Open AccessApplication of in Silico Fragment and Data Analysis (ISIDA) Approaches for the Design of Novel Hydroxamic Acids Targeting HDAC2
Author(s) -
Hai Pham-The,
Dao Thi Kim Oanh,
Doan Viet Nga,
Bùi Thanh Tùng,
Lê Thị Thu Hương
Publication year - 2017
Publication title -
tạp chí khoa học đại học quốc gia hà nội: khoa học y dược (vnu journal of science: medical and pharmaceutical sciences)
Language(s) - English
Resource type - Journals
eISSN - 2615-9309
pISSN - 2588-1132
DOI - 10.25073/2588-1132/vnumps.4073
Subject(s) - in silico , hydroxamic acid , quantitative structure–activity relationship , histone deacetylase , computational biology , druggability , histone deacetylase 2 , chemistry , combinatorial chemistry , stereochemistry , biology , biochemistry , histone , dna , gene
Finding a new treatment for cancer is one of the most interested fields for pharmaceutical research worldwide. Enzyme histone deacetylase 2 (HDAC2), being a member of HDAC class I appear to be an important druggable target.This study focused on rational design of novel HDAC2 inhibitorsusing molecular descriptors derived from ISIDA fragmentor methodology. Quantitative structure-activity relationship was explored to develop mathematical models able to predict HDAC2 inhibitory bioactivity of acid hydroxamic derivatives. Multiple linear regression (MLR) algorithm implemented in STATISTICA 8.0 was used for model development. Consequently 3 QSAR models were obtained showing acceptable performance r2> 0.70 for further use. Based on these models 10 important fragments attributing to better inhibitory potency were identified. Finally several novel hydroxamic derivatives were designed and screened for HDAC2 inhibitory activity.