Chromatographic HILIC indexes to characterize the lipophilicity of zwitterions

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Chromatographic HILIC indexes to characterize the lipophilicity of zwitterions Maura Vallaro , Giuseppe Ermondi , Giulia Caron PII: DOI: Reference:

S0928-0987(20)30021-X https://doi.org/10.1016/j.ejps.2020.105232 PHASCI 105232

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European Journal of Pharmaceutical Sciences

Received date: Revised date: Accepted date:

13 November 2019 3 January 2020 20 January 2020

Please cite this article as: Maura Vallaro , Giuseppe Ermondi , Giulia Caron , Chromatographic HILIC indexes to characterize the lipophilicity of zwitterions, European Journal of Pharmaceutical Sciences (2020), doi: https://doi.org/10.1016/j.ejps.2020.105232

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Chromatographic HILIC indexes to characterize the lipophilicity of zwitterions Maura Vallaro, Giuseppe Ermondi and Giulia Caron* University of Torino, Molecular Biotechnology and Health Sciences Dept., CASSMedChem, via Quarello 15, 10135 Torino, Italy. E-mail: [email protected], telephone: +39 011 6708337

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Abstract Reverse phase high pressure liquid chromatography (RP-HPLC) is widely employed in drug discovery for lipophilicity measurements. Hydrophilic interaction liquid chromatography (HILIC) may represent a good alternative to RP-HPLC in the determination of the lipophilicity of hydrophilic compounds like zwitterions. In this paper three different HILIC stationary phases (ZIC®-HILIC, ZIC®-pHILIC and ZIC®-cHILIC) and two different mobile phases (80%ACN/20%buffer and 90%ACN/10%buffer) were combined to set-up six chromatographic systems. A computational tool named Block Relevance (BR) analysis was firstly used to deconvolute the balance of intermolecular forces governing retention in the six systems. Then the lipophilicity profiles (log k vs pH) of ten model ampholytes were determined. Results support that the lipophilicity of zwitterions at any pH can be successfully determined with a ZIC®-cHILIC stationary phase and an 80%ACN/20%buffer mobile phase. To extend the dataset and confirm results, a second series of zwitterionic drugs was also analysed.

Keywords Ampholytes, BR analysis, HILIC, lipophilicity, zwitterions

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1. Introduction Ampholytes are compounds bearing at least one acidic and one basic group. All ampholytes have an acidic and a basic group but the relative acidity of the two functional groups can be different. Therefore, ampholytes can be distinguished in zwitterions and ordinary ampholytes. In zwitterions the acidic and the basic group can be simultaneously ionized and the relation pKa acidic < pKa basic is true. Conversely, the two groups cannot ionize simultaneously in ordinary ampholytes, since the relation pKa acidic > pKa basic holds here. [1] Ampholytes and zwitterions are used as medicines in various therapeutic areas (antibacterials, antiallergics, diuretics [2],[3]) and few drug metabolites show a zwitterionic structure. Although zwitterions have potential therapeutic medicinal properties, some issues mostly related to their complex ionization profiles [1][3] do not support a routinely application in drug discovery and call for new experimental tools to make easier their physicochemical characterization. Chromatographic methods are widely used in drug discovery for lipophilicity determination since they are generally less sensitive to impurities, faster and more amenable to automation than traditional biphasic methods such as shake-flask [4][5]; reversed-phase high performance liquid chromatography (RP-HPLC) is considered as the gold standard due to its robustness and versatility. Nevertheless, RP-HPLC is only appropriate for those compounds with log P (logarithm of the partitioning coefficient in the octanol/water system) comprised between -1 and about 6.5 since hydrophilic compounds (with log P < -1) are not sufficiently retained under RP-HPLC conditions. Hydrophilic interaction liquid chromatography (HILIC) is a variant of normal phase liquid chromatography (NP-LC), but its retention mechanism is more complicated and not completely understood. [6] In the HILIC mode, the retention mechanism is based on the differential distribution of the solute molecules between the acetonitrile-rich mobile phase and a water-enriched layer adsorbed onto the hydrophilic stationary phase. HILIC may therefore represent a good alternative to RP-HPLC in the determination of lipophilicity of hydrophilic compounds.[7] Several HILIC stationary phases have been reported in the literature [8]. This paper focuses on zwitterionic stationary phases since it has been reported that they strongly absorb water and thus promote partitioning as retention mechanism. In these columns the active layer is grafted onto either a pore silica gel or a polymer support and contains both strongly acidic groups (e.g. sulfonic acid) and strongly basic quaternary ammonium groups separated by a short alkyl spacer. Zwitterionic columns are commercially available under the tradenames ZIC®-HILIC (to hereafter named HILIC) on a silica gel support and ZIC® -pHILIC (to hereafter named pHILIC) on a polymer support (Figure 1) [6]. More recently the ZIC®-cHILIC column (to hereafter named cHILIC) has been introduced on the market. It exhibits an opposite charge arrangement of HILIC with the quaternary ammonium as a distal moiety and the negatively charged phosphoric group in the proximal location to the bead surface (Figure 1). [9]. Since HILIC systems offer more retention than RP 3

for polar compounds, they are expected to be relevant for the determination of the lipophilicity of zwitterions. Kadar et al. [10] were the first to use HILIC columns to obtain physico-chemical descriptors and not for separative purposes. Then Bart and coworkers proposed HILIC chromatography to measure lipophilicity of basic drugs. [11] More recently, some of us also applied HILIC chromatography to characterize small sets of peptides [12] and cyclopeptides [13]. To our knowledge, no study has been reported until now about the application of HILIC systems in the characterization of the lipophilicity of zwitterions. Therefore, the main aim of the study is the identification of the best HILIC system(s) to employ in the determination of zwitterions lipophilicity at different pHs. Results are expected to support a larger integration in research programs of zwitterions, often discarded by medicinal chemists since difficult to handle. Notably we are not interested in finding surrogates of log P/log D in octanol/water but we are looking for new chromatographic indexes. To reach our aim we firstly used a computational tool (i.e. the Block Relevance (BR) analysis [14][15]) to deconvolute the balance of intermolecular forces governing HILIC systems using a widely known dataset of 36 neutral compounds. Then we set-up six HILIC systems by combining three columns and two mobile phases and a first dataset of 9 zwitterions and 1 ordinary ampholyte (ampicillin, azapropazone, cephalexin, cetirizine, phenylalanine, piroxicam, rifampicin, rifapentine, tyrosine and 3-aminophenol) was submitted to chromatographic runs. Overall for any compound we collected six series of chromatographic indexes (log k) at 4-6 different pHs. Data analysis allowed to identify which HILIC system performed better in the determination of the lipophilicity of zwitterions. Finally, to extend the study, a second dataset of zwitterionic drugs was also analysed.

2. Materials and Methods 2.1.

Experimental Part

A HPLC Varian ProStar instrument equipped with a 410 autosampler, a PDA 335 LC Detector and Galaxie Chromatography Data System Version 1.9.302.952 was used. Three stationary phases were used: (1) ZIC®-pHILIC column (sulfoalkyl-betaine zwitterionic phase covalently attached to porous polymer beads 10 cm, 4.6 mm, 5 µm particle size) from SeQuant (Umeå, Sweden); (2) ZIC®-HILIC column (sulfoalkyl-betaine zwitterionic phase on a silica gel support, 10 cm, 4.6 mm, 5 µm packing, 200 Å pore size) from SeQuant (Umeå, Sweden) and (3) ZIC®-cHILIC column (phosphorylcholine zwitterionic phase on a silica gel support, 10cm ,4.6 mm, 3 µm packing, 100 Å pore size) from SeQuant (Umeå, Sweden). The analyses were performed at 30°C with buffer solutions in mixture with acetonitrile at 80 or 90%. Buffers composition is the following (pH was measured before and after ACN addition): pH = 2.0 (formic acid 0.13M); pH = 3.0 (formic acid 0.13M, pH adjusted with ammonium hydroxide); pH = 5.0 4

(ammonium Formate 0.08M, pH adjusted with formic acid); pH = 6.9 (ammonium acetate 0.02M); pH = 8.0 (ammonium acetate 0.02M, pH adjusted with ammonium hydroxide); pH = 10 (potassium hydroxide 0.5M, pH adjusted with hydrochloric acid 0.1M). The flow rate was 1.0 ml/min. The analytes were purchased from various commercial sources and were in the 95-99% purity range. All samples were dissolved in the mobile phase and a concentration of about 50–100μg/ml was used. The monitored wavelength was the one for which the compound showed the maximum absorbance. An exemplifying chromatogram is shown in the S.I. (Fig. S1). The dead time t0 was determined using toluene. Retention times (tR) were measured in triplicate. Isocratic log k (capacity factor k = (tR - t0)/t0) values were determined (in the literature the symbol k′ is often used for the retention factor, particularly in liquid chromatography; the original reason for this was to clearly distinguish it from the partition coefficient (distribution constant) for which the symbol K had been utilized. Since, however, the distribution constants are all identified with a subscript, there is no reason to add the prime sign to this symbol). SD (log k) was less than 0.02.

2.2.

Computational Part

QSPR models were built as follows. The SMILES codes of the 36 compounds were submitted to VS+ (version 1.0.7, http://www.moldiscovery.com) and converted to 3D structures. 82 VS+ descriptors were calculated using default settings and four probes (OH2, DRY, N1, and O probes that mimic, respectively, water, hydrophobic, HBA, and HBD properties of the environment) and then exported in a .csv file. A second .csv file was obtained by including log k values of compounds. The two .csv files were submitted to Matlab (ver. R2019a, https://it.mathworks.com/) to perform Partial Least Square Regression (PLSR). PLSR and VIP analysis were carried out using the libPLS library (ver 1.98, http://www.libpls.net/). Internal K-fold cross validation of PLS is implemented in libPLS and was used to validate the models (two K values were used: K=4 and K equal to the number of compounds to obtain Leave-One-Out validation, LOO). Finally, an inhouse Matlab script grouped the descriptors in blocks and processed the corresponding VIPs to draw the BR plots shown in Figure 2. Processing was done on a notebook equipped with a 4 cores Intel i7-4700MQ and 12 GB of RAM operating with Windows 10.

3. Results and Discussion 3.1.

The datasets

In this paper we refer to three datasets (Table 1).

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Table 1. Investigated datasets: overview Dataset name DS36 DSmain DSzw

compounds neutral compounds 1 ampholyte + 9 zwitterions zwitterions

n 36 10 11

Use preliminary analysis main dataset to extend the number of investigated zwitterions

A widely known dataset of 36 neutral compounds [17] (called DS36, Table S1) is used to aid the set-up of the chromatographic systems and to deconvolute the intermolecular forces governing retention. Overall, the 36 molecules cover a reasonably extended physico chemical space (e.g. log P range from -0.55 to 5.40). DSmain is the most investigated dataset of the study and consists in ten ampholytes listed in Table 2 (the chemical structures are reported in Fig. S2). Phenylalanine and tyrosine are two aminoacids, building block of peptides and proteins. Ampicillin is a semi-synthetic derivative of penicillin that functions as an orally active broad-spectrum beta-lactam antibiotic. Cephalexin is a beta-lactam antibiotic too but within the class of first-generation cephalosporins. Azapropazone is a nonsteroidal anti-inflammatory drug (NSAID), piroxicam as well but the two structures are completely different. Cetirizine is a well-known secondgeneration long-acting H1 antagonist, used to treat allergy symptoms. Rifampicin and rifapentine are macrocyclic ansamycin natural product antibacterials. Both of them share a large and flexible structure and belong the beyond-Rule-of-5 (bRo5) chemical space (i.e. they do not comply with Lipinski’s Rule-of-5 [16]). For ampholytes in Table 2 the zwitterionic species may not be the most populated at physiological pH. Therefore, the ampholytes were classified in agreement with a recent study [17] in three main classes: a) ordinary ampholytes (OA) for which the zwitterion is never present, b) zwitterions “certain” (ZC) if the zwitterionic species is dominant in a large (> 2 pH unities) physiological pH range and c) zwitterions “uncertain” (ZU) if more species and the zwitterion are present around the physiological pH range. DSmain includes therefore 1 OA, 7 ZCs and 2 ZUs (Table 2).

Table 2. DSmain: pKa are taken from the paper by Caudana et al. [17], pI is the isoelectric point. Ampholytes were classified in ordinary ampholytes (OA), zwitterions “certain”(ZC) and zwitterions “uncertain” as recently reported in the literature [17]. Compound 3-Aminophenol Ampicillin Azapropazone Cephalexin Cetirizine Phenylalanine Piroxicam Rifampicin Rifapentine Tyrosine

MW 109 349 298 365 461 165 331 823 717 181

pKa (a) 9.8 2.6 <1.8 2.6 3.0 2.2 2.0 3.0 2.8 2.2

pKa (b) 4.4 7.4 6.5 7.0 8.0 9.1 5.1 7.5 7.6 9.0

pI 5.0 <4.2 4.8 5.5 5.6 3.6 5.2 5.2 5.6

Classification OA ZC ZU ZC ZC ZC ZU ZC ZC ZC 6

Finally, a third dataset of 11 zwitterionic drugs (named DSzw, Table S8) enabled to extend the number of investigated compounds once identified the most performing chromatographic system.

3.2.

The chromatographic systems

Six chromatographic systems were set-up and schematized in Figure 1. Three columns (pHILIC, HILIC and cHILIC), and two mobile phases (80ACN: 20 buffer and 90ACN:10 buffer) were tested.

Figure 1. Chromatographic systems investigated in the study.

Stationary phase

Type

Mobile phase

pH range

Descriptor

pHILIC

Negative charge exposed

80ACN/20buffer

2-10

log k80 pHILIC

HILIC

Negative charge exposed

80ACN/20buffer

3-8

log k80 HILIC

cHILIC

Positive charge exposed

80ACN/20buffer

3-8

log k80 cHILIC

pHILIC

Negative charge exposed

90ACN/10buffer

2-10

log k90 pHILIC

HILIC

Negative charge exposed

90ACN/10buffer

3-8

log k90 HILIC

cHILIC

Positive charge exposed

90ACN/10buffer

3-8

log k90 cHILIC

One main concern in this study is that the pH of the buffer in the presence of 80% and 90% acetonitrile is close to that in water. This pH value is important, considering that the log ks are pH specific. Roses and Bosch provided a review on the influence of mobile phase acid–base equilibria on the chromatographic behavior of proteolytic compounds [18]. The authors found out that an organic solvent (e.g. acetonitrile) in the mobile phase (at least up to 75%) can change the pKa of the buffer, as well as that of the analyte. This pKa deviation is compound specific. For practical purposes as also suggested in the literature [10][19] we decided to assume that ionization properties of the buffer and compounds in the mobile phase are modified but not neglected. This is expected to hold in the presence of 80%ACN, but some doubts arise when 90%ACN is present in the mobile phase. One second concern is that the six systems in Figure 1 provide different information or not. To get this information we decided to deconvolute the balance of intermolecular forces governing the six log ks. Therefore, firstly we determined the six log ks for DS36 (data in Table S1) and then applied a computational tool designed and implemented in our laboratories and called Block Relevance (BR) analysis [20][15]. Briefly, BR analysis allows the interpretation of QSPR models (where log k is the dependent variable, 82 VS+ 7

descriptors the independent variables and PLS the algorithm) by organizing the 82 descriptors into six blocks (Size, Water, DRY, N1, O, and Others) of straightforward significance. In a very simplistic way, BR analysis gives the relevance of each block to the model. BR analysis graphical outputs for the six HILIC systems are collected in Figure 2 (statistical data in the Annex 1 of the Supporting Information) and provide the following information: a) in the pHILIC systems the impact of solutes’ dimension and shape (green block, detrimental to retentions because of the negative sign) is significantly larger than in other systems, b) the higher the amount of acetonitrile in the mobile phase, the higher the retention because of the lower impact of the Size block (green) and c) in the pHILIC systems the red block (solutes’ HBD properties) is higher than the blue block but the reverse is true for the HILIC and cHILIC systems; this probably supports that in these latter the impact of free silanols cannot be neglected and thus the effects due to the different exposed charges is less evident. Recently, a pHILIC column has been characterized with the Abraham’s model [21], which provides similar information than BR analysis and results are in line with those reported here.

Figure 2. BR analysis graphical output and the interpretation scheme

log k80 pHILIC

log k80 HILIC

log k90 pHILIC

log k80 cHILIC

log k90 HILIC

log k90 cHILIC

Size

OH2

DRY

O

N1

Others

Volume and surface

Molecular polarity

Hydrophobicity

H-Bond donor properties

H-Bond acceptor properties

Polarity unbalance

molecular hydrophobic interaction with the system mainly of entropic nature

the interaction of the polar regions of the solute with the system

local interactions between apolar regions of the solute and the system

specific HB interactions between solute and system

specific HB interactions between solute and system

difference in interactions of solutes and system due to different location of polar and apolar regions

8

Overall BR analysis supports that the six systems are expected to provide different information and thus all of them deserve being experimentally tested. Finally, for compounds in DSmain (and DSzw) we decided to measure in any system the whole lipophilicity profile, i.e. the variation of log k as a function of pH. Although this requested a huge amount of work, our experience with zwitterions clearly showed that log k at a single pH value is not sufficient to evaluate zwitterions lipophilicity. [22]

3.3.

Lipophilicity profiles

Lipophilicity profiles were built using log k values reported in Table S2-S7 (Supporting Information). Since we refer to normal-phase chromatographic systems, the higher the log k the lower the lipophilicity of the compounds. Fig. 3 shows the lipophilicity profiles obtained in the three HILIC systems when a mobile phase with 80% ACN was used.

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Fig. 3. Lipophilicity profiles (log k vs pH) of the ampholytes included in DSmain (Table 1) obtained using a mobile phase of 80%ACN/20%buffer and three different stationary phases: A) pHILIC, B) HILIC and C) cHILIC 2.00

1.50 3-aminophenol

1.00

azapropazone

Log k80 p-HILIC

0.50

ampicillin cephalexin

0.00

cetirizine -0.50

phenylalanine

piroxicam

-1.00

rifampicin -1.50

rifapentine tyrosine

-2.00

-2.50 2

3

4

5

6

pH

7

8

9

10

A

11

2.00 1.50

3-aminophenol

1.00

ampicillin

Log k80 HILIC

0.50

azapropazone 0.00

cephalexin

cetirizine

-0.50

phenylalanine -1.00

piroxicam

rifampicin

-1.50

rifapentine

-2.00

tyrosine -2.50 2

3

4

5

6

7

8

9

10

11

B

pH 2.00 1.50

3-aminophenol

1.00

azapropazone

Log k80 c-HILIC

0.50

ampicillin 0.00

cephalexin

cetirizine

-0.50

phenylalanine -1.00

piroxicam

rifampicin

-1.50

rifapentine

-2.00

tyrosine -2.50 2

3

4

5

6

7

pH

8

9

10

11

C

Notably, when a pHILIC stationary phase is considered a pH range from 2 to 10 can be explored, whereas for HILIC systems the pH range is 3 - 8. Comparison between log k at pH = 2 and pH = 10 in the pHILIC system (Fig. 3A) shows that the cationic species dominant at acidic pHs are more retained by the column than the anionic species dominant at basic pHs (missing data are in line with these trends, see Supporting

10

Information). This supports that the pHILIC system exposes a negative charge (Fig. 1) that favors electrostatic interactions with positively charged species of compounds. When focusing on the 3-8 pH range, phenylalanine and tyrosine together with ampicillin and cephalexin are the most hydrophilic compounds all along the pH range in any system. These four compounds show similar log k values at pH = 3, but higher log k differences are monitored when increasing pH. At basic pHs tyrosine is significantly the most hydrophilic compound, then phenylalanine, cephalexin and ampicillin. As expected, log k of the only ordinary ampholyte 3-aminophenol does not vary with pH in any system. Cetirizine, that is zwitterionic in a large pH range (Table 2), behaves very similarly to 3-aminophenol in HILIC and cHILIC systems but pHILIC retention is significantly lower. This behavior is in line with BR analysis results which showed (Fig. 2) that pHILIC columns are more sensible to solutes size than HILIC and cHILIC stationary phases. The remaining ampholytes (piroxicam, azapropazone, rifampicin and rifapentine) are often experimentally inaccessible in the pHILIC and HILIC systems since too much lipophilic and thus poorly retained. The lipophilicity profiles of all but rifapentine could only be obtained in the cHILIC system (Fig. 3C). Fig. 3C shows for azapropazone a very slight decrease in log k when increasing pH, whereas piroxicam and rifampicin show a net decrease in log k also larger than that observed for the two antibiotics (ampicillin and cephalexin). According to pKa values (Table 2), a decrease of log k is expected at basic pHs for all the zwitterions. This finding is probably due to the different chemical structures and delocalization level of the negative charge present at basic pHs. Overall Fig. 3 highlights that at pH=7.0 the most lipophilic ampholyte is rifapentine, then rifampicin, piroxicam, azapropazone, cetirizine and 3-aminophenol, then ampicillin, cephalexin, phenylalanine and tyrosine that is the most hydrophilic. Some small deviations from this trend are observed at different pHs. Fig. 4 shows the lipophilicity profiles of the ampholytes included in DSmain in the three HILIC systems when a mobile phase with 90% ACN was used. Again, only the cHILIC system allows a full characterization of all the ampholytes. Notably, the compounds are more retained than with 80% ACN as predicted by BR analysis (see above). The overall trend of log k is not very different from Fig. 3. However, for rifampicin and piroxicam, the decrease in log k at higher pHs is less evident, probably due to the huge impact of the organic solvent on ionization (see previous section). Overall, these results support that the combination of the cHILIC column with an 80%ACN/20%buffer mobile phase is the best system to assess the lipophilicity of ampholytes.

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Fig. 4. Lipophilicity profiles (log k vs pH) of the ampholytes included in DSmain (Table 1) obtained using a mobile phase of 90%ACN/10%buffer and three different stationary phases: A) pHILIC, B) HILIC and C) cHILIC 2.00 1.50

1.00

3-aminophenol azapropazone

Log k90 p-HILIC

0.50

ampicillin 0.00

cephalexin

cetirizine

-0.50

phenylalanine

-1.00

piroxicam rifampicin

-1.50

rifapentine tyrosine

-2.00 -2.50 2

3

4

5

6

7

8

9

10

A

11

pH 2.00 1.50

3-aminophenol

1.00

azapropazone

Log k90 HILIC

0.50

ampicillin 0.00

cephalexin

cetirizine

-0.50

phenylalanine -1.00

piroxicam

rifampicin

-1.50

rifapentine

-2.00

tyrosine -2.50 2

3

4

5

6

7

8

9

10

11

B

pH

2.00 1.50

3-aminophenol

1.00

ampicillin

Log k90 c-HILIC

0.50

azapropazone 0.00

cephalexin

cetirizine

-0.50

phenylalanine -1.00

piroxicam

rifampicin

-1.50

rifapentine

-2.00

tyrosine -2.50 2

3

4

5

6

7

pH

8

9

10

11

C

To extend the study, a second series of zwitterions (DSzw in Table 1, pKa in Table S8) was analysed. According to previous results, we used the cHILIC column and a mobile phase with 80%ACN (for comparative purposes, log ks were also obtained with the 90%ACN mobile phase, Fig. S3). Results are shown in Fig. 5. 12

Already at first sight, one can verify that the behavior of rifampicin is significantly different from that registered for the other zwitterions since log k changes with pH are more evident. Mesalamine and cefadroxil show a decrease in retention (=an increase in lipophilicity) when passing from acidic to neutral pHs. No compound in DSmain showed this behavior. Ceftriaxone, lisinopril, lomefloxacin, ofloxacin and labetalol show a log k trend similar to ampicillin and cephalexine. The remaining zwitterions do not show significant log k variation with pH as observed for cetirizine. When a mobile phase with 90%ACN was used, similar results were found (Fig. S3, Supporting Information).

Fig. 5. log k80 cHILIC vs pH for an additional series of zwitterions (DSzw); rifampicin is shown for comparative purposes. 2.00 1.50

rifampicin cefadroxil

1.00

ceftriaxone

Log k80 c-HILIC

0.50

chlortetracycline 0.00

enrofloxacin

labetalol

-0.50

lisinopril -1.00

lomefloxacin

mesalamine

-1.50

norfloxacin

-2.00

ofloxacin -2.50 2

3

4

5

6

7

8

9

10

11

oxytetracycline

pH

4. Conclusions Chromatographic indices have already been successfully used in early drug discovery to determine molecular lipophilicity. Here we investigated three different HILIC stationary phases and verified their skills in characterizing the lipophilicity of zwitterions. These latter have potential therapeutic medicinal properties, but difficulties to a rapid access to their physico-chemical profiles do not support a routinely application in drug discovery. Results showed that logk80 cHILIC is the most convenient chromatographic index to assess the lipophilicity of zwitterions at different pHs. Moreover, we verified that lipophilicity profiles (log k vs pH) trend is not the same for all the investigated zwitterions and thus their experimental determination is mandatory. We also showed rifampicin behaves differently from other zwitterions. This study also highlights the relevance of computational tools like BR analysis which can deconvolute the balance of intermolecular forces governing chromatographic systems and thus rationalize experimental data. For instance, BR analysis does not support the use of pHILIC columns, too sensible to solutes’ dimensions. 13

Overall, ad hoc chromatographic indexes can be used to characterize the physicochemical profile of zwitterions often inaccessible to experimental and computational tools implemented in the drug discovery pipeline; this in turn can make easier their integration in drug discovery programs.

14

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Graphical Abstract

Zwitterions lipophilicity log k80 pHILIC

log k80 HILIC

log k80 cHILIC

log k90 pHILIC

log k90 HILIC

log k90 cHILIC

2.00 1.50

3-aminophenol

log k80 c-HILIC

BR value with sign

1.00

azapropazone

Log k80 c-HILIC

0.50

ampicillin

0.00

cephalexin

cetirizine

-0.50

phenylalanine

-1.00

piroxicam

rifampicin

-1.50

rifapentine

-2.00

tyrosine -2.50 2

Size OH2 DRY

O

N1

Others

3

4

5

6

pH pH

7

8

9

10

11

16