PMID- 22657398
OWN - NLM
STAT- MEDLINE
DCOM- 20140317
LR  - 20181202
IS  - 1549-960X (Electronic)
IS  - 1549-9596 (Linking)
VI  - 52
IP  - 7
DP  - 2012 Jul 23
TI  - Four-dimensional structure-activity relationship model to predict HIV-1 integrase 
      strand transfer inhibition using LQTA-QSAR methodology.
PG  - 1722-32
LID - 10.1021/ci300039a [doi]
AB  - Despite highly active antiretroviral therapy (HAART) implementation, there is a 
      continuous need to search for new anti-HIV agents. HIV-1 integrase (HIV-1 IN) is 
      a recently validated biological target for AIDS therapy. In this work, a 
      four-dimensional quantitative structure-activity relationship (4D-QSAR) study 
      using the new methodology named LQTA-QSAR approach with a training set of 85 
      HIV-1 IN strand transfer inhibitors (INSTI), containing the beta-diketo acid (DKA) 
      substructure, was carried out. The GROMACS molecular dynamic package was used to 
      obtain a conformational ensemble profile (CEP) and LQTA-QSAR was employed to 
      calculate Coulomb and Lennard-Jones potentials and to generate the field 
      descriptors. The partial least-squares (PLS) regression model using 14 field 
      descriptors and 8 latent variables (LV) yielded satisfactory statistics (R2= 
      0.897, SEC = 0.270, and F = 72.827), good performance in internal (QLOO2 = 0.842 
      and SEV = 0.314) and external prediction (Rpred2 = 0.839, SEP = 0.384, AREpred = 
      4.942%, k = 0.981, k' = 1.016, and |R02 - R0'2 = 0.0257). The QSAR model was 
      shown to be robust (leave-N-out cross validation; average QLNO2 = 0.834) and was 
      not built by chance (y-randomization test; R2 intercept = 0.109; Q2 intercept = 
      -0.398). Fair chemical interpretation of the model could be traced, including 
      descriptors related to interaction with the metallic cofactors and the 
      hydrophobic loop. The model obtained has a good potential for aid in the design 
      of new INSTI, and it is a successful example of application of LQTA-QSAR as an 
      useful tool to be used in computer-aided drug design (CADD).
FAU - de Melo, Eduardo B
AU  - de Melo EB
AD  - Theoretical Medicinal and Environmental Chemistry Laboratory (LQMAT), Department 
      of Pharmacy, Western Parana State University-Unioeste, 2069 Universitaria St, 
      Cascavel, PR 85819-110, Brazil.
FAU - Ferreira, Marcia M C
AU  - Ferreira MM
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20120621
PL  - United States
TA  - J Chem Inf Model
JT  - Journal of chemical information and modeling
JID - 101230060
RN  - 0 (Anti-HIV Agents)
RN  - EC 2.7.7.- (HIV Integrase)
RN  - YY6481J2FF (p31 integrase protein, Human immunodeficiency virus 1)
SB  - IM
MH  - Anti-HIV Agents/*chemistry/pharmacology
MH  - *Drug Design
MH  - Enzyme Activation/drug effects
MH  - HIV Integrase/*metabolism
MH  - HIV-1
MH  - *Models, Biological
MH  - Molecular Conformation
MH  - *Molecular Dynamics Simulation
MH  - Quantitative Structure-Activity Relationship
EDAT- 2012/06/05 06:00
MHDA- 2014/03/19 06:00
CRDT- 2012/06/05 06:00
PHST- 2012/06/05 06:00 [entrez]
PHST- 2012/06/05 06:00 [pubmed]
PHST- 2014/03/19 06:00 [medline]
AID - 10.1021/ci300039a [doi]
PST - ppublish
SO  - J Chem Inf Model. 2012 Jul 23;52(7):1722-32. doi: 10.1021/ci300039a. Epub 2012 
      Jun 21.