Design and in silico assessment of quinoxaline platinum complexes as ATPase competitive topoisomerase inhibitors

doi:10.21203/rs.3.rs-4898786/v1

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Design and in silico assessment of quinoxaline platinum complexes as ATPase competitive topoisomerase inhibitors

https://doi.org/10.21203/rs.3.rs-4898786/v1

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The topoisomerase TOP2 enzyme is reliant on ATP hydrolysis for DNA relegation, when the ATPase domain is competitively inhibited the enzymatic process is halted and at stable DNA lesion results. This leads to increased apoptotic processes. Metal based topoisomerase inhibitors offer a unique perspective due to their greater diversity of molecular geometries, electrostatic charge and valencies compared with organic based inhibitors. To this effect, a range of platinum (II) complexes were designed and assessed in silico for their ability to competitively inhibit the TOP2 ATPase domain. The ligands were derived from the lead compound XK469 with modifications made on the quinoxaline core which was truncated to include different amino acid groups coordinated to a variety of platinum ions and secondary ligands. Binding energies were calculated for the interaction of the ligands and their complexes with the TOP2 ATPase domain and compared to binding energies for XK469 and ATP with the TOP2 ATPase domain. Platinum coordination was found to be beneficial with the majority of complexes demonstrating a higher binding energy with the TOP2 ATPase domain compared with the lead XK469 compound with 3 complexes exhibiting higher binding energy than the target ATP molecule. The results support two design strategies to improve the affinity for XK469 derivatives for the TOP2 ATPase domain, the first being the coordination of large secondary ligands (2,2'‑bipyridine and 1,10-phenanthroline) in close proximity to the aromatic quinoxaline group, and the second being the coordination of smaller ethylenediamine secondary ligand to a hydrophilic terminus.

Topoisomerase inhibitor

Platinum

In Silico

XK469

Cancer is a disease of unregulated cell replication which is driven by many cellular processes that can be targeted for therapeutic intervention. One such factor are topoisomerase enzymes which play a critical role by resolving DNA torsion to facilitate duplication and translation of genetic materials [1-4]. Topoisomerase enzymes form a complex with DNA and then either cleave one phosphate backbone strand to allow the strand to unwind, as is the case for topoisomerase I enzymes (TOP1), or cleave both strands and pass a loop of DNA through the resulting gap, as is the case for topoisomerase II (TOP2) α and β enzymes (TOP2A and TOP2B). The final stage of this process is the religation of the DNA strands and dissociation of the topoisomerase from the DNA [5]. Should the function of either TOP1 or TOP2 be prevented, the unresolved enzyme-DNA complex results in a DNA lesion, the accumulation of which eventually triggers apoptotic pathways [6-9]. When TOP2 catalyses the process, the re‑ligation step is dependent on ATP hydrolysis [10-12]. As such, competitive inhibition of the TOP2 ATPase domain halts the enzymatic process and results in a stable DNA lesion. Furthermore, the replicative and transcriptional stress present in cancer cells results in the upregulation of topoisomerases. This results in a magnifying factor in the effectiveness of topoisomerase inhibiting treatments, the outcome of which is an increased number of DNA lesions and an accelerated activation of apoptotic pathways [13, 14]. While the efficacy of topoisomerase inhibitors, such as daunorubicin and doxorubicin, has placed them on the World Health Organisation’s list of essential medicines [15], these compounds can still cause potentially fatal cardiomyopathy amongst other side effects [16]. As such, there is still an urgent and largely unmet need for improved anticancer treatments with enhanced efficacy and reduced side effects [16-18].

Computational methods which facilitate in silico screening have become a routine first-step in most drug discovery programs. This strategy informs synthetic chemists what molecules they should be pursuing based on their likelihood of drug-target interactions [15], as well as avoiding troublesome molecular scaffolds which can be eliminated using a variety of in silico filters [19]. An example of a molecule which has benefited from in silico modelling to enhance activity is the previously reported TOP2B ATPase competitive inhibitor, 2-(4-((7-chloroquinoxalin-2-yl)oxy)phenoxy)propanoic acid (XK469).

Lead XK469 has demonstrated efficacy against colorectal, pancreatic, and mammary adenocarcinoma in preclinical trials, but was withdrawn from testing due to causing myelosuppression [20, 21]. The XK469 pharmacophore has been thoroughly interrogated, with an extensive structure activity relationship dataset available [21-26]. Specifically, the quinoxaline backbone, hydroquinone linker and a terminal carboxylic acid (Figure 1) have been identified as being crucial to the activity of XK469 for TOP2 ATPase inhibition. Xia et al. used in silico docking to reveal binding patterns and interactions of XK469 derivatives with the TOP2 ATPase domain [27]. This work showed that derivatives capable of more H-bonding and hydrophobic interactions had improved anti-proliferative potencies, as shown in Figure 1.

While previous studies have modified functional groups and the backbone of XK469, in this study we wanted to explore the effect of including a metal complex to access a greater diversity of molecular geometries, electrostatic charge and valencies. Such a strategy was presented in the review by Gaikwad et al. which discussed how metal complexed topoisomerase inhibitors have shown promise through increased selectivity for Type I and II topoisomerases [28]. Hence, we propose that metal complex analogues of XK469 will achieve the enhanced interaction required for improved anti-proliferative activities. To aid the metal complexes design, an in silico approach was used to explore how the introduction of a metal binding site into the overall structure of XK469 would alter interactions with the ATPase domain, Figure 1. Design considerations included point of functionalisation and the choice of secondary ligands. In this study we selected platinum (II) as the metal ion for complexation, as it is used in anticancer drugs (such as cisplatin, oxaliplatin and phenanthriplatin) [29-31], and provides a square planar coordination geometry that would encourage coordinated ligands to closely interact with the domain surface, as the lack of axial ligands would not sterically hinder such interactions.

At the time of this study, the location of the TOP2B ATPase domain had not been discovered, with previous studies substituting for the TOP2A ATPase domain, due to the similarities in structure, sequence and catalytic properties between the two [32–34]. As such, this study uses the TOP2A ATPase domain for its molecular modelling. Interactions between XK469 analogues and the topoisomerase IIα (TOP2A) ATPase domain were modelled using AutoDock (version 4.2.6) with the graphical user interface AutoDock tools (version 1.5.6).

A model of the TOP2A enzyme crystal structure (PDB ID: 1ZXM) was obtained from the Research Collaboratory for Structural Bioinformatics protein databank (RCSB PDB). Models of inhibitor compounds were generated using the NIH online Simplified Molecular-Input Line-Entry System (SMILES) translator and structure file generator, before conversion to the pdbqt file format with Open Babel GUI software (version 3.1.1).

The TOP2A crystal structure was modified by the removal of adenylyl-imidodiphosphate (AMPPNP) molecules, magnesium cofactors and associated H₂O molecules that were included in the model. Non-polar hydrogens were merged with the carbons of methyl and methylene groups to form united atoms [35]. Following preparation of the TOP2A structure, an area previously identified as the ATPase domain [22] was identified as a grid (80 × 80 × 80 points, spaced at 0.375 Å), centred on Ser149 (located at 38.217 x-axis, − 4.812 y-axis, 40.737 z-axis).

Docking simulations were performed using a Lamarckian genetic algorithm with 150 runs, a population of 300, 2.5 × 10⁶ evaluations and 2.7 × 10⁴ generations, with all other parameters kept as standard and Gasteiger partial charges for both the ligands and topoisomerase enzymes calculated by the software. AutoDock parameters for transition metals were obtained from the Scripps Research Institute website [36, 37]. Following the simulation of topoisomerase-drug interactions, the binding energy between the docked complex and the binding site was obtained from the docking log files and binding poses were visualised in either AutoDock tools GUI or PyMOL visualisation software. Validation of the software used is detailed in ESI.

3.1 Exploration of the TOP2 ATPase domain

The binding energies and docking poses of both ATP and XK469 with the TOP2 ATPase domain were first determined, to better understand the ATPase domain topography and electrostatic charges. Validation of the docking software was performed with the resultant binding poses and binding energies compared to the reported results (see ESI Figures S1 and S2). Calculated binding energies within 2 kcal/mol were considered to compare favourably to literature results as a value of ±2 kcal/mol is reported as the typical error of molecular modelling calculations [35, 36]. Once validated the interactions of ATP and XK469 with the TOP2 ATPase domain were simulated for control and reference. ATP was found to have a binding energy of −14.80 kcal/mol with the ATPase domain, while XK469 had a weaker binding energy of −11.80 kcal/mol (see Table 1). These values were used as benchmarks to compare the complexes that would be designed in this project. Both ATP and XK469 exhibited markedly similar binding poses with analogous moieties of each compound occupying the same regions of the ATPase domain (Figure 2); to the best of our knowledge this is the first report of such similarity. Modelling of the TOP2 ATPase domain and its interaction with both ATP and XK469, suggested that these molecules interact with only a portion of the ATPase domain, with large areas and the domain entrance not utilised.

From the modelling experiments two regions of the domain were identified that could support additional interaction with XK469 analogues; henceforth termed region I and region II (Figure 2). The quinoxaline group of XK469 locates in the broad region I which is comprised of hydrophilic charges, due to Asn91, Ala92, Asp94, and Asn95 (Figures S3 and S4), and a large hydrophobic area dominated by Pro138, Ile141, and Phe142. The in silico work clearly suggests that ATP sits deep within region I, further suggesting that opportunities for expansion in this region exist.

The propionic acid group of XK469 and triphosphate group of ATP locate in region II, which contains Asn150 and Gly166 that support the formation of hydrogen bonds to the phosphate group of ATP and the carboxylic acid group of XK469. Region II also features a hydrophobic area created by Val90, Lys378 and Ile317 residues. As such, a molecule truncated with a hydrophobic moiety could potentially interact with this region. The modelling data also suggests that the ATPase domain entrance is unoccupied by either ATP or XK469. The entrance contains both hydrophobic and hydrophilic regions due to the presence of Arg98, Ser149 and Lys157.

3.2 Design considerations

With the investigation of region I, II, and the domain entrance in mind, analogues of XK469 were explored with two locations for metal insertion, in combination with different functionalisation at the 3^rd position of the quinoxaline and alterations to the Pt(II) secondary ligands. Two different metal complex designs derived from XK469 were investigated, with platinum complex coordination sites located either at the quinoxaline group (1, EDA-quin) or following the amide group (2, aminoethylamide). We propose for the EDA-quin complexes that the introduction of a Pt(II) coordinating group in the form of ethylenediamine at the quinoxaline 3-position will provide new hydrogen bonding opportunities, different 3D structural arrangement and different hydrophobic properties by incorporating different Pt(II) secondary ligands. The data obtained by Xia et al. suggested that modification at the 3-position could improve interactions in region I, and that while alterations to the linker between the hydroquinone and the carboxylic acid were tolerated, the ability to hydrogen bond in region II was important. A structurally diverse group of amino acids were selected to explore their interactions with region II; glycine, alanine, leucine and phenylalanine. The ᴅ‑isomer of each amino acid was selected as they have been found to be more resistant to degradation from endogenous proteases, such as trypsin, which preferentially or specifically degrade the ʟ‑isomer [38, 39].

For the aminoethylamide complexes we explored how a Pt(II) complex would interact with region II compared to the carboxylic acid terminus of XK469. In this design we also explored a variety of alkylamines (dodecyl amine, benzylamine, and isopropyl amine) to promote additional hydrophilic and hydrophobic interactions in region I. Dodecyl amine at position 3 of the quinoxaline has been shown to interact in the narrow entrance to the ATPase domain, while benzylamine and isopropyl amine were selected to explore the effect of hydrophobic groups of different sizes.[27] A set of non‑functionalised quinoxaline compounds were also explored for comparison.

Four Pt(II) secondary ligands were also explored with the aim of improving interactions with the ATPase domain. We selected benzene-1,2-diamine, 2,2'‑bipyridine and 1,10‑phenanthroline due to their aromatic nature that may result in greater hydrophobic interaction with the ATPase domain. In addition, ethylenediamine was chosen as a secondary ligand to explore the effect that a smaller complex would have on binding with the TOP2 ATPase domain. Figure 3 gives the general structures of the EDA-quin and aminoethylamide designs, 1 and 2, that were explored. The chlorine in the 7^th position was omitted from this work as Xia et al. has shown it wasn’t necessary for activity.

3.3 Molecular modelling

The ligands and their complexes of general design structures 1 and 2, were modelled with the TOP2 ATPase domain to simulate their binding interactions. The majority of the complexes (3–42) demonstrated a higher binding energy with the TOP2 ATPase domain than XK469, with three complexes (4, 19 and 37) also exhibiting a higher binding energy that the target ATP molecule (Tables 1-2). The binding pose of each ligand and complex was categorised into one of six categories (a–f; Figure 4).

3.3.1 Effect of secondary ligand on average binding energies.

The coordination of different secondary ligands was found to have varying effects on the average binding energy of aminoethylamide and EDA-quin complexes (Figure 5). In aminoethylamide complexes, the incorporation of secondary ligands was found to increase their average binding energy, with 2,2'-bipyridine and 1,10‑phenanthroline, resulting in the highest average binding energies recorded in this study. This was attributed to the larger complexes offering greater interactions with the interior surface of the domain and the simultaneous interaction of both aromatic ligands and the quinoxaline with hydrophobic regions of the TOP2 ATPase domain. A statistically significant opposite trend was observed for the EDA-quin complexes with the coordination of smaller ethylenediamine and diamino‑1,2‑benzene ligands resulting in higher average binding energies. This was attributed to the smaller secondary ligands allowing the aminoethylamide group to interact with hydrophilic regions of the TOP2 ATPase domain more closely.

3.3.2 Design 1 modelling (EDA-quin)

Analysis of the four ligands (3, 8, 13 and 18), prior to complexation, showed that the inclusion of the ethylenediamine functionality at the quinoxaline 3-position improved the binding energy, in comparison to XK469. The introduction of a Pt(II) metal with each of the secondary ligands resulted in enhanced binding energies for all complexes (4–22) compared with XK469, with both (4 and 19), exhibiting a higher binding energy then ATP (Table 1). Only complex 4, the smallest evaluated, was observed to bind with the same pose as XK469; binding pose ‘a’ (Figure 6a). For complex 4, the quinoxaline group was located in the hydrophobic area of region I, the amino acid within the hydrophobic area of region II, while the platinum ion and coordinated secondary ligand located towards the ATPase domain entrance. Complex 4 formed hydrogen bonds between its ether oxygen and both the amide of Ala167 and the R group of Lys168. Due to its orientation within region I, hydrogen bonded to the N² nitrogen of the ethylenediamine ligand of complex 4 also formed a hydrogen bond with the R group oxygen of Thr215. Interestingly, complex 11 also adopted binding pose ‘a’ (Figure S5), however it interacted with less amino acid residues and was not as close to region I or Lys168, ostensibly due to its larger size.

Complex 19 exhibited a higher binding energy (−15.93 kcal/mol) than the target ATP (−14.80 kcal/mol) and adopted binding pose ‘d’ (Figure 6b). Complexes 9 and 14, also shared this same binding pose and displayed relatively high binding energies (−14.43 kcal/mol and −14.72 kcal/mol). These three complexes contain an ethylenediamine ligand and bound with the functionalised quinoxaline Pt(II) component in the hydrophobic area of region I where the ethylenediamine secondary ligand interacted with Ile88, Asn91, and Asn120. The carboxylic acid terminus in these examples was located outside the TOP2 ATPase domain. Three other complexes (5, 10, and 15) were also determined to adopt binding pose ‘d’, but the orientation of the Pt(II) complex faced towards region II (Figure 6c). These complexes incorporated the larger diamino-1,2-benzene secondary ligand which interacted with Thr147.

Although complexes 12, 16, 17, and 21 maintained the interaction of the carboxylic acid with region II, the Pt(II) ion and secondary ligand became positioned in region I with the quinoxaline orientated at the entrance of the domain (Figure 5d). For these complexes, bonds formed with Asn91, located between region I and region II, and Ser149, located in the domain entrance, while also forming bonds with Ala167 and Lys168, located in region II. In addition, complex 12 formed bonds with Asn163 and Gly164, as the carboxylic acid of this complex fit further into region II which was attributed to its smaller methyl R group compared to the benzyl and isobutyl R groups of 16, 17, and 21. The remaining EDA‑quin complexes which included the 2,2'‑bipyridine and 1,10-phenanthroline ligands, were found to bind external to the domain.

The use of different amino acids in the design of the EDA-quin complexes was found to have no noticeable effect on the complexes binding energies, with similar average binding energies between −12.75 and −12.77 kcal/mol for each group of complexes (see Figure S6). Overall, the EDA-quin complexes showed that the smaller ethylenediamine coordinated Pt complexes had the overall highest binding energies (see Figure S7).

3.3.3 Design 2 modelling (Aminoethylamide)

All the complexes of this design exhibited higher binding energies (−12.05 kcal/mol to −15.20 kcal/mol) than XK469 (−11.80 kcal/mol) (Table 2). Only ligands 23, 28 and 38 prior to complexation showed the same binding orientation as XK469 (Figures S8, S9, and S10), with none of the complexes bound with binding pose ‘a’. The complexes with the smaller secondary ligands were found to adopt either binding pose ‘b’ (fitting wholly within the domain), or binding pose ‘c’ (the quinoxaline-alkylamine in the domain entrance). The benzyl substituted 33 also bound with binding pose ‘b’ (Figure S11).

Complexes 24 and 26 were found to fit wholly within the domain (binding pose ‘b’), with the Pt(II) ion and secondary ligand located in region I and the quinoxaline-alkyl amine in region II (Figure 7a). Forming hydrogen bonds between their ether oxygen and hydrogen of the Ala167 amide, a residue located between regions I and II. Complex 24 also formed a hydrogen bond between its ether oxygen and hydrogen of the R group amine of Lys168, an amino acid situated between region I and II. Due to its orientation within region I, the amine of the secondary ethylenediamine ligand of 24 also formed a hydrogen bond with the R group oxygen of Thr215, an amino acid adjacent the hydrophobic area of region I. It was noted that 26 made fewer hydrogen bonds and yet had a higher energy than 24. This was attributed to the increased size of the secondary 2,2'‑bipyridine ligand producing greater desolvation energy and greater hydrophobic interaction with the hydrophobic area of region II, when compared to the ethylenediamine ligand. Interestingly, these were the same amino acids that the EDA‑quin complex 4 had also interacted with.

Of the complexes which adopted binding pose ‘c’, (25, 29, 30, 34, 35 and 36, Figures 7b, S12 and S13), nearly all were found to form a hydrogen bond between the N¹ primary amine of each complex and the amide oxygen of Asn91; Asn91 is found between the two regions. Complexes 29 and 34 (Figure 7b) also exhibited a hydrogen-bond between the N¹ amine with the R group oxygen of Asn120 (situated adjacent to region I), the N² amine of each complex’s ethylenediamine ligand and the amide oxygen of Ile88 (situated between the two regions), and hydrogens bonded to their alkylamine groups and the R group oxygen of Tyr34 which is located in the entrance of the ATPase domain. While 29 and 34 both formed similar hydrogen bonds, 34 was calculated to have a higher binding energy, which was attributed to its benzylamine group either increasing the number of hydrophobic interactions with nearby hydrophobic residues or increasing desolvation energy through the displacement of more H₂O molecules. The benzylamine functionalisation resulted in a statistically significant difference in binding energies for all aminoethylamide complexes (Figure S14). Interestingly, the 2,2'‑bipyridine coordinated complex 36, which otherwise has a similar structure to the EDA coordinated complex 34 and occupied a similar pose did not form noticeable bonds with any amino acids.

Complexes 25 and 27, which did not have alkyl amine functionalisation at the quinoxaline 3‑position, both showed relatively poor fits (Figures S15 and S16, respectively). While complex 27 possessed a high binding energy of −14.06 kcal/mol, it formed no hydrogen bonds with amino acids of the ATPase domain and as such, this binding energy was attributed to electrostatic interactions with the domain and desolvation energy.

The larger aminoethylamide complexes were all found to adopt binding pose ‘d’ where the Pt(II) complex located external to the domain or in the entrance way. For these complexes, the location of the quinoxaline did vary slightly but for the majority it was found to locate in region I or the space between region I and II. Complexes 31, 32 and 37 (Figure 7c), all formed a hydrogen bond between the amide oxygen of each complex and the R group amine of Lys157, and between the amine of each quinoxaline alkylamine and the amide oxygen of Asn91. Complexes 39–42 formed the fewest hydrogen bonds (See Figures S17 and S18), with 41 and 42 forming only a single hydrogen bond between the amide oxygen of each complex and the R group amine of Lys157.

Interestingly, comparison of the average molecular weight for aminoethylamide complexes occupying each binding pose (Figure 7d) showed that the complexes that located entirely within the domain, the “b” pose complexes, had a lower average molecular weight than those that only fit partially within the domain. Further analysis by ANOVA showed that the difference between the aminoethylamide complexes average molecular weight and binding pose was statistically significant (ANOVA, f = 7.66, fcrit = 3.29, p = 0.00633). This is in contrast to EDA-quin complexes where there had been no such trend observed.

This study details the design and in silico assessment of 32 platinum complexed XK469 analogues. Modifications of XK469 consisted of alkylamine functionalisation of the quinoxaline in the 3-position, incorporation of different amino acids in place of the original propionic acid, and the coordination of a platinum centre and secondary ligands. The interaction of the designed complexes with the TOP2 ATPase domain were then modelled using AutoDock modelling software to calculate binding energies and binding poses.

Differences in the complexes binding energies became apparent when comparing the effects of quinoxaline functionalisation and the coordination of different secondary ligands. The coordination of a platinum ion and secondary ligand in the aminoethylamide complexes resulted in a noticeable increase in average binding energy compared to the uncoordinated compound. Coordination of 2,2'‑bipyridine and 1,10-phenanthroline resulted in higher average binding energies, 26 and 27 for example, although the difference in value compared to ethylenediamine and diamino-1,2-benzene was not statistically significant. This in turn differed from the EDA-quin complexes where the coordination of the smaller secondary ligands, ethylenediamine and diamino-1,2-benzene resulted in complexes with higher average binding energies; 4 and 5 for example. These results indicate that while the coordination of a platinum complex is beneficial, the proximity of the quinoxaline and complex in the EDA-quin complexes had a disruptive effect, possibly due to steric hindrance.

There was a statistically significant trend for the aminoethylamide complexes for the average molecular weight of complexes occupying different binding poses. For the complexes that located entirely within the domain, binding pose “b”, had an average molecular weight of less than 650 g/mol, while complexes that located partially within the domain, binding pose “c” and “d”, had average molecular weights of between 650 g/mol and 800 g/mol. This trend was not observed for the EDA-quin complexes. Two residues in particular were shown to frequently interact with the complexes via hydrogen bonds; Asn91 positioned between region I and region II, and Lys157 positioned in the domain entrance.

This study suggests that EDA-quin complexes coordinated to large aromatic secondary ligands (2,2'‑bipyridine and 1,10-phenanthroline) and aminoethylamide complexes coordinated to ethylenediamine secondary ligands, are molecules worth exploring to develop TOP2 ATPase domain inhibitors. These analogues demonstrate improved in silico binding compared to lead compound XK469, and offer a new class of Pt(II) complex for potential applications in cancer therapy.

Ala alanine

Asn asparagine

Asp aspartic acid

Arg arginine

AMPPNP adenylyl-imidodiphosphate

ANOVA analysis of variance

ATP adenosine 5'-triphosphate

Bipy 2,2'-bipyridine

ᴅ dextrorotatory

dab diaminobenzene

DNA deoxyribonucleic acid

EDA ethylenediamine

EDA-quin ethylenediamine-quinoxaline

En ethylenediamine ligand

f-ratio Fisher–Snedecor ratio

fcrit Fisher–Snedecor critical value

GUI graphical user interface

Gly glycine

Gln glutamine

Glu glutamic acid

Ile isoleucine

L levorotatory

Lys lysine

NIH National Institute of Health

OBGUI Open Babel graphical user interface

p probability

PDB protein databank

Phen 1,10-phenanthroline

Phe phenylalanine

RCSB Research Collaboratory for Structural Bioinformatics

Ser serine

SMILES simplified molecular input line entry system

Thr threonine

TOP1 topoisomerase I

TOP2 topoisomerase II

TOP2A topoisomerase IIα

TOP2B topoisomerase IIβ

Tyr tyrosine

Val valine

XK469 2-(4-((7-chloroquinoxalin-2-yl)oxy)phenoxy)propanoic acid

Ethics Approval

This work did not require approval for an ethics committee as it did not involve human or animal studies.

Competing interests

The authors declare that they have no competing financial or non financial interests as defined by Springer, or other interests that may be perceived to influence the results and/or discussion reported in this paper

Author’s Contributions

DWMP conducted the modelling, formal analysis and prepared all the figures. SEP conceptualized the project. SEP and SHM provided project oversight. All authors contributed to writing the manuscript, reviewing and editing.

Funding

The work was funded through an Australian Government Research Training Program PhD Scholarship.

Availability of data and materials

Data is provided within the manuscript or supplementary information files

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Tables 1 to 2 are available in the Supplementary Files section

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Design and in silico assessment of quinoxaline platinum complexes as ATPase competitive topoisomerase inhibitors

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Version 1

Abstract

Figures

1. Introduction

2. Method

3. Results and Discussion

Conclusions

Abbreviations

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1