Identification of New Putative Autotaxin Inhibitors via Structure‐Based Virtual Screening and Evaluation of Their Antiproliferative Properties Against Ovarian and Breast Cancer Cells

Abstract

Autotaxin (ATX), a lysophospholipase D playing an important role in several inflammatory diseases, as well as in tumor invasion, progression, and metastasis, is an attractive therapeutic target. Herein, we report a virtual screening study of an in‐house molecular database. In silico simulations highlighted five putative ATX inhibitors. The enzyme assay showed that compound 3 achieves inhibition potency in the submicromolar range (IC₅₀ = 0.534 µM), whereas all the other test compounds proved to be moderate (2) or weak (1, 4, and 5) inhibitors of ATX at 10 µM concentration. These compounds, evaluated for the in vitro antiproliferative activity in four ATX‐expressing cancer cell lines, namely the ovarian cancer cell lines A2780 and SK‐OV‐3, the breast cancer cells MCF‐7, and immortalized mouse embryonic fibroblast cell line NIH/3T3, demonstrated preliminary phenotypic effects, inhibiting cell proliferation with IC₅₀ values mostly in the low micromolar range. Compound 4 (IC₅₀ = 11.5 µM against SK‐OV‐3) significantly reduced the motility of SK‐OV‐3 ovarian carcinoma cells in the wound‐healing assay, suggesting that it may represent a hit structure for the development of potential antimetastatic agents.

A benzimidazole‐based sulfonamide derivative (4) was investigated through virtual and in vitro screening as putative inhibitor of autotaxin (ATX). It inhibited proliferation of ATX‐expressing ovarian and breast cancer cells in the low micromolar range and reduced the invasion of SK‐OV‐3 ovarian carcinoma cells, suggesting effects in metastatic inhibition.

1. Introduction

Autotaxin (ATX, ENPP2) is a secreted glycoprotein encoded by ENPP2 gene, first isolated in human melanoma cells [1], that belongs to the ectonucleotide pyrophosphatase/phosphodiesterase (ENPP) family [2]. Structurally, ATX is a multidomain protein, initially synthesized as a pre‐proenzyme until the production of a fully active enzyme, consisting of a central catalytic phosphodiesterase (PDE) domain that interacts on one side with the N‐terminal somatomedin‐like domain regions (SMB1‐2) and on the other side with the catalytically inactive N‐terminal nuclease‐like domain [3]. In particular, the activity of ATX, as a lysophospholipase D (lysoPLD), appears to be due to the deep hydrophobic pocket in the catalytic domain, not present in any other phospholipase [4], which binds the substrate lysophosphatidylcholine (LPC) and allows ATX to bind to the cell surface to directly deliver lysophosphatidic acid (LPA) to cells. Indeed, it is known that the biological effects of ATX emerge from the ATX/LPA axis signaling [5]. Since the beginning, ATX has been characterized as a potent pro‐migratory factor and increasing evidence has linked the ATX/LPA axis to a key factor in the pathophysiology of many inflammatory diseases, including cancer [4, 6]. Moreover, aberrant ATX/LPA signaling appears to affect tumor progression, invasiveness, metastatic potential, and resistance to therapy [7]. The analysis of tumor histotypes has shown that ATX is expressed not only by tumor cells but also by fibroblasts, suggesting that ATX expression and the pathways in which it is involved in tumor can play a key role [8, 9]. The mechanism of ATX expression in tumor cells is not yet fully understood; therefore, it is a candidate for further investigation.

The genesis of our study began following transcriptomic evaluations of activated fibroblast populations in tumor microenvironments of different embryonic origins and in the progression of the disease [8, 9]. The study adopted a nonnegative matrix factorization (NMF) framework that allowed the selection of some genes, including ENPP2/ATX [10, 11]. ATX expression is characteristic of tissue and temporal specificity [8, 9]. The ENPP2 gene, encoding ATX, is organized into 27 exons and alternative splicing results in the generation of several isoforms that differ in catalytic activity, substrate preference, or extracellular localization [5, 12]. Furthermore, ATX is regulated in different ways, including regulation at the transcriptional, posttranscriptional, and secretory levels.

This diversity raises a lot of questions in the identification of possible inhibitors. To date, several small‐molecule inhibitors have been identified (Figure 1), developed and evaluated in preclinical studies [4]. The boronic acid derivative HA155, along with several structural congeners [13], was the first inhibitor described. Ziritaxestat (GLPG1690) [14] and cudetaxestat (PAT‐409) [15] entered Phase‐2 for the treatment of idiopathic pulmonary fibrosis, while IOA‐289 [16] and PF‐8380 [17] proved useful in studying the structural and toxicological limitations, and PF‐8380 demonstrated the biological importance of ATX blockade.

FIGURE 1.

2D structure of five representative ATX inhibitors.

The growing interest toward this target stimulates the search for new highly selective and potent inhibitors. The identification of novel bioactive molecules can be significantly accelerated by exploiting collaborative chemical repositories designed to enable compound sharing and repurposing. In this context, our in‐house developed Mu.Ta.Lig. Chemotheca is a community‐driven molecular database collecting active and inactive compounds contributed by affiliated researchers, together with associated structural and biological data [18].

In this work, for the virtual screening (VS) campaign, a dedicated branch of the Mu.Ta.Lig. platform, namely the PRIN SUD Virtual Chemotheca (https://www.cclab.unicz.it/prin‐sud), was used as source of compounds. The PRIN SUD Virtual Chemotheca was populated within the framework of a PRIN project consortium (see acknowledgments for more information). The platform integrates user‐uploaded data with theoretical physicochemical, ADME, and molecular descriptors, enabling advanced querying. Notably, the platform facilitates the reevaluation of compounds that may have been previously discarded for a specific target, allowing their potential repositioning against alternative drug targets. The platform was specifically designed to enable secure compound sharing, data management, and collaborative activities among the consortium members. This makes the PRIN SUD Virtual Chemotheca a valuable resource for ligands’ discovery campaigns, including the identification of novel ligands targeting complex pathways, such as the ATX/LPA axis in this case.

This study was aimed at (i) carrying out a structure‐based VS of compounds prioritized as putative ATX ligands within the PRIN SUD Chemotheca database, (ii) in vitro evaluation of their inhibition potency in a suitable cell‐free enzyme assay, (iii) verifying the presence of ATX in cell lines of different tumor histotypes, and finally (iv) preliminarily evaluating in vitro the phenotypic effects on proliferation and migration in diverse cancer cell lines, the final goal being the identification of novel small molecules that could have utility in fighting some resistant forms of cancer.

2. Results and Discussion

2.1. Virtual Screening

To identify novel potential inhibitors of ATX, all compounds available into the PRIN SUD Virtual Chemotheca were submitted to structure‐based (i.e., molecular docking calculation) VS studies. The compounds were ranked according to their Glide docking score (D‐score), and finally five promising compounds were selected (Figure 2 and Table 1) for further biological evaluations. It is worth highlighting that the dialkylamino derivative of quinolino[3,4‐b]quinoxaline 1 had been found as poor inhibitor of topoisomerase IIα and stabilizer of G‐quadruplex oligonucleotides [19]; compounds 2 and 3 had been developed as potential ligands of GluN2B glutamate receptor [20], S1R receptors [21], and tyrosinase enzyme inhibitors [22], whereas the N‐substituted‐[(1H‐benzimidazol‐2‐yl] thio] acetamides 4 and 5 had been previously developed as non‐nucleoside reverse transcriptase inhibitors [23].

FIGURE 2.

2D chemical structures of the five top‐scored molecules as putative ATX ligands identified by VS.

TABLE 1.

PRIN SUD Chemotheca identification code (ID) and docking score (D‐score) of the five VS selected compounds.

#	ID	D‐scoreb
1	CMLDID416	−10.05
2	CMLDID167	−9.58
3	CMLDID198	−10.11
4	CMLDID370	−10.03
5	CMLDID376	−10.12
Ziritaxestata	—	−11.51

^a Ziritaxestat is the co‐crystallized ligand.

^b D‐score values are reported in kcal mol⁻¹.

The binding mode analysis highlighted a consistent interaction pattern among the identified compounds, characterized by hydrogen bonds (HBs), π–π interactions, π–cation contacts, and hydrophobic interactions that collectively contribute to the stabilization of the protein–ligand virtual complexes (Figure 3).

FIGURE 3.

Docking poses of ziritaxestat (A), 1 (B), 2 (C), 3 (D), 4 (E), and 5 (F) within the binding pocket of ATX. The protein backbone is represented as a slate cartoon and the binding site residues as slate sticks. Ligands are depicted as sticks using a different color per ligand. HBs and π interactions are represented as yellow ‐ and cyan‐dashed lines, respectively.

All compounds interacted with known pivotal residues of the ATX catalytic site, reproducing part of the interaction network established by ziritaxestat taken as reference ATX inhibitor (Figure 3A). In particular, compound 1 established one HB with Phe274 and engaged π–π stacking interactions with Phe211, His252, Trp255, and Phe275 (Figure 3B). Compound 2 achieved three HBs with Leu214, Phe274, and Phe306, as well as π–π stacking with His252 (T‐shape), Trp255, and Phe274 (Figure 3C). Compound 3 formed one HB with Phe250, π–π stacking with Phe274 and π‐cation interactions with Phe211 and Tyr307 side chains (Figure 3D). Compound 4 showed one HB withTrp255, and π–π stacking with Phe211 and Trp255 (Figure 3E). Similarly, 5 was engaged in HBs with Trp255 and Gly257 and π–π stacking with Phe211 and Trp255 (Figure 3F).

The observed interaction pattern demonstrated the capability of all selected compounds to productively recognize the ATX binding pocket.

2.2. In Vitro Inhibition of Autotaxin

The inhibition of ATX was assayed by means of a kit based on Amplex Red reaction, using lysophosphatidylcholine (LPC) as the substrate and the known reversible covalent ATX inhibitor HA155 as positive control. All the compounds were tested at 10 µM; for compounds achieving more than 60% inhibition at 10 µM the IC₅₀ values were determined. Data summarized in Table 2 showed for compound 3 a good inhibition potency of ATX with IC₅₀ in the submicromolar range (Figure 4) and a fair inhibitory activity (slightly lower than 50% inhibition at 10 µM) for the indole derivative 2; the remaining compounds (1, 4, and 5) achieved poor activities at 10 µM concentration.

TABLE 2.

Inhibitory activity of ATX for the five selected compounds and the reference inhibitor HA‐155.^a

#	% inhibition @ 10 μM	IC50, μM
1	10 ± 5
2	43 ± 5
3		0.534 ± 0.027
4	17 ± 4
5	18 ± 1
HA‐155		0.062 ± 0.003

^a Amplex Red assay kit. Data are means ± standard deviation (SD) from three independent experiments.

FIGURE 4.

Dose–response curves of inhibition of ATX by 3 and HA155.

2.3. Western Blotting of Autotaxin Protein

The presence of ATX protein was detected by Western blotting, using A2780 and SK‐OV‐3 tumor cells [24], representative of ovarian carcinoma, MCF‐7 for breast carcinoma [25], and NIH/3T3 for fibroblasts [26] representative of the microenvironment. The choice of these tumor lines allowed us to evaluate different tumor histotypes and an important component of the microenvironment. As shown in Figure 5, all cell lines showed the presence of ATX. NIH/3T3, A2780, and SK‐OV‐3 have significantly higher protein levels compared to the breast cancer line MCF‐7.

FIGURE 5.

Identification of the intracellular protein ENPP2/ATX in NIH/3T3, A2780, SK‐OV‐3, and MCF‐7 cell lines.

2.4. Inhibition of Cell Proliferation

All the compounds were tested at the maximum concentration of 50 µM and those achieving at that concentration more than 60% inhibition were evaluated at scalar concentrations for determining IC₅₀ values in three independent experiments. The potent covalent reversible ATX inhibitor HA155 was used as positive control. The cell proliferation inhibition data (IC₅₀, µM) obtained with sulforhodamine‐B (SRB) staining are summarized in Table 3.

TABLE 3.

Inhibition of proliferation on NIH/3T3, A2780, SK‐OV‐3, and MCF‐7 cell lines by compounds 1–5 (72 h exposure, SRB test) and HA155 taken as reference standard.^a

#	NIH/3T3	A2780	SK‐OV‐3	MCF‐7
1	7.56 ± 2.90	11.1 ± 2.0	17.6 ± 1.3	7.31 ± 2.30
2	1.65 ± 0.85	30.3 ± 4.8	26.2 ± 7.2	14.8 ± 7.6
3	5.51 ± 3.92	25.7 ± 5.6	>50	24.5 ± 5.6
4	3.08 ± 0.51	18.8 ± 5.2	11.5 ± 1.9	12.3 ± 1.5
5	9.50 ± 7.11	>50	19.5 ± 9.7	34.7 ± 1.4
HA155	4.85 ± 1.35	18.7 ± 1.2	26.6 ± 2.8	>50

^a Data are IC₅₀ values (µM) expressed as means ± SD from three independent experiments each performed in duplicate.

All the tested cell lines were supplemented with 10% standard fetal bovine serum (FBS), which contains high endogenous levels of the ATX substrate LPC and product LPA, the latter acting as mediator to sustain cell division and survival. The presence of LPA‐containing growth supplement like FBS may in principle confound the effect due to the inhibition of cell‐secreted ATX from that due to itself. Nevertheless, FBS should mimic the complex microenvironment of the cancer cell. It is worth pointing out that the purpose of this part of the study, rather than mechanistic validation (i.e., quantifying the effect of the ATX inhibition on anticancer activity), is a primary functional phenotypic screening on ovarian and breast cancer, as well as on fibroblasts taken as model of tumor microenvironment.

The general response of NIH/3T3 fibroblasts to all the compounds examined is quantified by IC₅₀ values in the low micromolar range. With only few exceptions (IC₅₀ > 50 µM), all the newly tested compounds proved to be effective in inhibiting the three cancer cell lines with IC₅₀ s < 30 µM.

Overall, the A2780, SK‐OV‐3, and MCF‐7 cell lines did not show different sensitivity to the antiproliferative action of the test compounds, and all compounds showed activity close to that of HA155. Among them, despite the weaker ATX inhibition potency, the antiproliferative efficacy of compound 4 not only was balanced for all the cell lines but also scored the best IC₅₀ value toward the chemoresistant SK‐OV‐3 line [27]. Therefore, it was selected for further investigation in the wound‐healing assay on the SK‐OV‐3 cell line.

2.5. Scratch Kinetics: Effect of Compo und 4 on the SK‐OV‐3 Tumor Line

The inhibition of cell migration was assessed by the wound‐healing assay performed on the SK‐OV‐3 cell line. Cells were treated with 4 at the concentration close to its IC₅₀ (11 µM) for 72 h and compared with HA155 (IC₅₀ = 27 µM) and vinblastine (IC₅₀ = 10 nM) [28], both taken as positive controls. The kinetics of scratch closure were evaluated at 24, 48, and 72 h (Figure 6).

FIGURE 6.

Effect of compound 4, HA 155, and vinblastine in the wound‐healing assay. (A) Microscope images obtained at 0, 24, and 72 h representative of the wound‐healing assay in SK‐OV‐3 treated at the IC₅₀ of 4, vinblastine, and HA155. The images show cells migrating into the scratch region in the presence of the inhibitor, compared to the control. (B) Percentage of wound closure induced in SK‐OV‐3 cells following treatment at the IC₅₀ value of the test compounds.

As shown in Figure 6, compound 4 significantly reduced (p < 0.05) cell migration after 48 h treatment (Figure 6B), with wound closure achieving a reduction of approximately 48% at 72 h compared to untreated. Closure kinetics were comparable to the reference HA155 (40%) and vinblastine (43%).

Previous transcriptomic investigations demonstrated that the ENPP2 gene is overexpressed in several tumor histotypes, supporting the relevance of ATX as a pharmacological target in cancer [8, 9]. Herein, the NIH/3T3, A2780, SK‐OV‐3, and MCF‐7 lines were evaluated, considering that ovarian cancer and breast cancer are among the most widespread tumors, associated with high mortality rate and development of resistance to chemotherapy [19, 20]. Our results (Figure 5) proved that NIH/3T3 mouse fibroblast cells, A2780 and SK‐OV‐3 ovarian cancer cell lines, all supplemented with ATX‐containing standard FBS, attain total levels of ATX higher than that shown by MCF‐7 breast cancer cells. These cell lines were thus eligible for the primary phenotypic screening of compounds selected as putative ATX‐modulators from the PRIN SUD Virtual Chemotheca database. NIH/3T3 fibroblasts were also indicative of the cytotoxicity on “normal” cells. In fact, they showed a greater sensitivity to the antiproliferative action with IC₅₀ values in the low micromolar range.

With a few exceptions, the test compounds achieved inhibition of cell proliferation in all the examined cell lines with IC₅₀ < 30 µM. In the case of NIH/3T3 fibroblasts, compounds 1– 5 achieved single‐digit micromolar inhibitory potency, some of them resulting in potency similar to that of the potent ATX inhibitor HA155. There is no direct correlation between in vitro inhibition of ATX (Table 2) and inhibition of proliferation in any of the cell lines tested (Table 2). The 4‐hydroxyphenyl‐piperazinamide derivative 3, the most active ATX inhibitor among the VS‐identified ATX modulators, just ninefold less potent than HA155, did not result in the most cytotoxic toward all the cell lines investigated. In contrast, the tetracyclic alkylamino derivative 1 and the benzimidazole sulfonamide derivative 4, regardless of their weak ATX inhibition, proved to be the best antiproliferative agents against the ovarian (A2780 and SK‐OV‐3) and breast (MCF‐7) cancer cells. Their cytotoxicity may be due to their multitarget activity. For compound 1, it may reflect the concurrent topoisomerase inhibition and stabilization of DNA G‐quadruplex structures [19], whereas it has to be highlighted that the chemotype 4 possesses two sulfonamide moieties that are privileged fragments able to establish favorable interactions with various enzymes involved in cancer, like carbonic anhydrases, aromatases, histone deacetylases, matrix metalloproteases [29, 30].

The benzimidazole derivative 4 deserved greater interest for its efficacy against SK‐OV‐3 cell line, which is known to be resistant to several cytotoxic drugs as well as to tumor necrosis factor [27]. The inhibition of migration by 4 was compared with that exerted by vinblastine, a natural alkaloid that binds microtubules, significantly altering their dynamics in living cells. This action, besides inhibiting the formation of mitotic spindles and preventing the tumor cell from completing division, affects the migratory capacity even at concentrations below apparent cytotoxicity [28]. The efficacy of 4 in inhibiting the scratch closure was comparable to those of the strong ATX inhibitor HA155 and vinblastine (Figure 6).

3. Conclusion

The present study shows that the combined application of structure‐based VS, enzyme inhibition assay, and primary phenotypic in vitro screening may be an effective strategy for identifying novel putative ligands targeting the ATX/LPA axis. Starting from the PRIN SUD Virtual Chemotheca database, five compounds were selected based on their predicted binding affinity toward ATX and subsequently evaluated for their enzyme inhibition and in vitro antiproliferative in four ATX‐expressing cancer cell lines.

Among the molecules prioritized by VS, compound 3 was experimentally found to be good inhibitor of ATX activity in the enzymatic assay, whereas the other compounds showed moderate (2) or weak (1, 4, and 5) enzyme inhibition potency. All the tested compounds showed noteworthy antiproliferative activity in the low micromolar range against NIH/3T3 fibroblasts, and with a few exceptions against ovarian (A2780 and SK‐OV‐3) and breast (MCF‐7) cancer cell lines. Even though the ATX inhibition did not appear as main mechanism underlying the inhibition of tumor cell growth of the tested cell lines, compound 3 emerged as priority chemotype for further optimization studies aimed at developing novel effective ATX inhibitors.

Although it is a weak ATX inhibitor, the benzimidazole‐based sulfonamide 4 can be considered a hit molecule as it displayed balanced antiproliferative activity across different tumor histotypes. Notably, compound 4 not only showed the highest efficacy against the chemoresistant SK‐OV‐3 ovarian carcinoma cell line, but also significantly inhibited cell migration in the wound‐healing assay, achieving effects comparable to those observed with the reference ATX inhibitor HA155 and the antimitotic agent vinblastine.

4. Experimental Section

4.1. The PRIN SUD Virtual Chemotheca

The VS campaign was supported by the PRIN SUD Virtual Chemotheca database (https://www.cclab.unicz.it/prin‐sud), a dedicated branch of the web‐accessible molecular platform developed within the framework of the COST Action CA15135 “MuTaLig” and hosted at the Magna Græcia University of Catanzaro [18]. The Chemotheca is a repository that enables registered users to upload, share, and search for chemical structures along with associated experimental and theoretical data.

4.2. Virtual Screening Studies

The target 3D model was derived from the Protein Data Bank (PDB) 5MHP X‐ray structure [31]. In order to be used for VS simulation, the original PDB has been submitted to a preliminary pretreatment by means of the Protein Preparation Wizard tool implemented in Maestro. OLPS_2005 force field has been applied to energy optimization. Residual crystallographic buffer components were removed, missing side chains were built, hydrogen atoms were added, and side chains protonation states were assigned at pH 7.4 ± 0.2 [32]. A single water molecule was retained as it was deemed important due to the formation of a water bridge between a carbonylic group of the co‐crystallized ligand and the side chain of Trp261. In order to evaluate the reliability of our molecular recognition approach, we performed redocking calculations by using Glide Standard Precision protocol [33], that was able to reproduce the experimental ligand binding geometry, as demonstrated by a root mean square deviation value equal to 0.597 Å. The docking simulation sampled 20 poses per ligand. All molecules reporting a docking score (D‐Score) within 2 kcal/mol above the co‐crystallized ligand were retained. These candidates were visually inspected to ensure chemical diversity, resulting in the selection of five compounds.

4.3. Ligands Preparation

All compounds, retrieved from the PRIN SUD Virtual Chemotheca on July 2021, were optimized with LigPrep tool [34]. Ionization states were computed using Epik at pH 7.4 ± 0.2. The prepared ligands library entailed 499 different molecules.

4.4. Chemical and Biological Materials

All chemicals were obtained from Merck Life Science S.r.l. (Milano, Italy), unless otherwise stated. Test compounds were provided by the medicinal chemistry laboratories at University of Bari and University of Messina as detailed below. The inhibitors HA155 and vinblastine, used as reference drugs, were purchased from Merck. All compounds were dissolved in dimethyl sulfoxide (DMSO) at an initial concentration of 10 mM and then diluted in working buffers.

Compounds 1 [19], 2 [20], 3 [21, 22], and 4 –5 [23] (Figure 2) were synthesized according to the synthetic methods previously reported and their purity ascertained through HPLC.

NIH/3T3 mouse embryonic fibroblasts, MCF‐7 breast cancer cells, A2780, and SKOV‐3 ovarian cancer cells were purchased from the American Tissue Culture Collection (ATCC, 10 801 University Blvd, Manassas, VA, USA). The A2780 and NIH/3T3 cell lines were cultured in Dulbecco’s Modified Eagle Medium while the SKOV‐3 and MCF‐7 tumor cell lines in RPMI 1640 medium. All media were supplemented with 10% FBS, 100 U/mL penicillin–streptomycin and maintained in a humidified atmosphere at 37 °C containing 5% CO₂.

4.5. In Vitro Inhibition of Autotaxin

The inhibitory activity of compounds 1–5 and reference inhibitor HA155 was assayed with the commercial Amplex Red phospholipase D assay kit supplied by Molecular Probes Inc. (Thermo Fisher Italy). Inhibitor HA155 and substrate lysophosphatidylcholine were from Merck Italy, ATX protein from Sino Biological (Prodotti Gianni, Milan, Italy). The assay was performed following the protocol supplied by the manufacturer, using a concentration of 10 μM of inhibitors tested at single‐point or seven concentrations ranging from 3 × 10⁻⁵ to 10⁻¹¹ M for IC₅₀ determinations. Experiments were run in triplicate, and the results were analyzed with Prism software 5.01 (GraphPad Software Inc., La Jolla, CA, USA).

4.6. Western Blot Analysis

Briefly, NIH/3T3 cells and A2780, SK‐OV‐3, MCF‐7 tumor cells were seeded in 25‐cm² flasks and cultured in the appropriate culture medium at plating densities (25,000–80,000 cells/mL) until reaching 80%–90% confluence. For Western blotting, cells were washed with cold PBS, lysed in RIPA buffer, supplemented with protease inhibitors and protein phosphatase inhibitors (20 mM NaF and 1 mM orthovanadate; Pierce), and centrifuged. Immunoblotting was performed according to the manufacturer’s instructions (Bio‐Rad Laboratory, Milano, Italy). Protein fractions together with a standard (Precision Plus Protein) providing a ten‐band, broad‐range molecular weight ladder (10–250 kD) were loaded in equal amounts into each lane (25 µg) and separated on a precast 7.5% polyacrylamide gel Mini‐PROTEAN TGX Stain‐Free Gels. The protein fractions after the electrophoresis run were transferred onto PVD membranes, precisely with the Trans‐Blot Turbo Mini PVDF Transfer Packs (includes filter paper, buffer, PVDF membrane,) by Trans‐Blot Turbo System. After transfer, the membrane was washed for 5–10 min. in TBS. Blocking followed, washing for 5–10 min. in TBS‐T and blotting with primary antibodies recognizing ATX/ENPP2 (ab13750 – Abcam‐DUOTECH SRL, Milano, Italy) and β‐actin (Cell Signing), respectively, appropriately diluted. This was followed by incubation with the secondary antibody Goat Anti‐Rabbit IgG (H + L)‐HRP Conjugate (1706515, Bio‐Rad). Protein expression was visualized using chemiluminescence reagents based on Stain‐Free Technology (ChemiDoc Go Imaging System‐ Bio‐Rad). Protein amounts were analyzed using Image J analysis software, version 1.54d (NIH‐USA).

4.7. In Vitro Growth Inhibition Assay

Cell proliferation inhibition assay of test compounds was performed using the SRB assay [25]. Briefly, cells were seeded in 96‐well microtiter plates in 100 µL of the appropriate culture medium at plating densities (25,000–80,000 cells/mL). After seeding, microtiter plates were incubated at 37 °C for 24 h before compound addition. After 24 h, several samples of each cell line were fixed in situ with cold trichloroacetic acid (TCA), representing a measurement of the cell population at the time of compound addition. Test compounds were freshly dissolved in the culture medium and gradually diluted to the desired final concentrations. After the addition of different concentrations of compounds, the plates were further incubated at 37 °C for 72 h. Cells were fixed in situ by the gentle addition of 50 µL of 50% (w/v) cold TCA (final concentration, 10%) and incubated for 1 h at 4 °C. The supernatant was discarded, and the plates were washed and air dried. A solution of 0.4% (w/v) SRB (100 µL) in 1% acetic acid was added to each well in all plates, including those at 0 h, and incubated for 30 min at room temperature. After staining, unbound dye was removed by washing with 1% acetic acid and the plates were air dried. Bound dye was then solubilized with 10 mM Trizma base and absorbance was read on an automatic plate reader SkanIt Software for Microplate Readers Software, version 6.1 (Carlo Erba srl), at 570 nm. The concentration of the compound able to inhibit cell growth by 50% (IC₅₀) was calculated from semilogarithmic dose–response plots.

4.8. Wound‐Healing Assay

The wound‐healing assay used SK‐OV‐3 ovarian carcinoma cells, seeded at a density of 2 × 10⁵ cells/mL in a 6‐well plate in RPMI and 10% FBS and grown until 80%–90% confluence. Then, a scratch was made on the cell monolayer using a p200 pipette tip. The plate was washed with sterile PBS to remove debris, and marks were made on the outside bottom of the plate with a marker tip to serve as reference points. The cell line was incubated with a medium containing concentrations equal to the IC₅₀ of each compound, namely 4 (11.48 µM), vinblastine (14.2 nM) [26], as well as HA155 (26 µM) and compared to the control. Images were acquired at 0, 24, 48, and 72 h using a microscope and Image J software, version 1.54d, was used to evaluate the scratched area. The migratory capacity of cells for wound healing was obtained by applying the following formula: [(wound area at 0h) – (wound area at the indicated time)]/(wound area at 0 h) × 100.

4.9. Statistics

All experiments were performed in triplicate, and the data expressed as mean ± SD. The significance test was performed with the Student t‐test. Values of p < 0.05 were considered statistically significant.

Conflicts of Interest

The authors declare no conflicts of interest.

Boccarelli Angelina, Coricello Adriana, Ambrosio Francesca Alessandra, Leo Valentina, Mirabile Salvatore, Gitto Rosaria, de Candia Modesto, Catto Marco, Ortuso Francesco, Altomare Cosimo D., Alcaro Stefano, Identification of New Putative Autotaxin Inhibitors via Structure‐Based Virtual Screening and Evaluation of Their Antiproliferative Properties Against Ovarian and Breast Cancer Cells, ChemMedChem 2026, 0, e70474. 10.1002/cmdc.70474

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.