同藥理同源途徑蛋白質對多標靶抑制劑之研發

Abstract

「單一藥物針對單一標靶，治療單一疾病」是過去數十年藥物發展的主要概念，這個概念促使研究者發展具有高專一性的藥物，然而這個概念逐漸變得不適用於治療疾病上，主要原因之一是單一標靶藥物容易受到蛋白質結合位上的突變之影響，而導致抗藥性的產生。因此，開發一個能尋找多標靶藥物之新策略，藉由抑制多個標靶來降低抗藥性之產生並且增加療效，將對藥物開發提供重要的價值。 針對此議題，我們提出一個新的概念「同藥理同源途徑蛋白質(pharmapathlog)」來尋找多標靶藥物。同藥理同源途徑蛋白質是一群具有下述特性的蛋白質：這些蛋白質（1）是同反應途徑上的同源蛋白質；（2）具有相似的核心結合環境；（3）能夠被相同的化合物所抑制。在生物體反應途徑上，因為一個蛋白質的產物是其下游蛋白質的受質，使得這些蛋白質在結合位上具有相似的物理化學特性及構型。此外，同源蛋白質常在結合位上具有高度保留性的區域，針對這些區域設計的藥物能降低產生抗藥性之機率。根據此概念，我們發展新的策略「以同藥理同源途徑蛋白質為基礎之藥物篩選(pharmapathlog-based screening strategy)」用以尋找多物種間之同藥理同源途徑蛋白質以及其核心結合環境，當化合物能同時符合此核心結合環境時將有潛力成為這些蛋白質之多標靶藥物，可增加療效並且降低產生抗藥性的機率。 我們應用此策略於尋找細菌及病毒之抑制劑，包括結核桿菌、幽門螺旋桿菌和流行性感冒病毒。在抗菌研究上，成功找出三個多標靶抑制劑（IC50 <10.0 μM）能同時抑制幽門螺旋桿菌中的莽草酸激酶和莽草酸去氫酶，此三個抑制劑也能抑制結核桿菌中的莽草酸激酶（IC50 <10.0 μM）。此外，我們發現三個能抑制流行性感冒病毒H1N1與H5N1神經胺酸酶之新型抑制劑（IC50 4~20 μM），實驗結果顯示此三個抑制劑能有效抑制抗藥性之神經胺酸酶（H274Y 和 I222R），並且不引起細胞毒性，提供對抗抗藥性病株的一個良好起始點。我們也設計了五個瑞樂沙衍生物，這些衍生物位於150 cavity中且有良好的抑制效果（IC50 <10.0 nM）。另外，統計結果顯示同藥理同源途徑蛋白質中的核心結合環境為高度保留性之區域，可以用來設計不易產生抗藥性之藥物。這些實驗結果顯示同藥理同源途徑蛋白質之藥物篩選的概念將有助於尋找多標靶抑制劑，我們相信此策略對於藥物研究開發具有極大價值。

The concept of "one-drug, one-target, one-disease" has been dominant to drug development strategy in the past decades. This strategy induces researchers to develop inhibitors with high specificity. However, the strategy is increasingly becoming inappropriate. One of the major reasons is that single-target inhibitors often lose potency because of even one residue mutation, leading to drug resistance. Therefore, developing a new strategy to discover multitarget inhibitors, which decrease probability of drug resistances and enhance therapeutic potency by inhibiting multiple targets, provides a great value for drug design. To address the issue, we proposed a new concept "pharmapathlog" to discover multitarget inhibitors. Pharmapathlog are a group of proteins that satisfy the following properties: (1) they are protein orthologs in the same pathway; (2) they share comparable core binding environments; (3) they can be inhibited by the same compounds. Proteins in the same pathway may share similarities in physical-chemical properties and shapes in their binding sites because a product of one enzyme is a substrate of the next enzyme in a series of catalytic reactions. Furthermore, orthologous proteins often share conserved core binding environments during evolution, providing an opportunity to develop multitarget inhibitors to target these conserved regions for reducing the probability of drug resistance. Based on the new concept, we developed a "pharmapathlog-based screening strategy" to identify pharmapathlogs in the same pathways across multiple species and their core binding environments by using site-moiety maps. A compound highly agreeing with the core binding environments of pharmapathlogs could simultaneously inhibit the multiple proteins of pharmapathlogs. To verify the utility of the pharmapathlog-based screening strategy, we applied this strategy to identify new inhibitors for bacteria and virus, including Helicobacter pylori, Mycobacterium tuberculosis, and influenza virus. Based on the strategy, three multitarget inhibitors simultaneously inhibiting shikimate dehydrogenase and shikimate kinase of Helicobacter pylori with low IC50 values (<10.0 μM) were discovered. The three inhibitors also showed inhibitory effects (IC50 <10 μM) for shikimate kinase of Mycobacterium tuberculosis. Subsequently, the strategy was successfully used to discover three new inhibitors with low IC50 values (4~20 μM) for H1N1 and H5N1 neuraminidases, and design five zanamivir derivatives located at the 150-cavity with IC50 values in the <10 nanomolar range. Our experimental results showed that the three inhibitors may overcome the drug resistances introduced by H274Y and I222R for H1N1 neuraminidase without causing apparent cytotoxicity, suggesting a starting point to combat drug-resistant strains. In addition, we found that core binding environments of pharmapathlogs are highly conserved, suggesting that targeting the core binding environments is useful to avoid drug-resistance. These experimental results show that the concept of pharmapathlogs is useful to discover multitarget inhibitors. We believe that the new strategy is useful to design new drugs toward human diseases.