Structural Optimization of Leads to Improve Select ADME Properties

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1 Application ote Structural ptimization of Leads to Improve Select ADME Properties Sanjivanjit K. Bhal & Karim Kassam Advanced Chemistry Development, Inc. Toronto,, Canada Introduction ne of the most challenging problems during the lead optimization phase of a potential drug candidate is achieving the right balance between efficacy, patentability concerns, toxicity, and ADME (absorption, distribution, metabolism, and excretion) properties. The synthesis of hundreds or thousands of analogs, at this stage, is aimed at improving or retaining therapeutic effectiveness while reducing toxicity, increasing solubility, increasing absorption, and/or increasing permeability. It is well known that these pharmacokinetic parameters are directly dependant on the physicochemical properties of a compound. In reality, the probability that a chemical entity will become a drug is very much dependant on its physicochemical properties. The medicinal chemist often relies on his or her experience, knowledge, ease of synthesis, and available literature resources to decide on the appropriate modifications around the pharmacaphore for lead optimization, and usually very little consideration is given to the physicochemical properties of the final molecule. This limitation can result in a time-consuming hit-and-miss approach in which valuable scientific resources are wasted and worse, the optimum drug candidate may be overlooked. While not claiming to be a complete solution to the lead optimization process, ACD/Structure Design Suite 1 is a software tool that significantly helps the medicinal chemist rapidly identify structural modifications to lead compounds (from a database of 30,000 substituents), that are expected to produce analogs with improved selected physicochemical properties. The chemist applies their knowledge of the pharmacaphore and physicochemical/adme liabilities to quickly generate a manageable group of analogs with an improved pharmacokinetic profile, for synthesis. In this application note, we will discuss how Structure Design Suite can be used to propose structural modifications of lead compounds to improve physicochemical properties such as logp and solubility. Discussion ptimizing LogP to Reduce Blood Brain Penetration To illustrate how Structure Design Suite helps in a lead optimization process, let us consider compound 1, which was the lead compound in clinical trials as a cardiotonic drug. Some patients taking this drug reported seeing bright visions ; a side-effect indicative of central nervous system (CS) activity caused by blood brain barrier (BBB) penetration. LogP of compound (1) is This value is very close to the rule of thumb logp value of 2 reported by Hansch, for a neutral compound to passively cross the BBB. 2

2 Application ote Kutter and Austel optimized this lead in-silico, making minor structural modifications resulting in reduced logp and improved therapeutic index. 3 A number of analogs were generated to this end and the candidate to successfully arrive on the market was Sulmazole (2), with a logp of Replacement of the methoxy substituent with a bioisosteric hydrophilic sulfinyl group sufficiently modified the liphophilicity of 1 to completely eliminate the unwanted CS related side-effects, but retained the desired activity. H 1 2 H S 2-(2-Dimethoxyphenyl)-1H-imidazo[4,5-b]pyridine Sulmazole LogP 2.59 LogP 1.17 Figure 1: Lead compound for cardiotonic activity (1) and final drug candidate (2). Compound Experimental logp Predicted logp 4 Lead candidate (1) Sulmazole (2) Figure 2: LogP values for compounds (1) and (2). Let us now study what structural modifications would be identified for this lead optimization problem using ACD/Structure Design Suite. In this investigation, the 4-methoxy position of 1 was selected as the site of modification to lower logp. 3 By the lead optimization stage, the pharmacaphore of a compound is generally well identified and structural modifications are focused to avoid changing this particular part of the molecule. We restricted the possibilities to neutral substituents within the molecular weight range to keep the suggested analogs as similar to the lead as possible. Given these criteria, the software successfully identified 55 analogs of 1 with predicted logp values below Moreover, Sulmazole (2) the structure arrived at by Kutter and Austel, was one of the analogues proposed. 2

3 Application ote Figure 3: Results from Structure Design Suite search for analogues of 1 with logp <2.59. Although we have not verified the experimental logp of all 55 analogues suggested using Structure Design Suite, confidence in these results can be garnered from the knowledge that predicted logp of 1 and 2 are very close to experimental values, and that Sulmazole (2) was one of the suggested analogues. Increasing Solubility to Improve ral Bioavailability In the previous example, we showed how Structure Design Suite could be used to suggest alternative substituents to change physicochemical properties of a compound in a desired direction. A similar approach can be taken where one would add new substituents to a molecule. It is not always possible, however, to add or alter substituents to optimize physicochemical properties without changing the overall topology of the molecule; thereby negatively impacting binding. In most cases, we want to limit ourselves to more subtle modifications such as heterocyclic ring replacement. As an example, let us investigate the optimization of acetyl sulfadiazine to improve solubility at ph 5.5 (a relevant description of the ph environment of the gastrointestinal tract) and consequently increase oral bioavailability. Due to the ph dependence of a drug moving through a physiological system, and resulting changes in the degree of ionization of the compound, physicochemical properties such as solubility and logd are affected by ph. In order to retain the overall topology of the molecule, we will consider only replacement of the diazine ring with structurally similar heterocycles. 3

4 Application ote H S H H 3 C Figure 4: Acetyl Sulfadiazine Using ACD/Labs Structure Design Suite software, we searched for six-membered rings that were within the molecular weight range , to improve the solubility of our lead compound at ph 5.5. By limiting the search to a narrow weight range we prevented suggestions of drastically modified analogues. This search resulted in 11 identified heterocyclic replacements. Those exhibiting dramatic improvement in solubility were removed from the hit list to avoid potential permeability problems, leaving 9 analogues to consider. Figure 5: Table view of suggested analogs of acetyl sulfadiazine, with improved solubility. It was interesting to discover the triazine ring as an identified replacement. In this example we hoped to improve solubility with minimal changes to the topology of the molecule. The subtle change of a carbon atom to nitrogen is unlikely to adversely effect binding to a target site triazine retains the aromatic character of diazine as well as its planarity and basicity. Comparing the solubility profiles of the triazine analog generated using Structure Designer with that of acetyl sulfadiazine, we observed that this simple heterocycle substitution was sufficient to increase solubility at ph 5.5 from 0.65 mg/ml to 2.45 mg/ml a four-fold increase in solubility from the 4

5 Application ote lead compound. This demonstrates that Structure Designer allows us to find analogues that markedly improve solubility with very subtle structural modification. With increased solubility at the relevant ph, and minimum impact on the overall topology of the compound, we could expect the triazine analog to have improved oral bioavailability compared with the parent acetyl sulfadiazine, while preserving therapeutic activity at a target site. Conclusion Physiochemical data can be invaluable in the lead optimization process, but this information is often elusive and difficult to apply in the practice of directing lead optimization. ACD/Structure Design Suite software helps chemists brainstorm chemical transformations based on selected physicochemical properties to quickly produce a concise list of analogs with the required enhancements. Consequently, chemists no longer have to rely solely on their understanding and knowledge of chemical classes, or spend hours consulting colleagues and literature to make the critical decision of how to best modify their lead. The lead optimization process can be more focused with a deeper understanding of the effect of different substituents on the physicochemical properties of a compound. The bottleneck of hit-and-miss analog generation can be avoided to speed up the process of identifying the optimum drug candidate. References 1. ACD/Structure Design Suite, version 9.10, Advanced Chemistry Development, Inc., Toronto, Canada, copyrighted C. Hansch, J. P. Björkrot, & A. Leo, J. Pharm. Sci. 1987, 76, E. Kutter & V. Austel, Arzneim.-Forsch. 1981, 31, ACD/LogP DB, version 9.05, Advanced Chemistry Development, Inc., Toronto, Canada, copyrighted