Parallel optimization

Abstract High quality leads provide the foundation for the discovery of successful clinical development candidates, and therefore the identification of leads is an essential part of drug discovery. Many factors contribute to the quality of a lead, including biological, physicochemical, ADME, and PK parameters. The identification of high quality leads, which are needed for successful lead optimization, requires the optimization of all of these parameters. Parallel optimization of all parameters is the most efficient way to achieve the goal of lead identification. 

Criteria for biological properties may be project specific, but ADME property and physical property criteria are generally invariant. Lead profiles will be addressed in more detail in the section on parallel optimization. 

The following examples taken from the literature since 2001 are intended to illustrate the parallel optimization of some or all of the parameters discussed above, and to illustrate how some of the tools described above can aid in lead generation. It is not meant to be an exhaustive survey of the literature. The specific criteria used to define a successful lead identification campaign vary by group, as do the processes used to reach the lead stage. However, there are also many themes that are common to many of the examples below. A summary of the examples described below is contained in Table 2. 

HCV NS5B polymerase is an RNA-dependent RNA polymerase that is essential for viral replication. Thus, the inhibition of this enzyme offers a potential treatment for hepatitis C infection. Beaulieu et al. [51] report on the parallel optimization of enzyme inhibition potency and physical properties. In the first stage of hit characteri-... 

Protein kinase C theta plays a critical role in T cell signaling and thus the inhibition of this enzyme has the potential to be useful for treating inflammatory diseases. Cywin et al. [55] describe the parallel optimization of potency against the enzyme,... 

CXCR2 is a member of the CXC family of chemokine receptors. IL-8 activates this receptor, and an antagonist would potentially be useful for the treatment of inflammatory diseases. Baxter et al. [58] describe the parallel optimization of binding and functional potency, physicochemical properties, ADME properties, and PK. The thiol of the HTS hit was varied with typical replacements (i.e., OH, NH2, SMe, NHAc, etc.), but this only led to inactive compounds. Variation of the substituent at N(2) showed that a benzyl moiety was required (Ph, Me substituents gave inactive compounds). Variation of the C(5) substituent showed that -substituents produced optimal activity. The optimized lead has substantially improved CXCR2 binding and functional activity as well as an excellent PK profile (Scheme 13). 

CDK2 is involved with controlling normal cell proliferation. Disregulation in cancer makes this a good antitumor target. Pevarello et al. [62] describe the parallel optimization of enzyme inhibition potency, cellular activity, physicochemical properties, and PK. A low MW hit (MW = 201) was specifically selected with the... 

The P2X7 receptor is a ligand-gated ion channel present in cells involved with inflammation. The receptor is activated by extracellular ATP, which leads to the processing and release of IL-1 (5. Baxter et al. [63] report on the parallel optimization of binding affinity, efficacy, physicochemical properties, ADME properties, and PK (Scheme 18). 

DPP-4 is a serine protease that inactivates GLP-1. GLP-1 stimulates insulin secretion and suppresses glucagon release. The inhibition of DPP-4 prolongs the half-life of GLP-1 and brings about beneficial effects on glucose levels and glucose tolerance in type 2 diabetics. Backes et al. [64] report on the parallel optimization of enzyme binding affinity and inhibition, selectivity, ADME properties, and PK (Scheme 19). 

The procedure and methods for the MEP determination by the NEB and parallel path optimizer methods have been explained in detail elsewhere [25, 27], Briefly, these methods are types of chain of states methods [20, 21, 25, 26, 30, 31]. In these methods the path is represented by a discrete number of images which are optimized to the MEP simultaneously. This parallel optimization is possible since any point on the MEP is a minimum in all directions except for the reaction coordinate, and thus the energy gradient for any point is parallel to the local tangent of the reaction path. 

Tondi, D., Slomczynska, U., Costi, M. P., Watteeson, D. M., and Ghelli, S. Structure-based discovery and in-parallel optimization of novel competitive inhibitors of thymidylate synthase. Chem. Biol. 1999, 6, 319-331. 

In particular, parallel optimization of affinity/selectivity and pharmacokinetic properties are difficult to achieve, especially if several PK parameters need to be... 

Becer CR, Schubert US (2009) Parallel optimization and high-throughput preparation of well-defined copolymer libraries using controlled/ living polymerization methods. Adv Polym Sci DOl 10.1007/12 2009 16... 

Parallel Optimization and High-Throughput Preparation of Well-Defined Copolymer Libraries Using Controlled/ Living Polymerization Methods... 

In this chapter, we will focus on the use of CLP techniques for the synthesis of systematic copolymer libraries using high-throughput approaches. Prior to that, automated parallel optimization reactions that have been performed for different CLP techniques will be discussed. At the end of this chapter there will be a highlight on the latest synthetic approaches to synthesize well-defined polymer libraries. 

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