http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Arooj, Mahreen,Thangapandian, Sundarapandian,John, Shalini,Hwang, Swan,Park, Jong Keun,Lee, Keun Woo Molecular Diversity Preservation International (MD 2011 INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES Vol.12 No.12
<P>Human chymase is a very important target for the treatment of cardiovascular diseases. Using a series of theoretical methods like pharmacophore modeling, database screening, molecular docking and Density Functional Theory (DFT) calculations, an investigation for identification of novel chymase inhibitors, and to specify the key factors crucial for the binding and interaction between chymase and inhibitors is performed. A highly correlating (<I>r</I> = 0.942) pharmacophore model (Hypo1) with two hydrogen bond acceptors, and three hydrophobic aromatic features is generated. After successfully validating “Hypo1”, it is further applied in database screening. Hit compounds are subjected to various drug-like filtrations and molecular docking studies. Finally, three structurally diverse compounds with high <I>GOLD</I> fitness scores and interactions with key active site amino acids are identified as potent chymase hits. Moreover, DFT study is performed which confirms very clear trends between electronic properties and inhibitory activity (IC<SUB>50</SUB>) data thus successfully validating “Hypo1” by DFT method. Therefore, this research exertion can be helpful in the development of new potent hits for chymase. In addition, the combinational use of docking, orbital energies and molecular electrostatic potential analysis is also demonstrated as a good endeavor to gain an insight into the interaction between chymase and inhibitors.</P>
S· · ·S Interaction in Pd(II) Complexes of Bis(phosphino)oligothiophene with Various Substituents
Arooj, Mahreen,Kim, Kyeong-Hyeon,Kim, Dong-Hwan,Kim, Byung-Sun,Park, Gye-Young,Jeong, Si-Hwa,Shin, Sung-Chul,Park, Jong-Keun Korean Chemical Society 2009 Bulletin of the Korean Chemical Society Vol.30 No.12
Arooj, Mahreen,Thangapandian, Sundarapandian,John, Shalini,Hwang, Swan,Park, Jong K.,Lee, Keun W. Blackwell Publishing Ltd 2012 Chemical biology & drug design Vol.80 No.6
<P>To provide a new idea for drug design, a computational investigation is performed on chymase and its novel 1,4‐diazepane‐2,5‐diones inhibitors that explores the crucial molecular features contributing to binding specificity. Molecular docking studies of inhibitors within the active site of chymase were carried out to rationalize the inhibitory properties of these compounds and understand their inhibition mechanism. The density functional theory method was used to optimize molecular structures with the subsequent analysis of highest occupied molecular orbital, lowest unoccupied molecular orbital, and molecular electrostatic potential maps, which revealed that negative potentials near 1,4‐diazepane‐2,5‐diones ring are essential for effective binding of inhibitors at active site of enzyme. The Bayesian model with receiver operating curve statistic of 0.82 also identified arylsulfonyl and aminocarbonyl as the molecular features favoring and not favoring inhibition of chymase, respectively. Moreover, genetic function approximation was applied to construct 3D quantitative structure–activity relationships models. Two models (genetic function approximation model 1 <I>r</I><SUP>2</SUP> = 0.812 and genetic function approximation model 2 <I>r</I><SUP>2</SUP> = 0.783) performed better in terms of correlation coefficients and cross‐validation analysis. In general, this study is used as example to illustrate how combinational use of 2D/3D quantitative structure–activity relationships modeling techniques, molecular docking, frontier molecular orbital density fields (highest occupied molecular orbital and lowest unoccupied molecular orbital), and molecular electrostatic potential analysis may be useful to gain an insight into the binding mechanism between enzyme and its inhibitors.</P>
John, Shalini,Thangapandian, Sundarapandian,Arooj, Mahreen,Hong, Jong Chan,Kim, Kwang Dong,Lee, Keun Woo BioMed Central 2011 BMC bioinformatics Vol.12 No.14
<P><B>Background</B></P><P>Renin has become an attractive target in controlling hypertension because of the high specificity towards its only substrate, angiotensinogen. The conversion of angiotensinogen to angiotensin I is the first and rate-limiting step of renin-angiotensin system and thus designing inhibitors to block this step is focused in this study.</P><P><B>Methods</B></P><P>Ligand-based quantitative pharmacophore modeling methodology was used in identifying the important molecular chemical features present in the set of already known active compounds and the missing features from the set of inactive compounds. A training set containing 18 compounds including active and inactive compounds with a substantial degree of diversity was used in developing the pharmacophore models. A test set containing 93 compounds, Fischer randomization, and leave-one-out methods were used in the validation of the pharmacophore model. Database screening was performed using the best pharmacophore model as a 3D structural query. Molecular docking and density functional theory calculations were used to select the hit compounds with strong molecular interactions and favorable electronic features.</P><P><B>Results</B></P><P>The best quantitative pharmacophore model selected was made of one hydrophobic, one hydrogen bond donor, and two hydrogen bond acceptor features with high a correlation value of 0.944. Upon validation using an external test set of 93 compounds, Fischer randomization, and leave-one-out methods, this model was used in database screening to identify chemical compounds containing the identified pharmacophoric features. Molecular docking and density functional theory studies have confirmed that the identified hits possess the essential binding characteristics and electronic properties of potent inhibitors.</P><P><B>Conclusion</B></P><P>A quantitative pharmacophore model of predictive ability was developed with essential molecular features of a potent renin inhibitor. Using this pharmacophore model, two potential inhibitory leads were identified to be used in designing novel and future renin inhibitors as antihypertensive drugs.</P>