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Relationship: 933


The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

Binding of inhibitor, NADH-ubiquinone oxidoreductase (complex I) leads to Inhibition, NADH-ubiquinone oxidoreductase (complex I)

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes. Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Inhibition of the mitochondrial complex I of nigro-striatal neurons leads to parkinsonian motor deficits adjacent High Low Andrea Terron (send email) Open for citation & comment TFHA/WNT Endorsed
Inhibition of complex I of the electron transport chain leading to chemical induced Fanconi syndrome adjacent Not Specified Not Specified Marvin Martens (send email) Under development: Not open for comment. Do not cite
Mitochondrial complex inhibition leading to liver injury adjacent Not Specified Not Specified Wanda van der Stel (send email) Under development: Not open for comment. Do not cite

Taxonomic Applicability

Select one or more structured terms that help to define the biological applicability domain of the KER. In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

It is well documented that binding of an inhibitor to CI inhibits its activity (see MIE). Naturally occurring and synthetic CI inhibitors have been shown to inhibit the catalytic activity of CI, leading to partial or total inhibition of its activity in a dose response manner (Degli Esposti and Ghelli, 1994; Ichimaru et al. 2008; Barrientos and Moraes, 1999; Betarbet et al., 2000). Indeed, binding of inhibitors stops the electron flow from CI to ubiquinone. Therefore, the Fe-S clusters of CI become highly reduced and no further electrons can be transferred from NADH to CI. This leads to the inhibition of the NADH oxido-reductase function, i.e. CI inhibition.

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help
Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured (see page 40 of the User Handbook for further information).   More help

The weight of evidence supporting the relationship between binding of an inhibitor to NADH-ubiquinone oxidoreducatse and its inhibition is strong.

Biological Plausibility

There is an extensive understanding of the functional relationship between binding of an inhibitor to NADH-ubiquinone oxidoreductase (CI) and its inhibition. As the first entry complex of mitochondrial respiratory chain, CI oxidizes NADH and transfers electrons via a flavin mononucleotide cofactor and several Fe-S complexes to ubiquinone. The electron flow is coupled to the translocation of protons from the matrix to the intermembrane space. This helps to establish the electrochemical gradient that is used to fuel ATP synthesis (Greenamyre et al., 2001). If an inhibitor binds to CI, the electron transfer is blocked. This compromises ATP synthesis and maintenance of Δψm, leading to mitochondrial dysfunction. As CI exerts a higher control over oxidative phosphorylation in synaptic mitochondria than in non-synaptic mitochondria in the brain (Davey and Clark, 1996), specific functional defects observed in PD may be explained. It is well documented that CI inhibition is one of the main sites at which electron leakage to oxygen occurs. This results in a production of ROS, such as superoxide (Efremov and Sazanow, 2011) and hydrogen peroxide, which are main contributors to oxidative stress (Greenamyre et al., 2001).

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

It is not clear the number of subunits constituting CI in mammals, as according to the existing literature different numbers are cited (between 41-46) (Vogel et al., 2007a; Hassinen, 2007). The majority of data claims that mammalian CI is composed of 46 (Greenamyre et al., 2001; Hassinen, 2007) or 45 subunits (Vogel et al., 2007a). It is not sure whether there may exist tissue-specific subunits of CI isoforms (Fearnley et al., 2001). It is unclear, which subunit(s) bind rotenone or other inhibitors of CI. Additionally, it is not clear whether CI has other uncharacterized functions, taking into consideration its size and complexity (43-46 subunits vs. 11 subunits of complex III or 13 subunits of complex IV) (Greenamyre et al., 2001). There is no strict linear relationship between inhibitor binding and reduced mitochondrial function. Low doses of rotenone that inhibit CI activity partially do not alter mitochondrial oxygen consumption. Therefore, bioenergetic defects can not account alone for rotenone-induced neurodegeneration. Instead, under such conditions, rotenone neurotoxicity may result from oxidative stress (Betarbet et al., 2000). Few studies used human brain cells/human brain mitochondria. Therefore, full quantitative data for humans are not available.

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help
This sub-section should be used to provide information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help
Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help
Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help

The CI is well-conserved across species from lower organism to mammals. The central subunits of CI harboring the bioenergetic core functions are conserved from bacteria to humans. CI from bacteria and from mitochondria of Yarrowia lipolytica, a yeast genetic model for the study of eukaryotic CI (Kerscher et al., 2002) was analyzed by x-ray crystallography (Zickermann et al., 2015). However, the affinity of various chemicals to cause partial or total inhibition of CI activity across species is not well studied (except rotenone).


List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

Barrientos A, and Moraes CT. 1999. Titrating the Effects of Mitochondrial Complex I Impairment in the Cell Physiology. 274(23)16188–16197.

Beretta S, et al. 2006. Partial mitochondrial complex I inhibition induces oxidative damage and perturbs glutamate transport in primary retinal cultures. Relevance to Leber Hereditary Optic Neuropathy (LHON). Neurobiol Dis. 24:308–317.

Betarbet R, Sherer TB, MacKenzie G, Garcia-Osuna M, Panov AV, Greenamyre JT. 2000. Chronic systemic pesticide exposure reproduces features of Parkinson's disease. Nat Neurosci 3:1301-1306.

Cheville NF. 1994. Ultrastructural Pathology: The Comparative Cellular Basis of Disease Wiley John Wiley & Sons, 09 dic 2009 - 1000 pagine Chinopoulos C, Adam-Vizi V. 2001. Mitochondria deficient in complex I activity are depolarized by hydrogen peroxide in nerve terminals: Relevance to Parkinson’s disease. J Neurochem. 76:302–306.

Choi WS, Kruse SE, Palmiter R, Xia Z. 2008. Mitochondrial complex I inhibition is not required for dopaminergic neuron death induced by rotenone, MPP, or paraquat. PNAS. 105(39):15136-15141.

Cleeter MW, Cooper JM, Schapira AH. 1992. Irreversible inhibition of mitochondrial complex I by 1-methyl-4-phenylpyridinium: evidence for free radical involvement. J Neurochem. 58(2):786-9.

Davey GP, Clark JB. 1996. Threshold effects and control of oxidative phosphorylation in nonsynaptic rat brain mitochondria, J. Neurochem. 66:1617 24.

Degli Esposti M, Ghelli A. 1994. The mechanism of proton and electron transport in mitochondrial complex I. Biochim Biophys Acta.1187(2):116–120.

Degli Esposti (1998) Inhibitors of NADH-ubiquinone reductase: an overview Biochimica et Biophysica Acta 1364-222-235. Efremov RG, Sazanov LA. Structure of the membrane domain of respiratory complex I. Nature. 2011 Aug 7;476(7361):414-20.

Fearnley IM, Carroll J, Shannon RJ, Runswick MJ, Walker JE, and Hirst J. 2001. GRIM-19, a cell death regulatory gene product, is a subunit of bovine mitochondrial NADH:ubiquinone oxidoreductas (complex I). J. Biol. Chem. 276(42):38345-8.

Greenamyre TJ, Sherer TB, Betarbet R, and Panov AV. 2001. Complex I and Parkinson’s Disease. Critical Review.IUBMB Life, 52: 135–141.

Grivennikova VG, Maklashina EO, Gavrikova EV, Vinogradov AD. 1997. Interaction of the mitochondrial NADH-ubiquinone reductase with rotenone as related to the enzyme active/inactive transition. Biochim et Biophys. Acta. 1319:223–232.

Hassinen I. 2007. Regulation of Mitochondrial Respiration in Heart Muscle. In Mitochondria – The Dynamic Organelle Edited by Schaffer & Suleiman. Springer ISBN-13: 978-0-387-69944-8.

Ichimaru N, Murai M, Kakutani N, Kako J, Ishihara A, Nakagawa Y, Miyoshi H. 2008.. Synthesis and Characterization of New Piperazine-Type Inhibitors for Mitochondrial NADH-Ubiquinone Oxidoreductase (Complex I). Biochemistry. 47(40)10816–10826.

Koopman W, Hink M, Verkaart S, Visch H, Smeitink J, Willems P. 2007. Partial complex I inhibition decreases mitochondrial motility and increases matrix protein diffusion as revealed by fluorescence correlation spectroscopy. Biochimica et Biophysica Acta 1767:940-947. Krug AK, Gutbier S, Zhao L, Pöltl D, Kullmann C, Ivanova V, Förster S, Jagtap S, Meiser J, Leparc G, Schildknecht S, Adam M, Hiller K, Farhan H, Brunner T, Hartung T, Sachinidis A, Leist M (2014) Transcriptional and metabolic adaptation of human neurons to the mitochondrial toxicant MPP(+). Cell Death Dis. 8(5):e1222. doi: 10.1038/cddis.2014.166. Lambert AJ, Brand MD. Inhibitors of the quinone-binding site allow rapid superoxide production from mitochondrial NADH:ubiquinone oxidoreductase (complex I). J Biol Chem. 2004 Sep 17;279(38):39414-20.

Langston JW. 1996. The etiology of Parkinson’s disease with emphasis on the MPTP story. Neurology. 47, S153–160.

Mizuno Y, Ohta S, Tanaka M, Takamiya S, Suzuki K, Sato T, Oya H, Ozawa T, Kagawa Y. 1989. Deficiencies in complex I subunits of the respiratory chain in Parkinson's disease. Biochem Biophys Res Commun. 29;163(3):1450-5.

Nicklas WJ, Yougster SK, Kindt MV, Heikkila RE. 1987. MPTP, MPP+ and mitochondrial function. Life Sci. 40:721-729.

Okun JG, Lummen PL, Brandt U. 1999. Three Classes of Inhibitors Share a Common Binding Domain in Mitochondrial Complex I (NADH:Ubiquinone Oxidoreductase) 274(5)2625–2630.

Parker Jr WD, Swerdlow RH. 1998. Mitochondrial dysfunction in idiopathic Parkinson disease. Am J Hum Genet 62:758 –762.

Ramsay RR, Krueger MJ, Youngster SK, Singer TP. Evidence that the inhibition sites of the neurotoxic amine 1-methyl-4-phenylpyridinium (MPP+) and of the respiratory chain inhibitor piericidin A are the same. Biochem J. 1991 Jan 15;273(Pt 2):481-4.

Sayre LM, Arora PK, Feke SC, Urbach FL. 1986. Mechanism of induction of Parkinson’s disease by I-methyl-4-phenyl- 1,2,3,6-tetrahydropyridine (MPTP). Chemical and electrochemical characterization of a geminal-dimethyl-blocked analogue of a postulated toxic metabolite. J Am Chem Sot. 108:2464-2466.

Schapira AH, Cooper JM, Dexter D, Jenner P, Clark JB, and Marsden CD. 1989. Mitochondrial complex I deficiency in Parkinson’s disease. Lancet. 1,1269.

Schuler F, Casida JE.The insecticide target in the PSST subunit of complex I. Pest Manag Sci. 2001 Oct;57(10):932-40.

Shults CW. 2004. Mitochondrial dysfunction and possible treatments in Parkinson’s disease–a review. Mitochondrion 4:641– 648.

Vogel RO, van den Brand MA, Rodenburg RJ, van den Heuvel LP, Tsuneoka M, Smeitink JA, Nijtmans LG. (2007a). Investigation of the complex I assembly chaperones B17.2L and NDUFAF1 in a cohort of CI deficient patients. Mol. Genet. Metab. 91:176–182.