Target Information

Target General Information

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Target ID

T25608 (Former ID: TTDNC00653)

Target Name

Free fatty acid receptor 1 (GPR40)

Synonyms

Gprotein coupled receptor 40; FFAR1

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Gene Name

FFAR1

Target Type

Clinical trial target

[1]

Disease

[+] 1 Target-related Diseases

Type 2 diabetes mellitus [ICD-11: 5A11]

Function

G-protein coupled receptor for medium and long chain saturated and unsaturated fatty acids that plays an important role in glucose homeostasis. Fatty acid binding increases glucose- stimulated insulin secretion, and may also enhance the secretion of glucagon-like peptide 1 (GLP-1). May also play a role in bone homeostasis; receptor signaling activates pathways that inhibit osteoclast differentiation. Ligand binding leads to a conformation change that triggers signaling via G-proteins that activate phospholipase C, leading to an increase of the intracellular calcium concentration. Seems to act through a G(q) and G(i)-mediated pathway.

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BioChemical Class

GPCR rhodopsin

UniProt ID

FFAR1_HUMAN

Sequence

MDLPPQLSFGLYVAAFALGFPLNVLAIRGATAHARLRLTPSLVYALNLGCSDLLLTVSLP
LKAVEALASGAWPLPASLCPVFAVAHFFPLYAGGGFLAALSAGRYLGAAFPLGYQAFRRP
CYSWGVCAAIWALVLCHLGLVFGLEAPGGWLDHSNTSLGINTPVNGSPVCLEAWDPASAG
PARFSLSLLLFFLPLAITAFCYVGCLRALARSGLTHRRKLRAAWVAGGALLTLLLCVGPY
NASNVASFLYPNLGGSWRKLGLITGAWSVVLNPLVTGYLGRGPGLKTVCAARTQGGKSQK

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3D Structure

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AlphaFold

HIT2.0 ID

T88MHO

Drugs and Modes of Action

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Clinical Trial Drug(s)

[+] 10 Clinical Trial Drugs

Fasiglifam hemihydrate

Drug Info

Phase 3

Type-2 diabetes

[2]

TAK-875

Drug Info

Phase 3

Type-2 diabetes

[3], [4]

JTT-851

Drug Info

Phase 2

Type-2 diabetes

[5], [6]

P-1736

Drug Info

Phase 2

Diabetic complication

[7]

PBI-4050

Drug Info

Phase 2

Idiopathic pulmonary fibrosis

[8]

CPL207-280CA

Drug Info

Phase 1

Type 2 diabetes

[9]

LY-2881835

Drug Info

Phase 1

Type-2 diabetes

[10]

LY2922470

Drug Info

Phase 1

Type 2 diabetes

[11]

P11187

Drug Info

Phase 1

Type-2 diabetes

[12]

SHR0534

Drug Info

Phase 1

Type 2 diabetes

[13]

Preclinical Drug(s)

[+] 3 Preclinical Drugs

BMS-986118

Drug Info

Preclinical

Type 2 diabetes

[14]

CNX-011-67

Drug Info

Preclinical

Type 2 diabetes

[9]

DS-1558

Drug Info

Preclinical

Type 2 diabetes

[9]

Mode of Action

[+] 4 Modes of Action

Modulator

[+] 5 Modulator drugs

Fasiglifam hemihydrate

Drug Info

[1], [15]

TAK-875

Drug Info

[16]

P-1736

Drug Info

[7]

LY-2881835

Drug Info

[17]

P11187

Drug Info

[17]

Agonist

[+] 16 Agonist drugs

JTT-851

Drug Info

[17]

PBI-4050

Drug Info

[18]

CPL207-280CA

Drug Info

[9]

LY2922470

Drug Info

[19]

SHR0534

Drug Info

[9]

BMS-986118

Drug Info

[20]

DS-1558

Drug Info

[22]

alpha-linolenic acid

Drug Info

[23]

AMG-837

Drug Info

[24]

CNX-011

Drug Info

[25]

GW9508

Drug Info

[26]

medica 16

Drug Info

[27]

PMID18477808CB

Drug Info

[28]

TUG-424

Drug Info

[29]

TUG-469

Drug Info

[25]

TUG-770

Drug Info

[30]

Inhibitor

[+] 1 Inhibitor drugs

CNX-011-67

Drug Info

[21]

Antagonist

[+] 1 Antagonist drugs

GW1100

Drug Info

[26]

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

Protein Name	Pfam ID	Percentage of Identity (%)	E value
Olfactory receptor 1E1 (OR1E1)	PF13853	27.338 (38/139)	1.00E-03
Olfactory receptor 6S1 (OR6S1)	PF13853	27.419 (34/124)	2.00E-03
Olfactory receptor 1N1 (OR1N1)	PF13853	26.667 (36/135)	4.00E-03

KEGG Pathway	Pathway ID	Affiliated Target	Pathway Map
Insulin secretion	hsa04911	Affiliated Target
Class: Organismal Systems => Endocrine system	Pathway Hierarchy

Degree	2	Degree centrality	2.15E-04	Betweenness centrality	1.42E-05
Closeness centrality	1.87E-01	Radiality	1.32E+01	Clustering coefficient	0.00E+00
Neighborhood connectivity	2.85E+01	Topological coefficient	5.00E-01	Eccentricity	12
Download	Click to Download the Full PPI Network of This Target

Chemical Structure based Activity Landscape of Target

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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 Poor or Non Binders

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Target Poor or Non Binders

Target Poor or Non Binders Info

Target Profiles in Patients

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Target Expression
Profile (TEP)

Target Expression Profile Info

Drug Resistance
Mutation (DRM)

Drug Resistance Mutation Info

Target Affiliated Biological Pathways

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KEGG Pathway

[+] 1 KEGG Pathways

Insulin secretion

Reactome

[+] 2 Reactome Pathways

G alpha (q) signalling events

Fatty Acids bound to GPR40 (FFAR1) regulate insulin secretion

WikiPathways

[+] 6 WikiPathways

GPCRs, Class A Rhodopsin-like

Incretin Synthesis, Secretion, and Inactivation

Gastrin-CREB signalling pathway via PKC and MAPK

Integration of energy metabolism

GPCR ligand binding

GPCR downstream signaling

References

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REF 1

A novel antidiabetic drug, fasiglifam/TAK-875, acts as an ago-allosteric modulator of FFAR1. PLoS One. 2013 Oct 10;8(10):e76280.

REF 2

ClinicalTrials.gov (NCT02015780) Fasiglifam in Type 2 Diabetic Subjects With Chronic Kidney Disease Stage 4 or 5 on Hemodialysis. U.S. National Institutes of Health.

REF 3

URL: http://www.guidetopharmacology.org Nucleic Acids Res. 2015 Oct 12. pii: gkv1037. The IUPHAR/BPS Guide to PHARMACOLOGY in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands. (Ligand id: 6484).

REF 4

ClinicalTrials.gov (NCT01609582) Study of TAK-875 in Adults With Type 2 Diabetes and Cardiovascular Disease or Risk Factors for Cardiovascular Disease. U.S. National Institutes of Health.

REF 5

ClinicalTrials.gov (NCT01699737) Safety and Efficacy Study of JTT-851 in Patients With Type 2 Diabetes Mellitus. U.S. National Institutes of Health.

REF 6

Clinical pipeline report, company report or official report of the Pharmaceutical Research and Manufacturers of America (PhRMA)

REF 7

Discovery of p1736, a novel antidiabetic compound that improves peripheral insulin sensitivity in mice models. PLoS One. 2013 Oct 23;8(10):e77946.

REF 8

Clinical pipeline report, company report or official report of Liminal BioSciences.

REF 9

Targeting metabolic dysregulation for fibrosis therapy. Nat Rev Drug Discov. 2020 Jan;19(1):57-75.

REF 10

ClinicalTrials.gov (NCT01358981) A Study of LY2881835 in Healthy People and People With Diabetes. U.S. National Institutes of Health.

REF 11

ClinicalTrials.gov (NCT01867216) A Study of Multiple Doses of LY2922470 in Participants With Diabetes. U.S. National Institutes of Health.

REF 12

ClinicalTrials.gov (NCT01874366) Determination of Safety,Tolerability,Pharmacokinetics,Food Effect& Pharmacodynamics of Single & Multiple Doses of P11187. U.S. National Institutes of Health.

REF 13

ClinicalTrials.gov (NCT03006159) A Phase 1, Randomized, Placebo-controlled, Multiple Dose Escalation Study to Investigate Safety, Pharmacokinetics, and Pharmacodynamics of SHR0534 in Chinese Type 2 Diabetic Patients. U.S. National Institutes of Health.

REF 14

Free fatty acid receptor agonists for the treatment of type 2 diabetes: drugs in preclinical to phase II clinical development. Expert Opin Investig Drugs. 2016 Aug;25(8):871-90.

REF 15

TAK-875, a GPR40/FFAR1 agonist, in combination with metformin prevents progression of diabetes and beta-cell dysfunction in Zucker diabetic fatty rats. Br J Pharmacol. 2013 Oct;170(3):568-80.

REF 16

Efficacy and safety of fasiglifam (TAK-875), a G protein-coupled receptor 40 agonist, in Japanese patients with type 2 diabetes inadequately controlled by diet and exercise: a randomized, double-blind, placebo-controlled, phase III trial. Diabetes Obes Metab. 2015 Jul;17(7):675-81.

REF 17

Treatment of Type 2 Diabetes by Free Fatty Acid Receptor Agonists. Front Endocrinol (Lausanne) 2014; 5: 137.

REF 18

Phase 2 clinical trial of PBI-4050 in patients with idiopathic pulmonary fibrosis. Eur Respir J. 2019 Mar 18;53(3):1800663.

REF 19

The Discovery, Preclinical, and Early Clinical Development of Potent and Selective GPR40 Agonists for the Treatment of Type 2 Diabetes Mellitus (LY2881835, LY2922083, and LY2922470). J Med Chem. 2016 Dec 22;59(24):10891-10916.

REF 20

Discovery of Potent and Orally Bioavailable Dihydropyrazole GPR40 Agonists. J Med Chem. 2018 Feb 8;61(3):681-694.

REF 21

CNX-011-67, a novel GPR40 agonist, enhances glucose responsiveness, insulin secretion and islet insulin content in n-STZ rats and in islets from type 2 diabetic patients. BMC Pharmacol Toxicol. 2014 Mar 25;15:19.

REF 22

Discovery of DS-1558: A Potent and Orally Bioavailable GPR40 Agonist. ACS Med Chem Lett. 2015 Jan 13;6(3):266-70.

REF 23

Free fatty acids regulate insulin secretion from pancreatic beta cells through GPR40. Nature. 2003 Mar 13;422(6928):173-6.

REF 24

Identification and pharmacological characterization of multiple allosteric binding sites on the free fatty acid 1 receptor. Mol Pharmacol. 2012 Nov;82(5):843-59.

REF 25

REF 26

Pharmacological regulation of insulin secretion in MIN6 cells through the fatty acid receptor GPR40: identification of agonist and antagonist small... Br J Pharmacol. 2006 Jul;148(5):619-28.

REF 27

A human cell surface receptor activated by free fatty acids and thiazolidinedione drugs. Biochem Biophys Res Commun. 2003 Feb 7;301(2):406-10.

REF 28

Selective small-molecule agonists of G protein-coupled receptor 40 promote glucose-dependent insulin secretion and reduce blood glucose in mice. Diabetes. 2008 Aug;57(8):2211-9.

REF 29

Discovery of potent and selective agonists for the free fatty acid receptor 1 (FFA(1)/GPR40), a potential target for the treatment of type II diabetes. J Med Chem. 2008 Nov 27;51(22):7061-4.

REF 30

Discovery of TUG-770: A Highly Potent Free Fatty Acid Receptor 1 (FFA1/GPR40) Agonist for Treatment of Type 2 Diabetes. ACS Med Chem Lett. 2013 May 9;4(5):441-445.

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