Non-Nucleoside HIV-1 Reverse Transcriptase Inhibition Activity of a Series of Dihydroalkoxybenzyloxopyrimidine (DABO) Derivatives: CoMFA, CoMSIA and Docking Studies

2020 ◽  
Vol 5 (3) ◽  
pp. 265-272
Author(s):  
Bikash Kumar Sarkar ◽  
Ananda Sarkar ◽  
Atish Dipankar Jana
Keyword(s):  
3D Qsar ◽  
Docking Study ◽  
Binding Pocket ◽  
Qsar Model ◽  
Docking Studies ◽  
Field Analysis ◽  
Qsar Studies ◽  
3D Space ◽  
Pyrimidine Moiety ◽  
Hiv 1

CoMFA, CoMSIA and molecular docking studies have been carried out for a set of 42 dihydroalkoxybenzyloxopyrimidine (DABO) derivatives for which anti-HIV activity values are available. In 3D-QSAR studies-comparative molecular field analysis (CoMFA) as well as comparative molecular similarity indices analysis (CoMSIA) have been performed. Both the QSAR model nicely explains the inhibitory activities of DABO derivatives as well as provides molecular level insights revealing which regions in 3D space around the molecules are more important for their anti HIVactivities. These models have a quite high square correlation coefficient (r2 = 0.817 for CoMFA and r2 = 0.943 for CoMSIA). A docking study of the highest active molecule into the binding site of the protein HIV-1 RT (PDB ID-1RT1) shows that hydrogen bonding between pyrimidine moiety of the ligand and the Lysine-101 moiety along with Valine-106 moiety of the HIV protein play most important role for stabilizing the ligand in the binding pocket of the protein.

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

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.

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

2012 ◽  
Vol 62 (3) ◽  
pp. 287-304 ◽  
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.

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

INDIAN DRUGS ◽  
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.

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

2011 ◽  
Vol 361-363 ◽  
pp. 263-267 ◽  
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 .

scholarly journals Docking and 3D QSAR Studies on p38α MAP Kinase Inhibitors

2011 ◽  
Vol 8 (4) ◽  
pp. 1596-1605
Author(s):  
Mohan Babu Jatavath ◽  
Sree Kanth Sivan ◽  
Yamini Lingala ◽  
Vijjulatha Manga
Keyword(s):  
Map Kinase ◽  
Kinase Inhibitors ◽  
Inflammatory Diseases ◽  
Biological Activities ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Chemotherapeutic Agents ◽  
Field Analysis ◽  
Qsar Studies

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.

3D QSAR Based Virtual Screening of Pyrido[1,2-a] Benzimidazoles as Potent Antimalarial Agents

2019 ◽  
Vol 16 (3) ◽  
pp. 301-312
Author(s):  
Kalicharan Sharma ◽  
Apeksha Srivastava ◽  
Pooja Tiwari ◽  
Shweta Sharma ◽  
Mohammad Shaquiquzzaman ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Antimalarial Activity ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Qsar Model ◽  
Docking Studies ◽  
Activity Data ◽  
Qsar Studies ◽  
Antimalarial Agents ◽  
Fisher Ratio

Background: Development of novel antimalarial agents has been one of the sought areas in medicinal chemistry. In this study the same was done by virtual screening of in-house database on developed QSAR model. </P><P> Methods: A six point pharmacophore model was generated (AADHRR.56) from 41 compounds using PHASE module of Schrodinger software and used for pharmacophore based search. Docking studies of the obtained hits were performed using GLIDE. Most promising hit was synthesized & biologically evaluated for antimalarial activity. </P><P> Result: The best generated model was found to be statistically significant as it had a high correlation coefficient r2= 0.989 and q2 =0.76 at 3 component PLS factor. The significance of hypothesis was also confirmed by high Fisher ratio (F = 675.1) and RMSE of 0.2745. The model developed had good predicted coefficient (Pearson R = 0.8826). The virtual screening on this model resulted in six hits, which were docked against FP-2 enzyme. The synthesized compound displayed IC50 value of 0.27&#181;g/ml against CQS (3D7) and 0.57μg/ml against CQR (RKL9). </P><P> Conclusion: 3D QSAR studies reviled that hydrophobic groups are important for anti-malarial activity while H-donor is less desirable for the same. Electron withdrawing groups at R1 position favours the activity. The biological activity data of the synthesized hit proved that the pharmacophore hypothesis developed could be utilized for developing novel anti-malarial drugs.

scholarly journals Synthetic Analogues of Aminoadamantane as Influenza Viral Inhibitors—In Vitro, In Silico and QSAR Studies

Molecules ◽  
2020 ◽  
Vol 25 (17) ◽  
pp. 3989
Author(s):  
Radoslav Chayrov ◽  
Nikolaos A. Parisis ◽  
Maria V. Chatziathanasiadou ◽  
Eleni Vrontaki ◽  
Kalliopi Moschovou ◽  
...  
Keyword(s):  
Antiviral Activity ◽  
3D Qsar ◽  
Docking Studies ◽  
Field Analysis ◽  
Qsar Studies ◽  
Structure Activity ◽  
Synthetic Molecules ◽  
Amino Acid Analogues ◽  
Low Cytotoxicity

A series of nineteen amino acid analogues of amantadine (Amt) and rimantadine (Rim) were synthesized and their antiviral activity was evaluated against influenza virus A (H3N2). Among these analogues, the conjugation of rimantadine with glycine illustrated high antiviral activity combined with low cytotoxicity. Moreover, this compound presented a profoundly high stability after in vitro incubation in human plasma for 24 h. Its thermal stability was established using differential and gravimetric thermal analysis. The crystal structure of glycyl-rimantadine revealed that it crystallizes in the orthorhombic Pbca space group. The structure–activity relationship for this class of compounds was established, with CoMFA (Comparative Molecular Field Analysis) 3D-Quantitative Structure Activity Relationships (3D-QSAR) studies predicting the activities of synthetic molecules. In addition, molecular docking studies were conducted, revealing the structural requirements for the activity of the synthetic molecules.

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

Molecules ◽  
2018 ◽  
Vol 23 (11) ◽  
pp. 3036 ◽  
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.

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

2010 ◽  
Vol 7 (s1) ◽  
pp. S75-S84 ◽  
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.

Identification of Adjacent NNRTI Binding Pocket in Multi-mutated HIV1- RT Enzyme Model: An in silico Study

2018 ◽  
Vol 16 (2) ◽  
pp. 121-129 ◽  
Author(s):  
R.F. Kamil ◽  
U. Debnath ◽  
S. Verma ◽  
Y.S. Prabhakar
Keyword(s):  
In Silico ◽  
Point Mutations ◽  
Homology Model ◽  
Docking Study ◽  
Binding Pocket ◽  
Docking Studies ◽  
Primary Objective ◽  
Multiple Point ◽  
Enzyme Model ◽  
Hiv 1

Introduction: A possible strategy to combat mutant strains is to have a thorough structural evaluation before and after mutations to identify the diversity in the non-nucleoside inhibitor binding pocket and their effects on enzyme-ligand interactions to generate novel NNRTI’s accordingly. Objective: The primary objective of this study was to find effects of multiple point mutations on NNRTI binding pocket. This study included the contribution of each individual mutation in NNIBP that propose an adjacent binding pocket which can be used to discover novel NNRTI derivatives. Methods: An in Silico model of HIV-1 RT enzyme with multiple mutations K103N, Y181C and Y188L was developed and evaluated. Two designed NNRTI pyridinone derivatives were selected as ligands for docking studies with the homology model through alignment based docking and residue based docking approaches. Binding pockets of wild type HIV-1 RT and multi-mutated homology model were compared thoroughly. Result and Discussion: K103N mutation narrowed the entrance of NNRTI binding pocket and forbade electrostatic interaction with α amino group of LYS103. Mutations Y181C and Y188L prevented NNRTI binding by eliminating aromatic π interactions offered by tyrosine rings. Docking study against new homology model suggested an adjacent binding pocket with combination of residues in palm and connection domains. This pocket is approximately 14.46Å away from conventional NNRTI binding site. Conclusion: Increased rigidity, steric hindrance and losses of important interactions cumulatively prompt ligands to adapt adjacent NNRTI binding pocket. The proposed new and adjacent binding pocket is identified by this study which can further be evaluated to generate novel derivatives.

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