SUMMARY Somatic mutations in isocitrate dehydrogenase 1 or 2 (IDH1/2) contribute to the pathogenesis of cancer via production of the ‘oncometabolite’ D-2-hydroxyglutarate (D-2HG). Elevated D-2HG can block differentiation of malignant cells by functioning as a competitive inhibitor of alpha-ketoglutarate (α-KG)-dependent enzymes, including Jumonji family histone lysine demethylases. 2HG is a chiral molecule that can exist in either the D- or L- enantiomer. Although cancer-associated IDH1/2 mutations produce D-2HG, biochemical studies have demonstrated that L-2HG also functions as a potent inhibitor of α-KG-dependent enzymes. Here we report that under conditions of oxygen limitation, mammalian cells selectively produce L-2HG via enzymatic reduction of α-KG. Hypoxia-induced L-2HG is not mediated by IDH1 or IDH2, but instead results from promiscuous substrate usage primarily by lactate dehydrogenase A (LDHA). During hypoxia, the resulting increase in L-2HG is necessary and sufficient for the induction of increased methylation of histone repressive marks, including histone 3 lysine 9 (H3K9me3).

The metabolite 2-hydroxyglutarate (2HG) can be produced as either a D(R)- or L(S)- enantiomer, each of which inhibits alpha-ketoglutarate (αKG)-dependent enzymes involved in diverse biologic processes. Oncogenic mutations in isocitrate dehydrogenase produce D-2HG, which causes a pathologic blockade in cell differentiation. On the other hand, oxygen limitation leads to accumulation of L-2HG, which can facilitate physiologic adaptation to hypoxic stress in both normal and malignant cells. Here we demonstrate that purified lactate dehydrogenase (LDH) and malate dehydrogenase (MDH) catalyze stereospecific production of L-2HG via ‘promiscuous’ reduction of the alternative substrate αKG. Acidic pH enhances production of L-2HG by promoting a protonated form of αKG that binds to a key residue in the substrate-binding pocket of LDHA. Acid-enhanced production of L-2HG leads to stabilization of hypoxia-inducible factor 1 alpha (HIF-1α) in normoxia. These findings offer insights into mechanisms whereby microenvironmental factors influence production of metabolites that alter cell fate and function.

Somatic mutations in the isocitrate dehydrogenase 2 gene (IDH2) contribute to the pathogenesis of acute myeloid leukaemia (AML) through the production of the oncometabolite 2-hydroxyglutarate (2HG). Enasidenib (AG-221) is an allosteric inhibitor that binds to the IDH2 dimer interface and blocks the production of 2HG by IDH2 mutants. In a phase I/II clinical trial, enasidenib inhibited the production of 2HG and induced clinical responses in relapsed or refractory IDH2-mutant AML. Here we describe two patients with IDH2-mutant AML who had a clinical response to enasidenib followed by clinical resistance, disease progression, and a recurrent increase in circulating levels of 2HG. We show that therapeutic resistance is associated with the emergence of second-site IDH2 mutations in trans, such that the resistance mutations occurred in the IDH2 allele without the neomorphic R140Q mutation. The in trans mutations occurred at glutamine 316 (Q316E) and isoleucine 319 (I319M), which are at the interface where enasidenib binds to the IDH2 dimer. The expression of either of these mutant disease alleles alone did not induce the production of 2HG; however, the expression of the Q316E or I319M mutation together with the R140Q mutation in trans allowed 2HG production that was resistant to inhibition by enasidenib. Biochemical studies predicted that resistance to allosteric IDH inhibitors could also occur via IDH dimer-interface mutations in cis, which was confirmed in a patient with acquired resistance to the IDH1 inhibitor ivosidenib (AG-120). Our observations uncover a mechanism of acquired resistance to a targeted therapy and underscore the importance of 2HG production in the pathogenesis of IDH-mutant malignancies.

Accurately predicting protein-ligand binding affinities and binding modes is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes. In this technique, the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically-relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.