PMID- 19182860
OWN - NLM
STAT- MEDLINE
DCOM- 20090529
LR  - 20191210
IS  - 1549-9596 (Print)
IS  - 1549-9596 (Linking)
VI  - 49
IP  - 2
DP  - 2009 Feb
TI  - Novel inhibitors of human histone deacetylase (HDAC) identified by QSAR modeling 
      of known inhibitors, virtual screening, and experimental validation.
PG  - 461-76
LID - 10.1021/ci800366f [doi]
AB  - Inhibitors of histone deacetylases (HDACIs) have emerged as a new class of drugs 
      for the treatment of human cancers and other diseases because of their effects on 
      cell growth, differentiation, and apoptosis. In this study we have developed 
      several quantitative structure-activity relationship (QSAR) models for 59 
      chemically diverse histone deacetylase class 1 (HDAC1) inhibitors. The variable 
      selection k nearest neighbor (kNN) and support vector machines (SVM) QSAR 
      modeling approaches using both MolconnZ and MOE chemical descriptors generated 
      from two-dimensional rendering of compounds as chemical graphs have been 
      employed. We have relied on a rigorous model development workflow including the 
      division of the data set into training, test, and external sets and extensive 
      internal and external validation. Highly predictive QSAR models were generated 
      with leave-one-out cross-validated (LOO-CV) q2 and external R2 values as high as 
      0.80 and 0.87, respectively, using the kNN/MolconnZ approach and 0.93 and 0.87, 
      respectively, using the SVM/MolconnZ approach. All validated QSAR models were 
      employed concurrently for virtual screening (VS) of an in-house compound 
      collection including 9.5 million molecules compiled from the ZINC7.0 database, 
      the World Drug Index (WDI) database, the ASINEX Synergy libraries, and other 
      commercial databases. VS resulted in 45 structurally unique consensus hits that 
      were considered novel putative HDAC1 inhibitors. These computational hits had 
      several novel structural features that were not present in the original data set. 
      Four computational hits with novel scaffolds were tested experimentally, and 
      three of them were confirmed active against HDAC1, with IC50 values for the most 
      active compound of 1.00 microM. The fourth compound was later identified to be a 
      selective inhibitor of HDAC6, a Class II HDAC. Moreover, two of the confirmed 
      hits are marketed drugs, which could potentially facilitate their further 
      development as anticancer agents. This study illustrates the power of the 
      combined QSAR-VS method as a general approach for the effective identification of 
      structurally novel bioactive compounds.
FAU - Tang, Hao
AU  - Tang H
AD  - Lab. for Molecular Modeling, and Carolina Exploratory Center for Cheminformatics 
      Res., Div. of Medicinal Chemistry and Natural Products, School of Pharmacy, UNC, 
      Chapel Hill, North Carolina 27599-7360, USA.
FAU - Wang, Xiang S
AU  - Wang XS
FAU - Huang, Xi-Ping
AU  - Huang XP
FAU - Roth, Bryan L
AU  - Roth BL
FAU - Butler, Kyle V
AU  - Butler KV
FAU - Kozikowski, Alan P
AU  - Kozikowski AP
FAU - Jung, Mira
AU  - Jung M
FAU - Tropsha, Alexander
AU  - Tropsha A
LA  - eng
GR  - GM066940/GM/NIGMS NIH HHS/United States
GR  - HG003898/HG/NHGRI NIH HHS/United States
GR  - HHSN-271-2008-00025-C/HS/AHRQ HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
PT  - Validation Study
PL  - United States
TA  - J Chem Inf Model
JT  - Journal of chemical information and modeling
JID - 101230060
RN  - 0 (Enzyme Inhibitors)
RN  - 0 (Histone Deacetylase Inhibitors)
SB  - IM
MH  - Enzyme Inhibitors/*chemistry/*pharmacology
MH  - *Histone Deacetylase Inhibitors
MH  - Humans
MH  - Models, Molecular
MH  - Quantitative Structure-Activity Relationship
EDAT- 2009/02/03 09:00
MHDA- 2009/05/30 09:00
CRDT- 2009/02/03 09:00
PHST- 2009/02/03 09:00 [entrez]
PHST- 2009/02/03 09:00 [pubmed]
PHST- 2009/05/30 09:00 [medline]
AID - 10.1021/ci800366f [pii]
AID - 10.1021/ci800366f [doi]
PST - ppublish
SO  - J Chem Inf Model. 2009 Feb;49(2):461-76. doi: 10.1021/ci800366f.