Probing Allosteric Hsp70 Inhibitors by Molecular Modelling Studies to Expedite the Development of Novel Combined F508del CFTR Modulators

Cystic fibrosis (CF) is caused by different mutations related to the cystic fibrosis transmembrane regulator protein (CFTR), with F508del being the most common. Pioneering the development of CFTR modulators, thanks to the development of effective correctors or potentiators, more recent studies deeply encouraged the administration of triple combination therapeutics. However, combinations of molecules interacting with other proteins involved in functionality of the CFTR channel recently arose as a promising approach to address a large rescue of F508del-CFTR. In this context, the design of compounds properly targeting the molecular chaperone Hsp70, such as the allosteric inhibitor MKT-077, proved to be effective for the development of indirect CFTR modulators, endowed with ability to amplify the accumulation of the rescued protein. Herein we performed structure-based studies of a number of allosteric HSP70 inhibitors, considering the recent X-ray crystallographic structure of the human enzyme. This allowed us to point out the main interaction supporting the binding mode of MKT-077, as well as of the related analogues. In particular, cation-π and π–π stacking with the conserve residue Tyr175 deeply stabilized inhibitor binding at the HSP70 cavity. Molecular docking studies had been followed by QSAR analysis and then by virtual screening of aminoaryl thiazoles (I–IIIa) as putative HSP70 inhibitors. Their effectiveness as CFTR modulators has been verified by biological assays, in combination with VX-809, whose positive results confirmed the reliability of the whole applied computational method. Along with this, the “in-silico” prediction of absorption, distribution, metabolism, and excretion (ADME) properties highlighted, once more, that AATs may represent a chemical class to be further investigated for the rational design of novel combination of compounds for CF treatment.


Introduction
Cystic fibrosis (CF) is the autosomal recessive disorder most common in Caucasian populations [1]. It is caused by different mutations in the cystic fibrosis transmembrane regulator protein (CFTR) [2,3].
This protein belongs to the ABC (ATP-Binding Cassette) Transporter Superfamily, being made of five distinctive domains, namely two transmembrane domains (TMDs), two nucleotide-binding domains (NBDs), and a regulatory (R) domain. It is well established MKT-077 is a cationic rhodacyanine, proposed as an anti-proliferative agent, active against MCF-7 breast cancer cells. Despite its little cytotoxicity against either normal human fibroblasts or immortalized epithelial cells, it was withdrawn by Phase I clinical trials because of poor metabolic stability [35]. For this reason, during the last years, a number of studies have been performed to modify the chemical structure of the prototype towards novel compounds maintaining the same HSP70 allosteric modulator ability but exhibiting a better safety and pharmacokinetic (PK) profile [36,37].
In this context, we deemed it interesting to better explore the putative binding mode of a consistent series of MKT-077 analogues that have, so far, been reported in the literature [36,37] as allosteric HSP70 inhibitors, exhibiting variable ability to inhibit cellular growth in cancer lines (MKT-077, YM-01 and 1-90; see Supplementary Tables S1 and S2). Indeed, it has been found that the MCF-7 antiproliferative ability of these series of compounds was related to the HSP70 inhibitory one, by testing the ligand binding affinity towards the HSP70 protein of active/inactive ligands, when evaluated as MCF-7 antiproliferative agents [37].
As shown in Figure 1, most of the collected compounds maintained the MKT-077 pyridinium substituent as a terminal group, while a number of them have been optimized as thiazolyl-containing congeners, as experienced by JG-98 (30) and JG-231 (71). Herein, their most important key features involved in the MCF-7 antiproliferative ability as a result of its activity as an HSP70 inhibitor have been analyzed performing molecular docking studies and Quantitative-Structure Activity Relationship (QSAR) analyses.
In particular, while the docking calculations so far reported in the literature were performed based on the bovine protein, the recent X-ray crystallographic of the human HSP70 data released on the protein data bank (pdb code: 6CZ1 released: 10 April 2019, resolution = 1.68 Å) [38] allowed us to apply a more reliable structure-based approach, towards the design of further new molecules.
These findings paved the way for the following screening and evaluation of novel MKT-077 analogues, to be exploited, in combination with F508del correctors, conceivably in order to improve their rescue ability. This was done by initially focusing on the benzothiazole-containing compounds present in our in-house series of aminoarylthiazoles (AATs), previously explored as F508del-CFTR correctors [39].
Indeed, our research group synthesized a number of thiazole-based compounds with an interesting ability to improve both the trafficking and gating of mutant CFTR [40,41], Herein, their most important key features involved in the MCF-7 antiproliferative ability as a result of its activity as an HSP70 inhibitor have been analyzed performing molecular docking studies and Quantitative-Structure Activity Relationship (QSAR) analyses.
In particular, while the docking calculations so far reported in the literature were performed based on the bovine protein, the recent X-ray crystallographic of the human HSP70 data released on the protein data bank (pdb code: 6CZ1 released: 10 April 2019, resolution = 1.68 Å) [38] allowed us to apply a more reliable structure-based approach, towards the design of further new molecules.
These findings paved the way for the following screening and evaluation of novel MKT-077 analogues, to be exploited, in combination with F508del correctors, conceivably in order to improve their rescue ability. This was done by initially focusing on the benzothiazole-containing compounds present in our in-house series of aminoarylthiazoles (AATs), previously explored as F508del-CFTR correctors [39].
Indeed, our research group synthesized a number of thiazole-based compounds with an interesting ability to improve both the trafficking and gating of mutant CFTR [40,41], with a lot of them a library of new AAT-VX-809 hybrid derivatives. These compounds proved to act, especially, as correctors in biochemical experiments [40,41].
Herein, MKT-077 and the best-scored and filtered AATs I-IIIa have been evaluated, in combination with VX-809, in order to confirm their CFTR modulator effectiveness. Meantime, the insilico prediction of descriptors, related to absorption, distribution, metabolism, and excretion properties (ADME), have been determined, in order prioritize the most promising AATs for further optimization. This approach allowed us to assess the rescue ability of the selected multi-compound treatment, supporting the CFTR amplifier ability promoted for the allosteric HSP70 inhibitors.
In addition, the explored I-IIIa, which may represent lead compounds for the development of optimized multi-drugs that correct the basic defect in CF patients, being of high relevance for the development of treatments able to revert or arrest the progression of the disease.

Exploring In Silico the Human HSP70 Protein
Up to now, structure-based studies concerning the putative binding positioning experienced by the well-known HSP70 inhibitor MKT-077 have performed, taking into account the X-ray data of the bovine protein (PDB code = 3HSC) [42]. These studies revealed that MKT-077 and its analogs bind within a highly conserved, hydrophobic pocket, adjacent to the nucleotide-binding cleft. In particular, the main benzothiazole core shows favorable hydrophobic contacts with the protein cavity, while the rhodacyanine group appears to play a role in orienting the other rings but detecting a few numbers of direct contacts. Conversely, the benzothiazole ring occupied a relatively narrow pocket, suggesting the need of a flat core able to occupy this region, showing small substituents.
Herein, MKT-077 and the best-scored and filtered AATs I-IIIa have been evaluated, in combination with VX-809, in order to confirm their CFTR modulator effectiveness. Meantime, the insilico prediction of descriptors, related to absorption, distribution, metabolism, and excretion properties (ADME), have been determined, in order prioritize the most promising AATs for further optimization. This approach allowed us to assess the rescue ability of the selected multi-compound treatment, supporting the CFTR amplifier ability promoted for the allosteric HSP70 inhibitors.
In addition, the explored I-IIIa, which may represent lead compounds for the development of optimized multi-drugs that correct the basic defect in CF patients, being of high relevance for the development of treatments able to revert or arrest the progression of the disease.

Exploring In Silico the Human HSP70 Protein
Up to now, structure-based studies concerning the putative binding positioning experienced by the well-known HSP70 inhibitor MKT-077 have performed, taking into account the X-ray data of the bovine protein (PDB code = 3HSC) [42]. These studies revealed that MKT-077 and its analogs bind within a highly conserved, hydrophobic pocket, adjacent to the nucleotide-binding cleft. In particular, the main benzothiazole core shows favorable hydrophobic contacts with the protein cavity, while the rhodacyanine group appears to play a role in orienting the other rings but detecting a few numbers of direct contacts. Conversely, the benzothiazole ring occupied a relatively narrow pocket, suggesting the need of a flat core able to occupy this region, showing small substituents.
Herein, we proceed for the first time to a careful analysis of the docking mode of the inhibitor MKT-077, as well as of the analogues reported in the literature, see Supplementary Tables S1 and S2), relying on the experimental data of the human enzyme (PDB code = 6CZ1) [37]. This kind of approach is expected to clarify the most important chemical interactions, and the related amino acids supporting the compound HSP70 inhibitory ability, and to open the way for the following virtual screening strategy.
Initially, the three-dimensional coordinates of the human Hsp70 (monomer A) and bovine one had been aligned and superposed, by means of MOE software [45], giving pairwise percentage residue identity values of 69.9%, while the root mean square deviation value (RMSD; calculated on the carbon atom alignment) between the two proteins was of 1.254 Å (see the protein alignment in Figure 3).
ity JG-294, as representative of the series for purified Hsp70 in vitro, using a fluorescence shift assay. Compound JG-258 (62; pEC50 = 5.30 M) was also used as negative control.
Herein, we proceed for the first time to a careful analysis of the docking mode of the inhibitor MKT-077, as well as of the analogues reported in the literature, see Supplementary Tables S1 and S2), relying on the experimental data of the human enzyme (PDB code = 6CZ1) [37]. This kind of approach is expected to clarify the most important chemical interactions, and the related amino acids supporting the compound HSP70 inhibitory ability, and to open the way for the following virtual screening strategy.
Initially, the three-dimensional coordinates of the human Hsp70 (monomer A) and bovine one had been aligned and superposed, by means of MOE software [45], giving pairwise percentage residue identity values of 69.9%, while the root mean square deviation value (RMSD; calculated on the carbon atom alignment) between the two proteins was of 1.254 Å (see the protein alignment in Figure 3).  [37], with respect to the bovine one (PDB code = 3HSC) [42]. The conserved residues are highlighted in grey. Poorly conserved aminoacids, in terms of hydrophilic or hydrophobic properties, are shown in black. When polar features or lipophilic requirements are shared or maintained, the related couple of aligned residues is colored. The alignment was depicted thanks to the visualization UCSF Chimera software [46]. These findings supported a good similarity, shared by the two enzymes, as confirmed by the superimposition of 6CZ1 on the X-ray data of 3HSC, reported in Figure 4 (left; ribbon in cyan and light yellow, respectively). A perspective of the overall conserved regions of the two proteins is also shown in green (Figure 4; right).  [37], with respect to the bovine one (PDB code = 3HSC) [42]. The conserved residues are highlighted in grey. Poorly conserved aminoacids, in terms of hydrophilic or hydrophobic properties, are shown in black. When polar features or lipophilic requirements are shared or maintained, the related couple of aligned residues is colored. The alignment was depicted thanks to the visualization UCSF Chimera software [46]. These findings supported a good similarity, shared by the two enzymes, as confirmed by the superimposition of 6CZ1 on the X-ray data of 3HSC, reported in Figure 4 (left; ribbon in cyan and light yellow, respectively). A perspective of the overall conserved regions of the two proteins is also shown in green (Figure 4; right).
Accordingly, several residues resulted to be maintained along the whole structure of the two Hsp70 proteins, suggesting quite comparable binding sites at the two macromolecules. As shown in Table 1, a number of residues supporting the MKT-077 binding at the bovine HSP70 cavity, as reported in the literature [37], are conserved at the human HSP70. Among them, four aminoacids, scouted as key residues for the ligand binding at the bovine protein by mutagenesis experiments (Y149, T222, H227, and L228), were maintained as Y175, T247, H252, and L263 within the human protein.
Nevertheless, two residues featured electrostatic and steric variation, moving from the bovine enzyme to the human one, as exemplified by the two small and hydrophobic A223 and V82 residues in 3HSC, which correspond to the human hydrophilic N248 and S107 residues. As a consequence, the overall cavity delimited at the 6CZ1 allosteric binding site could be differently occupied by the inhibitors.

Molecular Docking Studies of MKT-077 and Related Analogues
On this basis, and to further assess the reliability of the human HSP70 putative binding site, proposed as previously described, we have considered the site finder module of the MOE software to identify the best score binding site at 6CZ1. The results suggested and  Figure 4. Superimposition of the X-ray crystallographic data of the human HSP70 (PDB code = 6CZ1; ribbon in cyan) [37] onto those of the bovine protein (PDB code = 3HSC; ribbon in light yellow) [42] (left side). A perspective of the conserved regions of the two proteins, based on the visualization UCSF Chimera software [46], is highlighted in green (right side).
Accordingly, several residues resulted to be maintained along the whole structure of the two Hsp70 proteins, suggesting quite comparable binding sites at the two macromolecules. As shown in Table 1, a number of residues supporting the MKT-077 binding at the bovine HSP70 cavity, as reported in the literature [37], are conserved at the human HSP70. Among them, four aminoacids, scouted as key residues for the ligand binding at the bovine protein by mutagenesis experiments (Y149, T222, H227, and L228), were maintained as Y175, T247, H252, and L263 within the human protein. Table 1. Comparison of the putative MKT-077 binding domain at the bovine HSP70 cavity and human HSP70. The key residues for the ligand binding, based on mutagenesis experiments, are labelled in cyan [37].

Protein PDB Code
Binding Site: Pairwise Amino Acids  3HSC  K71  R72  V82  P147  Y149  F150  T222  6CZ1  K96  R97  S107  P173  Y175  F176  T247  3HSC  A223  G224  D225  T226  H227  L228  6CZ1  N248  G249  D250  T251  H252  L263 Nevertheless, two residues featured electrostatic and steric variation, moving from the bovine enzyme to the human one, as exemplified by the two small and hydrophobic A223 and V82 residues in 3HSC, which correspond to the human hydrophilic N248 and S107 residues. As a consequence, the overall cavity delimited at the 6CZ1 allosteric binding site could be differently occupied by the inhibitors.

Molecular Docking Studies of MKT-077 and Related Analogues
On this basis, and to further assess the reliability of the human HSP70 putative binding site, proposed as previously described, we have considered the site finder module of the MOE software to identify the best score binding site at 6CZ1. The results suggested and confirmed the same crevice, identified by comparison with 3HSC, giving us the opportunity to proceed with the following molecular docking calculations described.
Starting from this data, we performed docking studies of the reference compound MKT-077, as well as of the aforementioned different analogues reported in the literature 1-90 (see Supplementary Tables S1 and S2). The related scoring functions have been shown in Supplementary Table S3. Based on our calculations, the docking positioning of the reference Hsp70 allosteric inhibitor MKT-077 experienced polar contacts, involving the carbonyl oxygen atom of the main five-membered ring and side chains of R97 and T251 (see Figure 5). In addition, it . Superimposition of the X-ray crystallographic data of the human HSP70 (PDB code = 6CZ1; ribbon in cyan) [37] onto those of the bovine protein (PDB code = 3HSC; ribbon in light yellow) [42] (left side). A perspective of the conserved regions of the two proteins, based on the visualization UCSF Chimera software [46], is highlighted in green (right side). Starting from this data, we performed docking studies of the reference compound MKT-077, as well as of the aforementioned different analogues reported in the literature 1-90 (see Supplementary Tables S1 and S2). The related scoring functions have been shown in Supplementary Table S3. Based on our calculations, the docking positioning of the reference Hsp70 allosteric inhibitor MKT-077 experienced polar contacts, involving the carbonyl oxygen atom of the main five-membered ring and side chains of R97 and T251 (see Figure 5). In addition, it proved to be highly stabilized at the HSP70 surface, thanks to: (i) polar and cation-π interactions, involving the terminal benzothiazole ring and Mg 2+ , K96; (ii) cation-π contacts between the pyridine-containing cation group and Y175 sidechain.
Notably, the key role played by interacting with Y175 was in accordance with mutagenesis experiments solved by other authors for the corresponding bovine HSP70 residue Y149 (see the previously cited Table 1). Thus, specific requirements, in terms of proper balanced hydrophilic and hydrophobic properties within the allosteric inhibitor, resulted to be mandatory to fit the protein surface, as shown in Figure S1, as a ligplot of YM-01. Accordingly, YM-01 featured an extended and consistent electron-rich flat core, which was properly projected towards positively charged motifs of the biological target, such as Mg2+, Lys96, and Arg97. Conversely, the inhibitor cation moiety was oriented in proximity of the solvent-exposed surface of the HSP70 protein, being involved in cation-π stacking with Tyr175 (see Figure 6, the electrostatic properties of YM-01 are shown on the left).
It is worth noting that the aforementioned electrostatic properties turned out to be efficiently guaranteed by the conjugated system, through the folded aromatic structure of the inhibitor YM-01, being endowed with two terminal aromatic rings. These would contribute to stabilize the compound at the HSP70 surface, thanks to aromatic interactions and cation-π stacking with Tyr175 and Lys96, also fulfilling the steric requirements, as described by this narrow pocket of the enzyme (see Figure 6, where the lipophilic properties of YM-01 are shown on the right). proved to be highly stabilized at the HSP70 surface, thanks to: (i) polar and cation-π interactions, involving the terminal benzothiazole ring and Mg 2+ , K96; (ii) cation-π contacts between the pyridine-containing cation group and Y175 sidechain. Notably, the key role played by interacting with Y175 was in accordance with mutagenesis experiments solved by other authors for the corresponding bovine HSP70 residue Y149 (see the previously cited Table 1). Thus, specific requirements, in terms of proper balanced hydrophilic and hydrophobic properties within the allosteric inhibitor, resulted to be mandatory to fit the protein surface, as shown in Figure S1, as a ligplot of YM-01. Accordingly, YM-01 featured an extended and consistent electron-rich flat core, which was properly projected towards positively charged motifs of the biological target, such as Mg2+, Lys96, and Arg97. Conversely, the inhibitor cation moiety was oriented in proximity of the solvent-exposed surface of the HSP70 protein, being involved in cation-π stacking with Tyr175 (see Figure 6, the electrostatic properties of YM-01 are shown on the left). It is worth noting that the aforementioned electrostatic properties turned out to be efficiently guaranteed by the conjugated system, through the folded aromatic structure of between the pyridine-containing cation group and Y175 sidechain. Notably, the key role played by interacting with Y175 was in accordance with mutagenesis experiments solved by other authors for the corresponding bovine HSP70 residue Y149 (see the previously cited Table 1). Thus, specific requirements, in terms of proper balanced hydrophilic and hydrophobic properties within the allosteric inhibitor, resulted to be mandatory to fit the protein surface, as shown in Figure S1, as a ligplot of YM-01. Accordingly, YM-01 featured an extended and consistent electron-rich flat core, which was properly projected towards positively charged motifs of the biological target, such as Mg2+, Lys96, and Arg97. Conversely, the inhibitor cation moiety was oriented in proximity of the solvent-exposed surface of the HSP70 protein, being involved in cation-π stacking with Tyr175 (see Figure 6, the electrostatic properties of YM-01 are shown on the left). It is worth noting that the aforementioned electrostatic properties turned out to be efficiently guaranteed by the conjugated system, through the folded aromatic structure of With the introduction of several chemical substituents on two reference inhibitors MKT-077 (MCF-7 pEC 50 = 5.66) and YM-01 (MCF-7 pEC 50 = 5.28), and, in particular, with the insertion of halogens or ether substituents in the main bicyclic core, effective fluorinated analogues, such as 5-8 (MCF-7 pEC 50 = 5.62-6.10) and 1-4 (MCF-7 pEC 50 = 4.74-6.00), have been constructed, respectively.
As shown in Figure 7, the docking positioning observed for the HSP70 inhibitor 1 was highly comparable with that of YM-01, revealing a proper role played by the electron-rich 3-F group to detect polar contacts with Mg 2+ .
Any substitution to the substituents R2 and R3, considering the (aryl)alkyl groups, resulted in a promising effect, created by the benzyl group in R3 (rather than R2), by maintaining the ethyl part in R2, especially in the presence of the chlorine atom or additional hydrophobic groups in R1, at position 5 of the bicyclic nucleus. nated analogues, such as 5-8 (MCF-7 pEC50 = 5.62-6.10) and 1-4 (MCF-7 pEC50 = 4.74-6.00), have been constructed, respectively.
As shown in Figure 7, the docking positioning observed for the HSP70 inhibitor 1 was highly comparable with that of YM-01, revealing a proper role played by the electronrich 3-F group to detect polar contacts with Mg 2+ . Any substitution to the substituents R2 and R3, considering the (aryl)alkyl groups, resulted in a promising effect, created by the benzyl group in R3 (rather than R2), by maintaining the ethyl part in R2, especially in the presence of the chlorine atom or additional hydrophobic groups in R1, at position 5 of the bicyclic nucleus.
Indeed, as shown in Figure 8, the benzothiazole moiety and terminal benzyl group were projected towards the cation Mg 2+ and the Tyr175, displaying cation-π and π-π stackings. This kind of positioning was deeply stabilized by additional H-bonds, involving the ester moiety and Thr247, while the carbonyl oxygen atom and protonated nitrogen one experienced polar contacts with the surrounding Arg97 and Asp250.
It is thought that proper steric properties are required for optimized aromatic substituents as R3, which would efficiently fit the enzyme cavity delimited by Tyr175, Asn248, Gly249, Asp250, and Thr251. This information is supported by the high pEC 50 value observed for the dimethyl-substituted thiophene-containing derivative 72 (MCF-7 pEC 50 = 7.01). Indeed, as shown in Figure 8, the benzothiazole moiety and terminal benzyl group were projected towards the cation Mg 2+ and the Tyr175, displaying cation-π and π-π stackings. This kind of positioning was deeply stabilized by additional H-bonds, involving the ester moiety and Thr247, while the carbonyl oxygen atom and protonated nitrogen one experienced polar contacts with the surrounding Arg97 and Asp250. Moreover, the isosteric replacement of the benzyl group as R3 with the thiophene ring led to further MKT-077 analogues, such as 68-72 (MCF-7 pEC50 = 6.14-7.01), also endowed with MCF-7 inhibitory ability, including some with comparable potency values, compared to benzyl-containing compound 30 (MCF-7 pEC50 = 6.40).
It is thought that proper steric properties are required for optimized aromatic substituents as R3, which would efficiently fit the enzyme cavity delimited by Tyr175, Asn248, Gly249, Asp250, and Thr251. This information is supported by the high pEC50 value observed for the dimethyl-substituted thiophene-containing derivative 72 (MCF-7 pEC50 = 7.01).

QSAR Analyses
During the last years, applying computational methods to the search of novel bioactive compounds proved to be highly effective and useful along the drug discovery process [47,48]. While protein modelling allows to simulate the main drug-target binding interactions, QSAR analyses turns in quantitative methods to predict the potency of further novel compounds [49,50].
In this context, we deemed it interesting to explore, by development of a QSAR model, the different potency featured by the MKT-077 analogues, herein investigated (1-90) as putative HSP70 inhibitors, referring to their MCF-7 antiproliferative ability.

QSAR Analyses
During the last years, applying computational methods to the search of novel bioactive compounds proved to be highly effective and useful along the drug discovery process [47,48]. While protein modelling allows to simulate the main drug-target binding interactions, QSAR analyses turns in quantitative methods to predict the potency of further novel compounds [49,50].
In this context, we deemed it interesting to explore, by development of a QSAR model, the different potency featured by the MKT-077 analogues, herein investigated (1-90) as putative HSP70 inhibitors, referring to their MCF-7 antiproliferative ability.
The QSAR model, developed considering the compound positioning observed by docking calculations, is expected to deepen our knowledge of the main relevant chemical substitutions to efficiently design novel MKT-077 analogues as MCF-7 inhibitors.
This study was performed applying a statistical approach, previously described [51]. The final model was obtained by splitting the compounds into a training and test set, using the Kennard-Stone design [52], one of the most popular algorithms for guiding the selection of a subset of samples with a distribution as close as possible to the uniform distribution. In particular, the Kennard-Stone algorithm was performed, adding the response vector (pEC 50 ) as an additional column to the matrix of the descriptors, in order to ensure that the training set compounds were distributed evenly within not only in the space defined by the descriptors but also by the response values [53].
Among the 333 molecular descriptors, the most informative ones were identified using a multivariate variable selection method. In particular, iterative stepwise elimination PLS (ISEPLS) [54] was applied, in order to evaluate the relevance of the predictors, with regard to the possibility of predicting the response variable y (pEC 50 ). Following this approach, eight descriptors were retained, as related to the MCF-7 inhibitory ability experienced by the collected compounds, most of them being 2D descriptors (see Table 2). Indeed, five descriptors fall in the 2D cluster, as follows: one in the 2D-I group, two in the 2D-II group, and one in the 2D-V and 2D-VI groups, respectively. Then, two parameters fall in the 3D-I cluster, with the final one in the 3D-VI. Table 2. List of the selected descriptors, in tandem with the related type, series, and relative importance index (RI).

Descriptor
Type Series RI bpol Sum of the absolute value of the difference between atomic polarizabilities of all bonded atoms in the molecule (including implicit hydrogens).

Q_VSA_POS
Total positive van der Waals surface area. This is the sum of the vi, such that q i is non-negative. The vi are calculated using a connection table approximation. The predictive model was calculated by dividing the whole dataset of ninety-two compounds into a training set, (MKT-077, 1, 3-12, 14, 16-19, 21-25 67, 70, 77, 82, 86), in order to assess the reliability of the regression model. In particular, the final model was generated by employing PLS analysis to give a cross validated r 2 (r 2 cv ) = 0.78, a non-cross validated r 2 (r 2 ncv ) = 0.82, root mean square error (RMSE) = 0.310, and a test set r 2 (r 2 pred ) = 0.85. The predicted and experimental MCF-7 inhibitor ability for all the compounds is reported as tables, along with the collected descriptors, as shown in Supplementary Table S4. A perspective of the high performance of this model is represented in Figure 9, in terms of distribution of the predicted (Pred.pEC 50 ), with respect to the experimental (Exp.pEC 50 ) potency values of the dataset compounds.
Quantitatively, the MCF-7 inhibitory ability of the compounds, here investigated, is explained by the following Equation (1): pEC 50 = 2.30164 + 0.06220 · bpol − 0.11591 · E_str + 0.03423 · E_strain + 0.00122 · Q_VSA_POS − 0.03745 · SlogP_VSA1 − 0.01321 · SlogP_VSA3 + 0.00554 · vsa_hyd + 0.04307 · vsurf_DD23 (1) Most of the selected descriptors deal with the polarity profile of the compounds (such as bpol and Q_VSA_POS), extended along the molecular surface of the ligands, which would exhibit quite flat or poorly flexible conformation (see the E_str descriptor). This turns in specific requirements, in order to guarantee the necessary hydrophilic/hydrophobic properties onto the overall surface extent, as suggested by the vsa_hyd descriptor. This is in harmony with the results obtained by docking calculations, regarding the likely role played by two aromatic terminal rings being engaged in cation-π or π-π stacking with the cation Mg 2+ and Tyr175.
give a cross validated r 2 (r 2 cv) = 0.78, a non-cross validated r 2 (r 2 ncv) = 0.82, root mean square error (RMSE) = 0.310, and a test set r 2 (r 2 pred) = 0.85. The predicted and experimental MCF-7 inhibitor ability for all the compounds is reported as tables, along with the collected descriptors, as shown in Supplementary Table S4. A perspective of the high performance of this model is represented in Figure 9, in terms of distribution of the predicted (Pred.pEC50), with respect to the experimental (Exp.pEC50) potency values of the dataset compounds. Quantitatively, the MCF-7 inhibitory ability of the compounds, here investigated, is explained by the following Equation (1): pEC50 = 2.30164 + 0.06220 · bpol − 0.11591 · E_str + 0.03423 · E_strain + 0.00122 · Q_VSA_POS − 0.03745 · SlogP_VSA1 − 0.01321 · SlogP_VSA3 + 0.00554 · vsa_hyd + 0.04307 · vsurf_DD23 (1) Most of the selected descriptors deal with the polarity profile of the compounds (such as bpol and Q_VSA_POS), extended along the molecular surface of the ligands, which would exhibit quite flat or poorly flexible conformation (see the E_str descriptor). This turns in specific requirements, in order to guarantee the necessary hydrophilic/hydrophobic properties onto the overall surface extent, as suggested by the vsa_hyd descriptor. This is in harmony with the results obtained by docking calculations, regarding the likely role In particular, in Table 3, the mean values of a number of descriptors chosen as representative for the related 2D and 3D sub-classes are reported based on the main cation portion of the compounds. Only the most active thiazole-containing derivatives (pEC 50 > 6.80 M) had been considered as references for optimized derivatives. Table 3. List of the mean values of the most relevant 3D and 2D descriptors featured by pyridine-and thiazole-based MKT-077 analogues.

MCF-7 Inhibitors
E_Str mean SlogP_VSA1 mean bpol mean Q_VSA_POS mean Vsa_hyd mean pEC 50 Pyridine-based MKT-077 analogues 18 Among them, the E_str and SlogP_VSA1 proved to be negatively related to the compound potency (shown in italic in Table 3), while increasing values of bpol, Q_VSA_POS, and Vsa_hyd led to more promising analogues. Accordingly, the calculated mean values of E_str for the most potent thiazoles (pEC 50 > 6.80 M; E_Str mean = 3.5747) was lower than that for the less promising pyridine-based analogues (pEC 50 4.72-6.10; E_Str mean = 18.4938), while the related SlogP_VSA1 mean values were quite comparable. Then, all the parameters positively related to the biological activity reported in Table 3 (bpol, Q_VSA_POS and Vsa_hyd) were properly higher for the most promising thiazoles than for the bioisostere pyridine-containing precursors.
A schematic representation of the role played by most of them is shown in Figure 10, once again revealing the high correlation between the reported descriptors and experimental pEC 50 values of the whole dataset.
Along with this information, the optimal number of the bpol, Q_VSA_POS, and Vsa_hyd descriptors should be higher than 40, 300, and 400, respectively.
The reliability of this information is verified by the mean values observed for the aforementioned bpol, Vsa_hyd, and Q_VSA_POS, when focusing on the only most active thiazoles (pEC 50 > 6.80 M). As shown in Table 4, within the thiazole series, the most potent benzyl-containing derivatives featured slightly higher values for these parameters than the five-membered ring analogues, with the exception of Q_VSA_POS. On the other hand, the five-membered, ring-containing analogues displayed limited, just adequate bpol values.
ters positively related to the biological activity reported in Table 3 (bpol, Q_VSA_POS and Vsa_hyd) were properly higher for the most promising thiazoles than for the bioisostere pyridine-containing precursors.
A schematic representation of the role played by most of them is shown in Figure 10, once again revealing the high correlation between the reported descriptors and experimental pEC50 values of the whole dataset. Along with this information, the optimal number of the bpol, Q_VSA_POS, and Vsa_hyd descriptors should be higher than 40, 300, and 400, respectively.  Despite this, by an overall perspective of the data shown in Table 4, in any case, the described thiazoles experienced acceptable descriptor values, often in accordance with the previously recommended ones (bpol > 40, Q_VSA_POS >300 and Vsa_hyd > 400).

Virtual Screening of AATs as Putative HSP70 Inhibitors
In the search of CFTR modulators, during the last years, we evaluated various AATs with the interesting ability to improve both the trafficking and gating of mutant CFTR [39], while, more recently, we have synthetized a library of new AAT-VX-809 hybrid derivatives featuring the reference corrector benzodioxole-based carboxamide moiety, maintaining the prototype corrector ability [40,41].
Thus, this novel class of correctors was further optimized by us towards the discovery of a number of analogues featuring comparable potency, with respect to VX809 (EC 50 = 2600 nM), such as compound 7m (EC 50 = 70 nM), shown in Figure S3. The effectiveness of these compounds, as F508del CFTR correctors, was confirmed by biological and biochemical experiments [41].
Nowadays, based on the efficient F508del-CFTR rescue, achieved by co-administration of VX809, in the presence of the HSP70 allosteric inhibitor MKT-077 [31], we proceeded with virtual screening campaigns towards the discovery of novel likely HSP70 inhibitors.
Based on the aforementioned information, obtained by molecular docking studies and QSAR calculations, we filtered a number of MKT-077 analogues within the in-house series of AATs, taking into account their ability to share the observed docking mode of the reference compound MKT-077. In particular, we focused on and then better explored compound Ia, whose chemical structure highly resembles the one of the prototype MKT-077.
Indeed, Ia appears to show chemical characteristics comparable to the precursor but with a thiazole core as spacer between the flat benzothiazole terminal ring and pyridine group of the prototype, being that this one changed in a phenyl ring for compound Ia (see Figure 11). Our preliminary computational studies supported the structural similarity between MKT-077 and Ia, revealing comparable electrostatic properties and hydrophobic contact areas onto the related Connolly surface. In fact, the two compounds share similar shape and distribution of hydrophobic features, suggesting a key role played by the aromatic and hydrophobic ring within the HSP70 inhibitor chemical structure. As shown in Figure  12 (upper left and right side of the image, MKT-077 and Ia are reported), the extended hydrophobic area of the two derivatives is represented in green, while less lipophilic groups are highlighted in white. Our preliminary computational studies supported the structural similarity between MKT-077 and Ia, revealing comparable electrostatic properties and hydrophobic contact areas onto the related Connolly surface. In fact, the two compounds share similar shape and distribution of hydrophobic features, suggesting a key role played by the aromatic and hydrophobic ring within the HSP70 inhibitor chemical structure. As shown in Figure 12 (upper left and right side of the image, MKT-077 and Ia are reported), the extended hydrophobic area of the two derivatives is represented in green, while less lipophilic groups are highlighted in white.
Running activeLP calculations gives a perspective of the overall mild polar, H-bonding, and hydrophobic properties of the two compounds, being shown in blue, yellow, and red, respectively (see Figure 12, down, left, and right side of the image, MKT-077 and Ia are reported).
Thus, Ia was endowed by adequate electrostatic properties and H-bonding features, thanks to the thiazole ring heteroatoms, if compared to the electro-negatively charged carbonyl group of the MKT-077 thiazolidine one.
In addition, molecular docking calculations revealed a common binding positioning for both MKT-077 and Ia within the human HSP70 putative allosteric binding site, detecting the previously mentioned π-π stacking and cation-π contacts with the key residue Tyr175 and Mg 2+ . As shown in Figure 12, the amino-aryl moiety of Ia was properly superposed on the prototype pyridine ring, while the thiazole core overlapped the MKT-077 thiazolidine ring. This allowed compound Ia to maintain the necessary Van der Waals and polar contacts with the surrounding residues Gly249, Tyr175, Arg97, and Arg101. On the other Our preliminary computational studies supported the structural similarity between MKT-077 and Ia, revealing comparable electrostatic properties and hydrophobic contact areas onto the related Connolly surface. In fact, the two compounds share similar shape and distribution of hydrophobic features, suggesting a key role played by the aromatic and hydrophobic ring within the HSP70 inhibitor chemical structure. As shown in Figure  12 (upper left and right side of the image, MKT-077 and Ia are reported), the extended hydrophobic area of the two derivatives is represented in green, while less lipophilic groups are highlighted in white. In order to better explore the effectiveness of aromatic features, enriched with electro withdrawing substituents, aimed to improve the polar contacts with their neighboring residues, also we consider two Ia analogues, namely IIa and IIIa (see chemical structures in Figure 11).
In particular, the presence of the disubstituted phenyl ring at the amino-aryl portion (IIa) or tethered to the position 4 of the thiazole core (IIIa) is expected to simulate the behavior played by the benzothiazole of MKT-077.
Accordingly, based on the docking positioning of IIa and IIIa, the disubstituted phenyl ring of the two compounds quite overlapped the benzothiophene-based ring of MKT-077 (see Figures S4 and S5). In this way, II-IIIa maintained the required cation-stacking with the metal ion, while the terminal mono-substituted aromatic ring guarantees the proper π-π interactions with Tyr175.
Based on these encouraging data, the aforementioned compounds I-IIIa have been submitted to the following chemical synthesis and biological evaluation. In particular, we synthesized compounds I-IIa based on the chemical synthesis previously described [39], and then measured their cellular effects as pharmacological chaperones, in combination with correctors VX-809 and 7m.

Biological Evaluation of I-IIIa in Presence of F508del CFTR Correctors
Compounds I-IIIa had been synthesized based on the chemical synthesis previously described [39], and then, by exploiting the YFP-based functional assay, we performed a preliminary evaluation of their efficacy in rescuing mutant F508del-CFTR trafficking, as single agents or in combination with correctors VX-809 and 7m [41].
In order to assess the effect of HSP70 pharmacological inhibition on mutant CFTR rescue, we first evaluated the ability of our reference compound MKT-077 to improve CFTR trafficking and function, when administered in the presence of VX-809. To this aim, we exploited the YFP-based functional assay.
Our results show that cells treated with VX809 displayed an increase in iodide influx that was further enhanced when MKT-077 (10nM) was added in combination with VX809. As shown in Figure 13, these data are in agreement with the data reported in the literature [31]. We then focused on the MKT-077 highly related analogue Ia. As in the case of MKT-077, the YFP-based functional assay demonstrated its rescue activity, as well as its comparable additive effect, when co-administered with VX-809. Interestingly, these data strongly support: (i) the common indirect CFTR modulator ability likely via HSP70 inhibition and then (ii) the effectiveness of neutral substituents at terminal aromatic ring (such as the compound Ia phenyl ring). Indeed, biological assays reported in the literature also demonstrated the maintained anti-proliferative activity of derivatives bearing neutral pyridines, targeting the HSP70 protein [55].
Similar additive effects of Ia were also observed, when combined with another corrector, the in-house VX-809 hybrid 7m (see Figure 14).  We then focused on the MKT-077 highly related analogue Ia. As in the case of MKT-077, the YFP-based functional assay demonstrated its rescue activity, as well as its comparable additive effect, when co-administered with VX-809. Interestingly, these data strongly support: (i) the common indirect CFTR modulator ability likely via HSP70 inhibition and then (ii) the effectiveness of neutral substituents at terminal aromatic ring (such as the compound Ia phenyl ring). Indeed, biological assays reported in the literature also demonstrated the maintained anti-proliferative activity of derivatives bearing neutral pyridines, targeting the HSP70 protein [55].
Similar additive effects of Ia were also observed, when combined with another corrector, the in-house VX-809 hybrid 7m (see Figure 14). We then focused on the MKT-077 highly related analogue Ia. As in the case of MKT-077, the YFP-based functional assay demonstrated its rescue activity, as well as its comparable additive effect, when co-administered with VX-809. Interestingly, these data strongly support: (i) the common indirect CFTR modulator ability likely via HSP70 inhibition and then (ii) the effectiveness of neutral substituents at terminal aromatic ring (such as the compound Ia phenyl ring). Indeed, biological assays reported in the literature also demonstrated the maintained anti-proliferative activity of derivatives bearing neutral pyridines, targeting the HSP70 protein [55].
Similar additive effects of Ia were also observed, when combined with another corrector, the in-house VX-809 hybrid 7m (see Figure 14).   As regarding compounds II-IIIa, IIa was the most effective, able to enhance the F508del CFTR rescue ability of VX-809, as previously described for the reference MKT-077 and benzothiazole-containing AAT Ia (see Figure 16). IIa was effective at comparable concentrations, with respect to the previous Ia (0.1 μM).  As regarding compounds II-IIIa, IIa was the most effective, able to enhance the F508del CFTR rescue ability of VX-809, as previously described for the reference MKT-077 and benzothiazole-containing AAT Ia (see Figure 16). IIa was effective at comparable concentrations, with respect to the previous Ia (0.1 µM).
Administering II-IIIa, in the presence of the hybrid 7m, also allowed us to modestly improve the compound corrector ability at low micromolar concentration (0.3 µM), as reported in Figure S6.
Further analyses of compound efficacy and mechanisms of action as CFTR modulators are needed to characterize these compounds, including testing in more relevant cell models, such as primary human bronchial cells from F508del-CFTR homozygous patients. These analyses are, however, beyond the scope of the present study.

In Silico PK Profile Prediction
Recently, the drug discovery process relied on the predictive ability of in-silico evaluation of absorption, distribution, metabolism, and excretion parameters (ADME). Evaluation by computational methods of the putative pharmacokinetic (PK) properties of ligands, deeply accelerated the hit-to-lead and lead optimization process [56][57][58]. In the search of effective and drug-like HSP70 modulators, it should be noticed that MKT-077 was found to be susceptible to rapid metabolism, due to oxidation of the benzothiazole ring and of the pyridinium group [55]. The following efforts had been attempted to design putative more drug-like analogues, leading to YM-01 (lacking any cation portion) and substituted benzothiazole-based compounds, such as JG98 and further congeners (JG231 and JG345) [37], being JG231 the most promising.
Thus, herein we explored in silico the predicted main PK properties, in terms of the drug-like profile of I-IIIa here discussed, in comparison with those calculated for the reference compound MKT-077 and previously mentioned highly related analogues YM-01, JG98, JG231, and JG345.
As regarding compounds II-IIIa, IIa was the most effective, able to enhance the F508del CFTR rescue ability of VX-809, as previously described for the reference MKT-077 and benzothiazole-containing AAT Ia (see Figure 16). IIa was effective at comparable concentrations, with respect to the previous Ia (0.1 μM).   It is well-known that the first ones (Lipinski's rule) suggest for ligands exhibiting MW < 500, cLogP < 5, HBA < 10, and HBD < 5, while the rule described by Veber concerns drug bioavailability, thanks to nRot_bonds ≤ 10, the sum of HBA and HBD < 12, and the TPSA descriptor ≤ 140 Å 2 .
According to the pK properties prediction, all the compounds fulfil Lipinski's and Veber's rules, with the exception of the suggested MW and cLogP values, which were quite > 500 for JG231, JG345 and >5 for II-IIIa, respectively. On the other hand, all the reported AATs experienced adequate molecular weight values (MW < 500), if compared to the MKT-077 analogues JG231 and JG345 (MW > 500).
Then, the in silico prediction of ADME properties was extended to human intestinal absorption (HIA), volume of distribution (Vd), and the evaluation of the plasmatic protein binding event (%PPB), as well as of the ligand affinity toward human serum albumin (LogKa HSA). These calculations had been performed, in order to assess the putative oral bioavailability as a percentage (%F) (see Table 6). As shown in Table 6

Ligand Preparation
All the studied correctors were manually built by the MOE Builder program [45] and then were parametrized (AM1 partial charges as calculation method), and energy was minimized by the energy minimize program, using a MMFF94x forcefield and RMS (root mean square) equal to 0.0001 Kcal/mol/A 2 of the MOE compute module, to produce a single low-energy conformation for each ligand [45]

Protein Preparation and In Silico Analysis
Both the two selected human and bovine HSP70 X-ray data had been collected from the protein data bank [38] and explored, thanks to the previous cited MOE software [45].
Alignment and superimposition of the two proteins have been performed by MOE. The related protein align module implements a modified version of the alignment methodology, originally introduced into molecular biology by [61]. In this approach, alignments are computed by optimizing a function based on residue similarity scores (obtained from applying an amino acid substitution matrix to pairs of aligned residues) and gap penalties. Penalties are imposed for introducing and extending gaps in one sequence, with respect to another. The final optimized function value is referred to as the alignment score. The basis of sequence-only alignment is the amino acid substitution matrix. MOE includes matrices derived directly from families of aligned proteins, as well as matrices derived by application of an evolutionary model to a set of closely related matrices. These matrices reside in a library included in the MOE software [45]. Calculation of the molecular electrostatic, hydrophobic, and ActiveLP properties at the Connolly surface of the human HSP70 protein had been performed, thanks to the surface and map tool implemented in MOE [45]. In particular, specific electrostatic properties had been reported onto the molecular surface of the protein, as preferred locations of hydrophobic, H-bond acceptor, and H-bond donor sites, based on the solutions of the Poisson-Boltzmann equation.
The molecular surface represents an approximation to the solvent-excluded surface, previously mentioned as the Connolly surface. The solvent-excluded surface encloses the volume, from which a probe sphere (usually with water radius 1.4 Å) is excluded when it rolls over a molecule. If the atoms of the molecule are represented as spheres having van der Waals radii, then the solvent-excluded volume comprises these sphere volumes, plus the regions in-between that are too small for the probe to fit into [62]. The surfaces of those regions, between neighboring atoms, are smooth concavities and are sometimes referred to as re-entrant [63,64]. The solvent-excluded surface is related to the accessible surface, which is the surface traced out by the center of a probe sphere rolling over the atoms of the molecule. In contrast to the re-entrant surface, the accessible surface has sharp valleys, where the probe surface touches the van der Waals spheres of two or more atoms.
An analytical method to calculate the solvent-excluded surface was first described in [65], and other methods have appeared over the years [64]. MOE uses the method of level sets, as proposed by [66].

Molecular Docking Studies
All the molecular docking calculations, herein described, had been performed by means of the DOCK tool implemented in MOE [45], choosing, as a binding site, the one identified thanks to the MOE site finder module, agreeing with the one described in the literature, regarding the bovine HSP70 and MKT-077 putative complex. Specific details of the docking module were previously reported [56]. Briefly, the alpha triangle, as a placement algorithm, was chosen, running by superposition of compound atom triplets and triplets of biological target site points. The enzyme points are shown as alpha sphere centers. At each iteration, a random conformation is chosen. A random triplet of compound atoms and a random triplet of alpha sphere centers are exploited to determine the pose. After calculation of the enthalpy-based affinity DG scoring parameter, the proposed best-scored fifty poses had been refined by the induced fit method to the final ten ones. These poses were rescored, considering the alpha HB methodology, based on H-bonding estimation.
This affinity DG function estimates the enthalpic contribution to the free energy of binding, by means of a linear function reported in our previous work, as well as details about the induced fit module [67].

QSAR Analysis
QSAR studies were performed based on calculations of about three hundred molecular descriptors, including 2D and 3D parameters, by means of the MOE software. The 2D molecular descriptors are defined to be numerical properties that can be calculated from the connection table representation of a molecule (e.g., elements, formal charges, and bonds, but not atomic coordinates). The 2D descriptors are, therefore, not dependent on the conformation of a molecule and are most suitable for large database studies. They include descriptors related to physical properties, subdivided surface areas, atom and bond counts, connectivity-based descriptors, partial charges descriptors, pharmacophore features descriptors, and the so-called adjacency and distance matrix descriptors. The 3D-descriptors consist of potential energy descriptors, MOPAC descriptors, surface area, volume and shape descriptors, and conformation dependent charge descriptors.
A final data matrix of 92 rows (molecules) and 333 columns (molecular descriptors) was obtained.
As a first step, the CHECK module implemented in the chemometric package PARVUS [68] was used in order to eliminate descriptors with constant or almost constant values for all molecules. Also, pairs of variables with a correlation coefficient greater than 0.99 were removed from the data matrix.
The remaining data was collected in an n × m matrix, where n = 92 and m = 294 were the numbers of molecules and descriptors, respectively.
Then, the Kennard-Stone duplex design [53] was used for splitting the input data into a training and a test set. In this way, both sets scattered over the whole range of the considered space, defined by the descriptors of molecular structure (X) and response (y) value (pEC 50 ). The Kennard-Stone duplex algorithm was applied using the first eight principal components of the autoscaled data, accounting for the 80% of the total variance. The 72 representative molecules were selected for the training set, and 20 were assigned to the test set (20% of the total molecules).
Among the 294 molecular descriptors, the most informative ones were identified using a multivariate variable selection method. In particular, iterative stepwise elimination PLS (ISEPLS) [54] was applied, in order to evaluate the relevance of the predictors, with regard to the possibility of predicting the response variable y (pEC 50 ). ISE is based on the importance of the predictors, defined as: where b v is the regression coefficient and s v the standard deviation of the descriptor v. In each elimination cycle, the descriptor with the minimum importance is eliminated, and the model is computed again with the remaining predictors. The final model, that with the maximum predictive ability in cross validation, retained eight relevant descriptors.
QSAR was performed by the application of partial least-squares (PLS) regression analysis, considering the selected eight molecular descriptors as independent variables and corrector pEC 50 values, as dependent variables. The leave-one-out validation procedure was used to check the internal predictability of the derived models. The predictive ability of the derived model was finally evaluated for the test set compounds (expressed as r 2 pred ), by using the following equation: SD is the sum of the squared deviations between the biological activities of the test set molecules and the mean activity of the training set compounds, and PRESS is the sum of the squared deviation between the observed and predicted activities of the test set compounds.

In Silico Evaluation ADME Properties
The prediction of any parameter related to ADME properties was performed, thanks to the Advanced Chemistry Development (ACD) Percepta platform [69]. This software works on the basis of the implemented training libraries, which include different series of compounds, in tandem with their experimentally evaluated pharmacokinetic properties.

Fluorescence Assay for CFTR Activity
CFBE41o-cells with stable expression of mutant CFTR and HS-YFP were plated on clear-bottom, 96-well black microplates (Corning Life Sciences, Acton, MA, USA), at a density of 50,000 cells/well and kept at 37 • C in 5% CO 2 for 24 h.
Prior to the assay, CFBE41o-cell plates were transferred to a microplate's reader (FluoStar Galaxy; BMG Labtech, Offenburg, Germany), equipped with high quality excitation (HQ500/20X: 500 ± 10 nm) and emission (HQ535/30M: 535 ± 15 nm) filters for YFP (Chroma Technology, Brattleboro, VT). Fluorescence was monitored continuously for 14 s, with 2 s before and 12 s after injection of an iodide-substituted solution (165 µL of a modified PBS, containing I-instead of Cl -; final Iconcentration in the well: 100 mM). Data were normalized to the initial background-subtracted fluorescence. To determine the fluorescence quenching rate, associated with I-influx, the final 10 s of data for each well were fitted with an exponential function to extrapolate initial slope (dF/dt).
Dose-response relationships from each experiment were fitted with the Hill equation, using the Igor software (WaveMetrics) to calculate EC 50 , maximal effect, and Hill coefficient.

Conclusions
The design of compounds targeting further biological targets involved in the CFTR physiological pathway, such as the molecular chaperone Hsp70, was found to be a promising strategy to optimize drug combinations for the treatment of CF. Accordingly, the allosteric HSP70 inhibitor MKT-077 proved to deeply amplify the corrector ability of VX-809. Despite this, it was withdrawn by Phase I clinical trials because of poor metabolic stability.
In this work, we reported, for the first time, structure-based studies related to the putative docking mode of MKT-077, as well as of several analogues described in the literature, considering the recent X-ray crystallographic structure of the human HSP70. This allowed us to point out the main interaction supporting their HSP70 allosteric inhibitor ability, including cation-π and π-π stacking, with the conserve residue Tyr175. All these compounds had been further explored by means QSAR analysis and used as reference compounds for the in-silico evaluation of AATs (I-IIIa), as putative HSP70 inhibitors, to be exploited in combination with VX-809. Following biological assays confirmed the effectiveness of I-IIIa in the presence of the reference F508del CFTR corrector VX-809, with IIa being the most promising. Further assays, performed in combination with the hybrid 7m, confirmed the indirect CFTR modulator ability featured by these AATs, when co-administered in the presence of potent F508del CFTR correctors. As a result, the biological assays validated the computational approach, herein proposed to guide the search of novel putative human Hsp70 inhibitors. Furthermore, prediction of the I-IIIa ADME and physicochemical properties versus MKT-077 and related optimized analogues (such as JG-231) enlightened favorable characteristics for the proposed AATs. This is expected to pave the way for the rational design of novel compounds lacking pyridinium ring. This could turn into new derivatives, endowed with a better bioavailability and metabolic stability.
Further analyses are, however, required to confirm the efficacy of putative HSP70 inhibitors, in order to improve mutant CFTR rescue, when co-administered with CFTR modulators. The development of compounds able to maximize CFTR function, when co-administered with modulator drugs, is of great interest, in particular for those patients bearing mutations displaying trafficking and/or gating defects poorly responsive to already approved modulators.
Overall, the positive outcome derived from this study verified the reliability of the applied computational studies, as well as the applied virtual screening protocol, shedding light on the thiazole core, as a privileged scaffold for the design of optimized CFTR modulators, probably via inhibition of the HSP70 protein.
Supplementary Materials: The following are available online at https://www.mdpi.com/article/ 10.3390/ph14121296/s1. Figure S1: electrostatic properties of the HSP70 inhibitor YM-01 and related ligplot at the HSP70 protein; Figure S2: molecular docking positioning of compound 43 and related ligplot; Figure S3: chemical structures of VX-809 and of compound 7m; Figure S4: molecular docking positioning of MKT-077 and of compound IIa; Figure S5: molecular docking positioning of MKT-077 and of compound IIIa; Figure S6: representative bar graphs, showing F508del-CFTR activity, measured with the HS-YFP microplate reader assay; Table S1: chemical structure and biological data of MKT-077 and the related six-membered ring analogs; Table S2: chemical structure of the five-membered ring analogs of the HSP70 inhibitor MKT-077; Table S3: molecular docking scoring functions, as related to MKT-077 and analogues; Table S4: list of the predicted and experimental MCF-7 antiproliferative ability for all the dataset compounds, in tandem with the collected descriptors.