Optimization of a lead

Whole cell growth inhibition screens combined with subsequent target identification using molecular methods have proven viable approaches to the discovery of novel antibacterial inhibitors. Andries and colleagues (2005) at Johnson Johnson employed whole cell assays to discover a series of antimycobacterial diarylquinolines (DARQs). Chemical optimization of a lead compound led to DARQ derivatives exhibiting potent in vitro activities against several mycobacteria including Mycobacterium tuberculosis (Andries et al., 2005 Ji et al., 2006), with MICs below 0.5 pg/mL. Antimycobacterial efficacy in vivo was confirmed for three of the derivatives. 

These two objectives are discussed together because many of the selection criteria for screening compounds are important to fulfill both objectives, namely physical chemical properties and chemical purity and stability. Especially with respect to optimizability, a violation of the selection criteria discussed here is not a definite reason for exclusion, but it is a liability of the compound, which needs to be addressed during the optimization of the compound that follows the discovery of the hit. The more such liabilities a compound exhibits, the more difficult the optimization of a lead compound will be. Also, not every violation of a technology compatibility criterion is a hard reason for exclusion, but rather it increases the potential of a compound to cause artifacts under a certain assay technology appropriate experimental procedures are required to detect these artifacts. 

R, R) stereoisomer) (Figure 1) was obtained by the optimization of a lead compound. The initial lead compound, with a modest 10 (J.M potency, has been optimized by rational design and three-dimensional modeling based on the known interactions of NPY and [Leu31,Pro34]NPY with NPY receptors in different species (Allen etal., 1987 ... 

Fig. 3.14. Flowchart for the Optimization of a Lead inhibitor. [Adapted From Amaravani M et aL Ind. J Ghent, 45A 174-181, 2006.]...

Most often QSAR analyses are retrospective studies, whether they follow a rational design of investigated structures or not. Only after performing syntheses and biological testing, a quantitative relationship is derived. Often the optimization of a lead compound is step by step accompanied by QSAR analyses. 

As stated earlier, prediction is not the main goal of a QSAR analysis. Much more often general conclusions on the reduction of toxic properties, on selectivity, on optimum lipophilicity to pass the blood-brain barrier or, on the other hand, to avoid CNS side effects, are more important for the optimization of a lead structure. As it still is industrial praxis (and will remain for patent reasons) to synthesize and test large numbers of closely related analogs, QSAR is also an important tool to decide when to stop a synthetic program (compare e.g. eqs. 178, 179 chapter 7.4) [786, 1095]. 

During the optimization of a lead structure to a development candidate, all of the above mentioned methods can be used as well. 

From a medicinal chemistry perspective, the optimization of a lead series for affinity, selectivity, and pharmacological profile is often more intuitive if the efficacy target(s) is known. This suggests that MMoA elucidation (i.e., the so-called target deconvolution or deorphaning) of the hits or leads derived from phenotypic screens can be useful both in their further development and for finding additional chemical series. 

The implementation and optimization of a lead-free SMT manufacturing process requires attention to several process details. There are few new rules for process development and optimization procedures. For the most part, the existing procedures and rules remain. It is the execution of these procedures and rules that will dramatically change. 

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