Target Information

Target General Information

Target ID

T09544 (Former ID: TTDI02573)

Target Name

Galectin-1 (LGALS1)

Synonyms

SLac lectin 1; S-Lac lectin 1; Putative MAPKactivating protein PM12; Putative MAPK-activating protein PM12; Lectin galactosidebinding soluble 1; Lectin galactoside-binding soluble 1; Lactosebinding lectin 1; Lactose-binding lectin 1; HPL; HLBP14; HBL; Galaptin; Gal1; Gal-1; Betagalactosidebinding lectin L14I; Beta-galactoside-binding lectin L-14-I; 14 kDa lectin; 14 kDa lamininbinding protein; 14 kDa laminin-binding protein

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Gene Name

LGALS1

Target Type

Patented-recorded target

[1]

Function

Plays a role in regulating apoptosis, cell proliferation and cell differentiation. Inhibits CD45 protein phosphatase activity and therefore the dephosphorylation of Lyn kinase. Strong inducer of T-cell apoptosis. Lectin that binds beta-galactoside and a wide array of complex carbohydrates.

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UniProt ID

LEG1_HUMAN

Sequence

MACGLVASNLNLKPGECLRVRGEVAPDAKSFVLNLGKDSNNLCLHFNPRFNAHGDANTIV
CNSKDGGAWGTEQREAVFPFQPGSVAEVCITFDQANLTVKLPDGYEFKFPNRLNLEAINY
MAADGDFKIKCVAFD

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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: Cysteine Sulfenic Acid

Ligand Info

Structure Description

X-RAY CRYSTAL STRUCTURE OF C2S HUMAN GALECTIN-1 COMPLEXED WITH GALACTOSE

PDB:1W6M

Method

X-ray diffraction

Resolution

2.30 Å

Mutation

Yes

[3]

PDB Sequence

ASGLVASNLN

¹⁰¹⁰

LKPGELRVRG

¹⁰²¹

EVAPDAKSFV

¹⁰³¹

LNLGKDSNNL

¹⁰⁴¹

CLHFNPRFNA

¹⁰⁵¹

HGDANTIVCN

¹⁰⁶¹

SKDDGAWGTE

¹⁰⁷¹

QREAVFPFQP

¹⁰⁸¹

GSVAEVCITF

¹⁰⁹¹

DQANLTVKLP

¹¹⁰¹

DGYEFKFPNR

¹¹¹¹

LNLEAINYMA

¹¹²¹

ADGDFKIKCV

¹¹³¹

AFD

Residue

Distance (Å)

LEU1011

4.429

GLY1014

3.960

GLU1015

1.329

LEU1017

1.327

ARG1018

3.945

CYS1088

3.756

Residue

Distance (Å)

ILE1089

3.521

THR1090

3.628

ALA1132

3.833

PHE1133

3.709

ASP1134

3.174

Ligand Name: S,S-(2-Hydroxyethyl)Thiocysteine

Ligand Info

Structure Description

Galectin-1 in Complex with Ligand JB60

PDB:5MWX

Method

X-ray diffraction

Resolution

1.29 Å

Mutation

[4]

PDB Sequence

CGLVASNLNL

¹¹

KPGELRVRGE

²²

VAPDAKSFVL

³²

NLGKDSNNLC

⁴²

LHFNPRFNAH

⁵²

GDANTIVCNS

⁶²

KDGGAWGTEQ

⁷²

REAVFPFQPG

⁸²

SVAEVITFDQ

⁹³

ANLTVKLPDG

¹⁰³

YEFKFPNRLN

¹¹³

LEAINYMAAD

¹²³

GDFKIKVAFD

¹³⁴

Residue

Distance (Å)

LEU11

3.140

GLY14

3.996

GLU15

1.334

LEU17

1.332

ARG18

2.465

VAL19

2.665

ARG20

2.022

GLY21

4.423

GLU86

2.407

VAL87

1.318

ILE89

1.316

THR90

2.176

Residue

Distance (Å)

THR97

3.635

VAL98

2.787

LYS99

1.853

LEU100

3.182

PRO101

2.584

ASP102

4.837

ILE128

2.939

LYS129

1.314

VAL131

1.343

ALA132

3.324

PHE133

3.125

ASP134

1.986

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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). 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 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).

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

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.

Degree	1	Degree centrality	1.07E-04	Betweenness centrality	0.00E+00
Closeness centrality	2.10E-01	Radiality	1.37E+01	Clustering coefficient	0.00E+00
Neighborhood connectivity	1.07E+02	Topological coefficient	1.00E+00	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 Regulators

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Target-regulating microRNAs

Target-regulating microRNAs Info

Target-interacting Proteins

Target-interacting Proteins Info

References

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REF 1

Human Galectin-1 and its inhibitors: Privileged target for cancer and HIV. Mini Rev Med Chem. 2019 Mar 4.

REF 2

Galactoside inhibitors of galectins. US8703720.

REF 3

Growth-regulatory human galectin-1: crystallographic characterisation of the structural changes induced by single-site mutations and their impact on the thermodynamics of ligand binding. J Mol Biol. 2004 Oct 29;343(4):957-70.

REF 4

Galectin-1 in Complex with Ligand JB60

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