Ac-Thr-Ile-Nle-psi(CH2NH)Nle-Gln-Arg-NH2
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Ac-Thr-Ile-Nle-psi(CH2NH)Nle-Gln-Arg-NH2

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Ac-Thr-Ile-Nle-psi(CH2NH)Nle-Gln-Arg-NH2 is an HIV-1 protease inhibitor whose sequence is derived from the cleavage site of the viral gag-pol poly-protein. Electron density studies have shown that this inhibitor binds to the active site of the HIV-1 protease.

Category
Peptide Inhibitors
Catalog number
BAT-015166
CAS number
128657-47-6
Molecular Formula
C35H67N11O8
Molecular Weight
769.98
Ac-Thr-Ile-Nle-psi(CH2NH)Nle-Gln-Arg-NH2
IUPAC Name
(2S)-2-[[(2S)-2-[[(2S)-2-[[(2S,3S)-2-[[(2S,3R)-2-acetamido-3-hydroxybutanoyl]amino]-3-methylpentanoyl]amino]hexyl]amino]hexanoyl]amino]-N-[(2S)-1-amino-5-(diaminomethylideneamino)-1-oxopentan-2-yl]pentanediamide
Synonyms
MVT-101; N-acetyl-Thr-Ile-Nle-psi(CH2-NH)-Nle-Gln-Arg-amide; N-acetyl-threonyl-isoleucyl-norleucyl-psi(CH2-NH)-norleucyl-glutaminyl-argininamide; N-{(2S)-2-[(N-Acetyl-L-threonyl-L-isoleucyl)amino]hexyl}-L-norleucyl-L-glutaminyl-L-argininamide; L-Argininamide, N-[(2S)-2-[[(2S,3S)-2-[[(2S,3R)-2-(acetylamino)-3-hydroxy-1-oxobutyl]amino]-3-methyl-1-oxopentyl]amino]hexyl]-L-norleucyl-L-glutaminyl-
Appearance
White Powder
Purity
95%
Density
1.31±0.1 g/cm3
Sequence
Ac-TI-Nle-psi(CH2NH)Nle-QR-NH2
Storage
Store at -20°C
InChI
InChI=1S/C35H67N11O8/c1-7-10-13-23(43-33(53)28(20(4)9-3)46-34(54)29(21(5)47)42-22(6)48)19-41-25(14-11-8-2)31(51)45-26(16-17-27(36)49)32(52)44-24(30(37)50)15-12-18-40-35(38)39/h20-21,23-26,28-29,41,47H,7-19H2,1-6H3,(H2,36,49)(H2,37,50)(H,42,48)(H,43,53)(H,44,52)(H,45,51)(H,46,54)(H4,38,39,40)/t20-,21+,23-,24-,25-,26-,28-,29-/m0/s1
InChI Key
MQPXOVRKKPPKFZ-QYKDHROSSA-N
Canonical SMILES
CCCCC(CNC(CCCC)C(=O)NC(CCC(=O)N)C(=O)NC(CCCN=C(N)N)C(=O)N)NC(=O)C(C(C)CC)NC(=O)C(C(C)O)NC(=O)C
1. Influence of N-Base and O-Base Hybridization on Triel Bonds
Xin Yang,Qingqing Yang,Xin Yao ACS Omega . 2020 Aug 14;5(33):21300-21308. doi: 10.1021/acsomega.0c03394.
The complexes of TrR3(Tr = B and Al; R = H, F, Cl, and Br) with three N-bases (NH3, CH2NH, and HCN) and three O-bases (CH3OH, H2CO, and CO) are utilized to explore the hybridization effect of N and O atoms on the strength, properties, and nature of the triel bond. The sp-hybridized O and N atoms form the weakest triel bond, followed by the sp2-hybridized O atom or the sp3-hybridized N atom, and the sp3-hybridized O atom or the sp2-hybridized N atom engages in the strongest triel bond. The hybridization effect is also related to the substituent of TrR3. Most complexes are dominated by electrostatic, with increasing polarization contribution from sp to sp2to sp3. Although the CO oxygen engages in a weaker triel bond, its carbon atom is a better electron donor and the interaction energy even amounts to -37 kcal/mol in the BH3complex.
2. 2-[(Pyrimidin-2-yl-amino)-meth-yl]phenol
Jing Xu,Shan Gao,Seik Weng Ng Acta Crystallogr Sect E Struct Rep Online . 2011 Dec 1;67(Pt 12):o3258. doi: 10.1107/S1600536811046848.
In the title compound, C(11)H(11)N(3)O, the aromatic rings at either ends of the -CH(2)-NH- link are twisted by 72.58 (8)°; the hy-droxy substituent is a hydrogen-bond donor to an N atom of the pyrimidine ring. The other N atom of the pyrimidine ring is a hydrogen-bond acceptor to the amino group of an inversion-related mol-ecule.
3. 2-[(Pyridin-3-yl-amino)-meth-yl]phenol
Jing Xu,Shan Gao,Seik Weng Ng Acta Crystallogr Sect E Struct Rep Online . 2011 Dec 1;67(Pt 12):o3259. doi: 10.1107/S160053681104685X.
In the title compound, C(12)H(12)N(2)O, the aromatic rings at either ends of the -CH(2)-NH- link are twisted by 68.79 (7)°. In the crystal, the hy-droxy substituent is a hydrogen-bond donor to the N atom of the pyridine ring of an adjacent mol-ecule, and the hydrogen bond generates a chain along the b axis; it is also a hydrogen-bond acceptor to the amino group of another adjacent mol-ecule. The two hydrogen bonds lead to the formation of a layer structure.
4. Deep Learning for Nonadiabatic Excited-State Dynamics
Ganglong Cui,Pavlo O Dral,Xiang-Yang Liu,Wen-Kai Chen,Wei-Hai Fang J Phys Chem Lett . 2018 Dec 6;9(23):6702-6708. doi: 10.1021/acs.jpclett.8b03026.
In this work we show that deep learning (DL) can be used for exploring complex and highly nonlinear multistate potential energy surfaces of polyatomic molecules and related nonadiabatic dynamics. Our DL is based on deep neural networks (DNNs), which are used as accurate representations of the CASSCF ground- and excited-state potential energy surfaces (PESs) of CH2NH. After geometries near conical intersection are included in the training set, the DNN models accurately reproduce excited-state topological structures; photoisomerization paths; and, importantly, conical intersections. We have also demonstrated that the results from nonadiabatic dynamics run with the DNN models are very close to those from the dynamics run with the pure ab initio method. The present work should encourage further studies of using machine learning methods to explore excited-state potential energy surfaces and nonadiabatic dynamics of polyatomic molecules.
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