Docking and 3D QSAR Studies on p38α MAP Kinase Inhibitors

The p38 signaling cascade has emerged as an attractive target for the design of novel chemotherapeutic agents for the treatment of inflammatory diseases. Three dimensional quantitative structure- activity relationship (3D- QSAR) studies were performed on a series of 25, 2-aminothiazole analogs as inhibitors of p38α mitogen activated protein (MAP) kinase. The docking results provided a reliable conformational alignment scheme for the 3D-QSAR model. The 3D-QSAR model showed very good statistical results namely q2, r2and r2predvalues for both comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The CoMFA and CoMSIA models & docking results provided the most significant correlation of steric, electrostatic, hydrophobic,H-bond donor,H-bond acceptor fields with biological activities and the provided values were in good agreement with the experimental results. The information rendered from molecular modeling studies gave valuable clues to optimize the lead and design new potential inhibitors.

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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.

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THREE-DIMENSIONAL QSAR MODELING BENZIMIDAZOLE ANALOGUES USING THE K-NEAREST NEIGHBOR METHOD

INDIAN DRUGS ◽

10.53879/id.56.12.11234 ◽

2019 ◽

Vol 56 (12) ◽

pp. 62-67

Author(s):

M. C Sharma ◽

◽

D. V. Kohli

Keyword(s):

Nearest Neighbor ◽

Three Dimensional ◽

Antihypertensive Agents ◽

3D Qsar ◽

Good Alternative ◽

Qsar Model ◽

Field Analysis ◽

K Nearest Neighbor ◽

Qsar Modeling ◽

Qsar Studies

We undertook the three-dimensional (3D) QSAR studies of a series of benzimidazole analogues to elucidate the structural properties required for angiotensin II. The 3D-QSAR studies were performed using the stepwise, simulated annealing (SA) and genetic algorithm (GA) selection k-nearest neighbor molecular field analysis approach; a leave-one-out cross-validated correlation coefficient q2 = 0.8216 and a pred_r2 = 0.7852 were obtained. The 3D QSAR model is expected to provide a good alternative to predict the biological activity prior to synthesis as antihypertensive agents.

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Molecular Docking and 3D-QSAR Studies of 4-Phenylpiperidine Derivatives as μ-Opioid Agonists

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.361-363.263 ◽

2011 ◽

Vol 361-363 ◽

pp. 263-267 ◽

Cited By ~ 1

Author(s):

Ming Liu ◽

Wen Xiang Hu ◽

Xiao Li Liu

Keyword(s):

Electrostatic Interactions ◽

Biological Activities ◽

3D Qsar ◽

Qsar Model ◽

Field Analysis ◽

Qsar Studies ◽

Chemical Structures ◽

Opioid Agonists ◽

Qsar Models ◽

Leave One Out

A predictive 3D-QSAR model which correlates the biological activities with the chemical structures of a series of 4-phenylpiperidine derivatives as μ opioid agonists was developed by means of comparative molecular field analysis (CoMFA). The stabilities of the 3D-QSAR models were verified by the leave-one-out cross-validation method. Moreover, the predictive capabilities of the models were validated by an external test set. Best predictions were obtained with CoMFA standard model(q2=0.504, N=6, r2=0.968) which revealed how steric and electrostatic interactions contribute to agonists bioactivities, and provided us with important information to understand the interaction of agonists and μ opioid receptor .

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

Letters in Drug Design & Discovery ◽

10.2174/1570180815666180810112321 ◽

2019 ◽

Vol 16 (8) ◽

pp. 868-881

Author(s):

Yueping Wang ◽

Jie Chang ◽

Jiangyuan Wang ◽

Peng Zhong ◽

Yufang Zhang ◽

...

Keyword(s):

Reverse Transcriptase ◽

Three Dimensional ◽

Predictive Ability ◽

3D Qsar ◽

Binding Mode ◽

Quantitative Structure Activity Relationship ◽

Field Analysis ◽

Reverse Transcriptase Inhibitors ◽

Qsar Studies ◽

Hiv 1

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.

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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.

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Virtual Screening, Biological Evaluation, and 3D-QSAR Studies of New HIV-1 Entry Inhibitors That Function via the CD4 Primary Receptor

Molecules ◽

10.3390/molecules23113036 ◽

2018 ◽

Vol 23 (11) ◽

pp. 3036 ◽

Cited By ~ 5

Author(s):

Chaozai Zhang ◽

Huijun Zhang ◽

Lina S. Huang ◽

Siyu Zhu ◽

Yan Xu ◽

...

Keyword(s):

Biological Activities ◽

Similarity Index ◽

3D Qsar ◽

Biological Evaluation ◽

Rational Drug Design ◽

Field Analysis ◽

Qsar Studies ◽

Entry Inhibitors ◽

Primary Receptor ◽

Hiv 1

Human immunodeficiency virus type 1 (HIV-1) is responsible for the majority of HIV infections worldwide, and we still lack a cure for this infection. Blocking the interaction of HIV-1 and its primary receptor CD4 is one strategy for identifying new anti-HIV-1 entry inhibitors. Here we report the discovery of a novel ligand that can inhibit HIV-1 entry and infection via CD4. Biological and computational analyses of this inhibitor and its analogs, using bioactivity evaluation, Rule of Five (RO5), comparative molecular field analysis (CoMFA)/comparative molecular similarity index analysis (CoMSIA) models, and three-dimensional quantitative structure-activity relationship (3D-QSAR), singled out compound 3 as a promising lead molecule for the further development of therapeutics targeting HIV-1 entry. Our study demonstrates an effective approach for employing structure-based, rational drug design techniques to identify novel antiviral compounds with interesting biological activities.

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QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP ANALYSIS OF NOVEL PYRAZOLINE DERIVATIVES USING K NEAREST NEIGHBOUR MOLECULAR FIELD ANALYSIS METHOD

International Journal of Pharmacy and Pharmaceutical Sciences ◽

10.22159/ijpps.2017v9i12.19401 ◽

2017 ◽

Vol 9 (12) ◽

pp. 87

Author(s):

Deepali M. Jagdale ◽

Ramaa C. S.

Keyword(s):

Three Dimensional ◽

3D Qsar ◽

Qsar Model ◽

Quantitative Structure Activity Relationship ◽

Field Analysis ◽

Quantitative Structure ◽

Relationship Analysis ◽

Structure Activity ◽

Novel Approach ◽

Vlife Mds

Objective: Malonyl CoA decarboxylase (MCD) enzyme plays important role in fatty acid and glucose oxidation. Inhibition of MCD might turn to a novel approach to treat ischemia. The main objective of this research article was to develop a novel pharmacophore for enhanced activity.Methods: Three-dimensional quantitative structure-activity relationships (3D-QSAR) was performed for pyrazoline derivatives as MCD inhibitors using VLife MDS 4.6 software. The QSAR model was developed using the stepwise 3D-QSAR kNN-MFA method.Results: The statistical results generated from kNN-MFA method indicated the significance and requirements for better MCD inhibitory activity. The information rendered by 3D-QSAR model may render to better understanding and designing of novel MCD inhibitors.Conclusion: 3D-QSAR is an important tool in understanding the structural requirements for the design of novel and potent MCD inhibitors. It can be employed to design new drug discovery.

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CoMFA and CoMSIA Studies on Inhibitors of HIV-1 Integrase - Bicyclic Pyrimidinones

E-Journal of Chemistry ◽

10.1155/2010/717865 ◽

2010 ◽

Vol 7 (s1) ◽

pp. S75-S84 ◽

Cited By ~ 1

Author(s):

V. Radhika ◽

S. Sree Kanth ◽

M. Vijjulatha

Keyword(s):

Biological Activities ◽

3D Qsar ◽

Qsar Model ◽

Quantitative Structure Activity Relationship ◽

Field Analysis ◽

Integrase Inhibitors ◽

Inhibitory Potency ◽

Similarity Indices ◽

Qsar Models ◽

Hiv 1

To understand the structural requirements of HIV-1 integrase inhibitors and to design new ligands against human HIV-1 integrase with enhanced inhibitory potency, a 3D QSAR (quantitative structure-activity relationship) study with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a dataset of 35 bicyclic pyrimidinones which are inhibitors of human HIV-1 integrase was performed. QSAR models were computed with Sybyl. The 3D QSAR model showed very good statistical result, namely q2, r2and r2predvalues were high for both CoMFA and CoMSIA. Based on the high values for q2and r2we are confident that the 3D QSAR model gives good predictions that may be used to design better HIV-1 integrase inhibitors. The CoMFA and CoMSIA models reveal that steric and electrostatic fields contribute significantly with biological activities of the studied compounds.

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