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Article

Steroidal Oximes and Cervical Cancer: An In Silico Mechanistic Pathway Approach

by
Carlos Antonio Sánchez-Valdeolivar
1,
Alan Carrasco-Carballo
1,2,3,*,
Jorge Organista-Nava
1,
Jesús Sandoval-Ramírez
4 and
Berenice Illades-Aguiar
1,*
1
Laboratory of Molecular Biomedicine, Faculty of Chemical Biological Sciences, Autonomous University of Guerrero, Chilpancingo 30090, Guerrero, Mexico
2
Laboratory of Elucidation and Synthesis in Organic Chemistry, Chemistry Center, Institute of Sciences, Meritorious Autonomous University of Puebla, Puebla 72570, Mexico
3
SECIHTI, LESQO, ICUAP, BUAP, Puebla 72570, Mexico
4
Laboratory of Synthesis and Modification of Natural Products, Faculty of Chemical Sciences, Meritorious Autonomous University of Puebla, Puebla 72570, Mexico
*
Authors to whom correspondence should be addressed.
Sci. Pharm. 2025, 93(3), 36; https://doi.org/10.3390/scipharm93030036
Submission received: 7 June 2025 / Revised: 17 July 2025 / Accepted: 21 July 2025 / Published: 4 August 2025
(This article belongs to the Topic Bioinformatics in Drug Design and Discovery—2nd Edition)
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Abstract

Cervical cancer affects 661,000 women worldwide; as a result, new treatment alternatives are still being sought, with steroid oximes being the most prominent. However, the molecular targets where steroid oximes exert their anticancer activity remain unknown. In this study, reports of the activity in cell lines were obtained, and the targets associated with cervical cancer were identified using bioinformatics tools, based on two- and three-dimensional structural similarity analysis. Subsequently, molecular targets were analyzed via molecular docking using Schrödinger software v.2022-4 to determine their effects compared with reference drugs. Interrelated proteins and isolated proteins were observed, suggesting both the multi-target and single-target activity of steroid oximes. The analysis revealed that 60% of the 42 identified proteins had previously been reported in the literature and were associated with cervical cancer in processes related to cell proliferation, invasion, migration, and apoptosis. Among them, SRC, IGF1R, and MDM2 showed feasibility for multi-target interaction, which is consistent with the lower IC50 values reported for oximes in cervical cancer cell lines (HeLa and CaSki). This finding suggests that steroid oximes are multi-target molecules that can inhibit the proteins associated with cervical cancer, particularly through the IGF1R, MDM2, and SRC pathways related to cell proliferation and apoptosis, serving as a guideline for the future design of new steroidal oximes.

1. Introduction

Cervical cancer (CC) represents a significant global health burden, accounting for a considerable number of deaths among women. However, the disease can be prevented [1]. CC represents the third most common type of cancer in women, after breast and lung cancers [2,3,4]. As indicated by GLOBOCAN data, CC accounts for 3.1% of all cancer cases and 7.7% of cancer-related deaths worldwide [2]. The principal cause of CC is the high-risk human papillomavirus (HR-HPV) [5], which is frequently identified in co-infections [6]. The conventional treatments for CC include paclitaxel, cisplatin, or topotecan in combination with radiotherapy [7]. However, many patients experience disease recurrence, highlighting the need for alternative chemotherapies [8]. Several research groups have been working on the design, synthesis, and evaluation of novel antiproliferative compounds and therapies for the cessation of CC cell line growth [9,10,11,12,13]. For this purpose, both natural and synthetic compounds—such as coumarins [14], flavonoids [15], triterpenes [16], and steroids [17,18,19,20]—have been subjected to analysis. Among these compounds, a group of steroidal oximes has demonstrated lower IC50 values than reference drugs, including cisplatin and tamoxifen [21]. Some steroidal ketones and oximes were initially extracted from marine sponges and subsequently modified [22].
The introduction of the oxime group into a steroid skeleton has been shown to enhance the biological activity of the initial ketone compound. This is also the case for the hydroxyimino derivatives of diosgenin, which have been demonstrated to exhibit antiproliferative [23], proapoptotic [23,24], anti-inflammatory [25], antiviral [26], and antitumoral properties [21,27]. The hydroxyimino steroidal family includes androstanes, cholestanes, furostans, sex hormones, glucocorticoid hormones, bile acids, and spirostans. These families have been tested on CC cell lines, including HeLa, SiHa, CaSki, and C33A, and their corresponding oximes have demonstrated beneficial effects [21,28]. However, the varying effects observed on different cell lines make it difficult to ascertain the mechanism of action of these oximes [21,29]. To address this challenge, this study employs bioinformatics to investigate a database of steroid oximes with anti-CC cell line activity. However, it is necessary to know the possible molecular targets with which they may be interacting in a selective or multi-target manner, which gives rise to the need for inclusion and selection criteria for future candidates for synthesis. This approach aims to identify the key molecular targets associated with their reported biological activities and to propose novel design strategies for new bioactive steroidal oxime molecules. Given the results in the literature, the target molecules are unknown; however, given the observed effects, it is theorized that they are associated with proteins such as SRC, IGF1R, and MDM2 as the main targets for triggering antiproliferative and/or cytotoxic processes.

2. Materials and Methods

2.1. Database Construction

Using the descriptors “Steroidal Oxime CC” and “Steroidal Hydroxyimino CC” in the SciFinder, Google Scholar, and PubMed databases, manuscripts presenting results related to steroidal oximes against HeLa, SiHa, CaSki, Vivo, C33A, and HaCat cell lines were collected, and 176 different structures were identified (see Supplementary Material Table S1) [21,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75]. The ADME prediction was elaborated by [76].

2.2. Target Selection

The construction of a frequency diagram was carried out using the probability of interaction due to structural similarity via Swiss target prediction (STP) (http://www.swisstargetprediction.ch, accessed on 7 July 2024) [75], presented as a percentage frequency with p ≠ 0 according to the previously reported protocol [13]. Interactome construction was performed on the STRING platform (https://string-db.org/ accessed on 23 April 2025) [77] using UniProt input codes (https://www.uniprot.org/ accessed on 10 August 2024), with targets selected using the STP frequency diagram, via the full STRING network. Evidence is indicated via line color according to the type of interaction evidence, including text mining, experiments, databases, and co-expression. Neighborhood, gene fusion, and co-occurrence were also obtained, with medium confidence (0.400) and without interactors, for PPI enrichment p-values ≤ 0.05.

2.3. In Silico Studies

2.3.1. Protein Preparation

The Protein Data Bank (PDB) codes of the proteins used for molecular docking are listed in Table 1, each one co-crystallized with a reference inhibitor and complemented with inhibitors reported in the literature for cases that did not present an inhibitor as a co-crystal. Each protein was prepared in Schrödinger’s Protein Wizard Prepare module (https://www.schrodinger.com/ accessed on 19 October 2024) [78]. The protonation and tautomeric states of Asp, Glu, Arg, Lys, and His were adjusted to a pH of 7.4. Water molecules inside a sphere of 5 Å in the active site were removed. The orientation of the hydrogen bridge bonds was adjusted around the active site using PROPKA at a pH of 7.4, and water molecules had one or two hydrogen bridges removed. Finally, OPLS4 was used to minimize the complete protein at 0.3 Å root-mean-square deviation.

2.3.2. Ligand Preparation

Reference ligands (Table 2) and steroidal oximes were minimized with MacroModel [108] and OPLS4 [109] and subsequently brought to physiological conditions in Schrödinger’s LigPrep [110]. Water was used as a solvent for minimization, along with the PGRP minimization model with OPLS4 force fields. For LigPrep with an OPLS4 force field, all possible protonated centers and ionization states were calculated for scaffolding using an ionizer at pH 7.4. Stereoisomers were retained according to their original crystal structures, which were limited to 32 isomers for each ligand. Tautomeric states were generated for each group and those with a lower energy for each ligand were selected.

2.3.3. Molecular Docking

Molecular docking studies were performed in the Glide module [130] with precision-level XP, with flexible ligands and flexible proteins in the active site according to a previously reported protocol [12,13]. Each grid box was built based on co-crystallized reference ligands or inhibitors; softening of the nonpolar parts of the receptors was carried out by scaling the van der Waals radii by a factor of 0.08. Atoms were considered nonpolar if their absolute partial atomic charge was <0.25. In terms of flexibility, additional ligand rotations were allowed for the hydroxyl groups in Ser, Thr, and Tyr, and the thiol group in Cys residues. For each ligand, 100 independent docking runs were performed to ensure reproducibility and the consistent sampling of conformational space. For each of the 100 docking runs, the top-ranked binding score (docking value) was recorded, and the most favorable binding energy conformation (BCE) from this set was selected for the evaluation of molecular interactions and the construction of the 2D interaction diagrams. This approach ensured statistical robustness and biological relevance in the selection of binding poses. Further, the lowest energy binding position of each ligand was maintained. The validation of each protein was carried out with the co-crystal (see Supplementary Material Table S2), resulting in RMSD values < 2.0 Å in all cases.

3. Results

3.1. Structural Similarity Analysis

Up to 2023, 172 steroid oximes had demonstrated activity against cervical cancer (CC) cell lines. Several studies have been conducted on a variety of steroid structures, including cholestane, bisnorcholanic lactones, androstanes, and spirostans, which feature the hydroxyimino group on the basic skeleton or the side chain. The hydroxyimino group has demonstrated promising anticancer activity against some cancers, indicating its versatility for use in cancer treatment. Through STP, a structural similarity analysis was carried out, and a database of 42 target proteins was created. These proteins showed an anticancer frequency greater than 30% (Figure 1A). Certain proteins are associated with hormonal regulation, reproductive processes, and the central nervous system, highlighting the potential for a multi-target approach using steroidal oximes.
Of the 42 proteins analyzed, only 26 were found to be related to CC. These involve several key processes, including migration [79,80,81,86,91,92,93,94,95,102,103], invasion activation [86,91,92,93,94,95,102,103], apoptosis promotion [83,85], proliferation [87,91,92,93,94], and immune response [82,90,106] (Table 1). It is possible that these proteins are responsible for the antiproliferative and/or cytotoxic activities observed in the aforementioned in vitro studies. The aim of this research was to elucidate the mechanism of action of steroidal oximes and identify new molecular targets, with a view to developing alternative agents against CC.
These proteins are not isolated from each other; instead, they can interact between themselves. To understand these correlations, an interactome was constructed using the STRING v.10.5 tool. The interactome revealed a group comprising proteins such as kinases, tyrosine, receptors, and phosphatases, indicating a possible correlated response in the proliferation, metastasis, and apoptosis process, mainly due to the interaction observed between ALK, JAK1, JAK2, JAK3, IGF1R, PTPN1, KDR, MDM2, SRC, and TRPV1. According to the STRING platform, these relationships have been reported experimentally and assigned to databases, in addition to co-expression and gene co-occurrence, suggesting that the interaction of steroidal oximes with these proteins could modulate their activity. However, some isolated proteins have a direct correlation with biological interests according to reports [88,96,102,104,116,131,132,133]. These findings suggest that steroid oximes could be used for mono-targeted activity. To properly analyze this correlation, it is necessary to perform structural similarity analysis through energetic and interactional analysis. This study can be divided into groups of proteins that are directly correlated (Figure 1B).

3.2. Molecular Docking Analyses

A total of 26 proteins were investigated; 25 were found to couple with steroidal oximes in their active sites. The histamine type 1 receptor was the only case in which this coupling was not observed due to the narrowness of its active site, which prevents access to enough large molecules such as steroidal oximes. This receptor is more suited to histamine, which acts as an agonist on the receptor. Among the remaining 25 proteins, at least 20 oximes were found to be coupled with each of them. However, not all these couplings exhibited a higher energy level in comparison to the reference drug/inhibitor/antagonist or to the ligand/substrate. Figure 2 illustrates which proteins demonstrated superior interactions with the studied steroidal oximes.
After analyzing the binding coupling energies (BCEs) of several targets, they were grouped into three categories based on their level of interaction (Figure 2). The first group consisted of KCNH2, TRPV1, PTPN1, ALK, RORC, and CRHR1, but they were eliminated due to their low level of interaction. In addition, none of the steroidal oximes displayed an interaction like or better than the reference ligands for the corresponding proteins (Table 2). The second group of proteins showed interactions with at least one oxime that had a better BCE than the reference ligands but was not better than the average of the database. This group includes STS, JAK1, JAK3, HCRTR2, FNTA, CNR1, NR3C1, KDR, and JAK2 proteins. These proteins are significant case studies, but they are not a common denominator for establishing the mechanism of action of steroidal oximes in CC. The third group included proteins where the central mean or most of the steroidal oximes showed better BCEs than the reference ligands. This group includes NR1H3, IGFR1, HSD11B, OPRD1, MDM2, NR1H4, SRC, and CNR2 proteins. The above suggests a mechanism of action of steroidal oximes through these proteins. Groups two (STS, JAK1, JAK3, HCRTR2, FNTA, CNR1, NR3C1, KDR, and JAK2 proteins) and three (NR1H3, IGFR1, HSD11B, OPRD1, MDM2, NR1H4, SRC, and CNR2 proteins) will be studied to determine the influence of the hydroxyimino group and establish the need for this group in direct interaction with the target in question.

3.2.1. Molecular Docking via Linear Interactions Between Steroidal Oximes

Targets that interact with certain steroidal oximes or show a low potential for interaction do not permit us to propose a common action mechanism. Nevertheless, they permit the formulation of precise objectives for a subset of steroidal oximes when examining proteins with low frequency. A total of 72 interactions were observed, exceeding those of reference ligands, substrates, or inhibitors. These interactions correspond to a total of 49 different oximes, where 31 of them interact with just one protein, 13 with two proteins simultaneously, and 5 with three low-frequency proteins. The oximes showing the greatest interaction included three that were also present in the previous groups, which interacted with the proteins NR3C1, KDR, JAK2, FNTA, and CNR1. The three molecules studied by Mernyák [107] (S.O.1, S.O.2, and S.O.3; Figure 3A–C) had an opened steroidal nucleus E-ring. The study found that the hydroxyimino group did not play a significant role in forming the main interaction at the active site of three proteins, namely NR3C1, KDR, and FNTA (Figure 3A). Instead, it was observed that the aromatic ring was the primary coupling agent at the site. In the case of the FTNA protein, it was the acetyl group on the steroidal oxime that formed an interaction with the catalytic Zn2+ site of the protein. In contrast to the second (Figure 3B) and third structures (Figure 3C), the hydroxyimino group primarily interacts with the protein to form a hydrogen bond in the cases of NR3C1 and CNR1. These interactions suggest that the second molecule may play an agonist role in this pathway, in comparison to the key amino acids for activation (Phe170, Phe174, Phe177, Leu193, Thr197, Trp258, Trp279, Phe379, Ser383) [134]. However, the third molecule (Figure 3C) has the potential to inhibit any of the three proteins, which may explain its pronounced antiproliferative effect on CC cell lines.
Two estrogen derivative structures that exhibit triple-protein activity have been identified. The initial structure (Figure 3D) entails the formation of an estrone oxime, whereas the second structure (Figure 3E) involves the formation of an additional carbonyl group on the E-ring. These structures have JAK2 as a common protein and exhibit a polar environment in the E-ring, which forms a hydrogen bond at the catalytic site. Consequently, they have the potential to inhibit the activity of this enzyme. It is postulated that the oxime of estrone may act on the JAK3 protein by forming a hydrogen bond between the hydroxyl group at the C-3 and the hydroxyimino group, thereby enhancing the anchor of the active site. This suggests that the compound in question displays dual activity regarding the JAKs pathway. It has the potential to influence the KDR protein, which may result in a reduction in the angiogenesis of tumor cells, particularly those of the cervix. It is hypothesized that the α-carbonyl of the oxime derivative may inhibit STS protein activity. This is due to the rigidity of the α-carbonyl, which allows the aromatic ring to be coupled with calcium. Oxime is responsible for binding to the active site, which may result in the inhibition of STS protein activity. Upon interaction with the HCRTR2 protein, this molecule generates a polar type of interaction through the A- and D-rings.

3.2.2. Molecular Docking of Steroidal Oximes with Greater Interactions

The results of the coupling analysis identified eight proteins where steroidal oximes exhibit interactions that exceed the BCEs of reference ligands. Notably, five of the eight proteins have been isolated from each other and from the other proteins of interest, indicating a mono-targeted action with high specificity directed towards an antiproliferative effect. Conversely, the SRC, MDM2, and IGFR1 proteins show a strong correlation with one another. The NR1H3 protein represents the initial isolated target to interact with 37 steroidal oximes. Figure 4A depicts five representative structures of these steroidal oximes, illustrating the formation of a hydroxyimino group in the A, B, or D steroidal rings and the reference drug. The presence of the hydroxyimino group results in the generation of a polar environment surrounding the site, which subsequently increases the coupling energy. Furthermore, in certain instances it forms a hydrogen bond, exerting an antagonistic effect that obstructs the active site and prevents the binding of its endogenous ligands, which correspond to the amino acids Leu102, Ala103, Val118, Ile121, and Leu212 [136]. The oxime formed in the A- and B-rings facilitates polar interactions.
The analysis focused on the protein HSD11B, which is the second isolated target and plays a role in the modification of steroid hormones. A total of 44 steroidal oximes were identified that exhibited a higher BCE than the reference ligands. To reduce the biological activity and the production of hormone steroids, the analysis sought to identify steroidal oximes that could competitively inhibit the catalytic site of the enzyme. It was determined that the steroidal oximes with inhibitory potential were those that exhibited a hydrophobic environment in their core (Figure 4B). The majority of the identified oxime groups were those placed in the side chain or on the D-ring, while those present in the B-ring lacked polar groups in the remainder of the skeleton. This is because the endogenous substrates of this enzyme are hydrophobic, necessitating the involvement of steroidal oximes in this pathway. Conversely, the OPDR1 protein exhibited a site with a positively and negatively charged environment, resulting from the presence of Arg291, His301, Glu112, and Asp210 (Figure 4C). The steroidal oximes that were generated with a polar environment were found to be the most effective in binding to this site. The hydroxyimino group generates negatively charged interactions, and its polar environment allows for attraction by charges due to the presence of nitrogen and hydroxyl groups. However, one exception was observed: the steroidal oxime S.O.18 (Figure 4C) [137] generated a hydrophobic environment around the second oxime in the skeleton, indicating that a polar environment is necessary around the steroidal oxime to achieve interaction at the site.
In the active site of the NR1H4 protein (Figure 5A), the hydroxyimino group fulfills a dual function. It forms a hydrogen bond with His451 and Ser356, as well as a hydrophobic interaction around rings A or B, where it is present. It has been demonstrated that cholestane and androstane hydroxyamino derivatives exhibit the highest BCE interactions with this protein, due to their reduced active site. The former compacts its side chain towards the steroidal skeleton, thereby reducing its volume and occupying the active site. In the case of the type 2 cannabinoid receptor (Figure 5B), which has an apolar environment, most of the steroidal oximes exhibit a core comprising aromatic rings derived from estrone, either condensed or etherified with aromatic rings. These characteristics facilitate the formation of π–π interactions with Phe and Trp amino acids in the active site, resulting in interactions such as those observed between CBD and Phe87, Leu182, and Phe183 amino acids [138], which exhibit 75% to 92% similarity. This suggests the existence of an activation pathway that may contribute to the promotion of an anti-inflammatory response. The compounds S.O.9, S.O.13, and S.O.18, which present IC50 values around 30, 6.25, and 41.64 µM, respectively, demonstrate that the presence of oximes through the specific pathways NR1H3, HSD11B, OPDR1 as selective molecular targets result in another antiproliferative effect.
The proteins SRC, IGFR1, and MDM2 have been shown to be associated with each other (Figure 6). These proteins interact with 11 structures derived from androstane and estrogens. These structures present modifications in the D-ring and oxime. The modification is predominantly observed in rings A and D, as well as derivatives of ring D. These rings are opened either via the formation of nitriles or via the formation of an oxime resulting from the opening.
Regarding the SRC protein (Figure 6A), it is essential that it interacts with the cofactor for its inhibitory action [136], which occurs in a spatial context due to the polar interactions of the hydroxyimino group in each of the skeletons around Glu176 and Glu320. The formation of hydrogen bonds with Glu176 is a common occurrence in these types of interactions, which can occur through oxime hydroxyl or the C-3 hydroxyl. These findings indicate that hydroxy derivatives with a C-3 hydroxyl group exhibit enhanced inhibitory activity. Similarly, for the inhibition of IGFR1, a hydroxyl group (or polar group) is required at each end of the steroidal skeleton (Figure 6B). This is because the S.O.30 (Figure 6) [107] molecule does not comply with this combination and has the lowest BCE. To achieve anchorage in the active site and form hydrogen bonds with Met1052, Ser979, or Thr1053, the center of the structure must contain a hydrophobic core. In the inhibition of MDM2 protein (Figure 6C), interactions occur in a polar manner around the hydroxyl group. Some interactions are caused by hydrogen bonding at the site, and only 18% of the molecules with energy higher than the reference group are present with Try100 via the hydroxyl group, thereby inducing enhanced inhibition through an apoptotic effect via a triple system of SRC, MDM2, and IGFR1. This second group of proteins is attracted towards compounds with hydrophobic side chains with IC50 values less than 2 µM, such as HeLa, indicating the greater importance of presenting a greater antiproliferative effect in the inhibition of these (S.O.28, 10, 29, and 30.).

3.3. Target Selection via Ligand–Target Interactions and Structural Requirements

A detailed analysis of the set of targets associated with steroidal oximes identified the presence of two distinct subgroups. These represent potential targets in the design of new steroidal oximes, where nuclei that interact particularly in the JAK1, JAK2, and JAK3 system can generate selective or triple regulators of these proteins. The FNTA, STS, and HCRTR2 proteins exhibit minimal interactions but high specificity for the hydroxyimino group. In contrast to proteins that have a high frequency of interaction with steroidal oximes, it is the key hydroxyimino group that is primarily responsible for increasing the coupling energy in most cases. This phenomenon can be attributed to the formation of hydrogen bonds or the creation of polar environments. These molecules exhibit low selectivity due to their ability to interact with multiple targets. However, they exhibit distinct energies that facilitate selective interactions with specific groups, including SRC, MDM2, and IGFR1. Furthermore, these proteins have been observed to interact with NR1H3, HSB11B, OPDR1, NR1H4, and CNR2, which is a relatively uncommon occurrence.
The enrichment of pathways (Figure 7) such as corticosteroid receptor signaling, as well as responses to isoquinoline alkaloids and morphine, suggests that steroidal oximes may modulate key mechanisms related to inflammation, hormonal signaling, and cellular stress, all of which are known to influence cervical cancer progression and therapeutic resistance. These associations support the potential role of these compounds as multitarget agents in the context of cervical cancer.

3.4. ADME and Molecular Dynamic Studies

However, a multitarget effect has the deficiency of the presence of adverse effects so it is necessary to consider the properties of administration, distribution, metabolism and excretion in the selection criteria to improve the selection of these. In Table 3, you can see the main properties associated with these, highlighting a great similarity between them and mostly falling within what is recommended for them, which can be seen in the violations to lipinski, ghose, veber egan and muegge that mostly present 0, 1 and 2, giving guidelines for discarding oximes with too many violations, as well as those that permeate the blood–brain barrier to avoid effects on the central nervous system, where they highlight that oximes with lipophilicity in the order of 3 to 4 in log p give it the amphipathic property to cross, recommending more lipophilic oximes.
Finally, by showing that the molecules have great potential as inhibitors of the aforementioned enzymes, particularly with a multi and mono target approach, molecular dynamics studies were carried out with the best in each case, in order to validate the molecular docking studies; these were modeled at 120 ns under conditions of 0.15 M NaCl, 300 K and pressure of 1.01325 Bar, as described in the previously reported protocol [139]. In Figure 8, the root mean square deviation (RMSD) values for the multitarget and single target analysis as a function of time at 120 ns can be observed; the protein–ligand contact analysis, protein–ligand contact histogram, RMSF and P-SSE histogram are found in Supplementary Material Figures S27–S31.

4. Discussion

The investigation of enhanced therapeutic modalities for cervical cancer (CC) has led to an examination of steroidal oximes [28]. These molecules possess biological properties that facilitate the regulation of cellular processes, including cell growth, cell death, cancer metastasis, and angiogenesis [40,135]. This suggests that they may serve as regulators of crucial processes in tumor biology and are promising candidates for therapeutic intervention [20]. A group of 176 steroidal oximes [21,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76] reported to have activity against CC were analyzed in the search for molecular targets, revealing that 26 molecular targets play a role in the development of CC, influencing processes such as proliferation, metastasis, apoptosis, and immune system evasion. Some of these proteins are involved in common signaling pathways, providing insight into how steroidal oximes affect CC.
In the analysis of the biological activity of steroidal oximes, the molecular targets were classified into three groups. The first group was excluded from further analysis as it did not demonstrate interactions that were comparable to those observed with reference ligands, possibly due to steric hindrance, a lack of key functional groups, or low binding affinity, which may have limited their ability to effectively interact with the target binding sites. Nevertheless, the proteins in this group have been associated with proliferation [102], metastasis, immune system evasion [106], and prognostic value [140]. It is therefore recommended that further analysis be conducted using different steroid derivatives with enhanced binding capabilities to these proteins. Therefore, it is recommended that further analysis be undertaken using different steroid derivatives that enhance the BCE with these proteins. The second and third groups comprise proteins that interact with more than one steroidal oxime, showing higher BCEs than the reference ligand. These groups include proteins associated with chemoresistance [93,94], cell survival [92], tumor progression [140], invasion [92], proliferation [92,140], angiogenesis [93,94], apoptosis [85,92], metastasis [92,96], radioresistance [88,141], and immune system avoidance [90] in CC. However, in this group, possible adverse effects must be considered, since having more than one molecular target creates a possible cross-interaction, so a prior analysis of administration, distribution, metabolism, excretion, and toxicity properties must be considered for a better selection of candidates for future biological evaluations.
In the second group of molecular targets, analysis has revealed that JAK2, FNTA, CNR1, NR3C1, and KDR exhibit heightened interactions in comparison to the other proteins. These proteins have not been previously reported to exhibit interrelated activities. However, their independent biological activities contribute to the persistence of CC cells. JAK2 is a signal transducer that phosphorylates STAT, thereby enabling dimerization and nuclear translocation. In the nucleus, it acts as a gene transcription factor that influences the activity of white blood cells [142,143]. FNTA is a highly expressed protein in a variety of cancers, including CC. The inhibitory potential of steroidal oximes on this protein suggests an effect in increasing TNF-α and CD8-T activity, and decreasing invasion, metastasis, proliferation, and metabolic changes through NF-κβ, CD44, and Akt/mTOR/HIF1α. The inhibitory potential of steroidal oximes on this protein indicates that they may increase TNF-α and CD8-T activity while simultaneously decreasing invasion, metastasis, proliferation, and metabolic changes through NF-κβ, CD44, Akt/mTOR/HIF1α, and MMP1 [131,144,145]. However, NR3C1 has been identified as a protein with predictive value in the progression of CC. Its overexpression has been demonstrated to promote chemoresistance to apoptosis-inducing drugs such as cisplatin through the suppression of p38 [106,146]. KDR is a protein that supports angiogenesis, linking it to the development of CC and poor overall survival. It has been reported that KDR inhibition suppresses the activity of STAT3 and BCL-2, inhibiting angiogenesis and tumor growth in cases of osteosarcoma [147,148]. Therefore, it can be inferred that steroidal oximes interacting with these proteins can serve as targeted therapies along with current therapeutic agents.
The proteins of the third group demonstrated interaction with most steroidal oximes, exceeding the BCE values of reference ligands. This suggests that they are the primary molecular targets through which steroidal oximes exert their anticancer activity. NR1H3, which is also known as Liver X Receptor alpha (LXRα), is a protein that is upregulated in CC. It promotes metastasis and cell mobility through the secretion of clusterin, leading to chemoresistance to therapies such as cisplatin, doxorubicin, and camptothecin [148]. However, IGFR1 possesses a kinase domain that activates the PI3K/AKT/MTOR and RAS/RAF/MEK/ERK pathways, which are associated with the survival and proliferation of CC cells [149,150]. HSD11B converts cortisone into cortisol, which suppresses the immune system’s activity. It plays a role in controlling infectious diseases, including CC and its precursor lesions [151,152]. OPRD1 is associated with the activation of EGFR, which in turn activates the MAPK1, JAK2/STAT, and mTOR pathways, all of which are associated with survival, cell proliferation, and angiogenesis [96,133]. MDM2 is an E3 ligase ubiquitin that targets P53/TP53, allowing an uncontrolled cell cycle and promoting cervical carcinogenesis. Decreasing MDM2 levels arrests the cell cycle, reduces cell growth, and activates apoptosis [153,154]. SRC phosphorylation increases glycolysis through the activation of HK1/2, promoting tumorigenesis and increased ROS levels. In addition, Src functions as an intermediary in the activation of JAK2, PI3K, and MEK1/2, key proteins for cell proliferation [155]. SRC is considered a prognostic marker in the recurrence of CC [91,156].
The molecular targets previously described are highly important for their roles in the development, maintenance, and persistence of CC cells. Identifying a group of compounds that can interact with these molecules and have the potential to inhibit them, such as steroidal oximes, suggests a potential source of agents that can contribute to current therapies. In comparison with drugs commonly used for the treatment of cervical cancer, such as cisplatin, paclitaxel, and topotecan, the steroidal oxime derivatives demonstrated a multi-target activity profile. However, a multi-target effect presents a greater possibility of negative effects, so these must be considered prior to selection. This is necessary for the prediction of these properties and determination of the routes of administration, distribution, metabolism, and excretion to increase the selection parameters of candidates for new compounds against CC. Steroidal oximes exhibit high interaction with other two molecular targets, NR1H4 and CNR2. NR1H4 is a negative aromatase regulator that synthesizes estrogen, favoring tumorigenesis and the progression of CC. Its activation inhibits estrogen signaling and induces cellular apoptosis [157,158]. Further, CNR2 promotes apoptosis in CC cells by regulating the expression of Bax and Bad and reducing BCL-2 expression. Studies have evaluated CNR2 agonists, such as AM1241, which induce autophagy and apoptosis in SiHa cells through the activation of the Pink1/Parkin pathway [159,160], Furthermore, with the multi-target approach [161], the need to analyze the probability of adverse effects as well as their ADME properties should be highlighted, finding that for the oximes in common they have properties within the accepted parameters with minimal violations, except for those with Log p between 3 and 4, which being lower allows the transfer of the BBB, increasing the probability of adverse effects. The root mean square deviation (RMSD) analysis demonstrated that the IGFR, SRC and MDM2 with S.O.12 complex exhibited the highest structural stability throughout the simulation, with RMSD values remaining around 2.0, 0.5 and 1.0 A, respectively, indicating minimal conformational changes (Figure 8A); for single-target studies, a similar behavior was obtained, although in this case the interval variations range from 0.5 to 1.5 A. The root means square fluctuation (RMSF) analysis of individual amino acid residues revealed that the highest flexibility was observed in the N- and C-terminal regions of the proteins, which is consistent with the expected structural characteristics (See Supplementary material). The average RMSF values for the central regions of the protein remained below 0.5 nm, indicating relative rigidity and demonstrating again the high affinity of these oximes for the selected molecular targets.
Steroidal oximes are expected to act as agonists for these molecular targets, increasing the activity of these proteins and promoting anticancer effects. The results presented here serve as a starting point for further in vitro studies in cellular models. This study will contribute to the search for new steroid-type therapeutic agents, guiding subsequent analyses on the mechanism of action, IC50, particularly in the HeLa and Siha cell line, and the biological activities of steroidal oximes. Additionally, the results of this study will facilitate the exploration of structural modifications and the development of new derivatives of steroidal oximes that demonstrate improved results.

5. Conclusions

The in silico analysis of steroidal oximes has identified potential molecular targets that regulate biological processes in CC cells. The results indicate that these steroidal oximes affect tumor progression, cell proliferation, metastasis, and the inhibition of apoptosis, interacting with proteins such as JAK2, NCR1, NR3C1, KDR, and FTNA. Of these, FTNA stands out as the only target that directly interacts with the hydroxyimino group in its catalytic site, suggesting its potential as a mediator for inducing cellular apoptosis. Moreover, the MDM2, IGF1R, and SRC proteins were identified as key targets through which steroidal oximes exert their effects, particularly SRC, which plays a crucial role in the activation of cell survival pathways. These findings provide a promising avenue for future research relating to the development of more efficacious targeted therapies for cervical cancer. However, it is necessary to include the prediction of ADMETx properties to improve screening, especially in multi-target cases, to reduce possible adverse effects, particularly lipophilicity and the ability to cross the blood–brain barrier.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/scipharm93030036/s1, Table S1. Database of steroidal oximes with anticancer effects vs. cervical cancer. Table S2. RMSD and 3D superposition of each protein validation for molecular docking i. Figure S1. Top 9 best steroidal oxime couplings for each protein via molecular docking. Figure S2. Top 9 best steroidal oximes couplings for CNR1 by molecular docking. Figure S3. Top 9 best steroidal oximes couplings for CNR2 by molecular docking. Figure S4. Top 9 best steroidal oximes couplings for CRFIR by molecular docking. Figure S5. Top 9 best steroidal oximes couplings for ESR2 by molecular docking. Figure S6. Top 9 best steroidal oximes couplings for FNTA by molecular docking. Figure S7. Top 9 best steroidal oximes couplings for HCRTR2 by molecular docking. Figure S8. Top 9 best steroidal oximes couplings for HSD11B1 by molecular docking. Figure S9. Top 9 best steroidal oximes couplings for IGFR by molecular docking. Figure S10. Top 9 best steroidal oximes couplings for JAK1 by molecular docking. Figure S11. Top 9 best steroidal oximes couplings for JAK2 by molecular docking. Figure S12. Top 9 best steroidal oximes couplings for JAK3 by molecular docking. Figure S13. Top 9 best steroidal oximes couplings for KCHN2 by molecular docking. Figure S14. Top 9 best steroidal oximes couplings for KDR by molecular docking. Figure S15. Top 9 best steroidal oximes couplings for NR1H3 by molecular docking. Figure S16. Top 9 best steroidal oximes couplings for MDM2 by molecular docking. Figure S17. Top 9 best steroidal oximes couplings for NR3C1 by molecular docking. Figure S18. Top 9 best steroidal oximes couplings for NRIH4 by molecular docking. Figure S19. Top 9 best steroidal oximes couplings for OPRD1 by molecular docking. Figure S20. Top 9 best steroidal oximes couplings for PTPN1 by molecular docking. Figure S21. Top 9 best steroidal oximes couplings for RORC by molecular docking. Figure S22. Top 9 best steroidal oximes couplings for SRC by molecular docking. Figure S23. Top 9 best steroidal oximes couplings for STS by molecular docking. Figure S24. Top 9 best steroidal oximes couplings for VDR by molecular docking. Figure S25. Molecular Dynamics studies of best steroidal oximes. Figure S26. (A) RMSD for multi-target S.O.12 and S.O.12 RMSF in (B) IGFR1 B) MDM2. C) SRC. Figure S27. LP-Contacts 2D Summary, PL-Contacts Histogram and P-SSE Histogram for S.O.12 (A) IGFR1 (B) MDM2. Figure S28. RMSD and RMSF for Single-Target (A) S.O.1 in KDR, (B) S.O.1 inNR3C1, and (C) S.O.18 in FTNA. Figure S29. LP-Contacts 2D Summary, PL-Contacts Histogram and P-SSE Histogram for S.O.1 in KDR. Figure S30. LP-Contacts 2D Summary, PL-Contacts Histogram and P-SSE Histogram for S.O.18 in FTNA. Figure S31. LP-Contacts 2D Summary, PL-Contacts Histogram and P-SSE Histogram for S.O.1 in NR3C1.

Author Contributions

C.A.S.-V.: data curation, formal analysis, investigation, methodology, validation, visualization, writing—review and editing. A.C.-C.: conceptualization, data curation, formal analysis, investigation, methodology, validation, visualization, writing—original draft, writing—review and editing. J.O.-N.: funding acquisition, investigation, methodology, project administration, supervision, visualization, writing—review and editing. J.S.-R.: conceptualization, funding acquisition, methodology, project administration, supervision, visualization, writing—review and editing. B.I.-A.: conceptualization, funding acquisition, methodology, project administration, supervision, visualization, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Consejo Nacional de Humanidades, Ciencias y Tecnologías, México (Grants FORDECYT-PRONACES/1717349/2020 (J.O.N.)). The Schrödinger License was supported by the National Council of Science and Technology of México (CONAHCYT; Grants PRONACES/317580/2021 (J.S.R.)).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

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

Acknowledgments

Carlos A. Sanchez Valdeolivar was the recipient of doctoral fellowships from CONACYT (grant: 760870/CVU: 746206). Alan Carrasco Carballo acknowledges FORDECYT-PRONACES/1717349/2020 for postdoctoral fellowships.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Identification and interaction network of molecular targets of steroidal oximes for cervical cancer. (A) Graph showing the molecular targets identified for steroidal oximes with a frequency greater than 30% according to STP analysis. Blue bars indicate targets reported in association with cervical cancer. Yellow bars are targets associated with other conditions, by frequency at p ≠ 0. (B) Interactome for cervical cancer-associated targets and steroidal oximes, with a PPi enrichment p-value of 2.49 × 10−13, avg local clustering coefficient of 0.67, and average node degree of 3.92. The nodes represent proteins identified as molecular targets related to cervical cancer, and the edges indicate protein–protein interactions obtained from the STRING database.
Figure 1. Identification and interaction network of molecular targets of steroidal oximes for cervical cancer. (A) Graph showing the molecular targets identified for steroidal oximes with a frequency greater than 30% according to STP analysis. Blue bars indicate targets reported in association with cervical cancer. Yellow bars are targets associated with other conditions, by frequency at p ≠ 0. (B) Interactome for cervical cancer-associated targets and steroidal oximes, with a PPi enrichment p-value of 2.49 × 10−13, avg local clustering coefficient of 0.67, and average node degree of 3.92. The nodes represent proteins identified as molecular targets related to cervical cancer, and the edges indicate protein–protein interactions obtained from the STRING database.
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Figure 2. Distribution of binding coupling energy (BCE) values between molecular targets and steroidal oximes/reference inhibitors (blue line) by protein. Box plot shows the distribution of binding coupling energy values, with the median, interquartile range (IQR), and outliers. The inhibitors and endogenous ligands are listed in Table 2.
Figure 2. Distribution of binding coupling energy (BCE) values between molecular targets and steroidal oximes/reference inhibitors (blue line) by protein. Box plot shows the distribution of binding coupling energy values, with the median, interquartile range (IQR), and outliers. The inhibitors and endogenous ligands are listed in Table 2.
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Figure 3. Two-dimensional interaction diagram showing the lowest interaction potential of steroidal oximes. Each subsection corresponds to a steroidal oxime reported with anti-CC activity that interacts weakly with target proteins associated with cervical cancer. The colors assigned to each amino acid residue are indicated in the lower section. (A) S.O.1 interacting with NR3C1, KDR, and FTNA. (B) S.O.2 interacting with NR3C1, KDR, and CNR1. (C) S.O.3 interacting with NR3C1, KDR, and JAK2. (D) S.O.4 interacting with KDR, JAK2, and JAK3. (E) S.O.5 interacting with JAK2, STS, and HCRTR2. S.O.: steroidal oxime. Referencies: S.O.1 [107], S.O.2 [107], S.O.3 [107], S.O.4 [135], S.O.5 [46].
Figure 3. Two-dimensional interaction diagram showing the lowest interaction potential of steroidal oximes. Each subsection corresponds to a steroidal oxime reported with anti-CC activity that interacts weakly with target proteins associated with cervical cancer. The colors assigned to each amino acid residue are indicated in the lower section. (A) S.O.1 interacting with NR3C1, KDR, and FTNA. (B) S.O.2 interacting with NR3C1, KDR, and CNR1. (C) S.O.3 interacting with NR3C1, KDR, and JAK2. (D) S.O.4 interacting with KDR, JAK2, and JAK3. (E) S.O.5 interacting with JAK2, STS, and HCRTR2. S.O.: steroidal oxime. Referencies: S.O.1 [107], S.O.2 [107], S.O.3 [107], S.O.4 [135], S.O.5 [46].
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Figure 4. Two-dimensional interaction diagram of representative steroidal oximes. (A) NR1H3, (B) HSD11B, (C) OPDR1 protein. S.O.: steroidal oxime. References: S.O.2 [100], S.O.3 [107], S.O.6 [21], S.O.7 [69], S.O.8 [58], S.O.9 [46], S.O.10 [61], S.O.11 [46], S.O.12 [135], S.O.13 [61], S.O.14 [57], S.O.15 [69], S.O.16 [65], S.O.17 [61], S.O.18 [137].
Figure 4. Two-dimensional interaction diagram of representative steroidal oximes. (A) NR1H3, (B) HSD11B, (C) OPDR1 protein. S.O.: steroidal oxime. References: S.O.2 [100], S.O.3 [107], S.O.6 [21], S.O.7 [69], S.O.8 [58], S.O.9 [46], S.O.10 [61], S.O.11 [46], S.O.12 [135], S.O.13 [61], S.O.14 [57], S.O.15 [69], S.O.16 [65], S.O.17 [61], S.O.18 [137].
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Figure 5. Two-dimensional interaction diagram in active site: (A) NR1H4 and (B) CNR2. S.O.: steroidal oxime. References: S.O.10 [61], S.O.19 [71], S.O.20 [50], S.O.21 [70], S.O.22 [46], S.O.23 [54], S.O.24 [52], S.O.25 [46], S.O.26 [107], S.O.27 [69].
Figure 5. Two-dimensional interaction diagram in active site: (A) NR1H4 and (B) CNR2. S.O.: steroidal oxime. References: S.O.10 [61], S.O.19 [71], S.O.20 [50], S.O.21 [70], S.O.22 [46], S.O.23 [54], S.O.24 [52], S.O.25 [46], S.O.26 [107], S.O.27 [69].
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Figure 6. Two-dimensional interaction diagram in the active site. (A) SRC, (B) IGFR1, (C) MDM2. S.O.: steroidal oxime. References: S.O.10 [61], S.O.12 [135], S.O.28 [35], S.O.29 [135], S.O.30 [107], S.O.31 [65], S.O.32 [53].
Figure 6. Two-dimensional interaction diagram in the active site. (A) SRC, (B) IGFR1, (C) MDM2. S.O.: steroidal oxime. References: S.O.10 [61], S.O.12 [135], S.O.28 [35], S.O.29 [135], S.O.30 [107], S.O.31 [65], S.O.32 [53].
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Figure 7. KEGG pathway enrichment analysis of predicted molecular targets for steroidal oximes. The bar plot displays the top enriched pathways ranked by gene count and statistical significance (−log10 p-value 0.05). Color gradient indicates the level of significance, with red tones representing higher enrichment.
Figure 7. KEGG pathway enrichment analysis of predicted molecular targets for steroidal oximes. The bar plot displays the top enriched pathways ranked by gene count and statistical significance (−log10 p-value 0.05). Color gradient indicates the level of significance, with red tones representing higher enrichment.
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Figure 8. The root mean square deviation (RMSD) over 100 ns of simulation: (A) multitarget in complexes with S.O.12: (B) single-target best oximes in KDR, FTNA and NR3C1.
Figure 8. The root mean square deviation (RMSD) over 100 ns of simulation: (A) multitarget in complexes with S.O.12: (B) single-target best oximes in KDR, FTNA and NR3C1.
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Table 1. Main molecular targets for steroidal oximes obtained via STP and reported to be associated with cervical cancer.
Table 1. Main molecular targets for steroidal oximes obtained via STP and reported to be associated with cervical cancer.
TargetUniProt IDReported Data on Cervical Cancer (CC)Reference
ALKQ9UM73Induces cell migration and cancer survival. Together with IGF-1R, ALK can activate pathways related to cancer progression (Akt and Stat3).[79,80,81]
CNR1P21554Present in CC cell lines (HeLa, CaSki, C33A). Its overexpression suggests a protective effect.[82]
CNR2P34972CBR2 overexpression has been reported to promote apoptosis in CC CaSki cells.[83]
CRHR1P34998Associated with immuno-escape from CC cells by decreasing NKG2D ligand.[82]
ESR2Q92731Related to the progression of CC. Increases along with the transcription factor BORIS as the degree of the lesion increases (LSIL, HSIL, SC).[84]
FNTAP49354Inhibition of farnesyl transferase protein induces apoptosis in SiHa CC cells.[85]
HCRTR2O43614Related to migration and invasion of CC.[86]
HSD11B1P28845Identified in primary cancerous tissue from CC.[48]
HRH1P35367Promotes the proliferation of HeLa cisR cells.[87]
IGF1RP08069Induces autophosphorylation and activation of specific tyrosine kinase residues, initiating signaling cascades such as Ras/Raf/MAPK and PI3K, involved in resistance to radiotherapy and cell survival.[88,89]
JAK1P23458Takes part in the evasion of the immune system by HPV+ CC cells.[90]
JAK2O60674Necessary for activation of the STAT3 pathway and inhibition of apoptosis. Involved in the proliferation and survival of CC cells. Promotes invasion and metastasis by activating REX1.[91,92]
JAK3P52333Activates the transcription factor STAT, taking part in chemoresistance, proliferation, anti-apoptosis, angiogenesis, migration, invasion, and the Warburg effect.[93,94]
KCNH2Q12809Expressed in HeLa cells of CC. It has been related to invasion and metastasis in other cancers.[95]
KDRP35968Endothelial cell germination increased vascular permeability; expression of tissue matrix metalloproteinases (MMPs). Regulates EMT-linked stemming in CC cells via the Akt/GSK3β/β-Catenin and Snail pathway. More related to progress from CIN I to III.[96,97,98]
MDM2Q00987Overexpressed in CC cells. Inhibits p53 through ubiquitination and degradation in the proteasome.[99]
NR1H3Q13133O-GlcNAcylation increases LXR expression in CC, upregulating sCLU transcription related to proliferation and drug resistance.[84]
NR1H4Q96RI1Decreased in CC. Its overexpression inhibits the proliferation of CC cells by increasing p14ARF, MDM2, and p53.[100]
NR3C1P04150Expressed in cervical carcinoma tissue. HPV sequences can bind to translocate to the nucleus.[101]
OPRD1P41143Morphine stimulates the growth of C33A and CaSki CC cells through opioid receptors.[96]
PTPN1P18031Overexpressed in CC; associated with proliferation, migration, invasion, and EMT.[102,103]
RORCP51449Overexpressed in CC. Related to the polarization of Th22 and Th17 cells, which favor the development of solid tumors.[104]
SRCP12931Related to CC progression.[105]
STSP08842Induces the Wnt/B catenin and EMT pathway through Twist1 and HIF-1alpha. Promotes tumorigenesis and inhibits apoptosis in CC.[88]
TRPV1Q8NER1Related to tumor immunity through T cells.[106]
VDRP11473Its elevated expression in patients with cervical CC makes the risk of incidence 2 times higher.[107]
Table 2. Reference ligands and proteins used for molecular docking.
Table 2. Reference ligands and proteins used for molecular docking.
Reference LigandsPubChem IDTarget ProteinUniProt IDPDB IDReference
NVP-TAE68416038120ALKQ9UM732XB7[111]
CBD644019CNR1P215545TGZ[112]
CBD644019CNR2P349725ZTY[113]
CP-3763959862166CRHR1P349984K5Y[114]
Estradiol5757ESR2Q927315TOA[115]
PD0360271266FNTAP493541LD8[116]
Suvorexant24965990HCRTR2O436144S0V[105]
Arylsulfonylpiperazine Inhibitor735815HSD11B1P288453CZR[89]
Doxepin667477HRH1P353673RZE[97]
Benzimidazole inhibitor5798IGFR1P080692OJ9[117]
Upadacitinib58557659JAK1P234584EHZ[118]
Upadacitinib58557659JAK2O606743KRR[119]
Baricitinib44205240JAK3P523331YVJ[101]
Zonisamide5734KCNH2Q128096SYG[120]
Vatalanib151194KDRP359684AGD[121]
Imidazoline inhibitor68156MDM2Q009871RV1[84]
Dexametasone5743NR1H3Q131335AVI[100]
Tetrahydroazepinoindole66694474NR1H4Q96RI13L1B[122]
Stigmasterol5280794NR3C1P041504CSJ[123]
Naltrexone5360515OPRD1P411436PT2[124]
4-phosphonooxybenzyl-[4-phosphonooxy] benzene1757PTPN1P180311AAX[99]
Digoxin2724385RORCP514493B0W[125]
PP24878SRCP129311FMK[126]
Dehydroepiandrosterone sulfatase0009025621STSP088421P49[127]
Capsaisin1548943TRPV1Q8NER17LR0[128]
GW07429934458VDRP114733OGT[129]
Table 3. ADME prediction for multitarget steroidal oximes selected.
Table 3. ADME prediction for multitarget steroidal oximes selected.
Oxime#Aromatic Heavy AtomsFraction Csp3#Rotatable Bonds#H-Bond Acceptors#H-Bond DonorsLog pLog sGI AbsorptionBBB PermeantPgp SubstrateLog Kp (cm/s)LipinskiGhoseVeberEganMuegge
S.O.2170.488515.31−6.57HighNoYes−4.7113011
S.O.3120.426315.53−6.19HighNoYes−4.1411011
S.O.600.795316.42−7.18LowNoNo−3.4113011
S.O.760.728606.18−7.22LowNoYes−4.3624011
S.O.800.785425.71−7.14LowNoNo−3.312011
S.O.960.562722.18−4.00HighNoYes−6.6100000
S.O.1060.614525.81−6.36HighNoYes−4.3211011
S.O.1160.560422.81−4.16HighYesYes−5.5800000
S.O.1260.610323.38−3.96HighYesYes−5.6300000
S.O.1360.624423.38−3.96HighYesYes−5.6300000
S.O.1400.740214.36−5.08HighYesNo−4.1310001
S.O.1560.725525.34−6.52HighNoYes−4.6513011
S.O.1660.61225.34−6.52HighNoYes−4.6513011
S.O.1760.613425.75−6.69LowNoNo−4.2411011
S.O.1800.850624.53−5.96HighNoYes−5.3802001
S.O.1900.965435.25−6.62HighNoNo−3.9612001
S.O.2060.728317.4−8.49LowNoNo−3.2424011
S.O.2100.950323.61−4.22HighYesYes−5.3600000
S.O.2260.560422.81−4.16HighYesYes−5.5800000
S.O.2300.897615.53−7.20LowNoYes−3.9614011
S.O.2400.897425.12−6.52HighNoYes−4.4513011
S.O.25120.485504.76−5.73HighYesYes−5.2800001
S.O.26120.438405.81−6.36HighNoYes−4.3211011
S.O.2760.717615.78−7.00LowNoYes−4.524011
S.O.2800.752522.6−3.36HighNoYes−6.6500000
S.O.2960.50323.32−3.88HighYesYes−5.6900000
S.O.3060.654314.51−5.13HighYesNo−4.3800001
S.O.3160.61314.51−5.13HighYesNo−4.3800001
S.O.3200.885514.49−5.1HighNoNo−5.4600000
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Sánchez-Valdeolivar, C.A.; Carrasco-Carballo, A.; Organista-Nava, J.; Sandoval-Ramírez, J.; Illades-Aguiar, B. Steroidal Oximes and Cervical Cancer: An In Silico Mechanistic Pathway Approach. Sci. Pharm. 2025, 93, 36. https://doi.org/10.3390/scipharm93030036

AMA Style

Sánchez-Valdeolivar CA, Carrasco-Carballo A, Organista-Nava J, Sandoval-Ramírez J, Illades-Aguiar B. Steroidal Oximes and Cervical Cancer: An In Silico Mechanistic Pathway Approach. Scientia Pharmaceutica. 2025; 93(3):36. https://doi.org/10.3390/scipharm93030036

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Sánchez-Valdeolivar, Carlos Antonio, Alan Carrasco-Carballo, Jorge Organista-Nava, Jesús Sandoval-Ramírez, and Berenice Illades-Aguiar. 2025. "Steroidal Oximes and Cervical Cancer: An In Silico Mechanistic Pathway Approach" Scientia Pharmaceutica 93, no. 3: 36. https://doi.org/10.3390/scipharm93030036

APA Style

Sánchez-Valdeolivar, C. A., Carrasco-Carballo, A., Organista-Nava, J., Sandoval-Ramírez, J., & Illades-Aguiar, B. (2025). Steroidal Oximes and Cervical Cancer: An In Silico Mechanistic Pathway Approach. Scientia Pharmaceutica, 93(3), 36. https://doi.org/10.3390/scipharm93030036

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