with all

527

inhibitors in all isoforms and orthologues, though it should be pointed out that an effective inhibitor

528

need not interact with a catalytic residue. These results will be discussed in more detail (vide infra)

529

based on the interactions of each of the ligands with the human isoforms, for which the

530

experimental inhibition data are available (Supporting Information, Table S1). From this analysis,

531

we confirmed our eight key residues were observed in Sph and inhibitor binding and would be

532

able to discern results of selectivity based on presence of interaction and strength of interaction. In

533

addition, we identified new residues to include in refinement of these metrics in the future (e.g.

534

residues Phe173, Phe192, and Met422 – Supporting Information, Figure S10-S13).

535

Amgen 82 and SLC5111312 are dual inhibitors of the human isoforms.4, 14 Amgen 82

536

docking results demonstrated equal numbers of interactions with each of the isoforms and

537

orthologues (Supporting Information, Figures S15-S16). Amgen 82 had closer interactions with

538

Asp81 and Asp178 in hSphK1 but closer interactions with residues Ser 168 and His 427 in

539

hSphK2. The number and proximity of the interactions in both isoforms of each species likely

540

account for it acting as a dual inhibitor (Supporting Information, Table S6). SLC5111312 also

541

showed many favorable interactions in both the SphK1 and SphK2 binding cavities. The distances

542

between the ligand and Val174 at the top of the cavity and Phe419 at the bottom of the cavity are

543

very similar (3.7 Å and 3.7 Å respectively for hSphK2, and 3.3 Å and 3.6 Å, respectively, for

544

mSphK1 – Figure 4). For both docked poses, Asp178 at the head of the cavity has two polar

545

interactions with the –OH and nitrogen of the oxadiazole ring with comparable distance

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Journal of Chemical Information and Modeling

546

measurements (2.8 Å and 3.4 Å for hSphK2, and 3.1 Å and 3.2 Å for mSphK1). In this case, it

547

was particularly notable that a close interaction was observed in both isoforms with Asp178,

548

although with different atoms of the inhibitor. Additionally, the overall position of both of these

549

dual inhibitors in the Sph binding cavity was consistent between isoforms and orthologues

550

(Supporting Information, Figure S15, S22). Utilizing our identified key residues and docking

551

protocol, we can rationalize these inhibitors as being dual specific, despite having slightly different

552

binding

poses

in

the

Sph

pocket.

553 554 555 556 557 558 559 560 561 562 563

Figure 4. SLC5111312, dual inhibitor, docked in mSphK1 and hSphK2 shows comparable ligand positioning. Compound SLC5111312 docked into (A) mSphK1 and (B) hSphK2. Structures are rendered in cartoon with the protein colored based on orthologue as grey (human) or dark teal (mouse), with key residues shown as sticks, colored by atom, and labeled. SLC5111312 and ATP are shown as sticks and colored by green or wheat atom type, respectively. Mg2+ is omitted for clarity of image but was present in the docking. Distances shown are in Å. The positioning of the naphthyl rings is identical between the poses and distance measurements between Val174 and Phe419 are within 0.1 Å, highlighting the role of this residue region in inhibitor selectivity.

564

Four hSphK2-selective inhibitors were investigated in this study, including (R)-FTY720-

565

OMe (Ki of 16.5 µM46), K145 (Ki of 6.4 µM47), SLC5081308 (Ki of 0.98 µM17), and SLC5091592

566

(Ki of 1.02 µM17). SLC5091592 and SLC5081308 have the lowest Ki values towards hSphK2;

567

however, when comparing to inhibition of hSphK1, SLC5091592 is the best hSphK2-selective

568

inhibitor of the four tested, with SLC5091592 being 20-fold selective for hSphK2 and

569

SLC5081308 being 7-fold selective for hSphK2 (Supporting Information, Table S1). This

570

selectively towards hSphK2 for SLC5091592 was also observed in our docking results. Compound 25 ACS Paragon Plus Environment

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571

SLC5091592 docked more favorably into hSphK2 than hSphK1 based on Asp-ligand distance

572

measurements and tail region hydrophobic residue-ligand distance measurements (Figure 5),

573

which is consistent with the higher experimental selectivity for hSphK2. Similar criteria were used

574

to predict the selectivity of the compound in mice. Interestingly, the docked pose of SLC5091592

575

fit better into mSphK1 than mSphK2 based on head group interactions with the Asp residues (two

576

interactions at 3.7 and 3.3 Å for mSphK1 versus one 3.8 Å interaction in mSphK2). Figure 5

577

illustrates the similar binding mode of SLC5091592 within hSphK2 and mSphK1 based on the

578

distances between the ligand and key residues as well as ligand positioning. The docking results

579

for SLC5081308, which had the lowest experimental Ki value for hSphK2, had closer interactions

580

with Asp81 in hSphK2 than hSphK1, which may account for the selectivity, though the number of

581

total interactions between the two was similar. However, as noted above, SLC5081308 was

582

observed experimentally to be more weakly SphK2 selective compared to SLC5091592.

583

584 585 586 587 588 589 590 591 592 593

Figure 5. SLC5091592, an hSphK2 selective inhibitor, docked in mSphK1 and hSphK2. Compound SLC5091592 docked into (A) mSphK1 and (b) hSphK2. Structures are rendered in cartoon with the protein colored based on orthologue as grey (human) or dark teal (mouse), with key residues shown as sticks, colored by atom, and labeled. SLC5091592 and ATP are shown as sticks and colored by magenta or wheat atom type, respectively. Mg2+ is omitted for clarity of image but was present in the docking. Distances shown are in Å. The measurements to key residues are similar to SLC5091592 docked into mSphK1 in both the head and tail regions of the ligand. This similarity in binding to mSphK1 and hSphK2 is significant in that SLC5091592 is hSphK2 selective.

594

Considering the other hSphK2-selective inhibitors in this study, K145 is positioned

595

similarly in mSphK1 and hSphK2, with the polar region of the ligand sitting farther away from the 26 ACS Paragon Plus Environment

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596

Asp81 and Asp178 residues than in hSphK1. K145 in hSphK1 shows closer/stronger interactions

597

with the head group residues and the tail region residues, but there are more interactions with key

598

residues in hSphK2, leading to the affirmation of the SphK2 selectivity based on our ranking

599

system (Supporting Information, Figures S19-S20).

600

(R)-FTY720-OMe is the second smallest inhibitor in this test set, aligning with potential

601

mSphK2 selectivity coupled with volumetric analysis above, where mSphK2 is observed to have

602

the smallest Sph binding cavity. When comparing between hSphK1 and hSphK2, the selectivity

603

of (R)-FTY720-OMe was less discernable given a similar number of interactions between the

604

inhibitor and both human isoforms; however, our docking studies showed closer, stronger

605

interactions with Ser168 in hSphK2 than in hSphK1 (2.8 Å versus 3.5 Å, respectively).

606

Interestingly, the spatial positioning of (R)-FTY720-OMe within mSphK1 and hSphK2 is

607

extremely similar, while distinct from the docked poses in mSphK2 and hSphK1. This positioning

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similarity of (R)-FTY720-OMe further supports the hypothesis that mSphK1 and hSphK2 bind

609

ligands similarly (Supporting Information, Figure S17-S18).

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612 613 614 615 616 617 618 619

Figure 6. PF-543 shows hSphK1 selectivity, confirming docking analysis and key feature criteria for isoform selectivity. PF-543 lowest energy pose docked into (A) hSphK1, (B) hSphK2, (C) mSphK1, and (D) mSphK2. Structures are rendered in cartoon with the protein colored based on orthologue as grey (human) or dark teal (mouse), with key residues shown as sticks, colored by atom, and labeled. PF-543 and ATP are shown as sticks and colored by purple or wheat atom type, respectively. Mg2+ is omitted for clarity of image but was present in the docking. Distances are in Å.

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Two hSphK1-selective inhibitors were studied to further confirm key residues, docking

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protocol, and ability to assess inhibitor selectivity. PF-543 is hSphK1 selective (100-fold) with a

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Ki of 4.3 nM in hSphK1,19 and SLP7111228 is hSphK1 selective inhibitor with a Ki of 48 nM.39

623

Docking results of PF-543 showed selectivity for hSphK1 when compared to mSphK1 based on

624

our ranking of important interactions and distance measurements (Figure 6). The poses of PF-543

625

in hSphK2 and mSphK2 do not support selectivity for SphK2s. There are more, closer interactions

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between PF-543 with key residues in hSphK1 than hSphK2 (Supporting Information, Table S14),

627

supporting our argument of SphK1 selectivity. The position and distance measurements are very

628

similar between the docked poses of PF-543 in mSphK1 and hSphK2; however, only minor

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differences in distances between the ligand and residues (up to 0.9 Å) are observed. PF-543 is also

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inhibitor in selectivity and presenting PF-543 as a model ligand for hSphK1-only selectivity. The

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docked poses of PF-543 also support our hypothesis that hSphK2 and mSphK1 bind ligands in a

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similar fashion based on residue similarity in the Sph binding site. SLP7111228 showed

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discernable differences in distance measurements between the head and tail interactions between

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hSphK1 and hSphK2 isoforms, leading towards SphK1 selectivity with closer, stronger

636

electrostatic interaction distances to the inhibitor (Figure 7, Supporting Information, Table S14).

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Differences in planarity of the aromatic moieties were also observed in hSphK1, with the

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oxadiazole ring and phenyl rings having different tilt angles when compared to the position of the

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ligand in each of the other kinases (Supporting Information, Figure S26). Overall, using structural

640

analysis and docking results presented above, it was observed that the head region in SphK1 allows

641

for more room to flip or rotate the guanidine or oxadiazole ring as based on all docked poses and

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pocket volume analysis (Figure 3), so the Asp residues bind to different areas of the ligand.

643

Positioning of the hydrogen bond donor group in the structure-based pharmacophore models

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confirms the importance of the position of this feature for isoform selectivity, leading us to

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conclude that these aromatic features and their position and rotatability in the binding cavity can

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provide another level of distinction in identifying potent and selective inhibitors.

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648 649 650 651 652 653 654 655 656

Figure 7. SLP7111228 docked into SphK1 and SphK2 demonstrate importance of planarity of hydrophobic core binding ligand features. SLP7111228 lowest energy pose docked into (A) hSphK1, (B) hSphK2, (C) mSphK1, and (D) mSphK2. Structures are rendered in cartoon with the protein colored based on orthologue as grey (human) or dark teal (mouse), with key residues shown as sticks, colored by atom, and labeled. SLP7111228 and ATP are shown as sticks and colored by cyan or wheat atom type, respectively. Mg2+ is omitted for clarity of image but was present in the docking. Distances shown are in Å.

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As noted above, we observed structural similarities between mSphK1 and hSphK2 and

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similar docking results, notably with SLC5091592. To further support our hypothesis that mSphK1

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is more similar to hSphK2 than hSphK1, we altered in silico a key residue in mSphK1 to make it

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more closely mimic hSphK1. In particular, a Val 174 to Ile 174 “mutation” was made to mSphK1,

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and SLC5091592 was then docked into the altered mSphK1 (Supporting Information, Figure S24).

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This single amino acid change resulted in less favorable binding of SLC5091592 in this mSphK1

663

mutant, in that the interactions between the head and tail regions included longer distances, and

664

the general positioning of the naphthyl moiety was altered (Supporting Information, Figure S24).

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This outcome further validated the hypothesis that mSphK1 docks ligands similarly to hSphK2, as

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well as emphasized the role that residue 174 plays in inhibitor design for SphKs.

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Figure 8. Summary of structural and inhibitor features and their predicted influence on isoform and orthologue selectivity. The likelihood is based on comparing binding cavity volume analysis, ligand size analysis, pharmacophore models, and molecular docking results between each SpK. This figure is designed to visually represent and summarize the data presented above as well as to identify factors to consider for designing isoform and orthologue selective inhibitors for SphKs.

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Figures. S14-S28) supported our protocol and confirmed the role of the eight key residues that

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showed frequent and selective interactions across isoforms and orthologues. It is discerned from

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this work that inhibitor design for SphKs should account for the similarity in mSphK1 and hSphK2

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binding cavities and work towards designing inhibitors that are both isoform and orthologue

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specific (Figure 8). Coupled with pocket volume and pharmacophore analysis, the utilization of

681

this docking protocol will allow us to rationally identify new chemical moieties to enhance efficacy

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and selectivity of known inhibitors as well as design new classes of inhibitors. This procedure can

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also be utilized in other drug discovery experiments involving comparisons between both isoforms

Collectively, docking analysis of inhibitors and sphingosine (Supporting Information

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and orthologues, highlighting the need to couple receptor and ligand-based characteristics to best

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inform drug design.

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SUPPORTING INFORMATION

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Supporting information contains twelve tables of 2D inhibitor structures, receptor and ligand volume calculations, molecular docking free energies, and distance between heavy atoms of key residues and docked inhibitors. Also provided are 26 figures with homology validation results, structural overlays, pharmacophore models, fingerprinting analysis, and docked poses.

698 699 700 701 702 703 704 705 706 707 708 709

The authors would like to thank Dr. Stephanie N. Lewis and Amanda K. Sharp for careful critique of the manuscript. The authors also thank Jonathan S. Briganti for data visualization consultation.

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DATA AVAILABILITY

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[1] (2017) Cancer Facts and Figures 2017, American Cancer Society, Atlanta, Georgia. [2] (2016) Cancer Facts & Figures 2016, (Society, A. C., Ed.), American Cancer Society, Atlanta. [3] (2017) Targeted Cancer Therapies, National Cancer Institute.

CORRESPONDING AUTHOR David R. Bevan – 201 Engel Hall (0308), 340 West Campus Drive, Blacksburg, VA 24061. [email protected], 540-231-9080. ACKNOWLEDGEMENTS

AUTHOR CONTRIBUTIONS AMB, BLW, and DRB designed the research. BLW performed docking and cavity analysis experiments. AMB, BLW, DRB, and WLS analyzed the data. BLW, AMB, WLS, and DRB wrote the manuscript. All authors have given approval to the final version of the manuscript. COMPETING INTEREST STATEMENT The authors declare no competing interest.

Data files are available from the Virginia Tech Institutional Data Repository,VTechData, doi:[DOI to be provided pending publication]. Script files and input files are found on our public Open Science Framework page (https://osf.io/82n73/). FUNDING The work was supported by NIH Grants R01 GM104366 and R01 GM067958. Authors will release the atomic coordinates and experimental data upon article publication. REFERENCES4, 6, 11, 14, 17, 39, 40, 45, 48, 49

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