Background

The concept of "one-disease, one-target, one-drug" has been the dominating drug development strategy in the past decades ^1,2. This strategy induces researchers to develop inhibitors with high specificity. For example, in anti-influenza drug development, neuraminidase is considered a valid target, and two drugs, zanamivir and oseltamivir, have been reported^3-5. However, these single-target inhibitors may easily lose their effectiveness due to even one amino acid mutation in binding sites of target proteins, leading to drug resistance. For instance, some influenza strains that are resistant to oseltamivir have been reported since a single residue mutates ⁶. Another example is tetracycline, which is a broad spectrum antibiotic. Tetracycline loses its potency in Helicobacter pylori (H. pylori) because of a single triple-base-pair substitution⁷. Particularly in antibiotics, the increasing emergence of multiple-antibiotic-resistant superbugs causes a great concern in the world^8-10, revealing the insufficiency of the single-target strategy.

Therefore, developing a new strategy to discover multitarget inhibitors, which decrease probability of drug resistances by inhibiting multiple targets, provides a great value for drug design.

Proteins may share many similarities in physical-chemical properties and shapes in their binding sites despite low sequence or structural homology. For example, proteins in the same pathways contain comparable core binding environments because a product of one enzyme is a substrate of the next enzyme in a series of catalytic reactions. Hence, it is possible to design a multitarget inhibitor to simultaneously inhibit proteins in the same pathways by targeting their core binding environments. Furthermore, orthologous proteins often share conserved core binding environments during evolution, providing an opportunity to develop inhibitors to target

these conserved regions for reducing the probability of drug resistance and increasing hit rate.

Recently, the concept of polypharmacology, which means that a drug binds multiple target proteins, has been proposed to design drugs^11-13. In general, proteins with high sequence or structure similarity could be considered to be bound by the same compounds. However, designing these multitarget inhibitors is still a challenging task since these proteins often lack structural and sequence homology^14,15, resulting in a difficulty for extracting core binding environments among these proteins. Therefore, a new strategy for extracting core binding environments without relying on sequences of structures will be useful for discovering multitarget inhibitors.

To address these issues, we propose a new strategy, called pharmapathlog-based screening strategy, to discover multitarget inhibitors (Fig. 1.1). Pharmapathlogs 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. To extract core binding environments of protein binding sites, we developed the SiMMap server for generation of site-moiety maps¹⁶. A site-moiety map consists of anchors for a protein binding site. An anchor, presenting a key binding environment, includes three essential elements: (1) binding pockets, which are parts of the binding site, with conserved interacting residues; (2) moiety preferences; (3) interaction type (electrostatic, hydrogen-bonding, or van der Waals). A site-moiety map is able to present the relationship between the moiety preferences and the physico-chemical properties of the binding site through anchors.

Hence, protein orthologs sharing comparable core anchors (core binding environments) in the same pathway could be considered pharmapathlogs, and the core anchors of pharmapathlogs can be used to identify multitarget inhibitors. A compound that agrees with the core anchors is often able to simultaneously inhibit the multiple targets. In addition, the moiety preferences of the core anchors can guide lead optimization processes.

Figure 1.1. Concept of pharmapathlogs using protein orthologs in the shikimate pathways as the example. Orthologous proteins sharing similar binding environments in the same pathways can be considered pharmapathlogs. For example, shikimate dehydrogenase (SDH) and shikimate kinase (SK) are adjacent proteins in the shikimate pathway. The two proteins share two key hydrogen binding environments (green sphere) and two van der Waals binding environments (grey sphere), and can be regarded as pharmapathlogs in the pathway. In addition, orthologous SKs in Helicobacter pylori (H. pylori) and Mycobacterium tuberculosis (M.

tuberculosis) are regarded as pharmapathlogs in multiple species because of their comparable binding environments. The consensus binding environments among pharmapathlogs are core binding environments and can be used to find multitarget inhibitors agreeing with the core regions. Multitarget inhibitors have good therapeutic effectiveness and reduce probability of resistant mutations, whereas single target inhibitors often lose effectiveness when target residues mutate.

Single target inhibitor

SK SDH Helicobacter pylori

Mycobacterium tuberculosis

Other species Shikimate pathway

Multitarget Inhibitor

Drug

resistance Pharmapathlogs in the same pathway

…

SDH SK

Pharmapathlogs in multiple species

H. Pylori

M. tuberculosis

…

Pharmapathlogs

To verify the utility of the pharmapathlog-based screening strategy, at first, we applied this strategy to identify new multitarget inhibitors for shikimate pathway of H. pylori and Mycobacterium tuberculosis (M. tuberculosis), which are human pathogens and causes peptic ulcer disease and chronic infectious disease, respectively^17-19. The shikimate pathway containing seven proteins is an attractive target pathway for drug development because the pathway is absent in human ²⁰. By use of this strategy, we successfully discovered three multitarget inhibitors with low IC50 values (<10.0 μM) for simultaneously inhibiting shikimate dehydrogenase and shikimate kinase by collaborating with Dr. Ching Wang and Dr. Wen-Chi Cheng of National Tsing Hua University (NTHU). Subsequently, we applied the strategy to discover three new inhibitors with low IC₅₀ values (4~20 μM) for H1N1 and H5N1 neuraminidases, and design five zanamivir derivatives with IC50 values in the <10 nanomolar range by collaborating with Dr. John T.A. Hsu and Dr. Hui-Chen Hung of National Health Research Institutes, and Dr. Chun-Cheng Lin and Mr. Chien-Hung Lin of NTHU. 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. The experimental results showed that the concept of pharmapathlogs is useful to discover multitarget inhibitors.

We believe that the new strategy is useful to discover and optimize new lines of inhibitors toward human diseases.

The pharmapathlog-based screening is a general strategy for drug development, and can be extend to other human diseases and drug-resistant pathogens. A study showed that developing a drug costs 15 years and US$800 million on average²¹. The high cost and lengthy development time reveals the insufficiency of the traditional strategy in developing drugs for combating rapidly emerging diseases, such as malaria, tuberculosis, cholera, and avian flu.

Once drug-resistant pathogens emerge, current drug treatments may be ineffective. As a result,

the pharmapathlog-based screening, which is different to currently used single-target approaches, has great potential because of the following advantages: 1) High success rate. The new strategy simultaneously considers multiple target proteins for discovering inhibitors, providing an additive opportunity to discover true hits against diseases. 2) Reduction of drug resistance. The probability of drug resistant mutations arising in all targets is extremely low. 3) High treatment efficiency. Multitarget inhibitors inhibit multiple targets; therefore, these drugs increase the efficiency of therapy and are useful to treat complexity of diseases. 4) Reduction of cost and time. Based on above reasons, we believe our research results are helpful for the drug development process.