A mapping of drug space from the viewpoint of small molecule metabolism

Abstract

Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the "effect space" comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism.

Figure 1. Similarity Ensemble Approach (SEA).

SEA compares groups of ligands based upon bond topology. Example ligand sets include the thymidylate synthase reaction set, composed of the reaction substrates and products, and the nucleotide reverse transcriptase inhibitor (NRTI) drug set, which includes known inhibitors of the nucleoside reverse transcriptase enzyme. Fingerprints representing the bond topology of each molecule are generated. Raw scores between sets are calculated based upon Tanimoto coefficients between fingerprints for all molecule pairs. Finally, the raw scores are compared to a background distribution to determine the expectation value (E) representing the chemical similarity between sets. See Methods for further details.

Figure 2. Selected best hits between MetaCyc reaction sets and MDDR drug sets.

Figure 3. Effect-space map showing chemical similarity between specific drug classes and metabolites in human folate and pyrimidine biosynthesis.

Each node represents one reaction set – the substrates and products of a single human metabolic reaction. Edges connect the reactions in the canonical pathway as annotated in HumanCyc . As given in the color key, each reaction is colored according to the expectation value indicating the strength of similarity between that target reaction set and the respective MDDR drug set. Diamond shaped nodes indicate reactions catalyzed by enzymes annotated as known drug targets in the MDDR; circles indicate reactions catalyzed by enzymes not annotated as targets. Reaction key: 1. Deoxyuridine kinase 2. Thymidine kinase 3. Thymidylate kinase 4. Deoxythymidine diphosphate kinase 5. Thymidylate synthase (TS) 6. Methylene tetrahydrofolate reductase 7. Dihydrofolate reductase (DHFR) 8. Deoxyuridine diphosphate kinase 9. Deoxyuridine triphosphate diphosphatase.

Figure 4. Selected links between MDDR drug classes and human folate and pyrimidine metabolism.

Figure 5. Effect-space map showing chemical similarity between drugs and metabolites in MRSA.

Canonical pathway representation of methicillin-resistant Staphylococcus aureus (MRSA) small molecule metabolism colored by expectation value of the best hit against MDDR. Reactions that are also present in humans have been faded. Layout based upon the Cytoscape 2.5 y-files hierarchical layout. Edge lengths are not significant. For ease of viewing, reactions are not labeled but can be identified in the interactive versions of the maps available at the online resource.

Figure 6. Essential and synthetic lethal map of MRSA metabolism.

Canonical pathway representation of methicillin-resistant Staphylococcus aureus (MRSA) small molecule metabolism colored by essentiality and synthetic lethality of reactions. Key: black = essential reaction; other colors = synthetic lethal reaction pairs; node size = similarity to top MDDR hit (bigger is more drug-like); diamond shape = MDDR drug target; faded border = human reaction.