3D-QSAR Studies of S-DABO Derivatives as Non-nucleoside HIV-1  Reverse Transcriptase Inhibitors

Background: S-dihydro-alkyloxy-benzyl-oxopyrimidines (S-DABOs) as non-nucleoside reverse transcriptase inhibitors have received considerable attention during the last decade due to their high potency against HIV-1. Methods: In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) of a series of 38 S-DABO analogues developed in our lab was studied using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). The Docking/MMFF94s computational protocol based on the co-crystallized complex (PDB ID: 1RT2) was used to determine the most probable binding mode and to obtain reliable conformations for molecular alignment. Statistically significant CoMFA (q2=0.766 and r2=0.949) and CoMSIA (q2=0.827 and r2=0.974) models were generated using the training set of 30 compounds on the basis of hybrid docking-based and ligand-based alignment. Results: The predictive ability of CoMFA and CoMSIA models was further validated using a test set of eight compounds with predictive r2 pred values of 0.843 and 0.723, respectively. Conclusion: The information obtained from the 3D contour maps can be used in designing new SDABO derivatives with improved HIV-1 inhibitory activity.

Download Full-text

Structural investigations of CXCR2 receptor antagonists by CoMFA, CoMSIA and flexible docking studies

Acta Pharmaceutica ◽

10.2478/v10007-012-0029-7 ◽

2012 ◽

Vol 62 (3) ◽

pp. 287-304 ◽

Cited By ~ 1

Author(s):

Shravan Kumar Gunda ◽

Rohith Kumar Anugolu ◽

Sri Ramya Tata ◽

Saikh Mahmood

Keyword(s):

Standard Error ◽

Three Dimensional ◽

3D Qsar ◽

Homology Model ◽

Qsar Model ◽

Quantitative Structure Activity Relationship ◽

Field Analysis ◽

Structural Investigations ◽

Qsar Analysis ◽

Qsar Studies

= Three-dimensional quantitative structure activity relationship (3D QSAR) analysis was carried out on a et of 56 N,N’-diarylsquaramides, N,N’-diarylureas and diaminocyclobutenediones in order to understand their antagonistic activities against CXCR2. The studies included comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Models with good predictive abilities were generated with CoMFA q2 0.709, r2 (non-cross-validated square of correlation coefficient) = 0.951, F value = 139.903, r2 bs = 0.978 with five components, standard error of estimate = 0.144 and the CoMSIA q2 = 0.592, r2 = 0.955, F value = 122.399, r2 bs = 0.973 with six components, standard error of estimate = 0.141. In addition, a homology model of CXCR2 was used for docking based alignment of the compounds. The most active compound then served as a template for alignment of the remaining structures. Further, mapping of contours onto the active site validated each other in terms of residues involved with reference to the respective contours. This integrated molecular docking based alignment followed by 3D QSAR studies provided a further insight to support the structure-based design of CXCR2 antagonistic agents with improved activity profiles. Furthermore, in silico screening was adapted to the QSAR model in order to predict the structures of new, potentially active compounds.

Download Full-text

QSAR Studies on Thiazole Derivatives as HCV NS5A Inhibitors via CoMFA and CoMSIA Methods

Letters in Drug Design & Discovery ◽

10.2174/1570180815666180702153529 ◽

2019 ◽

Vol 16 (4) ◽

pp. 453-460 ◽

Cited By ~ 1

Author(s):

Jiayu Li ◽

Wenyue Tian ◽

Diaohui Gao ◽

Yuying Li ◽

Yiqun Chang ◽

...

Keyword(s):

Nonstructural Protein ◽

External Validation ◽

Three Dimensional ◽

3D Qsar ◽

Quantitative Structure Activity Relationship ◽

Field Analysis ◽

Thiazole Derivatives ◽

Hydrogen Bond Acceptor ◽

Qsar Studies ◽

Comfa Model

Background: Hepatitis C Virus (HCV) infection is the major cause of hepatitis after transfusion. And HCV Nonstructural Protein 5A (NS5A) inhibitors have become a new hotspot in the study of HCV inhibitors due to their strong antiviral activity, rapid speed of viral removing and broad antiviral spectrum. Methods: Forty-five NS5A inhibitors were chosen to process three-dimensional quantitative structure- activity relationship (3D-QSAR) by using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set consisting of 30 compounds was applied to establish the models and a test set consisting of 15 compounds was applied to do the external validation. Results: The CoMFA model predicted a q2 value of 0.607 and an r2 value of 0.934. And the CoMSIA model predicted a q2 value of 0.516 and an r2 value of 0.960 established on the effects of steric, electrostatic, hydrophobic and hydrogen-bond acceptor. 0.713 and 0.939 were the predictive correlation co-efficients (r2pred) of CoMFA and CoMSIA models, respectively. Conclusion: These conclusions provide a theoretical basis for drug design and screening of HCV NS5A complex inhibitors.

Download Full-text

3D-QSAR AND DOCKING STUDIES OF NOVEL QUINAZOLINE ANALOGUES AS ORAL INHIBITORS TOWARDS AP-1 AND NF-κB

Journal of Theoretical and Computational Chemistry ◽

10.1142/s021963360900468x ◽

2009 ◽

Vol 08 (03) ◽

pp. 373-384

Author(s):

LI QIAN ◽

HAI-LIANG LU ◽

SI-YAN LIAO ◽

TI-FANG MIAO ◽

YONG SHEN ◽

...

Keyword(s):

Molecular Design ◽

Three Dimensional ◽

Predictive Ability ◽

3D Qsar ◽

Quantitative Structure Activity Relationship ◽

Docking Studies ◽

Field Analysis ◽

Activator Protein 1 ◽

Mechanism Analysis ◽

Qsar Study

Three-dimensional quantitative structure-activity relationship (3D-QSAR) and Docking studies of novel quinazoline analogues, which are oral potential inhibitors towards the activator protein-1 (AP-1) and nuclear factor kappa B (NF-κB), have been carried out. The 3D-QSAR study based on the comparative molecular field analysis (CoMFA) shows the established model having a significant statistical quality and excellent predictive ability, in which the correlation coefficient R is 0.972 and cross-validation coefficient q2 is 0.619. The Docking results also show a considerable correlation (or trend) between the energy scores and the corresponding experimental values for these compounds at some sites. Meanwhile, it is very interesting to find the binding sites just fall on the joint regions between AP-1 (or NF-κB) and DNA. It may be the reason that the quinazoline analogues have inhibition function because their existence on these joint regions can effectively prevent free AP-1 and NF-κB from binding to DNA. Based on the established 3D-QSAR and Docking analyses, six new compounds of quinazoline analogues with higher inhibitory activities were theoretically designed and presented. The above results can offer some valuable theoretical references for the pharmaceutical molecular design as well as the action mechanism analysis.

Download Full-text

3D QSAR Studies of DAMNI Analogs as Possible Non-nucleoside Reverse Transcriptase Inhibitors

E-Journal of Chemistry ◽

10.1155/2008/712930 ◽

2008 ◽

Vol 5 (s2) ◽

pp. 1103-1113

Author(s):

S. Ganguly ◽

V. Gopalakrishnan

Keyword(s):

Reverse Transcriptase ◽

Minimum Energy ◽

Correlation Coefficients ◽

Predictive Ability ◽

3D Qsar ◽

Field Analysis ◽

Template Molecule ◽

Qsar Studies ◽

Contour Maps ◽

Nucleoside Inhibitors

The non-nucleoside inhibitors ofHIV-1-reverse transcriptase (NNRTIs) are an important class of drugs employed in antiviral therapy. Recently, a novel family ofNNRTIs commonly referred to as 1-[2-diarylmethoxy] ethyl) 2-methyl-5-nitroimidazoles (DAMNI) derivatives have been discovered. The 3D-QSARstudies onDAMNIderivatives asNNRTIs was performed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The global minimum energy conformer of the template molecule 15, the most active molecule of the series, was obtained by simulated annealing method and used to build the structures of the molecules in the dataset. The combination of steric and electrostatic fields inCoMSIAgave the best results with cross-validated and conventional correlation coefficients of 0.654 and 0.928 respectively. The predictive ability ofCoMFAandCoMSIAwere determined using a test set of tenDAMNIderivatives giving predictive correlation coefficients of 0.92 and 0.98 respectively indicating good predictive power. Further, the robustness of the models was verified by bootstrapping analysis. The information obtained fromCoMFAandCoMSIA3Dcontour maps may be of utility in the design of more potentDAMNIanalogs asNNRTIs in future.

Download Full-text

2D and 3D QSAR studies of diarylpyrimidine HIV-1 reverse transcriptase inhibitors

Journal of Computer-Aided Molecular Design ◽

10.1007/s10822-008-9217-4 ◽

2008 ◽

Vol 22 (11) ◽

pp. 831-841 ◽

Cited By ~ 10

Author(s):

Joseph Rebehmed ◽

Florent Barbault ◽

Cátia Teixeira ◽

François Maurel

Keyword(s):

Reverse Transcriptase ◽

3D Qsar ◽

Reverse Transcriptase Inhibitors ◽

Qsar Studies ◽

2D And 3D ◽

Hiv 1

Download Full-text

Receptor Guided 3D-QSAR: A Useful Approach for Designing of IGF-1R Inhibitors

Journal of Biomedicine and Biotechnology ◽

10.1155/2008/837653 ◽

2008 ◽

Vol 2008 ◽

pp. 1-9 ◽

Cited By ~ 7

Author(s):

M. Muddassar ◽

F. A. Pasha ◽

H. W. Chung ◽

K. H. Yoo ◽

C. H. Oh ◽

...

Keyword(s):

Structural Information ◽

Three Dimensional ◽

3D Qsar ◽

Quantitative Structure Activity Relationship ◽

Field Analysis ◽

Comparative Molecular Field Analysis ◽

Qsar Studies ◽

Similarity Indices ◽

Qsar Models ◽

Derivatives Of

Research by other investigators has established that insulin-like growth factor‐1 receptor (IGF-1R) is a key oncological target, and that derivatives of 1, 3-disubstituted-imidazo[1,5-] pyrazine are potent IGF-1R inhibitors. In this paper, we report on our three-dimensional quantitative structure activity relationship (3D-QSAR) studies for this series of compounds. We validated the 3D-QSAR models by the comparison of two major alignment schemes, namely, ligand-based (LB) and receptor-guided (RG) alignment schemes. The latter scheme yielded better 3D-QSAR models for both comparative molecular field analysis (CoMFA) (, ) and comparative molecular similarity indices analysis (CoMSIA) (, ). We submit that this might arise from the more accurate inhibitor alignment that results from using the structural information of the active site. We conclude that the receptor-guided 3D-QSAR may be helpful to design more potent IGF-1R inhibitors, as well as to understand their binding affinity with the receptor.

Download Full-text

Three Dimensional Quantitative Structure Activity Relationship and Molecular Docking Studies of Flavonoids as Reverse Transcriptase Inhibitors

Asian Journal of Organic & Medicinal Chemistry ◽

10.14233/ajomc.2021.ajomc-p303 ◽

2021 ◽

Vol 6 (1) ◽

pp. 33-39

Author(s):

Bikash Kumar Sarkar ◽

Nabanita Giri

Keyword(s):

Correlation Coefficient ◽

Three Dimensional ◽

Predictive Ability ◽

Binding Pocket ◽

Quantitative Structure Activity Relationship ◽

Docking Studies ◽

Field Analysis ◽

Comfa Model ◽

Bonding Interaction ◽

Hiv 1

A set of 29 flavonoid molecules are used to generate comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. The best CoMFA model showed a cross-validated correlation coefficient (q2) = 0.762, noncross- validated correlation coefficient (r2) = 0.939, standard error of estimate (S) = 0.038 and F = 396. And that for CoMSIA model were q2 = 0.758, r2 = 0.957, S = 0.063 and F = 236. The models show a high predictive ability, validated by 11 favonoid molecules. The docking studies shows the hydrogen bonding interaction is mostly responsible for binding of the flavonoids molecules in the binding pocket of HIV 1-RT protein (3HVT.pdb).

Download Full-text