Target Information
| Target General Information | Top | |||||
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| Target ID |
T39977
(Former ID: TTDC00103)
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| Target Name |
Macrophage migration inhibitory factor (MIF)
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| Synonyms |
Phenylpyruvate tautomerase; MMIF; L-dopachrome tautomerase; L-dopachrome isomerase; Glycosylation-inhibiting factor; GLIF; GIF
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| Gene Name |
MIF
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| Target Type |
Clinical trial target
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[1] | ||||
| Disease | [+] 1 Target-related Diseases | + | ||||
| 1 | Thrombocytopenia [ICD-11: 3B64] | |||||
| Function |
Involved in the innate immune response to bacterial pathogens. The expression of MIF at sites of inflammation suggests a role as mediator in regulating the function of macrophages in host defense. Counteracts the anti-inflammatory activity of glucocorticoids. Has phenylpyruvate tautomerase and dopachrome tautomerase activity (in vitro), but the physiological substrate is not known. It is not clear whether the tautomerase activity has any physiological relevance, and whether it is important for cytokine activity. Pro-inflammatory cytokine.
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| BioChemical Class |
Intramolecular oxidoreductase
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| UniProt ID | ||||||
| EC Number |
EC 5.3.2.1
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| Sequence |
MPMFIVNTNVPRASVPDGFLSELTQQLAQATGKPPQYIAVHVVPDQLMAFGGSSEPCALC
SLHSIGKIGGAQNRSYSKLLCGLLAERLRISPDRVYINYYDMNAANVGWNNSTFA Click to Show/Hide
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| 3D Structure | Click to Show 3D Structure of This Target | PDB | ||||
| ADReCS ID | BADD_A05088 ; BADD_A08298 | |||||
| HIT2.0 ID | T89GFN | |||||
| Drugs and Modes of Action | Top | |||||
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| Approved Drug(s) | [+] 1 Approved Drugs | + | ||||
| 1 | Anti-MIF antibodies | Drug Info | Phase 4 | Autoimmune diabetes | [3] | |
| Preclinical Drug(s) | [+] 1 Preclinical Drugs | + | ||||
| 1 | COR100140 | Drug Info | Preclinical | Inflammation | [4] | |
| Mode of Action | [+] 1 Modes of Action | + | ||||
| Inhibitor | [+] 8 Inhibitor drugs | + | ||||
| 1 | Anti-MIF antibodies | Drug Info | [1] | |||
| 2 | ISO-1 | Drug Info | [5] | |||
| 3 | COR100140 | Drug Info | [6] | |||
| 4 | 4-HYDROXYBENZALDEHYDE O-(CYCLOHEXYLCARBONYL)OXIME | Drug Info | [7] | |||
| 5 | 4-hydroxyphenylpyruvic acid | Drug Info | [7] | |||
| 6 | 6-HYDROXY-1,3-BENZOTHIAZOLE-2-SULFONAMIDE | Drug Info | [7] | |||
| 7 | AVP-13546 | Drug Info | [8] | |||
| 8 | AVP-13748 | Drug Info | [8] | |||
| Cell-based Target Expression Variations | Top | |||||
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| Cell-based Target Expression Variations | ||||||
| Drug Binding Sites of Target | Top | |||||
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| Ligand Name: 4-hydroxyphenylpyruvic acid | Ligand Info | |||||
| Structure Description | Ternary Complex of Macrophage Migration Inhibitory Factor (MIF) Bound Both to 4-hydroxyphenylpyruvate and to the Allosteric Inhibitor AV1013 (R-stereoisomer) | PDB:3IJJ | ||||
| Method | X-ray diffraction | Resolution | 1.25 Å | Mutation | No | [9] |
| PDB Sequence |
PMFIVNTNVP
10 RASVPDGFLS20 ELTQQLAQAT30 GKPPQYIAVH40 VVPDQLMAFG50 GSSEPCALCS 60 LHSIGKIGGA70 QNRSYSKLLC80 GLLAERLRIS90 PDRVYINYYD100 MNAANVGWNN 110 STFA
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| Click to View More Binding Site Information of This Target and Ligand Pair | ||||||
| Ligand Name: Dimethylformamide | Ligand Info | |||||
| Structure Description | Crystal Structure Analysis of Macrophage Migration Inhibitory Factor in complex with Dimethylformamide | PDB:4P0H | ||||
| Method | X-ray diffraction | Resolution | 1.93 Å | Mutation | No | [10] |
| PDB Sequence |
PMFIVNTNVP
10 RASVPDGFLS20 ELTQQLAQAT30 GKPPQYIAVH40 VVPDQLMAFG50 GSSEPCALCS 60 LHSIGKIGGA70 QNRSYSKLLC80 GLLAERLRIS90 PDRVYINYYD100 MNAANVGWNN 110 STFA
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| Click to View More Binding Site Information of This Target with Different Ligands | ||||||
| Different Human System Profiles of Target | Top |
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Human Similarity Proteins
of target is determined by comparing the sequence similarity of all human proteins with the target based on BLAST. The similarity proteins for a target are defined as the proteins with E-value < 0.005 and outside the protein families of the target.
A target that has fewer human similarity proteins outside its family is commonly regarded to possess a greater capacity to avoid undesired interactions and thus increase the possibility of finding successful drugs
(Brief Bioinform, 21: 649-662, 2020).
Human Tissue Distribution
of target is determined from a proteomics study that quantified more than 12,000 genes across 32 normal human tissues. Tissue Specificity (TS) score was used to define the enrichment of target across tissues.
The distribution of targets among different tissues or organs need to be taken into consideration when assessing the target druggability, as it is generally accepted that the wider the target distribution, the greater the concern over potential adverse effects
(Nat Rev Drug Discov, 20: 64-81, 2021).
Human Pathway Affiliation
of target is determined by the life-essential pathways provided on KEGG database. The target-affiliated pathways were defined based on the following two criteria (a) the pathways of the studied target should be life-essential for both healthy individuals and patients, and (b) the studied target should occupy an upstream position in the pathways and therefore had the ability to regulate biological function.
Targets involved in a fewer pathways have greater likelihood to be successfully developed, while those associated with more human pathways increase the chance of undesirable interferences with other human processes
(Pharmacol Rev, 58: 259-279, 2006).
Biological Network Descriptors
of target is determined based on a human protein-protein interactions (PPI) network consisting of 9,309 proteins and 52,713 PPIs, which were with a high confidence score of ≥ 0.95 collected from STRING database.
The network properties of targets based on protein-protein interactions (PPIs) have been widely adopted for the assessment of target’s druggability. Proteins with high node degree tend to have a high impact on network function through multiple interactions, while proteins with high betweenness centrality are regarded to be central for communication in interaction networks and regulate the flow of signaling information
(Front Pharmacol, 9, 1245, 2018;
Curr Opin Struct Biol. 44:134-142, 2017).
Human Similarity Proteins
Human Tissue Distribution
Human Pathway Affiliation
Biological Network Descriptors
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There is no similarity protein (E value < 0.005) for this target
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Note:
If a protein has TS (tissue specficity) scores at least in one tissue >= 2.5, this protein is called tissue-enriched (including tissue-enriched-but-not-specific and tissue-specific). In the plots, the vertical lines are at thresholds 2.5 and 4.
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| KEGG Pathway | Pathway ID | Affiliated Target | Pathway Map |
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| Tyrosine metabolism | hsa00350 | Affiliated Target |
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| Class: Metabolism => Amino acid metabolism | Pathway Hierarchy | ||
| Phenylalanine metabolism | hsa00360 | Affiliated Target |
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| Class: Metabolism => Amino acid metabolism | Pathway Hierarchy | ||
| Degree | 2 | Degree centrality | 2.15E-04 | Betweenness centrality | 0.00E+00 |
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| Closeness centrality | 1.94E-01 | Radiality | 1.33E+01 | Clustering coefficient | 1.00E+00 |
| Neighborhood connectivity | 2.35E+01 | Topological coefficient | 5.22E-01 | Eccentricity | 13 |
| Download | Click to Download the Full PPI Network of This Target | ||||
| Chemical Structure based Activity Landscape of Target | Top |
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| Drug Property Profile of Target | Top | |
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| (1) Molecular Weight (mw) based Drug Clustering | (2) Octanol/Water Partition Coefficient (xlogp) based Drug Clustering | |
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| (3) Hydrogen Bond Donor Count (hbonddonor) based Drug Clustering | (4) Hydrogen Bond Acceptor Count (hbondacc) based Drug Clustering | |
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| (5) Rotatable Bond Count (rotbonds) based Drug Clustering | (6) Topological Polar Surface Area (polararea) based Drug Clustering | |
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| "RO5" indicates the cutoff set by lipinski's rule of five; "D123AB" colored in GREEN denotes the no violation of any cutoff in lipinski's rule of five; "D123AB" colored in PURPLE refers to the violation of only one cutoff in lipinski's rule of five; "D123AB" colored in BLACK represents the violation of more than one cutoffs in lipinski's rule of five | ||
| Target Poor or Non Binders | Top | |||||
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| Target Poor or Non Binders | ||||||
| Target Regulators | Top | |||||
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| Target-regulating microRNAs | ||||||
| Target-interacting Proteins | ||||||
| Target Affiliated Biological Pathways | Top | |||||
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| KEGG Pathway | [+] 2 KEGG Pathways | + | ||||
| 1 | Tyrosine metabolism | |||||
| 2 | Phenylalanine metabolism | |||||
| Pathwhiz Pathway | [+] 1 Pathwhiz Pathways | + | ||||
| 1 | Tyrosine Metabolism | |||||
| WikiPathways | [+] 2 WikiPathways | + | ||||
| 1 | Spinal Cord Injury | |||||
| 2 | Adipogenesis | |||||
| Target-Related Models and Studies | Top | |||||
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| Target Validation | ||||||
| References | Top | |||||
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| REF 1 | Neutralization of Macrophage Migration Inhibitory Factor (MIF) by Fully Human Antibodies Correlates with Their Specificity for the beta-Sheet Structure of MIF. J Biol Chem. 2012 March 2; 287(10): 7446-7455. | |||||
| REF 2 | ClinicalTrials.gov (NCT02556814) Caffeic Acid Combining High-dose Dexamethasone in Management of ITP. U.S. National Institutes of Health. | |||||
| REF 3 | ClinicalTrials.gov (NCT01452997) Evaluation of Anti-inflammatories in the Reduction of Bite Reactions. U.S. National Institutes of Health. | |||||
| REF 4 | Trusted, scientifically sound profiles of drug programs, clinical trials, safety reports, and company deals, written by scientists. Springer. 2015. Adis Insight (drug id 800020117) | |||||
| REF 5 | The tautomerase active site of macrophage migration inhibitory factor is a potential target for discovery of novel anti-inflammatory agents. J Biol Chem. 2002 Jul 12;277(28):24976-82. | |||||
| REF 6 | Cortical Pty Ltd Presents MIF Antagonist Data at World Congress on Inflammation. Cortical Pty Ltd. 2005. | |||||
| REF 7 | The Protein Data Bank. Nucleic Acids Res. 2000 Jan 1;28(1):235-42. | |||||
| REF 8 | MIF in autoimmunity and novel therapeutic approaches. Autoimmun Rev. 2009 Jan;8(3):244-9. | |||||
| REF 9 | Allosteric inhibition of macrophage migration inhibitory factor revealed by ibudilast. Proc Natl Acad Sci U S A. 2010 Jun 22;107(25):11313-8. | |||||
| REF 10 | An Analysis of MIF Structural Features that Control Functional Activation of CD74. Chem Biol. 2015 Sep 17;22(9):1197-205. | |||||
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