Target Information

Target General Information

Target ID

T62746 (Former ID: TTDI02437)

Target Name

Rotamase F (PPIF)

Synonyms

Peptidylprolyl cistrans isomerase F, mitochondrial; Peptidyl-prolyl cis-trans isomerase F, mitochondrial; PPIase F; Mitochondrial cyclophilin; Cyclophilin F; CyPM; CyP-M; CyP-D; CYP3

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Gene Name

PPIF

Target Type

Literature-reported target

[1]

Function

Involved in regulation of the mitochondrial permeability transition pore (mPTP). It is proposed that its association with the mPTP is masking a binding site for inhibiting inorganic phosphate (Pi) and promotes the open probability of the mPTP leading to apoptosis or necrosis; the requirement of the PPIase activity for this function is debated. In cooperation with mitochondrial TP53 is involved in activating oxidative stress-induced necrosis. Involved in modulation of mitochondrial membrane F(1)F(0) ATP synthase activity and regulation of mitochondrial matrix adenine nucleotide levels. Has anti-apoptotic activity independently of mPTP and in cooperation with BCL2 inhibits cytochrome c-dependent apoptosis. PPIase that catalyzes the cis-trans isomerization of proline imidic peptide bonds in oligopeptides and may therefore assist protein folding.

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BioChemical Class

Cis-trans-isomerase

UniProt ID

PPIF_HUMAN

EC Number

EC 5.2.1.8

Sequence

MLALRCGSRWLGLLSVPRSVPLRLPAARACSKGSGDPSSSSSSGNPLVYLDVDANGKPLG
RVVLELKADVVPKTAENFRALCTGEKGFGYKGSTFHRVIPSFMCQAGDFTNHNGTGGKSI
YGSRFPDENFTLKHVGPGVLSMANAGPNTNGSQFFICTIKTDWLDGKHVVFGHVKEGMDV
VKKIESFGSKSGRTSKKIVITDCGQLS

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3D Structure

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PDB

Cell-based Target Expression Variations

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Cell-based Target Expression Variations

Cell-based Target Expression Variations Info

Drug Binding Sites of Target

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Ligand Name: Dimethylformamide

Ligand Info

Structure Description

Human cyclophilin D complexed with dimethylformamide

PDB:3RCG

Method

X-ray diffraction

Resolution

0.97 Å

Mutation

Yes

[2]

PDB Sequence

GNPLVYLDVD

⁵³

ANGKPLGRVV

⁶³

LELKADVVPK

⁷³

TAENFRALCT

⁸³

GEKGFGYKGS

⁹³

TFHRVIPSFM

¹⁰³

CQAGDFTNHN

¹¹³

GTGGKSIYGS

¹²³

RFPDENFTLK

¹³³

HVGPGVLSMA

¹⁴³

NAGPNTNGSQ

¹⁵³

FFICTIKTDW

¹⁶³

LDGKHVVFGH

¹⁷³

VIEGMDVVKK

¹⁸³

IESFGSKSGR

¹⁹³

TSKKIVITDC

²⁰³

GQLS

Residue

Distance (Å)

ARG97

2.453

PHE102

2.900

MET103

2.780

GLN105

2.679

MET142

4.931

ALA143

2.392

Residue

Distance (Å)

ASN144

2.419

PHE155

3.009

TRP163

4.925

LEU164

2.487

HIS168

2.574

Ligand Name: Carzenide

Ligand Info

Structure Description

Human Cyclophilin D Complexed with a Fragment

PDB:3R4G

Method

X-ray diffraction

Resolution

1.05 Å

Mutation

Yes

[2]

PDB Sequence

GNPLVYLDVD

⁵³

ANGKPLGRVV

⁶³

LELKADVVPK

⁷³

TAENFRALCT

⁸³

GEKGFGYKGS

⁹³

TFHRVIPSFM

¹⁰³

CQAGDFTNHN

¹¹³

GTGGKSIYGS

¹²³

RFPDENFTLK

¹³³

HVGPGVLSMA

¹⁴³

NAGPNTNGSQ

¹⁵³

FFICTIKTDW

¹⁶³

LDGKHVVFGH

¹⁷³

VIEGMDVVKK

¹⁸³

IESFGSKSGR

¹⁹³

TSKKIVITDC

²⁰³

GQLS

Residue

Distance (Å)

ALA54

3.559

ASN55

2.869

LYS57

3.639

LEU59

3.369

ARG97

4.144

ILE99

3.449

PRO100

4.953

SER101

2.815

Residue

Distance (Å)

PHE102

3.307

ILE159

3.446

TRP163

3.632

LYS183

2.815

PHE187

3.954

LYS190

4.000

LYS196

2.738

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Different Human System Profiles of Target	Top
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

Different Human System Profiles of Target

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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

There is no similarity protein (E value < 0.005) for this target


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.

KEGG Pathway	Pathway ID	Affiliated Target
Calcium signaling pathway	hsa04020	Affiliated Target
Class: Environmental Information Processing => Signal transduction	Pathway Hierarchy
cGMP-PKG signaling pathway	hsa04022	Affiliated Target
Class: Environmental Information Processing => Signal transduction	Pathway Hierarchy
Neutrophil extracellular trap formation	hsa04613	Affiliated Target
Class: Organismal Systems => Immune system	Pathway Hierarchy

Degree	11	Degree centrality	1.18E-03	Betweenness centrality	1.32E-03
Closeness centrality	2.50E-01	Radiality	1.43E+01	Clustering coefficient	1.64E-01
Neighborhood connectivity	6.16E+01	Topological coefficient	1.09E-01	Eccentricity	10
Download	Click to Download the Full PPI Network of This Target

Target Regulators

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Target-regulating microRNAs

Target-regulating microRNAs Info

References

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REF 1

Loss of cyclophilin D reveals a critical role for mitochondrial permeability transition in cell death. Nature. 2005 Mar 31;434(7033):658-62.

REF 2

Fragment-based discovery of a new family of non-peptidic small-molecule cyclophilin inhibitors with potent antiviral activities. Nat Commun. 2016 Sep 22;7:12777.

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