A Combined approach of Pharmacophore Modeling, QSAR Study, Molecular Docking and in silico ADME/Tox prediction of 4-Arylthio & 4- Aryloxy-3- Iodopyridine-2(1H)-one analogs to identify potential Reverse Transcriptase inhibitor: Anti-HIV agents

2020 ◽  
Vol 17 ◽  
Author(s):  
Debadash Panigrahi ◽  
Amiyakanta Mishra ◽  
Susanta Kumar Sahu ◽  
Mohd. Afzal Azam ◽  
C.M. Vyshaag
Keyword(s):  
Molecular Docking ◽  
Reverse Transcriptase ◽  
Active Site ◽  
3D Qsar ◽  
Qsar Model ◽  
Pharmacophore Modeling ◽  
Reverse Transcriptase Inhibitors ◽  
Rt Inhibitors ◽  
Anti Hiv ◽  
Exclusion Method

Background: Reverse transcriptase is an important therapeutic target to treat AIDS caused by the Human Immunodeficiency Virus (HIV). Despite many effective anti-HIV drugs, reverse transcriptase (RT) inhibitors remain the cornerstone of the drug regimen to treat AIDS. In the present work, we have expedited the use of different computational modules and presented an easy, cost-effective and high throughput screening method to identify potential reverse transcriptase inhibitors. Methods: A congeneric series of 4-Arylthio & 4-Aryloxy-3- Iodopyridine-2(1H)-one analogs having anti-HIV activity were subjected to structure-based 2D, 3D QSAR, Pharmacophore Modeling, and Molecular Docking to elucidate the structural properties required for the design of potent HIV-RT inhibitors. Prediction of preliminary Pharmacokinetic and the Drug Likeliness profile was performed for these compounds by in silico ADME study. Results: The 2D and 3D- QSAR models were developed by correlating two and three-dimensional descriptors with activity (pIC50) by sphere exclusion method and k-nearest neighbor molecular field analysis approach, respectively. The significant 2D- QSAR model developed by Partial Least Square associated with the Sphere Exclusion method (PLS-SE) having r2 and q2 values 0.9509 and 0.8038 respectively. The 3D-QSAR model by Step Wise variable selection method (SW-kNN MFA) is more significant which has a cross-validated squared correlation coefficient q2= 0.8509 and a non-cross-validated correlation coefficient pred_r2= 0.8102. The pharmacophore hypothesis was developed which comprised 5 features includes 3 aliphatic regions (Ala), 1 H-bond donor (HDr) and 1 H-bond acceptor (HAc). Docking studies of the selected inhibitors with the active site of reverse transcriptase enzyme showed hydrogen bond and π - π interaction with LYS-101, LYS-103, TYR- 181, TYR-188 and TRP-229 residues present at the active site. All the candidates with good bioavailability and ADMET drug likeliness properties. Conclusion: The results of the present work provide more useful information and important structural insights for the discovery, design of novel and potent reverse transcriptase inhibitors with high therapeutic windows in the future.

QSAR and Docking Studies of DATA Analogues as HIV-1 Reverse Transcriptase Inhibitors

2018 ◽  
Vol 16 (2) ◽  
pp. 153-159 ◽  
Author(s):  
Jianbo Tong ◽  
Shan Lei ◽  
Pei Zhan ◽  
Shangshang Qin ◽  
Yang Wang
Keyword(s):  
Biological Activity ◽  
Molecular Docking ◽  
Reverse Transcriptase ◽  
3D Qsar ◽  
Docking Studies ◽  
Reverse Transcriptase Inhibitors ◽  
Electronic Density ◽  
Topomer Comfa ◽  
Rt Inhibitors ◽  
Hiv 1

Background: Acquired Immunodeficiency Syndrome (AIDS) caused by Human Immunodeficiency Virus (HIV) has seriously threatened human health, so development of new, selective and safe non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs) remains a high priority for medical research. Diaryltriazine (DATA) have been identified as a new class of potent nonnucleoside HIV-1 Reverse Transcriptase (RT) inhibitors. The study deals with Topomer CoMFA (Comparative Molecular Field Analysis) and molecular docking to explore the important features of DATA analogues for exerting potent HIV-1 RT inhibitors activity. Methods: In this work, 40 DATA analogues were studied using a combination of molecular modeling techniques including Three-Dimensional Quantitative Structure–Activity Relationship (3D-QSAR), molecular docking, and Topomer CoMFA were used to build 3D-QSAR models. Results: The results show that the Topomer CoMFA analysis has the cross-validation q2 = 0.800, SDCV = 0.45, the non-cross-validated r2 = 0.958, SD = 0.21, and the correlation coefficient of external validation Q2 ext = 0.965 showed that the model is reasonable and credible, and has a good predictive ability. Then binding mode pattern of the compounds to the binding site of enzyme was confirmed and the mechanism of drug and acceptor was studied by docking studies, the results showed that the drug and GLU138, LYS101, THR139 sites have an obvious function, these researches have provided an useful information for designing more effective HIV-1IN inhibitors. Conclusion: A series of 40 DATAs analogues was subjected to a 3D-QSAR study. Using Topomer CoMFA 3D-QSAR method built model, and the model has shown a good predictive and statistical validation. Substituent with low electronic density in the R5 and R3 positions and substituent with high electronic density in the R2 and C2 positions will increase the biological activity, small substituent on R4 positions and naphthyloxy as the spacer group C6 substituent hydrophobic will increase biological activity. This effect is supported by Topomer CoMFA contour map and docking results of HIV-1RT inhibition active site, the results of the 3D-QSAR and docking analyses have provided a guide for the synthesis of new putative inhibitors for HIV-1RT to improved inhibitory activity.

scholarly journals Rational in silico drug design of HIV-RT inhibitors through G-QSAR and molecular docking study of 4-arylthio and 4-aryloxy-3-iodopyridine-2(1-H)-one derivative

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Debadash Panigrahi ◽  
Amiyakanta Mishra ◽  
Susanta Kumar Sahu
Keyword(s):  
Molecular Docking ◽  
Reverse Transcriptase ◽  
Active Site ◽  
Docking Study ◽  
Molecular Docking Study ◽  
Immunodeficiency Virus ◽  
Qsar Models ◽  
Hiv Rt ◽  
Rt Inhibitors ◽  
Anti Hiv

Abstract Background Human immunodeficiency virus infection and acquired immune deficiency syndrome (HIV/AIDS) is a spectrum of conditions caused by infection with the human immunodeficiency virus (HIV). Antiretroviral therapy (ART) against HIV infection offers the promise of controlling disease progression and prolonging the survival of HIV-infected patients. Reverse transcriptase (RT) inhibitors remain the cornerstone of the drug regimen to treat AIDS. In this direction, by using group-based QSAR study (G-QSAR), identification of the structural need for the development of lead structure with reverse transcriptase inhibition on 97 reported structures was carried out. Docking analysis was performed further and suggested the structural properties required for binding affinity with the receptor. The molecules in the data set were fragmented into six (R1, R2, R3, R4, R5, and R6) by applying the fragmentation pattern. Three G-QSAR models were selected based on the statistical significance of the model. The molecular docking study was performed to explain the structural properties required for the design of potent HIV-RT inhibitors. Results The statistically validated QSAR models reveal the presence of higher hydrophobic groups containing single-bonded –Br atom, 2 aromatic bonded –NH group with less electronegativity, and entropic interaction fields at R2 essential for better anti-HIV activity. The presence of a lipophilic group at R3, oxygen and sulfur connected with two aromatic bonds at R4, and –CH3 group at R5 was fruitful for reverse transcriptase inhibition. Docking studies of the selected inhibitors with the active site of reverse transcriptase enzyme showed hydrogen bond, Van der Waal’s, charge, aromatic, and π–π interactions with residues present at the active site. Conclusion The results of the generated models provide significant site-specific insight into the structural requirements for reverse transcriptase inhibition during the design and development of novel anti-HIV compounds. Molecular docking study revealed the binding interaction between the ligand and the receptor which gave insight towards the structure-based design for the discovery of more potent compounds with better activity against HIV infection.

scholarly journals QSAR, pharmacophore modeling and molecular docking studies to identify structural alerts for some nitrogen heterocycles as dual inhibitor of telomerase reverse transcriptase and human telomeric G-quadruplex DNA

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
R. D. Jawarkar ◽  
R. L. Bakal ◽  
P. N. Khatale ◽  
Israa Lewaa ◽  
Chetan M. Jain ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Carbon Atom ◽  
Reverse Transcriptase ◽  
Qsar Model ◽  
Pharmacophore Modeling ◽  
Telomerase Reverse Transcriptase ◽  
Quadruplex Dna ◽  
Pharmacophore Modelling ◽  
G Quadruplex ◽  
Dual Inhibition

Abstract Background Telomerase reverse transcriptase (TERT) and human telomeric G-quadruplex DNA are amongst the favorable target for researchers to discover novel and more effective anticancer agents. To understand and elucidate structure activity relationship and mechanism of inhibition of telomerase reverse transcriptase (TERT) and human telomeric G-quadruplex DNA, a QSAR modeling and molecular docking were conducted. Results Two robust QSAR model were obtained which consist of full set QSAR model (R2: 0.8174, CCCtr: 0.8995, Q2loo: 0.7881, Q2LMO: 0.7814) and divided set QSAR model (R2: 0.8217, CCCtr: 0.9021, Q2loo: 0.7886, Q2LMO: 0.7783, Q2-F1: 0.7078, Q2-F2: 0.6865, Q2-F3: 0.7346) for envisaging the inhibitory activity of telomerase reverse transcriptase (TERT) and human telomeric G-quadruplex DNA. The analysis reveals that carbon atom exactly at 3 bonds from aromatic carbon atom, nitrogen atom exactly at six bonds from planer nitrogen atom, aromatic carbon atom within 2 A0 from the center of mass of molecule and occurrence of element hydrogen within 2 A0 from donar atom are the key pharmacophoric features important for dual inhibition of TERT and human telomeric G-quadruplex DNA. To validate this analysis, pharmacophore modeling and the molecular docking is performed. Molecular docking analysis support QSAR analysis and revealed that, dual inhibition of TERT and human telomeric DNA is mainly contributed from hydrophobic and hydrogen bonding interactions. Conclusion The findings of molecular docking, pharmacophore modelling, and QSAR are all consistent and in strong agreement. The validated QSAR analyses can detect structural alerts, pharmacophore modelling can classify a molecule's consensus pharmacophore involving hydrophobic and acceptor regions, whereas docking analysis can reveal the mechanism of dual inhibition of telomerase reverse transcriptase (TERT) and human telomeric G-quadruplex DNA. The combination of QSAR, pharmacophore modeling and molecular docking may be useful for the future drug design of dual inhibitors to combat the devastating issue of resistance. Graphical abstract

Molecular Docking Studies and Synthesis of Amino-oxy-diarylquinoline Derivatives as Potent Non-nucleoside HIV-1 Reverse Transcriptase Inhibitors

Drug Research ◽  
2019 ◽  
Vol 69 (12) ◽  
pp. 671-682 ◽  
Author(s):  
Arthit Makarasen ◽  
Mayuso Kuno ◽  
Suwicha Patnin ◽  
Nanthawan Reukngam ◽  
Panita Khlaychan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Reverse Transcriptase ◽  
Lymphoblastic Leukemia ◽  
Docking Studies ◽  
Elisa Method ◽  
Reverse Transcriptase Inhibitors ◽  
Anti Hiv Agents ◽  
Near Future ◽  
Anti Hiv ◽  
Hiv 1

AbstractIn this study, amino-oxy-diarylquinolines were designed using structure-guided molecular hybridization strategy and fusing of the pharmacophore templates of nevirapine (NVP), efavirenz (EFV), etravirine (ETV, TMC125) and rilpivirine (RPV, TMC278). The anti-HIV-1 reverse transcriptase (RT) activity was evaluated using standard ELISA method, and the cytotoxic activity was performed using MTT and XTT assays. The primary bioassay results indicated that 2-amino-4-oxy-diarylquinolines possess moderate inhibitory properties against HIV-1 RT. Molecular docking results showed that 2-amino-4-oxy-diarylquinolines 8(a-d) interacted with the Lys101 and His235 residue though hydrogen bonding and interacted with Tyr318 residue though π-π stacking in HIV-1 RT. Furthermore, 8a and 8d were the most potent anti-HIV agents among the designed and synthesized compounds, and their inhibition rates were 34.0% and 39.7% at 1 µM concentration. Interestingly, 8a was highly cytotoxicity against MOLT-3 (acute lymphoblastic leukemia), with an IC50 of 4.63±0.62 µg/mL, which was similar with that in EFV and TMC278 (IC50 7.76±0.37 and 1.57±0.20 µg/ml, respectively). Therefore, these analogs of the synthesized compounds can serve as excellent bases for the development of new anti-HIV-1 agents in the near future.

scholarly journals Molecular docking based design of Inhibitors for viral Non-Nucleosidase as potential anti-retroviral agents

2020 ◽  
Vol 16 (10) ◽  
pp. 736-741
Author(s):  
Ahmed Alharbi ◽  
Keyword(s):  
Molecular Docking ◽  
Antiretroviral Therapy ◽  
Reverse Transcriptase ◽  
Active Site ◽  
Viral Protein ◽  
Protein Targeting ◽  
Antiretroviral Drugs ◽  
New Chemical Entities ◽  
Electronic Parameters ◽  
Rt Inhibitors

Reverse Transcriptase (RT) inhibitors are highly promising agents for use as an effective anti-retroviral therapy (HAART) which is typically a combination of three or four antiretroviral drugs. We used direct drug design approach to discover new chemical entities for the target protein. The validated template of the protein targeting reverse transcriptase PDB ID 1JKH was extracted for three sites hydrophobic, steric, and electronic parameters explain the interactions at the active site by the inhibitors. We used the Zinc library of compounds to explore the possible leads for HAART through RT inhibition. We report 12 new chemical entities with possible activity against the targeted viral protein. These leads will provide new therapeutic means in antiretroviral therapy.

Synthesis, anti-HIV activity and molecular modeling study of 3-aryl-6-adamantylmethyl-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazole derivatives

2015 ◽  
Vol 70 (8) ◽  
pp. 609-616 ◽  
Author(s):  
Mahmood-ul-Hassan Khan ◽  
Shahid Hameed ◽  
Muhammad Farman ◽  
Najim A. Al-Masoudi ◽  
Helen Stoeckli-Evans
Keyword(s):  
Molecular Docking ◽  
Molecular Modeling ◽  
Reverse Transcriptase ◽  
Reverse Transcriptase Inhibitors ◽  
Simple Method ◽  
X Ray ◽  
Structure Activity ◽  
Thiadiazole Derivatives ◽  
Anti Hiv ◽  
Hiv 1

AbstractA series of novel 3-aryl-6-adamantylmethyl-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazoles 6a–l were synthesized by a simple method with the aim of developing novel HIV non-nucleoside reverse transcriptase inhibitors. All the synthesized compounds were structurally confirmed by spectral analyses. The structure of 6a was unambiguously verified by X-ray structure determination. The synthesized compounds were evaluated for their anti-HIV activity and four analogs displayed moderate inhibitory activity with EC50 values ranging from 10.10 to 12.40 μg mL–1. Molecular docking of 6g with HIV-1 reverse transcriptase was studied to rationalize some structure-activity relationships (SARs).

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.

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