[Retracted] MicroRNA­599 targets high­mobility group AT­hook 2 to inhibit cell proliferation and invasion in clear cell renal carcinoma.

Following the publication of the above paper, it was drawn to the Editors' attention by a concerned reader that cell migration and invasion assay data shown in Fig. 5C were strikingly similar to data appearing in different form in other articles by different authors, which have been retracted. Owing to the fact that the contentious data in the above article were already under consideration for publication, or had already been published, elsewhere when it was submitted to Molecular Medicine Reports, the Editor has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive any reply. The Editor apologizes to the readership for any inconvenience caused. [Molecular Medicine Reports 17: 7451­7459, 2018; DOI: 10.3892/mmr.2018.8755].

Three epitope-distinct human antibodies from RenMab mice neutralize SARS-CoV-2 and cooperatively minimize the escape of mutants.

Coronavirus disease 2019 (COVID-19), a pandemic disease caused by the newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused more than 3.8 million deaths to date. Neutralizing antibodies are effective therapeutic measures. However, many naturally occurring mutations at the receptor-binding domain (RBD) have emerged, and some of them can evade existing neutralizing antibodies. Here, we utilized RenMab, a novel mouse carrying the entire human antibody variable region, for neutralizing antibody discovery. We obtained several potent RBD-blocking antibodies and categorized them into four distinct groups by epitope mapping. We determined the involved residues of the epitope of three representative antibodies by cryo-electron microscopy (Cryo-EM) studies. Moreover, we performed neutralizing experiments with 50 variant strains with single or combined mutations and found that the mixing of three epitope-distinct antibodies almost eliminated the mutant escape. Our study provides a sound basis for the rational design of fully human antibody cocktails against SARS-CoV-2 and pre-emergent coronaviral threats.

Rheum tanguticum Alleviates Cognitive Impairment in APP/PS1 Mice by Regulating Drug-Responsive Bacteria and Their Corresponding Microbial Metabolites.

Drugs targeting intestinal bacteria have shown great efficacy for alleviating symptoms of Alzheimer's disease (AD), and microbial metabolites are important messengers. Our previous work indicated that Rheum tanguticum effectively improved cognitive function and reshaped the gut microbial homeostasis in AD rats. However, its therapeutic mechanisms remain unclear. Herein, this study aimed to elaborate the mechanisms of rhubarb for the treatment of AD by identifying effective metabolites associated with rhubarb-responsive bacteria. The results found that rhubarb reduced hippocampal inflammation and neuronal damage in APP/PS1 transgenic (Tg) mice. 16S rRNA sequencing and metabolomic analysis revealed that gut microbiota and their metabolism in Tg mice were disturbed in an age-dependent manner. Rhubarb-responsive bacteria were further identified by real-time polymerase chain reaction (RT-PCR) sequencing. Four different metabolites reversed by rhubarb were found in the position of the important nodes on rhubarb-responsive bacteria and their corresponding metabolites combined with pathological indicators co-network. Furthermore, in vitro experiments demonstrated o-tyrosine not only inhibited the viabilities of primary neurons as well as BV-2 cells, but also increased the levels of intracellular reactive oxygen species and nitric oxide. In the end, the results suggest that rhubarb ameliorates cognitive impairment in Tg mice through decreasing the abundance of o-tyrosine in the gut owing to the regulation of rhubarb-responsive bacteria. Our study provides a promising strategy for elaborating therapeutic mechanisms of bacteria-targeted drugs for AD.

Research on a learning rate with energy index in deep learning.

The stochastic gradient descent algorithm (SGD) is the main optimization solution in deep learning. The performance of SGD depends critically on how learning rates are tuned over time. In this paper, we propose a novel energy index based optimization method (EIOM) to automatically adjust the learning rate in the backpropagation. Since a frequently occurring feature is more important than a rarely occurring feature, we update the features to different extents according to their frequencies. We first define an energy neuron model and then design an energy index to describe the frequency of a feature. The learning rate is taken as a hyperparameter function according to the energy index. To empirically evaluate the EIOM, we investigate different optimizers with three popular machine learning models: logistic regression, multilayer perceptron, and convolutional neural network. The experiments demonstrate the promising performance of the proposed EIOM compared with that of other optimization algorithms.

Deciphering biochemical basis of Qingkailing injection-induced anaphylaxis in a rat model by time-dependent metabolomic profiling based on metabolite polarity-oriented analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Qingkailing injection (QKLI) is prepared from eight traditional Chinese medicinal materials or their extracts, which is widely used in clinical practice to treat the upper respiratory inflammation, pneumonia, high fever and viral encephalitis, nonetheless, suffering from serious anaphylaxis. AIM OF STUDY: This study aims to develop an integrative metabolomics approach for deciphering the biochemical basis of QKLI induced anaphylaxis (QKLI-IA). MATERIALS AND METHODS: The accuracy of animal modeling, the coverage of detected metabolites and the timeliness of pathological reaction are three key factors for revealing the biochemical basis of disease with untargeted metabolomics. In this study, firstly, the allergic rats (responders) were first screened by passive cutaneous anaphylaxis experiment and then were utilized for modeling. To cover a wider range of metabolites, a large-scale untargeted metabolomics based on metabolites polarity-oriented analysis was performed using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Then, to evaluate the timeliness of QKLI-IA, a time-dependent metabolomic profiling including the early, mid and late anaphylaxis stages of QKLI-IA, was performed. RESULTS: Corresponding to early, mid and late anaphylaxis stages of QKLI-IA, 14, 9 and 4 potential biomarkers were identified, respectively. Metabolism pathway analysis revealed that QKLI-IA resulted in dynamic changes in serum amino acid, fatty acid, glycerolipid, and phospholipid metabolisms. Twenty-four metabolites were found with identical fluctuating trends across the three stages of QKLI-IA. The results indicate that the pathogenesis of QKLI-IA is closely related to arachidonic acid metabolism. CONCLUSION: This research provides a methodology reference for revealing the biochemical basis of disease using metabolomic profiling and offers a new insight to understand the pathogenesis of QKLI-IA.

MicroRNA­199b promotes cell proliferation and invasion in Wilms' tumour by directly targeting Runt­related transcription factor 3.

Emerging evidence has demonstrated that the deregulation of microRNAs (miRNAs) contributes to Wilms' tumour (WT) malignant progression. Therefore, identifying the essential miRNAs for WT onset and progression may be a promising therapeutic method for patients with this disease. Dysregulation of miRNA­199b (miR­199b) serves significant roles in various types of human cancer. However, its expression patterns, possible functions and associated mechanisms in WT are largely unknown. In the present study, the expression of miR­199b in WT tissues was detected by reverse transcription­quantitative polymerase chain reaction (RT­qPCR) analysis. The biological functions of miR­199b overexpression in WT cells were determined using Cell counting kit­8 and Transwell invasion assays. The mechanisms underlying the action of miR­199b in WT cells were also investigated using bioinformatics analysis, a luciferase reporter assay, RT­qPCR and western blot analysis. It was revealed that miR­199b expression was upregulated in WT tissues. In addition, the downregulation of miR­199b attenuated the proliferation and invasion of WT cells. Runt­related transcription factor 3 (RUNX3) was mechanistically predicted as a potential target of miR­199b. Subsequent experiments demonstrated that RUNX3 was a direct target gene of miR­199b in WT. In addition, the downregulation of RUNX3 in the WT tissues was inversely correlated with the miR­199b expression level. The recovered RUNX3 expression counteracted the oncogenic roles of miR­199b in WT cells. Therefore miR­199b may serve as an oncogene in WT progression by directly targeting RUNX3, thereby suggesting that the miR­199b/RUNX3 axis may be a promising therapeutic target for patients with WT.

MicroRNA-599 targets high-mobility group AT-hook 2 to inhibit cell proliferation and invasion in clear cell renal carcinoma.

Dysregulation of microRNAs (miRNAs) is associated with the occurrence and development of clear cell renal cell carcinoma (ccRCC) through their participation in a number of critical biological processes. Therefore, an in­depth investigation into miRNAs and their biological roles within ccRCC may provide useful insights and lead to the identification of novel therapeutic methods for patients with ccRCC. miRNA­599 (miR­599) serves critical roles in different types of human cancer. However, the expression pattern, biological function and molecular mechanism of miR­599 in ccRCC remain unknown. The present study aimed to detect the expression level of miR­599 in ccRCC, examine its effect on ccRCC progression and further explore the possible underlying mechanisms. It was observed that miR­599 was significantly underexpressed in ccRCC tissues and cell lines compared with the control. Functional assays revealed that restored expression of miR­599 restricted the proliferation and invasion of ccRCC cells. Bioinformatics analysis, luciferase reporter assay, reverse transcription­quantitative polymerase chain reaction and western blot analysis demonstrated that high­mobility group AT­hook 2 (HMGA2) was a direct target of miR­599 in ccRCC. HMGA2 knockdown simulated the suppressive effects caused by miR­599 overexpression in ccRCC. Recovered HMGA2 expression partially rescued the miR­599­mediated inhibition of ccRCC proliferation and invasion. These results suggest that miR­599 may serve tumour suppressive roles in ccRCC by directly targeting HMGA2, indicating that miR­599 may have potential as a treatment for patients with ccRCC.

[Rapid analysis on phenolic compounds in Rheum palmatum based on UPLC-Q-TOF/MSE combined with diagnostic ions filter].

Diagnostic ions filter method was used to rapidly detect and identify the phenolic compounds in Rheum palmatum based on ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MSE). The representative authentic standards of phenolic compounds, including gallic acid, (+)-catechin, (－)-epicatechin, (－)-epicatechin-3-O-gallate and procyanidin B2, were subjected to analysis by UPLC-Q-TOF/MSE system with negative ion mode. Fragmentation patterns of each standard were summarized based on assigned fragment ions. The prominent product ions were selected as diagnostic ions. Subsequently, diagnostic ions filter was employed to rapidly recognize analogous skeletons. Combined with retention time, accurate mass, characteristic fragments and previous literature data, the structures of the filtered compounds were identified or tentatively characterized. A total 63 phenolic compounds (36 phenolic acid derivatives, 8 flavonoid derivatives and 19 tennis derivatives) in R. palmatum were identified, including 6 potential new compounds. The method of diagnostic ions filter could rapidly detect and identify phenolic compounds in R. palmatum This study provides a method for rapid detection of phenolic compounds in R. palmatum and is expected to complete the material basis of rhubarb.

Pharmacometabolomics in Endogenous Drugs: A New Approach for Predicting the Individualized Pharmacokinetics of Cholic Acid.

The evaluation of individual variability in endogenous drugs' metabolism and disposition is a very challenging task. We developed and validated a metabotype to pharmacokinetics (PK) matching approach by taking cholic acid as an example to predict the individualized PK of endogenous drugs. The stable isotope-labeled cholic acid was selected as the substitute analyte of cholic acid to ensure the accurate measurement of blood concentration. First, large-scale metabolite profiling studies were performed on the predose urine samples of 28 rats. Then, to examine the individualized PK of deuterium 4-cholic acid (d4-cholic acid) in these rats, we determined its plasma concentrations and calculated the differential AUC values. Subsequently, we conducted a two-stage partial least-squares analysis in which 31 baseline metabolites were screened initially for predicting the individualized AUC values of d4-cholic acid using the data of predose urine metabolites. Finally, network biology analysis was applied to give the biological interpretation of the individual variances in cholic acid metabolism and disposition, and the result further narrowed the selection of baseline metabolites from 31 to 2 (sarcosine and S-adenosyl-l-homocysteine) for such prediction. Collectively, this pharmacometabolomics research provided a new strategy for predicting individualized PK of endogenous drugs.

An integrated strategy by using target tissue metabolomics biomarkers as pharmacodynamic surrogate indices to screen antipyretic components of Qingkaikling injection.

Traditional Chinese medicine (TCM) treatment can be valuable therapeutic strategies. However, the active components and action mechanisms that account for its therapeutic effects remain elusive. Based on the hypothesis that the components of a formula which exert effect would be measurable in target tissue, a target tissue metabolomics-based strategy was proposed for screening of antipyretic components in Qingkaikling injection (QKLI). First, we detected the components of QKLI which could reach its target tissue (hypothalamus) by determining the hypothalamus microdialysate and discovered that only baicalin and geniposide could be detected. Then, by conducting hypothalamus metabolomics studies, 14 metabolites were screened as the potential biomarkers that related to the antipyretic mechanisms of QKLI and were used as its pharmacodynamic surrogate indices. Subsequently, the dynamic concentration of baicalin and geniposide in hypothalamus microdialysates and biomarkers in hypothalamus were measured and correlated with each other. The results indicated that only baicalin shown a good correlation with these biomarkers. Finally, a network pharmacology approach was established to validate the antipyretic activity of baicalin and the results elucidated its antipyretic mechanisms as well. The integrated strategy proposed here provided a powerful means for identifying active components and mechanisms contributing to pharmacological effects of TCM.

Improving deep convolutional neural networks with mixed maxout units.

Motivated by insights from the maxout-units-based deep Convolutional Neural Network (CNN) that "non-maximal features are unable to deliver" and "feature mapping subspace pooling is insufficient," we present a novel mixed variant of the recently introduced maxout unit called a mixout unit. Specifically, we do so by calculating the exponential probabilities of feature mappings gained by applying different convolutional transformations over the same input and then calculating the expected values according to their exponential probabilities. Moreover, we introduce the Bernoulli distribution to balance the maximum values with the expected values of the feature mappings subspace. Finally, we design a simple model to verify the pooling ability of mixout units and a Mixout-units-based Network-in-Network (NiN) model to analyze the feature learning ability of the mixout models. We argue that our proposed units improve the pooling ability and that mixout models can achieve better feature learning and classification performance.

Applying characteristic fragment filtering for rapid detection and identification of ingredients in rhubarb by HPLC coupled with linear ion trap-Orbitrap mass spectrometry.

Chemical characteristic fragment filtering in MSn chromatograms was proposed to detect and identify the components in rhubarb rapidly using high-performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometry. Characteristic fragments consist of diagnostic ions and neutral loss fragments. Characteristic fragment filtering is a postacquisition data mining method for the targeted screening of groups with specific structures, including three steps: first, in order to comprehensively summarize characteristic fragments for global identification of the ingredients in rhubarb, representative authentic standards of dominant chemical categories contained in rhubarb were chosen, from which fragmentation rules and a characteristic fragments schedule were proposed; second, characteristic fragment filtering was used to rapidly recognize analogous skeletons; finally, combined with retention time, accurate mass, characteristic fragments, and previous literature, the structures of the filtered compounds were identified or tentatively characterized. As a result, a total of 271 compounds were detected and identified in rhubarb, including 34 anthraquinones, 83 anthrones, 46 tannins, 17 stilbenes, 24 phenylbutanones, 26 acylglucosides, 26 chromones, and 15 other compounds, 69 of which are potentially new compounds. The proposed characteristic fragment filtering strategy would be a reference for the large-scale detection and identification of the ingredients of herbal medicines.

Characterization of the potential new phthalides in Ligusticum chuanxiong Hort. using ultra-performance liquid chromatography coupled with quadrupole time of flight tandem mass spectrometry.

The characterization of unknown compounds is still a great challenge currently. A strategy for deduction of potential new phthalides through the characterization of isomers based on ultra-performance liquid chromatography coupled with quadrupole time of flight tandem mass spectrometry was proposed here to characterize the unknown compounds of Ligusticum chuanxiong Hort. (Chuanxiong). This proposed strategy consisted of four steps: (1) the high resolution MS data was collected, and the peaks were screened preliminarily by UNIFITM platform based on the in-house database; (2) the fragmentation patterns and the characteristic fragments were summarized based on the representative standards; (3) the target compounds were identified based on the fragmentation rules, standards comparison and false positive exclusion; (4) the unknown components were structurally characterized according to the accurate mass and fragmentation patterns analysis. This strategy was successfully applied to the identification and deduction of phthalides in Chuanxiong. A total of 81 phthalides were detected. Fifty-five known phthalides were identified, and 26 potential new phthalides were characterized. This research enriched the material basis of Chuanxiong, and provided a liquid chromatography tandem mass spectrometry-oriented method for the discovery of the potential new compounds.

Using UHPLC Q-Trap/MS as a complementary technique to in-depth mine UPLC Q-TOF/MS data for identifying modified nucleosides in urine.

Modified nucleosides, metabolites of RNA, are potential biomarkers of cancer before the appearance of morphological abnormalities. It is of great significance to comprehensively detect and identify nucleosides in human urine for discovery of cancer biomarkers. However, the lower abundance, the greater polarity and the matrix effects make it difficult to detect urinary nucleosides. In this paper, an integrated method consisted of sample preparation followed by ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC Q-TOF/MS) detection and primary identification, then ultra-high performance liquid chromatography coupled with hybrid triple quadrupole linear ion trap mass spectrometer (UHPLC Q-Trap/MS) further identification and validation were introduced. Firstly, to enrich the nucleosides and eliminate the urine matrix effects, different sorbent materials of solid phase extraction (SPE) and the elution conditions were screened. Secondly, UPLC Q-TOF/MS was used to acquire mass data in MSE mode. The structural formulas of nucleosides in urine sample were primarily identified according to retention time, accurate mass precursor ions and fragment ions from in-house database and online database. Thirdly, the preliminary identified nucleoside structures lacking of characteristic fragment ions were verified by UHPLC Q-Trap/MS in multiple reaction monitoring trigger enhanced product ion scan (MRM-EPI) and neutral loss scan (NL). At last, phenylboronic acid (PBA)-based SPE was utilized due to its higher MS signal and weaker matrix effects under optimized extraction conditions. Fifty-five nucleosides were primarily identified by UPLC Q-TOF/MS, among which 50 nucleosides were confirmed by UHPLC Q-Trap/MS. Five nucleosides, namely 4',5'-didehydro-5'-deoxyadenosine, 4',5'-didehydro-5'-deoxyinosine, isonicotinamide riboside, peroxywybutosine and hydroxywybutosine, were found from urine for the first time. The results will expand the Human Metabolome Database (HMDB).

Plasma metabolomics combined with lipidomics profiling reveals the potential antipyretic mechanisms of Qingkailing injection in a rat model.

Qingkailing injection (QKLI) has a notable antipyretic effect and is widely used in China as a clinical emergency medicine. To elucidate the pharmacological action thoroughly, following the investigation of the urine metabolome and hypothalamus metabolome, plasma metabolomics combined with lipidomics profiling of the QKLI antipyretic effect in a rat model is described in this paper. Compared with pure metabolomics profiling, this non-targeted plasma metabolomics combined with lipidomics profiling based on ultra-performance liquid chromatography-coupled with quadrupole time-of-flight mass spectrometry (UPLC Q-TOF/MS) could be used for a large-scale detection of features in plasma samples. The results showed that 15 metabolites at the 1 h time point and 19 metabolites at the 2 h time point after QKLI administration were associated with the antipyretic effect of QKLI, including amino acid, phosphatidylcholine and lysophosphatidylcholine. The metabolism pathway analysis revealed that the potential biomarkers, which were important for the antipyretic mechanism of QKLI, were closely responsible for correcting the perturbed pathways of amino acid metabolism and lipid metabolism. In conclusion, the use of complementary UPLC Q-TOF/MS based metabolomics and lipidomics allows for the discovery of new potential plasma biomarkers in the QKLI antipyretic process and the associated pathways, and aided in advancing the understanding of the holism and synergism of the Chinese drug.

Delipidation-based solid-phase extraction pretreatment technique for plasma broad-coverage metabolomic profiling to reveal the potential pathogenesis of yeast-induced fever in rats.

During the process of metabolomics profiling by using ultra high performance liquid chromatography coupled with time-of flight mass spectrometry, blood sample pretreatment is a crucial step for biomarker discovery. Herein, in order to prevent the potential loss of metabolites and ion suppression phenomena caused by the proteins and phospholipids contained in blood fluids, a delipidation-based solid-phase extraction pretreatment technique for plasma broad-coverage metabolomic profiling was performed. This technique can be summarized as a single extraction, a single elution of solid-phase extraction plate, followed by four times measuring with electrospray ionization in positive and negative ion mode, respectively. This approach significantly increased the number of features detected in plasma, and 1572 features in positive mode and 1352 features in negative mode were detected, respectively. Besides, the stability and repeatability of the approach were greatly improved. For these advantages, the approach was employed to elucidate the potential pathogenesis of yeast-induced fever in rats. The biomarkers associated with the pathogenesis of fever were shown to be related to amino acids metabolism and lipid metabolism. The delipidation-based solid-phase extraction pretreatment approach can provide a useful tool to reveal the pathological mechanisms of such systemic pathological process.

New IDH1 mutant inhibitors for treatment of acute myeloid leukemia.

Neomorphic mutations in isocitrate dehydrogenase 1 (IDH1) are driver mutations in acute myeloid leukemia (AML) and other cancers. We report the development of new allosteric inhibitors of mutant IDH1. Crystallographic and biochemical results demonstrated that compounds of this chemical series bind to an allosteric site and lock the enzyme in a catalytically inactive conformation, thereby enabling inhibition of different clinically relevant IDH1 mutants. Treatment of IDH1 mutant primary AML cells uniformly led to a decrease in intracellular 2-HG, abrogation of the myeloid differentiation block and induction of granulocytic differentiation at the level of leukemic blasts and more immature stem-like cells, in vitro and in vivo. Molecularly, treatment with the inhibitors led to a reversal of the DNA cytosine hypermethylation patterns caused by mutant IDH1 in the cells of individuals with AML. Our study provides proof of concept for the molecular and biological activity of novel allosteric inhibitors for targeting different mutant forms of IDH1 in leukemia.

Identification of Purines and 7-Deazapurines as Potent and Selective Type I Inhibitors of Troponin I-Interacting Kinase (TNNI3K).

A series of cardiac troponin I-interacting kinase (TNNI3K) inhibitors arising from 3-((9H-purin-6-yl)amino)-N-methyl-benzenesulfonamide (1) is disclosed along with fundamental structure-function relationships that delineate the role of each element of 1 for TNNI3K recognition. An X-ray structure of 1 bound to TNNI3K confirmed its Type I binding mode and is used to rationalize the structure-activity relationship and employed to design potent, selective, and orally bioavailable TNNI3K inhibitors. Identification of the 7-deazapurine heterocycle as a superior template (vs purine) and its elaboration by introduction of C4-benzenesulfonamide and C7- and C8-7-deazapurine substituents produced compounds with substantial improvements in potency (>1000-fold), general kinase selectivity (10-fold improvement), and pharmacokinetic properties (>10-fold increase in poDNAUC). Optimal members of the series have properties suitable for use in in vitro and in vivo experiments aimed at elucidating the role of TNNI3K in cardiac biology and serve as leads for developing novel heart failure medicines.

Crystallographic structure of a small molecule SIRT1 activator-enzyme complex.

SIRT1, the founding member of the mammalian family of seven NAD(+)-dependent sirtuins, is composed of 747 amino acids forming a catalytic domain and extended N- and C-terminal regions. We report the design and characterization of an engineered human SIRT1 construct (mini-hSIRT1) containing the minimal structural elements required for lysine deacetylation and catalytic activation by small molecule sirtuin-activating compounds (STACs). Using this construct, we solved the crystal structure of a mini-hSIRT1-STAC complex, which revealed the STAC-binding site within the N-terminal domain of hSIRT1. Together with hydrogen-deuterium exchange mass spectrometry (HDX-MS) and site-directed mutagenesis using full-length hSIRT1, these data establish a specific STAC-binding site and identify key intermolecular interactions with hSIRT1. The determination of the interface governing the binding of STACs with human SIRT1 facilitates greater understanding of STAC activation of this enzyme, which holds significant promise as a therapeutic target for multiple human diseases.

Mutant IDH1 enhances the production of 2-hydroxyglutarate due to its kinetic mechanism.

The human, cytosolic enzyme isocitrate dehydrogenase 1 (IDH1) reversibly converts isocitrate to α-ketoglutarate (αKG). Cancer-associated somatic mutations in IDH1 result in a loss of this normal function but a gain in a new or neomorphic ability to convert αKG to the oncometabolite 2-hydroxyglutarate (2HG). To improve our understanding of the basis for this phenomenon, we have conducted a detailed kinetic study of wild-type IDH1 as well as the known 2HG-producing clinical R132H and G97D mutants and mechanistic Y139D and (newly described) G97N mutants. In the reductive direction of the normal reaction (αKG to isocitrate), dead-end inhibition studies suggest that wild-type IDH1 goes through a random sequential mechanism, similar to previous reports on related mammalian IDH enzymes. However, analogous experiments studying the reductive neomorphic reaction (αKG to 2HG) with the mutant forms of IDH1 are more consistent with an ordered sequential mechanism, with NADPH binding before αKG. This result was further confirmed by primary kinetic isotope effects for which saturating with αKG greatly reduced the observed isotope effect on (D)(V/K)NADPH. For the mutant IDH1 enzyme, the change in mechanism was consistently associated with reduced efficiencies in the use of αKG as a substrate and enhanced efficiencies using NADPH as a substrate. We propose that the sum of these kinetic changes allows the mutant IDH1 enzymes to reductively trap αKG directly into 2HG, rather than allowing it to react with carbon dioxide and form isocitrate, as occurs in the wild-type enzyme.