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Lotha TN, Richa K, Sorhie V, Ketiyala, Nakro V, Imkongyanger, Ritse V, Rudithongru L, Namsa ND, Jamir L. Environmentally benign synthesis of unsymmetrical ureas and their evaluation as potential HIV-1 protease inhibitors via a computational approach. Mol Divers 2024; 28:749-763. [PMID: 36788191 DOI: 10.1007/s11030-023-10615-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 01/30/2023] [Indexed: 02/16/2023]
Abstract
The present work reports the cost-effective, high yielding and environmentally acceptable preparation of unsymmetrical ureas from thiocarbamate salts using sodium percarbonate as an oxidant. Efficacy of the unsymmetrical ureas as potential human immune deficiency virus (HIV-1) protease inhibitors has been evaluated via in silico approach. The results revealed interactions of the urea compounds at the active site of the enzyme with favorable binding affinities causing possible mutations hindering the functioning of the enzyme. Further computational assessment of IC50 using known references satisfactorily authenticated the inhibitory action of the selected compounds against HIV-1 protease. Added to the easy synthesis of the ureas following an environmentally benign protocol, this work may be a valuable addition to the ongoing search for drugs with better efficacy profiles and reduced toxicity against HIV.
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Affiliation(s)
- Tsenbeni N Lotha
- Department of Environmental Science, Nagaland University, Lumami, Nagaland, 798627, India
| | - Kikoleho Richa
- Department of Chemistry, Nagaland University, Lumami, Nagaland, 798627, India
| | - Viphrezolie Sorhie
- Department of Environmental Science, Nagaland University, Lumami, Nagaland, 798627, India
| | - Ketiyala
- Department of Environmental Science, Nagaland University, Lumami, Nagaland, 798627, India
| | - Vevosa Nakro
- Department of Environmental Science, Nagaland University, Lumami, Nagaland, 798627, India
| | - Imkongyanger
- Department of Environmental Science, Nagaland University, Lumami, Nagaland, 798627, India
| | - Vimha Ritse
- Department of Environmental Science, Nagaland University, Lumami, Nagaland, 798627, India
| | - Lemzila Rudithongru
- Department of Environmental Science, Nagaland University, Lumami, Nagaland, 798627, India
| | - Nima D Namsa
- Department of Molecular Biology and Biotechnology, Tezpur University, Napaam, Assam, 784028, India
| | - Latonglila Jamir
- Department of Environmental Science, Nagaland University, Lumami, Nagaland, 798627, India.
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Ghasedi N, Ahmadi S, Ketabi S, Almasirad A. DFT based QSAR study on quinolone-triazole derivatives as antibacterial agents. J Recept Signal Transduct Res 2021; 42:418-428. [PMID: 34693868 DOI: 10.1080/10799893.2021.1988971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
QSAR modeling was performed on 39 quinolone-triazole derivatives against gram-positive Staphylococcus aureus and gram-negative Pseudomonas aeruginosa bacteria. The molecular structures were optimized using the DFT/B3LYP method and 6-31 G basis set. Molecular descriptors were extracted using quantum mechanical calculations. The hierarchical cluster analysis was performed for a rational subset division. The initial dataset was divided into calibration and validation sets, and modeling was done by stepwise MLR method for each of the two bacteria. Internal and external validation methods confirmed the robustness and predictability of the obtained models. According to the obtained model for S. aureus (R2 = 0.889, R2ext = 0.938, Q2LOO = 0.853), the four descriptors- partial atomic charges for the N1 atom in triazole and C7 of the quinolone nucleus, 4-carbonyl bond length, and 13C-NMR chemical shift of 3-carboxylic acid- were found to be the descriptors controlling the activity. According to the obtained model for P. aeruginosa (R2 = 0.957, R2ext = 0.923, Q2LOO = 0.909), the O atom's partial charge in carbonyl, LUMO-HOMO energy gap, and logP were found to be the descriptors having the highest correlation with the antibacterial activity. Finally, some new compounds with higher activities were designed and proposed.
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Affiliation(s)
- Niloofar Ghasedi
- Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Shahin Ahmadi
- Department of Pharmaceutical Chemistry, Faculty of Pharmaceutical Chemistry, Tehran medical sciences, Islamic Azad University, Tehran, Iran
| | - Sepideh Ketabi
- Department of Pharmaceutical Chemistry, Faculty of Pharmaceutical Chemistry, Tehran medical sciences, Islamic Azad University, Tehran, Iran
| | - Ali Almasirad
- Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
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Olotu FA, Agoni C, Soremekun O, Soliman MES. The recent application of 3D-QSAR and docking studies to novel HIV-protease inhibitor drug discovery. Expert Opin Drug Discov 2020; 15:1095-1110. [PMID: 32692273 DOI: 10.1080/17460441.2020.1773428] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
INTRODUCTION Despite the availability of FDA approved inhibitors of HIV protease, numerous efforts are still ongoing to achieve 'near-perfect' drugs devoid of characteristic adverse side effects, toxicities, and mutational resistance. While experimental methods have been plagued with huge consumption of time and resources, there has been an incessant shift towards the use of computational simulations in HIV protease inhibitor drug discovery. AREAS COVERED Herein, the authors review the numerous applications of 3D-QSAR modeling methods over recent years relative to the design of new HIV protease inhibitors from a series of experimentally derived compounds. Also, the augmentative contributions of molecular docking are discussed. EXPERT OPINION Efforts to optimize 3D QSAR and molecular docking for HIV-1 drug discovery are ongoing, which could further incorporate inhibitor motions at the active site using molecular dynamics parameters. Also, highly predictive machine learning algorithms such as random forest, K-means, decision trees, linear regression, hierarchical clustering, and Bayesian classifiers could be employed.
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Affiliation(s)
- Fisayo A Olotu
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus , Durban, 4001, South Africa
| | - Clement Agoni
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus , Durban, 4001, South Africa
| | - Opeyemi Soremekun
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus , Durban, 4001, South Africa
| | - Mahmoud E S Soliman
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus , Durban, 4001, South Africa
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Melo R, Lemos A, Preto AJ, Bueschbell B, Matos-Filipe P, Barreto C, Almeida JG, Silva RDM, Correia JDG, Moreira IS. An Overview of Antiretroviral Agents for Treating HIV Infection in Paediatric Population. Curr Med Chem 2020; 27:760-794. [PMID: 30182840 DOI: 10.2174/0929867325666180904123549] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 07/11/2018] [Accepted: 07/11/2018] [Indexed: 12/19/2022]
Abstract
Paediatric Acquired ImmunoDeficiency Syndrome (AIDS) is a life-threatening and infectious disease in which the Human Immunodeficiency Virus (HIV) is mainly transmitted through Mother-To- Child Transmission (MTCT) during pregnancy, labour and delivery, or breastfeeding. This review provides an overview of the distinct therapeutic alternatives to abolish the systemic viral replication in paediatric HIV-1 infection. Numerous classes of antiretroviral agents have emerged as therapeutic tools for downregulation of different steps in the HIV replication process. These classes encompass Non- Nucleoside Analogue Reverse Transcriptase Inhibitors (NNRTIs), Nucleoside/Nucleotide Analogue Reverse Transcriptase Inhibitors (NRTIs/NtRTIs), INtegrase Inhibitors (INIs), Protease Inhibitors (PIs), and Entry Inhibitors (EIs). Co-administration of certain antiretroviral drugs with Pharmacokinetic Enhancers (PEs) may boost the effectiveness of the primary therapeutic agent. The combination of multiple antiretroviral drug regimens (Highly Active AntiRetroviral Therapy - HAART) is currently the standard therapeutic approach for HIV infection. So far, the use of HAART offers the best opportunity for prolonged and maximal viral suppression, and preservation of the immune system upon HIV infection. Still, the frequent administration of high doses of multiple drugs, their inefficient ability to reach the viral reservoirs in adequate doses, the development of drug resistance, and the lack of patient compliance compromise the complete HIV elimination. The development of nanotechnology-based drug delivery systems may enable targeted delivery of antiretroviral agents to inaccessible viral reservoir sites at therapeutic concentrations. In addition, the application of Computer-Aided Drug Design (CADD) approaches has provided valuable tools for the development of anti-HIV drug candidates with favourable pharmacodynamics and pharmacokinetic properties.
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Affiliation(s)
- Rita Melo
- Centro de Ciencias e Tecnologias Nucleares, Instituto Superior Tecnico, Universidade de Lisboa, CTN, Estrada Nacional 10 (km 139,7), Bobadela LRS 2695-066, Portugal.,CNC - Center for Neuroscience and Cell Biology; Rua Larga, FMUC, Polo I, 1ºandar, Universidade de Coimbra, Coimbra 3004-517, Portugal
| | - Agostinho Lemos
- CNC - Center for Neuroscience and Cell Biology; Rua Larga, FMUC, Polo I, 1ºandar, Universidade de Coimbra, Coimbra 3004-517, Portugal.,GIGA Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège 4000, Belgium
| | - António J Preto
- CNC - Center for Neuroscience and Cell Biology; Rua Larga, FMUC, Polo I, 1ºandar, Universidade de Coimbra, Coimbra 3004-517, Portugal
| | - Beatriz Bueschbell
- Pharmaceutical Chemistry I, PharmaCenter, Pharmaceutical Institute, University of Bonn, Bonn, Germany
| | - Pedro Matos-Filipe
- CNC - Center for Neuroscience and Cell Biology; Rua Larga, FMUC, Polo I, 1ºandar, Universidade de Coimbra, Coimbra 3004-517, Portugal
| | - Carlos Barreto
- CNC - Center for Neuroscience and Cell Biology; Rua Larga, FMUC, Polo I, 1ºandar, Universidade de Coimbra, Coimbra 3004-517, Portugal
| | - José G Almeida
- CNC - Center for Neuroscience and Cell Biology; Rua Larga, FMUC, Polo I, 1ºandar, Universidade de Coimbra, Coimbra 3004-517, Portugal
| | - Rúben D M Silva
- Centro de Ciencias e Tecnologias Nucleares, Instituto Superior Tecnico, Universidade de Lisboa, CTN, Estrada Nacional 10 (km 139,7), Bobadela LRS 2695-066, Portugal
| | - João D G Correia
- Centro de Ciencias e Tecnologias Nucleares, Instituto Superior Tecnico, Universidade de Lisboa, CTN, Estrada Nacional 10 (km 139,7), Bobadela LRS 2695-066, Portugal
| | - Irina S Moreira
- CNC - Center for Neuroscience and Cell Biology; Rua Larga, FMUC, Polo I, 1ºandar, Universidade de Coimbra, Coimbra 3004-517, Portugal.,Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Utrecht 3584CH, Netherland
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Leidner F, Kurt Yilmaz N, Schiffer CA. Target-Specific Prediction of Ligand Affinity with Structure-Based Interaction Fingerprints. J Chem Inf Model 2019; 59:3679-3691. [PMID: 31381335 PMCID: PMC6940596 DOI: 10.1021/acs.jcim.9b00457] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Discovery and optimization of small molecule inhibitors as therapeutic drugs have immensely benefited from rational structure-based drug design. With recent advances in high-resolution structure determination, computational power, and machine learning methodology, it is becoming more tractable to elucidate the structural basis of drug potency. However, the applicability of machine learning models to drug design is limited by the interpretability of the resulting models in terms of feature importance. Here, we take advantage of the large number of available inhibitor-bound HIV-1 protease structures and associated potencies to evaluate inhibitor diversity and machine learning models to predict ligand affinity. First, using a hierarchical clustering approach, we grouped HIV-1 protease inhibitors and identified distinct core structures. Explicit features including protein-ligand interactions were extracted from high-resolution cocrystal structures as 3D-based fingerprints. We found that a gradient boosting machine learning model with this explicit feature attribution can predict binding affinity with high accuracy. Finally, Shapley values were derived to explain local feature importance. We found specific van der Waals (vdW) interactions of key protein residues are pivotal for the predicted potency. Protein-specific and interpretable prediction models can guide the optimization of many small molecule drugs for improved potency.
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Affiliation(s)
- Florian Leidner
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Nese Kurt Yilmaz
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Celia A. Schiffer
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605, USA
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Padariya M, Kalathiya U, Baginski M. Molecular basis and potential activity of HIV-1 reverse transcriptase toward trimethylamine-based compounds. Biotechnol Appl Biochem 2017; 64:810-826. [DOI: 10.1002/bab.1543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Accepted: 10/31/2016] [Indexed: 11/10/2022]
Affiliation(s)
- Monikaben Padariya
- Department of Pharmaceutical Technology and Biochemistry; Faculty of Chemistry; Gdansk University of Technology; Gdansk Poland
| | - Umesh Kalathiya
- Department of Pharmaceutical Technology and Biochemistry; Faculty of Chemistry; Gdansk University of Technology; Gdansk Poland
| | - Maciej Baginski
- Department of Pharmaceutical Technology and Biochemistry; Faculty of Chemistry; Gdansk University of Technology; Gdansk Poland
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Chitre TS, Asgaonkar KD, Patil SM, Kumar S, Khedkar VM, Garud DR. QSAR, docking studies of 1,3-thiazinan-3-yl isonicotinamide derivatives for antitubercular activity. Comput Biol Chem 2017; 68:211-218. [PMID: 28411471 DOI: 10.1016/j.compbiolchem.2017.03.015] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Revised: 03/17/2017] [Accepted: 03/28/2017] [Indexed: 11/24/2022]
Abstract
The enzyme - enoyl acyl carrier protein reductase (enoyl ACP reductase) is a validated target for antitubercular activity. Inhibition of this enzyme interferes with mycolic acid synthesis which is crucial for Mycobacterium tuberculosis cell growth. In the present work 2D and 3D quantitative structure activity relationship (QSAR) studies were carried out on a series of thiazinan-Isoniazid pharmacophore to design newer analogues. For 2D QSAR, the best statistical model was generated using SA-MLR method (r2=0.958, q2=0.922) while 3D QSAR model was derived using the SA KNN method (q2=0.8498). These studies could guide the topological, electrostatic, steric, hydrophobic substitutions around the nucleus based on which the NCEs were designed. Furthermore, molecular docking was performed to gauze the binding affinity of the designed analogues for enoyl ACP reductase enzyme. Amongst all the designed analogues the binding energies of SKS 01 and SKS 05 were found to be -5.267kcal/mol and -5.237kcal/mol respectively which was comparable with the binding energy of the standard Isoniazid (-6.254kcal/mol).
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Affiliation(s)
- Trupti S Chitre
- Department of Pharmaceutical Chemistry, All India Shri Shivaji Memorial Society's College of Pharmacy, Kennedy Road, Near R.T.O., Pune 411001, M.S., India.
| | - Kalyani D Asgaonkar
- Department of Pharmaceutical Chemistry, All India Shri Shivaji Memorial Society's College of Pharmacy, Kennedy Road, Near R.T.O., Pune 411001, M.S., India
| | - Shital M Patil
- Department of Pharmaceutical Chemistry, All India Shri Shivaji Memorial Society's College of Pharmacy, Kennedy Road, Near R.T.O., Pune 411001, M.S., India
| | - Shiva Kumar
- Department of Pharmaceutical Chemistry, All India Shri Shivaji Memorial Society's College of Pharmacy, Kennedy Road, Near R.T.O., Pune 411001, M.S., India
| | - Vijay M Khedkar
- Paris Saclay University, U892 INRA, 78350 Jouy en Josas, France
| | - Dinesh R Garud
- Department of Chemistry, Sir Parashurambhau College, Affiliated to Savitribai Phule Pune University, Tilak Road, Pune 411030, India
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Islam MA, Pillay TS. Exploration of the structural requirements of HIV-protease inhibitors using pharmacophore, virtual screening and molecular docking approaches for lead identification. J Mol Graph Model 2015; 56:20-30. [DOI: 10.1016/j.jmgm.2014.11.015] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2014] [Revised: 11/24/2014] [Accepted: 11/30/2014] [Indexed: 12/19/2022]
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9
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Dong M, Ren Y. Molecular modeling studies of dihydro-alkyloxy-benzyl-oxopyrimidines (DABOs) as non-nucleoside inhibitors of HIV-1 reverse transcriptase using 3D-QSAR, Topomer CoMFA and molecular docking simulations. RSC Adv 2015. [DOI: 10.1039/c4ra15397a] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
The human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) is generally regarded as a target for the treatment of acquired immune deficiency syndrome (AIDS).
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Affiliation(s)
- Minghui Dong
- School of Chemical and Environmental Engineering
- Shanghai Institute of Technology
- Shanghai
- P. R. China
| | - Yujie Ren
- School of Chemical and Environmental Engineering
- Shanghai Institute of Technology
- Shanghai
- P. R. China
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10
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Khedkar VM, Joseph J, Pissurlenkar R, Saran A, Coutinho EC. How good are ensembles in improving QSAR models? The case with eCoRIA. J Biomol Struct Dyn 2014; 33:749-69. [DOI: 10.1080/07391102.2014.909744] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Vijay M. Khedkar
- Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Kalina, Santacruz (E), Mumbai 400098, India
| | - Jose Joseph
- Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Kalina, Santacruz (E), Mumbai 400098, India
| | - Raghuvir Pissurlenkar
- Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Kalina, Santacruz (E), Mumbai 400098, India
| | - Anil Saran
- Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Kalina, Santacruz (E), Mumbai 400098, India
| | - Evans C. Coutinho
- Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Kalina, Santacruz (E), Mumbai 400098, India
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Ul-Haq Z, Usmani S, Shamshad H, Mahmood U, Halim SA. A combined 3D-QSAR and docking studies for the In-silico prediction of HIV-protease inhibitors. Chem Cent J 2013; 7:88. [PMID: 23683267 PMCID: PMC3660290 DOI: 10.1186/1752-153x-7-88] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2013] [Accepted: 05/06/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Tremendous research from last twenty years has been pursued to cure human life against HIV virus. A large number of HIV protease inhibitors are in clinical trials but still it is an interesting target for researchers due to the viral ability to get mutated. Mutated viral strains led the drug ineffective but still used to increase the life span of HIV patients. RESULTS In the present work, 3D-QSAR and docking studies were performed on a series of Danuravir derivatives, the most potent HIV- protease inhibitor known so far. Combined study of 3D-QSAR was applied for Danuravir derivatives using ligand-based and receptor-based protocols and generated models were compared. The results were in good agreement with the experimental results. Additionally, docking analysis of most active 32 and least active 46 compounds into wild type and mutated protein structures further verified our results. The 3D-QSAR and docking results revealed that compound 32 bind efficiently to the wild and mutated protein whereas, sufficient interactions were lost in compound 46. CONCLUSION The combination of two computational techniques would helped to make a clear decision that compound 32 with well inhibitory activity bind more efficiently within the binding pocket even in case of mutant virus whereas compound 46 lost its interactions on mutation and marked as least active compound of the series. This is all due to the presence or absence of substituents on core structure, evaluated by 3D-QSAR studies. This set of information could be used to design highly potent drug candidates for both wild and mutated form of viruses.
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Affiliation(s)
- Zaheer Ul-Haq
- Dr, Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan.
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Li X, Wang X, Shi W, Liu H, Yu H. Analysis of Ah receptor binding affinities of polybrominated diphenyl ethers via in silico molecular docking and 3D-QSAR. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2013; 24:75-87. [PMID: 23121134 DOI: 10.1080/1062936x.2012.729225] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Polybrominated diphenyl ethers (PBDEs) have become ubiquitous contaminations due to their use as flame retardants. The structural similarity of PBDE to some dioxin-like compounds suggested that they may share similar toxicological effects: they might activate the aryl hydrocarbon receptor (AhR) signal transduction pathway and thus might have adverse effects on wildlife and humans. In this study, in silico computational workflow combining molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) was performed to investigate the binding interactions between PBDEs and AhR and the structural features affecting the AhR binding affinity of PBDE. The molecular docking showed that hydrogen-bond and hydrophobic interactions were the major driving forces for the binding of ligands to AhR, and several key amino acid residues were also identified. The CoMSIA model was developed from the conformations obtained from molecular docking and exhibited satisfactory results as q (2) of 0.605 and r (2) of 0.996. Furthermore, the derived model had good robustness and statistical significance in both internal and external validations. The 3D contour maps generated from CoMSIA provided important structural features influence the binding affinity. The obtained results were beneficial to better understand the toxicological mechanism of PBDEs.
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Affiliation(s)
- X Li
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, P.R. China
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13
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In silico screening of indinavir-based compounds targeting proteolytic activity in HIV PR: binding pocket fit approach. Med Chem Res 2011. [DOI: 10.1007/s00044-011-9941-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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Shih KC, Lin CY, Zhou J, Chi HC, Chen TS, Wang CC, Tseng HW, Tang CY. Development of Novel 3D-QSAR Combination Approach for Screening and Optimizing B-Raf Inhibitors in silico. J Chem Inf Model 2010; 51:398-407. [DOI: 10.1021/ci100351s] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Affiliation(s)
- Kuei-Chung Shih
- Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Chun-Yuan Lin
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
- Research Center for Emerging Viral Infections, Chang Gung University, Taoyuan 33302, Taiwan
| | - Jiayi Zhou
- Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Hsiao-Chieh Chi
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Ting-Shou Chen
- Biomedical Engineering Research Laboratories, Industrial Technology Research Institute, Chutung, Hsinchu, 31040, Taiwan
| | - Chun-Chung Wang
- Biomedical Engineering Research Laboratories, Industrial Technology Research Institute, Chutung, Hsinchu, 31040, Taiwan
| | - Hsiang-Wen Tseng
- Biomedical Engineering Research Laboratories, Industrial Technology Research Institute, Chutung, Hsinchu, 31040, Taiwan
| | - Chuan-Yi Tang
- Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan
- Department of Computer Science and Information Engineering, Providence University, Taichung 43301, Taiwan
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Myint KZ, Xie XQ. Recent advances in fragment-based QSAR and multi-dimensional QSAR methods. Int J Mol Sci 2010; 11:3846-66. [PMID: 21152304 PMCID: PMC2996787 DOI: 10.3390/ijms11103846] [Citation(s) in RCA: 76] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2010] [Revised: 09/17/2010] [Accepted: 09/23/2010] [Indexed: 12/13/2022] Open
Abstract
This paper provides an overview of recently developed two dimensional (2D) fragment-based QSAR methods as well as other multi-dimensional approaches. In particular, we present recent fragment-based QSAR methods such as fragment-similarity-based QSAR (FS-QSAR), fragment-based QSAR (FB-QSAR), Hologram QSAR (HQSAR), and top priority fragment QSAR in addition to 3D- and nD-QSAR methods such as comparative molecular field analysis (CoMFA), comparative molecular similarity analysis (CoMSIA), Topomer CoMFA, self-organizing molecular field analysis (SOMFA), comparative molecular moment analysis (COMMA), autocorrelation of molecular surfaces properties (AMSP), weighted holistic invariant molecular (WHIM) descriptor-based QSAR (WHIM), grid-independent descriptors (GRIND)-based QSAR, 4D-QSAR, 5D-QSAR and 6D-QSAR methods.
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Affiliation(s)
- Kyaw Zeyar Myint
- Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; E-Mail:
| | - Xiang-Qun Xie
- Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; E-Mail:
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15260, USA
- Pittsburgh Chemical Methodologies & Library Development (PCMLD) and Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
- * Author to whom correspondence should be addressed; E-Mail: ; Tel.: +1-412-383-5276; Fax: +1-412-383-7436
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