Given an abstract from a research paper, your task is to identify and label relationships between chemical compounds and genes mentioned in the abstract.

The relationship type must be one of ['DOWNREGULATOR', 'SUBSTRATE', 'INDIRECT-REGULATOR', 'PART-OF', 'MODULATOR-ACTIVATOR', 'REGULATOR', 'INHIBITOR', 'COFACTOR', 'UPREGULATOR', 'ACTIVATOR', 'ANTAGONIST', 'NOT', 'INDIRECT-DOWNREGULATOR', 'SUBSTRATE_PRODUCT-OF', 'INDIRECT-UPREGULATOR', 'AGONIST', 'PRODUCT-OF', 'MODULATOR', 'DIRECT-REGULATOR', 'UNDEFINED', 'AGONIST-INHIBITOR', 'AGONIST-ACTIVATOR', 'MODULATOR-INHIBITOR'].

Please format your output as a JSON array. Each entry in the array should express a single relation, formatted as ["<Entity_A>", "<RELATION_A_B>", "<Entity_B>"]. If no relations can be found, please output an empty JSON array [].

Abstract:

Accurate quantum chemical energies for tetrapeptide conformations: why MP2 data with an insufficient basis set should be handled with caution. High-level quantum chemical calculations have been carried out for biologically-relevant conformers of tetrapeptides. Our results indicate potential problems if the widely-applied MP2 approach is used in such situations with basis sets of insufficient size. Efficient alternatives are discussed.
[]