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Pharmacoinformatics and Molecular Dynamic Simulation Studies To Arabian Journal of Chemistry (2020) 13, 5107–5117 King Saud University Arabian Journal of Chemistry www.ksu.edu.sa www.sciencedirect.com ORIGINAL ARTICLE Pharmacoinformatics and molecular dynamic simulation studies to identify potential small-molecule inhibitors of WNK-SPAK/OSR1 signaling that mimic the RFQV motifs of WNK kinases Mubarak A. Alamri Department of Pharmaceutical Chemistry, College of Pharmacy, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj 11942, Saudi Arabia Received 14 January 2020; accepted 17 February 2020 Available online 21 February 2020 KEYWORDS Abstract The WNK-SPAK/OSR1 signaling is a complex of serine and threonine protein kinases Pharmacophore; that involves in the regulation of human blood pressure. The WNK kinases phosphorylate and MD simulation; activate SPAK and OSR1 kinases through the interaction of RFQV motifs of WNK kinases with SPAK; the C-terminal domains of SPAK and OSR1. Upon phosphorylation, SPAK and OSR1 phospho- + + À + À OSR1; rylate key ion co-transporters such as Na -[K ]-2Cl (NKCC1-2) and K -Cl (KCC1-4), which are Virtual screening; essential for electrolytes balance and blood pressure regulation. Targeting the binding site of the WNK RFQV motifs of WNK kinases on the C-terminal domain (CTD) of SPAK and OSR1 has emerged as a valuable approach to inhibit the WNK-SPAK/OSR1 signaling pathway. Herein, an effort has been intended to pinpoint non-peptidic small-molecules that could disrupt the binding of SPAK/OSR1 to WNK kinases, hence, inhibit the SPAK and OSR1 phosphorylation and activation by WNK kinases through pharmacoinformatics and molecular dynamic simulation methodologies. A sequential structure-based virtual screening of a focus protein-protein interaction chemical library composed of 11,870 compounds lead to the identification of three compounds having good lead-compound properties with respect to their predicted inhibitory constants, pharmacophore fit scores, binding affinities, ADME-T parameters, drug-likeness properties and ligand efficiency metrics. The mechanism of interaction and binding stability of these compounds to OSR1-CTD were confirmed using molecular docking and dynamic simulation studies. Hence, the identified E-mail address: [email protected] Peer review under responsibility of King Saud University. Production and hosting by Elsevier https://doi.org/10.1016/j.arabjc.2020.02.010 1878-5352 Ó 2020 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 5108 M.A. Alamri compounds may have therapeutic potential as novel antihypertensive agents subjected to experi- mental validation. Ó 2020 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 1. Introduction The virtual screening is a computational approach that is utilized in the early-stage drug discovery campaign to search The WNK-SPAK/OSR1 signaling is defined as a master regu- chemical databases for novel bioactive molecules against the lator of human blood pressure (Alessi et al., 2014). In 2001, the target of interest in timely and cost-effective way (Sliwoski first link between this signaling cascade and hypertension was et al., 2014). Generally, two distinct classes of virtual screening reported when an inherited form of hypertension in humans can be used, ligand-based and structure-based virtual screen- known as ‘‘Gordon’s syndrome” was found to results from ing, depending on the available information regarding the mutations of the genes that encoded for WNK (with no lysine), ligands and three-dimensional (3D) structure of the target, serine/threonine protein kinases (Wilson et al., 2001). Subse- respectively (Aparoy et al., 2012). Additionally, the pharma- quent biochemical studies showed that WNK kinases phos- cophore modeling is one of the significant tools in modern phorylate and activate two other intermediate serine/ drug discovery. It is defined as the process of identification threonine protein kinases namely, SPAK (SPS1-related of electronic and steric chemical features that are essential proline/alanine-rich kinase) and OSR1 (oxidative stress- for optimal interaction between a ligand and its target. The responsive kinase 1) kinases (Moriguchi et al., 2005). Active 3D pharmacophore model can be used as queries for SPAK and OSR1 in complex with Mo25, a scaffolding pharmacophore-based virtual screening, de novo design and protein, were found to regulation the function of key cation- lead optimization (Khedkar et al., 2007). The main focus of chloride cotransporters (CCCs) such as the Na/K/Cl co- this presented study is to screen Asinex protein-protein interac- transporters 1 and 2 (NKCC1/2), the Na/Cl co-transporter tion database for identification of novel binders of OSR1/ (NCC) and the K/Cl co-transporters (KCCs) by phosphoryla- SPAK C-terminal domains that could disrupt their interac- tion (Alessi et al., 2014; Filippi et al., 2011). Generating mouse tions with WNK kinases. The molecular mechanism of inhibi- models expressing an enzymatically inactive form of WNK, tion of obtained inhibitors were explored by molecular SPAK or OSR1 kinases result in a lowered blood pressure docking and molecular dynamic simulation. The good phar- due to the inhibition of CCCs phosphorylation (Hadchouel macodynamic and pharmacokinetic profiles of selected com- et al., 2016). The latter, highlighted the WNK-SPAK/OSR1 pounds suggesting the possibility of them to be potential signaling pathway as a valuable target for development of inhibitors of WNK signaling as a new class of antihyperten- novel class of antihypertensive agents. sion agents. Human SPAK and OSR1 are highly related homologues sharing 68% of their total primary amino acid sequences with 2. Material and methods ambiguous tissue expression profiles (Vitari et al., 2006). In addition to the kinase domain and serine-rich motif, SPAK and OSR1 possess a highly conserved carboxy-terminal The general methodology used in this research is depicted in domain (CTD); which is a 92-amino acids long (residues (Fig. 1). 456–545 for SPAK and 434–527 for OSR1) and is required for the binding of SPAK and OSR1 to the specific RFxV/I 2.1. Generation and validation of pharmacophore model (Arg-Phe-Xaa-Val/Ile) motifs within both upstream WNK kinases and downstream CCCs (Richardson and Alessi, The crystal structure of C-terminal domain (CTD) of OSR1 in 2008; Vitari et al., 2006). Co-crystallization of the CTD of complex with RFQV (Arg-Phe-Asn-Val) peptide derived from OSR1 with RFQV-peptide derived from WNK4 has demon- WNK4 (PDB: 2V3S) was imported into LigandScout software strated that the CTD has two adjacent hydrophobic pockets, from RCSB protein data bank (Villa et al., 2007). The termed primary and secondary pockets (Villa et al., 2007). structure-based pharmacophore was generated using auto- The RFQV-peptide binds to OSR1-CTD through the primary matic pharmacophore generating tool in LigandScout pro- pocket, while the secondary pocket has been suggested as an gram (Wolber and Langer, 2005). The resulted allosteric pocket (AlAmri et al., 2017). NMR structural study, pharmacophore model consists of the whole features involved indicated that the binding of RFQV-peptide to OSR1-CTD in the binding of RFQV peptide residues to the primary pocket induces large conformational changes that effect almost every of OSR1-CTD. STOCK1S-50699, a known WNK and SPAK amino acids within the CTD of OSR1 suggesting the crucial binding inhibitor, was docked (using Autodock vina) and role of this domain in the regulation of whole signaling trans- mapped on the generated pharmacophore model using duction (AlAmri et al., 2019). Targeting the primary pocket LigandScout program to obtain the final pharmacophore with small molecule protein–protein interaction inhibitors model (Mori et al., 2013). The final pharmacophore model has been exploited, however, the identified molecules such as was then validated using the receiver operating characteristic STOCK1S-50699 and STOCK2S-26016 lack the drug- (ROC) curve, with LigandScout software, by screening the likeness properties which hampered their further in vivo stud- pharmacophore model against a set of active and inactive com- ies (Ishigami-Yuasa et al., 2017; Mori et al., 2013). pounds to determine the ability of this pharmacophore to Pharmacoinformatics and molecular dynamic simulation studies 5109 Fig. 1 Graphical representation of in silico approach for the identification of hit molecules. distinguish between these compounds. STOCK1S-50699 and affinities in comparison to STOCK1S-50699 were considered STOCK2S-26016, known WNK-SPAK binding inhibitors, for further analysis. were used as active compounds. The two compounds were also used to generate the decoy set of 100 inactive compounds (50 2.4. In silico ADME-T analysis compounds per each) using DUD-E webserver (http://dude.docking.org/generate)(Mysinger et al., 2012). pkCSM server was used to evaluate the absorption, distribu- tion, metabolism and excretion- toxicity (ADME-T) parame- 2.2. Pharmacophore-based virtual screening ters for the identified hit compounds (Pires et al., 2015). For the compound to be selected as a hit, it must be non- In silico pharmacophore-based virtual screening was per- hepatotoxic and non-carcinogenic. SwissADME was used to formed with ‘‘Asinex focused protein–protein interaction assess other physiochemical properties of these hit compounds ” (PPI) library having 11,870 small-molecules against the gener- (Daina et al., 2017). ated pharmacophore model using LignadScout software. The library contains non-macrocyclic compounds with a diversity 2.5. Calculation of ligands efficiency metrics and inhibition of more than 500 scaffolds. The library was obtained from constants (https://www.asinex.com/ppi/) in sdf format and was con- verted into Idb using LigandScout library generation tool. The compounds that meet all pharmacophore features were The inhibition constants (Ki) of hit compounds were predicted considered as hit compounds and ranked based on their from Autodock vina binding energy scores using Eq.
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