Based on the model described above it was apparent; that the unsubstituted position on the pyridine ring in inhibitor 2, would be the most suitable position for the addition of a solubilising group as it would be highly solvent exposed (red arrow Figure 3.1). The phenyl ring situated at the top of the binding groove, appears to anchor the ligand in position through interaction with Leu43. Therefore following the Topliss scheme for optimisation of phenyl ring substitution, the only substitutions suggested in this region of the scaffold was the addition of a 4-chloro/ para-chloro group.[273] Despite
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the more lipophilic and electron withdrawing nature of the 4-chloro substitution, the ease of synthesis relative to other substituted compounds makes it a good first choice
for optimisation processes.[273] Furthermore the ortho and para substituted methyl
groups on the pyridine ring were removed, due to the fact that their presence could
render the molecule more lipophilic and thus less soluble.[274] The ortho methoxy
group of the pyridine ring was removed in favour of either a pyridine or pyridone ring
which would allow for substitutions at both meta positions. Finally selection of a
suitable solubilising group, resulted in investigations in heteroaliphatic and heteroaromatic rings, to determine which ring type would be most suitable.[275] The
different types of rings chosen to be screened (Figure 3.2) included; N-methyl
piperazine, morpholine, piperadine, imidazole and 1, 2, 4 triazole.
With the structural analysis of Inhibitor 2 complete, four main scaffolds were designed
(Figure 3.2), (a) and (b) pyridine, or (c) and (d) pyridone analogues, with meta
substitutions (R) being either amide or amine. This resulted in the design of 72 analogues however, due to the lack of commercial availability of a number of the solubilising groups, only 54 of the 72 analogues of Inhibitor 2 (Appendix Figure A.3.1 - A.3.3) were subsequently built and energy minimised in Spartan.[225]
Figure 3.2- Inhibitor 2 analogue design. The four main scaffolds can be observed with substitutions at the R (red) and R’ (blue) positions, resulted in 54 possible analogues of Inhibitor 2 to be computationally screened.
As with the workflow of the first generation of compounds, the 54 analogues of Inhibitor 2 were docked into NCS1 using GOLD and their predicted binding interactions assessed scored using Goldscore.[99] The one hundred docking poses of each of the compounds, were subsequently re-scored using the three scoring
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functions, Astex statistical potential (ASP), Chemscore and Chem Piecewise Linear Potential (PLP).[99,111] An average of the scoring functions was taken for each compound and the ADMET profiles (the physiochemical properties) were calculated in Pipeline Pilot.[125] Despite the additional solubilising groups the solubility profile of the 54 compounds was not always ideal (Appendix Section A.3 Table A.3.1). The predicted AlogP ranged from the unfavourable 3.787 to a much more favourable value of 0.413, which is considerably improved when compared to that of Inhibitor 2 whose AlogP was calculated as 3.737. The molecular solubility was also calculated for the 54 molecules and values ranged from the favourable -4.42 to a much less favourable value of -7.95, considerably less than that of Inhibitor 2 whose molecular solubility was calculated as -6.47. In fact of the 54 compounds designed to have an improved solubility, 15 were found to have a poorer profile than the parent compound and a further 19 were more negative than -6.0.
Due to the solubility issues of the first generation of inhibitors and the subsequent
challenges that this caused with the in vitro binding studies, it was decided the
selection process should filter out compounds with poor calculated molecular solubility. Compounds with a molecular solubility more negative than that of Inhibitor 2 were removed, the final 39 were ranked in ascending order of molecular solubility and the top 12 compounds (Table 3.1 and Figure 3.4) were selected for retro- synthetic analysis to determine compounds to synthesise.
Figure 3.3 - Second Generation Computational workflow. The computational workflow applied to the Inhibitor 2 analogues adapted from the previous first generation computational workflow used to select inhibitors 1, 2 and 3 (Chapter 2, Section 2.1). 54 compounds were designed and built in the molecular modelling package Spartan, they were subsequently docked into NCS1 using the docking programme GOLD where their binding poses were scored and re-scored. The ADMET profiles of each of the 54 compounds were then calculated and the ligands were ranked in order of their solubility and the top 10 compounds were selected for retro-synthetic analysis.
143 Table 3.1- Table showing the ADMET properties for the top 12 molecule derivatives on Inhibitor 2. Compounds are listed in descending order with respects to the overall best solubility profile. The molecular weight and solubility functions are indicated using a traffic light system following the Lipinski parameters and the filter of molecular solubility of Inhibitor 2 as -6.0: good values (green), intermediate (amber) and poor values (red).
Compound 3.13 has been included in the table in italics as it was selected for synthesis despite not ranking amongst the top 12 compounds.
D2R peptide Ligand Efficiency = 0.061
Figure 3.4- Top 12 compound derivatives of Inhibitor 2. The compounds ranked in order of their solubility profile. The relative ADMET properties for each compound can be seen in table 3.1.
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After retrosynthetic analysis, 3.5 was selected for synthesis and the synthetic route outlined in Section 3.2. Due to challenges encountered during the synthesis it was decided to also synthesise 3.13, a compound closely related to 3.5, the two only differ by a para-substituted chlorine (Figure 3.5). Compound 3.13 was not within the top 12 compounds with the best molecular solubility, however its predicted solubility was still predicted as being better that Inhibitor 2 (Table 3.1). The top predicted binding
pose for both 3.5 and 3.13 (Figure 3.5) indicate that the top binding pose of 3.5 is
different to that of Inhibitor 2, in comparison to 3.13 which is predicted to bind in a
145 Figure 3.5- Predicted binding poses of 3.5 and 3.13. (a) The top predicted binding pose of 3.5 with NCS1 (green) and the key residues highlighted (yellow) [4] along with the chemical structure. Compound 3.5 appears to adopt a curved binding pose in the lower region of the key residues within the hydrophobic binding groove of NCS1. (b) The top predicted binding pose of 3.13 and NCS1 (green) with the key residues highlighted (yellow) along with the chemical structure. Compound 3.13 appears to adopt a similar binding pose to that of Inhibitor 2 along the hydrophobic binding cleft, however the orientation is reversed.
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3.1.2 Summary
The significantly reduced solubility profiles of each of the three inhibitors determined during the biophysical analysis (Chapter 2.3) led to the subsequent development of a second generation of inhibitors.
Developing the second generation of inhibitors was conducted using Inhibitor 2 as a template due to its biophysical binding results (Chapter 2.3). The computational approach involved a more manual design process informed by docking results, through the analysis of the predicted binding interactions of Inhibitor 2. Compound design was informed by medicinal chemistry knowledge of solubilising groups. The 54 generated compounds were docked and their physiochemical properties calculated as with the first generation of inhibitors; however, the solubility profile of each compound was a key filter in the second generation selection process. The solubility profiles of the compounds were compared to that of Inhibitor 2 and those whose profile was not significantly improved were discarded. The remaining compounds were listed in ascending order with respect to their molecular solubility’s and the top 12 compounds were selected for retrosynthetic analysis. Compound 3.5 was intended to be the initial synthetic target, with the aim of synthesising a number
of closely related analogues; however, due to the challenging synthetic route, 3.13
was the only compound suitable. This compound has a similar structure and predicted binding pose to that of Inhibitor 2 and, hence, deemed a suitable second generation compound.
It has been said that the road to a successfully developed therapeutic is long, expensive and often frustrating.[117] There are many different options when it comes to “how to best design” a compound or target a specific interaction and they are all valid in one way or another. However the pipeline that has been developed here is a rationale and efficient method that combines different computational techniques, to produce the desired outcome of identifying hit compounds. The methodology could be applied to other protein-protein interactions and could significantly reduce the cost associated with experimentally screening vast chemical libraries. Although these are only calculated predictions and the experimental results may be found to differ, it is rational to start with a targeted approach.
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3.2 Second Generation Inhibitor Synthesis
3.2.1 Introduction
The first generation of inhibitors designed to disrupt the interaction between NCS1 and D2R peptide were analysed extensively using numerous biophysical techniques including NMR spectroscopy, ITC and tryptophan fluorescence (Chapter 2.3). However, limitations due to their limited solubility in aqueous buffer meant there were no quantifiable biophysical results. Therefore, it was decided to develop a second generation of inhibitors that would exhibit an improved solubility profile without losing efficacy towards the target. The selection process involved analysis of the predicted binding poses from the computational analysis of the first generation compounds; this was necessary since despite the extensive NMR experiments, there was a lack of accurate data that identified the exact binding locations of the inhibitors within NCS1. Inhibitor 2 was selected as the target scaffold because of the predicted binding pose along the hydrophobic groove of NCS1 (Chapter 2.1.5 Figure 2.13 d). As discussed previously, the computational process in designing and selecting these new
generation analogues involved the incorporation of solubilising groups such as N-
methylpiperazine, morpholine, piperidine, imidazole and 1,2,4-triazole. The pipeline took the 54 designed compounds and filtered them based on their solubility profile (Section 3.1). This resulted in 12 hit compounds that were analysed retrosynthetically to find a common route to synthesis that could be applied to all candidates. This would allow synthesis of a number of ligands with identical core scaffolds, but different solubilising functional groups. The first compound of the second generation, selected
for synthesis and for the development of the synthetic route was 3.6, due to the
commercial availability of the reagents.
Figure 3.6- Initial synthetic target 3.6.
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