An Intriguing Opportunity to Go Back to the Future by Revisiting Ones Roots

The concern that to optimize all of the efficacy and ADMET parameters within a single molecule might be difficult, if not impossible, to achieve on a routine basis even when prodrug strategies are relied upon to address absorption and distribution properties was raised within the prior discussion about drug distribution. Alternatively, the use of two or more molecules that might work together as a team also presents itself as a possibility toward potentially achieving such a multiparameter optimized profile. That some herbal remedies appear to demonstrate greater benefits as their mixtures than as their isolated components adds to this intriguing possibility and thus prompts a brief consideration of this topic. Although today's trend in the US to self-administer herbal remedies and preventatives is admittedly driven

288,289

more by consumerism than by solid science, , this potential reconnection of basic science to medicinal chemistry s historical roots also becomes noteworthy. Aside from their poorly defined analytical characterization and notoriously inadequate quality control, one of the major, basic science questions about herbals that do possess validated pharmacological properties is why their natural forms are sometimes superior to the more purified versions of their active constituents, even when the latter are adjusted to reflect varying concentration ratios thought to coincide with the natural relative abundances. Given their incomplete analytical characterizations, it should be apparent relative to the present discourse that, in addition to simple prodrug possibilities, numerous unidentified, nonefficacious, and otherwise silent constituents within any given herb could have an interaction with one or more of the efficaciously active constituents at any one or more levels of the latter's ADMET steps. When these interactions are favorable, the resulting overall pharmacological profile becomes altered in a seemingly synergistic manner that is obtainable from the more natural forms of the mixture but lost upon purification to matrices containing only the efficaciously active components.290 In fact, there is already experimental precedent for this scenario relative to efficaciously silent components improving the absorption,291 enhancing the distribution,292,293 and favorably altering the metabolism294 of their active herbal counterparts, as well as more classical synergies involving direct interactions that occur at the sites involved with efficacy.295 Therapeutic enhancements derived directly from multiple interactions at efficacy sites have been pursued for many years, with multivalent, single drug entities reflecting the latest trend in this direction.296 What should be truly remarkable in the following discourse, which at this point can be likened to going ''back to the future,'' is that the rapidly evolving process of drug discovery will undoubtedly continue to add the sophistication of the entire ADMET profile into such multi-action-directed considerations.297-301

Optimization of the overall pharmacological profile is precisely what is being striven for when selecting and/or chemically tailoring an NCE lead according to either the old or new paradigm of drug discovery. Restating, however, that it may be expecting too much even upon extending the new paradigm into the future as a knowledge-generating process, to obtain complete optimization within a single, multiparameterized molecule, perhaps it will again be Mother Nature that will once more lend her hand by revealing some of the modes of ADMET synergy that she, long ago, has already instilled into some of her herbal productions. At the very least, medicinal chemistry should take care to not forget its roots in natural product chemistry as it marches forward with biotechnology just behind genomics and proteomics further into the new millennium. For example, efforts can be directed toward uncovering efficacy and ADMET-related synergies that may be present among the constituents of herbs purported to have anticancer or cancer-preventative properties by taking advantage of the common cell culture panels already in place to assess anticancer activity along with various transporter system interactions via HTS format. However, because anticancer/cancer-preventative synergy could derive from favorable interactions across a wide variety of ADMET processes relative to any combination of one or more efficacy-related endpoints, several mechanism-based assays associated with several key possibilities for efficacy will also need to be deployed as part of such a program. One can only imagine how sophisticated this type of pursuit will become in the future when such highly interdisciplinary, efficacy networks are further coupled to an even wider network of ADMET parameter experimental protocols.

A more classical approach toward the interactions of multicomponent systems would be to utilize clinical investigations to study the interactions, either positive or negative, that herbals may have with drugs when both are administered to humans. Importantly, for all of these herb-related studies, it becomes imperative that extensive chemical constituent fingerprinting is also undertaken so that the observed effects, particularly those suggestive of synergy, can be correlated with overall chemical composition patterns and not with just the distinct concentrations of preselected components already known to possess established activity.302

In contrast to both of the aforementioned types of studies that can be considered to represent systematic examinations of 'herbal-directed, small libraries' and specified herb-drug clinical combinations, respectively, it becomes interesting to speculate how a truly random, brute force approach toward identifying synergy might proceed as a HTS survey of a random compound library in pursuit of optimal pair or even triple compound teams rather than as an attempt to identify a single, 'blue-chip' drug that can do it all. In this regard, however, it must first be recognized that the present trend to test mixtures of several compounds within a given well does not even begin to address synergy. This is because based upon considerable experience with various chemotherapeutic agents,303 synergy is most likely to be observed at very select ratios within very distinct concentrations of the involved players. In other words, looking at the most simple case of assessing the potential synergy between just two molecules, A and B, requires testing A in the presence of B across a range of molar ratios presented across a range of absolute concentrations.304-306 This situation is depicted in Figure 16.

Considering the brute force approach from a purely mathematical viewpoint and in a minimally elaborated pharmacological format, suppose the possibility for A plus B synergy relating to just a single, efficacy or ADMET-related HTS parameter is examined across a compound library having only 100 members wherein paired combinations are tested at just three relative molar ratios (e.g., A/B at 0.5/1, 1/1, and 1/0.5) at only three total concentrations of both members (e.g., 0.1, 1.0, and 10 mM), then a total of 44850 drug tests plus numerous control runs would be required for an n = 1 pass through the library.307 Perhaps because of these rather impressive numbers, brute force HTS will undoubtedly relish such pursuits. Once the HTS forces become mobilized in this area, such testing could set up an interesting 'John Henry' competition with more directed investigations, such as those that have been elaborated above that seek to systematically identify the specific synergies seemingly present within certain herbals. Ultimately, no matter how the identification of such favorable drug-drug partnering possibilities are uncovered and are able to better deal with the various ADMET parameters of tomorrow, as well as for the classical efficacy relationships of today, they will certainly prove to be invaluable toward alleviating the situation of trying to establish all of the most desired behaviors for a given therapeutic target within the context of a single molecular framework. Furthermore, it can be anticipated that this type of information will become extremely useful when it becomes further elaborated by medicinal chemistry into general structural motifs that have potential synergistic utilities and applications beyond what was initially uncovered by the specific mixtures of defined compounds.

Figure 16 Drug-drug interaction plot for two drugs A and B.303 EC50, T is the total concentration of the combined drugs which gives 50% of the maximum possible effect. The EC50, T is shown as a function of the fraction of drug A (drug B's fraction is one minus the fraction shown). Rescaling of drug concentrations to units of their EC50 allows simple additivity to be set at unity such that deviations below or above this line indicate synergism or antagonism, respectively. The dots are actual experimental results obtained for two anticancer agents, wherein the observed EC50, T values reflect 20 rays of fixed drug fractions as estimated from the data along that ray alone. The fitted curve was generated by a global model for the entire data set and indicates the complicated nature of interaction relationships within even a well-controlled cell culture environment. That synergism can be accompanied not only by simple additivity but also by ratio-dependent antagonistic relationships is apparent.

Proportion of A

Figure 16 Drug-drug interaction plot for two drugs A and B.303 EC50, T is the total concentration of the combined drugs which gives 50% of the maximum possible effect. The EC50, T is shown as a function of the fraction of drug A (drug B's fraction is one minus the fraction shown). Rescaling of drug concentrations to units of their EC50 allows simple additivity to be set at unity such that deviations below or above this line indicate synergism or antagonism, respectively. The dots are actual experimental results obtained for two anticancer agents, wherein the observed EC50, T values reflect 20 rays of fixed drug fractions as estimated from the data along that ray alone. The fitted curve was generated by a global model for the entire data set and indicates the complicated nature of interaction relationships within even a well-controlled cell culture environment. That synergism can be accompanied not only by simple additivity but also by ratio-dependent antagonistic relationships is apparent.

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