Target Information

Target General Information

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Target ID

T98459 (Former ID: TTDR00152)

Target Name

G2/mitotic-specific cyclin B1 (CCNB1)

Synonyms

G2/mitotic-specific cyclin-B1; Cyclin B1; CCNB

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Gene Name

CCNB1

Target Type

Patented-recorded target

[1]

Function

Essential for the control of the cell cycle at the G2/M (mitosis) transition.

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BioChemical Class

Eukaryotic nuclear pore complex

UniProt ID

CCNB1_HUMAN

Sequence

MALRVTRNSKINAENKAKINMAGAKRVPTAPAATSKPGLRPRTALGDIGNKVSEQLQAKM
PMKKEAKPSATGKVIDKKLPKPLEKVPMLVPVPVSEPVPEPEPEPEPEPVKEEKLSPEPI
LVDTASPSPMETSGCAPAEEDLCQAFSDVILAVNDVDAEDGADPNLCSEYVKDIYAYLRQ
LEEEQAVRPKYLLGREVTGNMRAILIDWLVQVQMKFRLLQETMYMTVSIIDRFMQNNCVP
KKMLQLVGVTAMFIASKYEEMYPPEIGDFAFVTDNTYTKHQIRQMEMKILRALNFGLGRP
LPLHFLRRASKIGEVDVEQHTLAKYLMELTMLDYDMVHFPPSQIAAGAFCLALKILDNGE
WTPTLQHYLSYTEESLLPVMQHLAKNVVMVNQGLTKHMTVKNKYATSKHAKISTLPQLNS
ALVQDLAKAVAKV

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3D Structure

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AlphaFold

HIT2.0 ID

T24LXT

Cell-based Target Expression Variations

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Cell-based Target Expression Variations

Cell-based Target Expression Variations Info

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 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 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 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 Pathway Affiliation

Biological Network Descriptors

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

KEGG Pathway	Pathway ID	Affiliated Target
FoxO signaling pathway	hsa04068	Affiliated Target
Class: Environmental Information Processing => Signal transduction	Pathway Hierarchy
Cell cycle	hsa04110	Affiliated Target
Class: Cellular Processes => Cell growth and death	Pathway Hierarchy
Oocyte meiosis	hsa04114	Affiliated Target
Class: Cellular Processes => Cell growth and death	Pathway Hierarchy
p53 signaling pathway	hsa04115	Affiliated Target
Class: Cellular Processes => Cell growth and death	Pathway Hierarchy
Cellular senescence	hsa04218	Affiliated Target
Class: Cellular Processes => Cell growth and death	Pathway Hierarchy
Progesterone-mediated oocyte maturation	hsa04914	Affiliated Target
Class: Organismal Systems => Endocrine system	Pathway Hierarchy
Click to Show/Hide the Information of Affiliated Human Pathways

Degree	85	Degree centrality	9.13E-03	Betweenness centrality	2.63E-03
Closeness centrality	2.39E-01	Radiality	1.42E+01	Clustering coefficient	1.87E-01
Neighborhood connectivity	3.21E+01	Topological coefficient	5.25E-02	Eccentricity	12
Download	Click to Download the Full PPI Network of This Target

Drug Property Profile of Target

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(1) Molecular Weight (mw) based Drug Clustering

(2) Octanol/Water Partition Coefficient (xlogp) based Drug Clustering

(3) Hydrogen Bond Donor Count (hbonddonor) based Drug Clustering

(4) Hydrogen Bond Acceptor Count (hbondacc) based Drug Clustering

(5) Rotatable Bond Count (rotbonds) based Drug Clustering

(6) Topological Polar Surface Area (polararea) based Drug Clustering

"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 Regulators

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Target-regulating microRNAs

Target-regulating microRNAs Info

Target-regulating Transcription Factors

Target-regulating Transcription Factors Info

Target-interacting Proteins

Target-interacting Proteins Info

Target Affiliated Biological Pathways		Top
KEGG Pathway	[+] 5 KEGG Pathways	+
1	FoxO signaling pathway
2	Cell cycle
3	Oocyte meiosis
4	p53 signaling pathway
5	Progesterone-mediated oocyte maturation
NetPath Pathway	[+] 1 NetPath Pathways	+
1	TCR Signaling Pathway
Panther Pathway	[+] 1 Panther Pathways	+
1	p53 pathway
PID Pathway	[+] 7 PID Pathways	+
1	p73 transcription factor network
2	Validated targets of C-MYC transcriptional activation
3	PLK1 signaling events
4	FoxO family signaling
5	Direct p53 effectors
6	FOXM1 transcription factor network
7	C-MYB transcription factor network
Reactome	[+] 16 Reactome Pathways	+
1	Polo-like kinase mediated events
2	Golgi Cisternae Pericentriolar Stack Reorganization
3	Regulation of APC/C activators between G1/S and early anaphase
4	Phosphorylation of the APC/C
5	Phosphorylation of Emi1
6	Condensation of Prophase Chromosomes
7	MASTL Facilitates Mitotic Progression
8	Resolution of Sister Chromatid Cohesion
9	Condensation of Prometaphase Chromosomes
10	Regulation of PLK1 Activity at G2/M Transition
11	Activation of NIMA Kinases NEK9, NEK6, NEK7
12	Recruitment of NuMA to mitotic centrosomes
13	Depolymerisation of the Nuclear Lamina
14	Cyclin A/B1 associated events during G2/M transition
15	G2/M DNA replication checkpoint
16	Chk1/Chk2(Cds1) mediated inactivation of Cyclin B:Cdk1 complex
WikiPathways	[+] 13 WikiPathways	+
1	DNA Damage Response
2	G1 to S cell cycle control
3	Mitotic Prophase
4	Mitotic Prometaphase
5	ATM Signaling Pathway
6	Retinoblastoma (RB) in Cancer
7	Mitotic G2-G2/M phases
8	Mitotic G1-G1/S phases
9	Cell Cycle
10	APC/C-mediated degradation of cell cycle proteins
11	Cell Cycle Checkpoints
12	miRNA Regulation of DNA Damage Response
13	AMPK Signaling

Target-Related Models and Studies

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Target Validation

Target Validation Info

References

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REF 1

Discovery of novel CDK1 inhibitors by combining pharmacophore modeling, QSAR analysis and in silico screening followed by in vitro bioassay. Eur J Med Chem. 2010 Sep;45(9):4316-30.

REF 2

Design of new inhibitors for cdc2 kinase based on a multiple pseudosubstrate structure. Bioorg Med Chem Lett. 1998 May 5;8(9):1019-22.

REF 3

Design, synthesis, and biological evaluation of 3,4-diarylmaleimides as angiogenesis inhibitors. J Med Chem. 2006 Feb 23;49(4):1271-81.

REF 4

Synthesis and cytotoxic activity of 2-methylimidazo[1,2-a]pyridine- and quinoline-substituted 2-aminopyrimidine derivatives. Eur J Med Chem. 2010 Jan;45(1):379-86.

REF 5

1-Azakenpaullone is a selective inhibitor of glycogen synthase kinase-3 beta. Bioorg Med Chem Lett. 2004 Jan 19;14(2):413-6.

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