ID: ALA3351133

Max Phase: Preclinical

Molecular Formula: C8H15NO6S

Molecular Weight: 253.28

Molecule Type: Small molecule

Representations

Canonical SMILES:  NC(=O)CS[C@H]1O[C@H](CO)[C@@H](O)[C@H](O)[C@H]1O

Standard InChI:  InChI=1S/C8H15NO6S/c9-4(11)2-16-8-7(14)6(13)5(12)3(1-10)15-8/h3,5-8,10,12-14H,1-2H2,(H2,9,11)/t3-,5-,6+,7-,8-/m1/s1

Standard InChI Key:  TYOVDLFVVPOLJR-RHROMQPHSA-N

Molecule Features

Natural Product: No

Oral: No

Chemical Probe: No

Parenteral: No

Molecule Type: Small molecule

Topical: No

First In Class: No

Black Box: No

Chirality: No

Availability: No

Prodrug: No

Properties

Molecular Weight: 253.28

Molecular Weight (Monoisotopic): 253.0620

AlogP: -3.00

#Rotatable Bonds: 4

Polar Surface Area: 133.24

Molecular Species: NEUTRAL

HBA: 7

HBD: 5

#RO5 Violations: 0

HBA (Lipinski): 7

HBD (Lipinski): 6

#RO5 Violations (Lipinski): 1

CX Acidic pKa: 12.48

CX Basic pKa:

CX LogP: -3.22

CX LogD: -3.22

Aromatic Rings: 0

Heavy Atoms: 16

QED Weighted: 0.36

Np Likeness Score: 0.93

References

1. Pastor M, Cruciani G, Clementi S..  (1997)  Smart region definition: a new way to improve the predictive ability and interpretability of three-dimensional quantitative structure-activity relationships.,  40  (10): [PMID:9154968] [10.1021/jm9608016]

2. Cruciani G, Watson KA..  (1994)  Comparative molecular field analysis using GRID force-field and GOLPE variable selection methods in a study of inhibitors of glycogen phosphorylase b.,  37  (16): [PMID:8057302] [10.1021/jm00042a012]

3. Pan D, Liu J, Senese C, Hopfinger AJ, Tseng Y..  (2004)  Characterization of a ligand-receptor binding event using receptor-dependent four-dimensional quantitative structure-activity relationship analysis.,  47  (12): [PMID:15163189] [10.1021/jm030586a]

4. Pastor M, Cruciani G, Watson KA..  (1997)  A strategy for the incorporation of water molecules present in a ligand binding site into a three-dimensional quantitative structure--activity relationship analysis.,  40  (25): [PMID:9406599] [10.1021/jm970273d]

5. Gohlke H, Klebe G..  (2002)  DrugScore meets CoMFA: adaptation of fields for molecular comparison (AFMoC) or how to tailor knowledge-based pair-potentials to a particular protein.,  45  (19): [PMID:12213058] [10.1021/jm020808p]

6. So SS, Karplus M..  (1997)  Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 2. Applications.,  40  (26): [PMID:9435905] [10.1021/jm970488n]

7. Uddin R, Saeed M, Ul-Haq Z.  (2013)  Molecular docking- and genetic algorithm-based approaches to produce robust 3D-QSAR models,  [10.1007/s00044-013-0812-0]

Source

Source(1):

• Scientific Literature