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Masand VH, Al-Hussain SA, Alzahrani AY, Al-Mutairi AA, Hussien RA, Samad A, Zaki MEA. Estrogen Receptor Alpha Binders for Hormone-Dependent Forms of Breast Cancer: e-QSAR and Molecular Docking Supported by X-ray Resolved Structures. ACS OMEGA 2024; 9:16759-16774. [PMID: 38617692 PMCID: PMC11007693 DOI: 10.1021/acsomega.4c00906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 03/16/2024] [Accepted: 03/19/2024] [Indexed: 04/16/2024]
Abstract
Cancer, a life-disturbing and lethal disease with a high global impact, causes significant economic, social, and health challenges. Breast cancer refers to the abnormal growth of cells originating from breast tissues. Hormone-dependent forms of breast cancer, such as those influenced by estrogen, prompt the exploration of estrogen receptors as targets for potential therapeutic interventions. In this study, we conducted e-QSAR molecular docking and molecular dynamics analyses on a diverse set of inhibitors targeting estrogen receptor alpha (ER-α). The e-QSAR model is based on a genetic algorithm combined with multilinear regression analysis. The newly developed model possesses a balance between predictive accuracy and mechanistic insights adhering to the OECD guidelines. The e-QSAR model pointed out that sp2-hybridized carbon and nitrogen atoms are important atoms governing binding profiles. In addition, a specific combination of H-bond donors and acceptors with carbon, nitrogen, and ring sulfur atoms also plays a crucial role. The results are supported by molecular docking, MD simulations, and X-ray-resolved structures. The novel results could be useful for future drug development for ER-α.
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Affiliation(s)
- Vijay H Masand
- Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati 444 602, Maharashtra, India
| | - Sami A Al-Hussain
- Department of Chemistry, College of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 11623, Saudi Arabia
| | - Abdullah Y Alzahrani
- Department of Chemistry, Faculty of Science and Arts, King Khalid University, Mohail 61421, Saudi Arabia
| | - Aamal A Al-Mutairi
- Department of Chemistry, College of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 11623, Saudi Arabia
| | - Rania A Hussien
- Department of Chemistry, Faculty of Science, Al-Baha University, Al-Baha 65799, Kingdom of Saudi Arabia
| | - Abdul Samad
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tishk International University, Erbil 44001, Iraq
| | - Magdi E A Zaki
- Department of Chemistry, College of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 11623, Saudi Arabia
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2
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Jawarkar RD, Zaki MEA, Al-Hussain SA, Al-Mutairi AA, Samad A, Masand V, Humane V, Mali S, Alzahrani AYA, Rashid S, Elossaily GM. Mechanistic QSAR modeling derived virtual screening, drug repurposing, ADMET and in- vitro evaluation to identify anticancer lead as lysine-specific demethylase 5a inhibitor. J Biomol Struct Dyn 2024:1-31. [PMID: 38385447 DOI: 10.1080/07391102.2024.2319104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 02/11/2024] [Indexed: 02/23/2024]
Abstract
A lysine-specific demethylase is an enzyme that selectively eliminates methyl groups from lysine residues. KDM5A, also known as JARID1A or RBP2, belongs to the KDM5 Jumonji histone demethylase subfamily. To identify novel molecules that interact with the LSD5A receptor, we created a quantitative structure-activity relationship (QSAR) model. A group of 435 compounds was used in a study of the quantitative relationship between structure and activity to guess the IC50 values for blocking LASD5A. We used a genetic algorithm-multilinear regression-based quantitative structure-activity connection model to forecast the bioactivity (PIC50) of 1615 food and drug administration pharmaceuticals from the zinc database with the goal of repurposing clinically used medications. We used molecular docking, molecular dynamic simulation modelling, and molecular mechanics generalised surface area analysis to investigate the molecule's binding mechanism. A genetic algorithm and multi-linear regression method were used to make six variable-based quantitative structure-activity relationship models that worked well (R2 = 0.8521, Q2LOO = 0.8438, and Q2LMO = 0.8414). ZINC000000538621 was found to be a new hit against LSD5A after a quantitative structure-activity relationship-based virtual screening of 1615 zinc food and drug administration compounds. The docking analysis revealed that the hit molecule 11 in the KDM5A binding pocket adopted a conformation similar to the pdb-6bh1 ligand (docking score: -8.61 kcal/mol). The results from molecular docking and the quantitative structure-activity relationship were complementary and consistent. The most active lead molecule 11, which has shown encouraging results, has good absorption, distribution, metabolism, and excretion (ADME) properties, and its toxicity has been shown to be minimal. In addition, the MTT assay of ZINC000000538621 with MCF-7 cell lines backs up the in silico studies. We used molecular mechanics generalise borne surface area analysis and a 200-ns molecular dynamics simulation to find structural motifs for KDM5A enzyme interactions. Thus, our strategy will likely expand food and drug administration molecule repurposing research to find better anticancer drugs and therapies.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Rahul D Jawarkar
- Department of Medicinal Chemistry and Drug discovery, Dr. Rajendra Gode Institute of Pharmacy, Amravati, Maharashtra, India
| | - Magdi E A Zaki
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | - Sami A Al-Hussain
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | - Aamal A Al-Mutairi
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | - Abdul Samad
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tishk International University, Erbil, Kurdistan Region, Iraq
| | - Vijay Masand
- Department of Chemistry, Amravati, Maharashtra, India
| | - Vivek Humane
- Department of Chemistry, Shri R. R. Lahoti Science college, Morshi District: Amravati, Maharashtra, India
| | - Suraj Mali
- School of Pharmacy, D.Y. Patil University (Deemed to be University), Nerul, Navi Mumbai, India
| | | | - Summya Rashid
- Department of Pharmacology & Toxicology, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Gehan M Elossaily
- Department of Basic Medical Sciences, College of Medicine, AlMaarefa University, Riyadh, Saudi Arabia
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Zaki MEA, AL-Hussain SA, Al-Mutairi AA, Samad A, Masand VH, Ingle RG, Rathod VD, Gaikwad NM, Rashid S, Khatale PN, Burakale PV, Jawarkar RD. Application of in-silico drug discovery techniques to discover a novel hit for target-specific inhibition of SARS-CoV-2 Mpro's revealed allosteric binding with MAO-B receptor: A theoretical study to find a cure for post-covid neurological disorder. PLoS One 2024; 19:e0286848. [PMID: 38227609 PMCID: PMC10790994 DOI: 10.1371/journal.pone.0286848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 05/24/2023] [Indexed: 01/18/2024] Open
Abstract
Several studies have revealed that SARS-CoV-2 damages brain function and produces significant neurological disability. The SARS-CoV-2 coronavirus, which causes COVID-19, may infect the heart, kidneys, and brain. Recent research suggests that monoamine oxidase B (MAO-B) may be involved in metabolomics variations in delirium-prone individuals and severe SARS-CoV-2 infection. In light of this situation, we have employed a variety of computational to develop suitable QSAR model using PyDescriptor and genetic algorithm-multilinear regression (GA-MLR) models (R2 = 0.800-793, Q2LOO = 0.734-0.727, and so on) on the data set of 106 molecules whose anti-SARS-CoV-2 activity was empirically determined. QSAR models generated follow OECD standards and are predictive. QSAR model descriptors were also observed in x-ray-resolved structures. After developing a QSAR model, we did a QSAR-based virtual screening on an in-house database of 200 compounds and found a potential hit molecule. The new hit's docking score (-8.208 kcal/mol) and PIC50 (7.85 M) demonstrated a significant affinity for SARS-CoV-2's main protease. Based on post-covid neurodegenerative episodes in Alzheimer's and Parkinson's-like disorders and MAO-B's role in neurodegeneration, the initially disclosed hit for the SARS-CoV-2 main protease was repurposed against the MAO-B receptor using receptor-based molecular docking, which yielded a docking score of -12.0 kcal/mol. This shows that the compound that inhibits SARS-CoV-2's primary protease may bind allosterically to the MAO-B receptor. We then did molecular dynamic simulations and MMGBSA tests to confirm molecular docking analyses and quantify binding free energy. The drug-receptor complex was stable during the 150-ns MD simulation. The first computational effort to show in-silico inhibition of SARS-CoV-2 Mpro and allosteric interaction of novel inhibitors with MAO-B in post-covid neurodegenerative symptoms and other disorders. The current study seeks a novel compound that inhibits SAR's COV-2 Mpro and perhaps binds MAO-B allosterically. Thus, this study will enable scientists design a new SARS-CoV-2 Mpro that inhibits the MAO-B receptor to treat post-covid neurological illness.
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Affiliation(s)
- Magdi E. A. Zaki
- Faculty of Science, Department of Chemistry, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | - Sami A. AL-Hussain
- Faculty of Science, Department of Chemistry, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | - Aamal A. Al-Mutairi
- Faculty of Science, Department of Chemistry, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | - Abdul Samad
- Faculty of Pharmacy, Department of Pharmaceutical Chemistry, Tishk International University, Erbil, Kurdistan Region, Iraq
| | - Vijay H. Masand
- Department of Chemistry, Vidya Bharti Mahavidyalaya, Amravati, Maharashtra, India
| | - Rahul G. Ingle
- Datta Meghe College of Pharmacy, DMIHER Deemed University, Wardha, India
| | - Vivek Digamber Rathod
- Department of Chemical Technology, Dr Babasaheb Ambedkar Marathwada University, Aurangabad, India
| | | | - Summya Rashid
- Department of Pharmacology & Toxicology, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Pravin N. Khatale
- Department of Medicinal Chemistry and Drug Discovery, Dr Rajendra Gode Institute of Pharmacy, University Mardi Road, Amravati, Maharashtra, India
| | - Pramod V. Burakale
- Department of Medicinal Chemistry and Drug Discovery, Dr Rajendra Gode Institute of Pharmacy, University Mardi Road, Amravati, Maharashtra, India
| | - Rahul D. Jawarkar
- Department of Medicinal Chemistry and Drug Discovery, Dr Rajendra Gode Institute of Pharmacy, University Mardi Road, Amravati, Maharashtra, India
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Veríssimo GC, Pantaleão SQ, Fernandes PDO, Gertrudes JC, Kronenberger T, Honorio KM, Maltarollo VG. MASSA Algorithm: an automated rational sampling of training and test subsets for QSAR modeling. J Comput Aided Mol Des 2023; 37:735-754. [PMID: 37804393 DOI: 10.1007/s10822-023-00536-y] [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: 06/06/2023] [Accepted: 09/14/2023] [Indexed: 10/09/2023]
Abstract
QSAR models capable of predicting biological, toxicity, and pharmacokinetic properties were widely used to search lead bioactive molecules in chemical databases. The dataset's preparation to build these models has a strong influence on the quality of the generated models, and sampling requires that the original dataset be divided into training (for model training) and test (for statistical evaluation) sets. This sampling can be done randomly or rationally, but the rational division is superior. In this paper, we present MASSA, a Python tool that can be used to automatically sample datasets by exploring the biological, physicochemical, and structural spaces of molecules using PCA, HCA, and K-modes. The proposed algorithm is very useful when the variables used for QSAR are not available or to construct multiple QSAR models with the same training and test sets, producing models with lower variability and better values for validation metrics. These results were obtained even when the descriptors used in the QSAR/QSPR were different from those used in the separation of training and test sets, indicating that this tool can be used to build models for more than one QSAR/QSPR technique. Finally, this tool also generates useful graphical representations that can provide insights into the data.
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Affiliation(s)
- Gabriel Corrêa Veríssimo
- Department of Pharmaceutical Products, Faculty of Pharmacy, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil
| | | | - Philipe de Olveira Fernandes
- Department of Pharmaceutical Products, Faculty of Pharmacy, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil
| | - Jadson Castro Gertrudes
- Department of Computing, Institute of Exact and Biological Sciences, Federal University of Ouro Preto, Ouro Preto, MG, 35400-000, Brazil
| | - Thales Kronenberger
- Department of Pharmaceutical and Medicinal Chemistry, University of Tübingen, Tübingen, BW, 72076, Germany
| | - Kathia Maria Honorio
- Federal University of ABC, Santo André, SP, 09210-170, Brazil
- School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, SP, 03828-000, Brazil
| | - Vinícius Gonçalves Maltarollo
- Department of Pharmaceutical Products, Faculty of Pharmacy, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil.
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Luukkonen S, Meijer E, Tricarico GA, Hofmans J, Stouten PFW, van Westen GJP, Lenselink EB. Large-Scale Modeling of Sparse Protein Kinase Activity Data. J Chem Inf Model 2023. [PMID: 37294674 DOI: 10.1021/acs.jcim.3c00132] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Protein kinases are a protein family that plays an important role in several complex diseases such as cancer and cardiovascular and immunological diseases. Protein kinases have conserved ATP binding sites, which when targeted can lead to similar activities of inhibitors against different kinases. This can be exploited to create multitarget drugs. On the other hand, selectivity (lack of similar activities) is desirable in order to avoid toxicity issues. There is a vast amount of protein kinase activity data in the public domain, which can be used in many different ways. Multitask machine learning models are expected to excel for these kinds of data sets because they can learn from implicit correlations between tasks (in this case activities against a variety of kinases). However, multitask modeling of sparse data poses two major challenges: (i) creating a balanced train-test split without data leakage and (ii) handling missing data. In this work, we construct a protein kinase benchmark set composed of two balanced splits without data leakage, using random and dissimilarity-driven cluster-based mechanisms, respectively. This data set can be used for benchmarking and developing protein kinase activity prediction models. Overall, the performance on the dissimilarity-driven cluster-based split is lower than on random split-based sets for all models, indicating poor generalizability of models. Nevertheless, we show that multitask deep learning models, on this very sparse data set, outperform single-task deep learning and tree-based models. Finally, we demonstrate that data imputation does not improve the performance of (multitask) models on this benchmark set.
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Affiliation(s)
- Sohvi Luukkonen
- Leiden Academic Centre of Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
| | - Erik Meijer
- Leiden Academic Centre of Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
| | | | - Johan Hofmans
- Galapagos NV, Generaal De Wittelaan L11 A3, 2800 Mechelen, Belgium
| | - Pieter F W Stouten
- Leiden Academic Centre of Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
- Galapagos NV, Generaal De Wittelaan L11 A3, 2800 Mechelen, Belgium
- Stouten Pharma Consultancy BV, Kempenarestraat 47, 2860 Sint-Katelijne-Waver, Belgium
| | - Gerard J P van Westen
- Leiden Academic Centre of Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
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Zaki MEA, Al-Hussain SA, Al-Mutairi AA, Samad A, Ghosh A, Chaudhari S, Khatale PN, Ajmire P, Jawarkar RD. In-silico studies to recognize repurposing therapeutics toward arginase-I inhibitors as a potential onco-immunomodulators. Front Pharmacol 2023; 14:1129997. [PMID: 37144217 PMCID: PMC10151555 DOI: 10.3389/fphar.2023.1129997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 02/27/2023] [Indexed: 05/06/2023] Open
Abstract
Rudolf Virchow was the first person to point out the important link between immune function and cancer. He did this by noticing that leukocytes were often found in tumors. Overexpression of arginase 1 (ARG1) and inducible nitric oxide synthase (iNOS) in myeloid-derived suppressor cells (MDSCs) and tumour-associated macrophages (TAMs) depletes both intracellular and extracellular arginine. TCR signalling is slowed as a result, and the same types of cells produce reactive oxygen and nitrogen species (ROS and RNS), which aggravates the situation. Human arginase I is a double-stranded manganese metalloenzyme that helps L-arginine break down into L-ornithine and urea. Thus, a quantitative structure-activity relationship (QSAR) analysis was performed to unearth the unrecognised structural aspects crucial for arginase-I inhibition. In this work, a balanced QSAR model with good prediction performance and clear mechanistic interpretation was developed using a dataset of 149 molecules encompassing a broad range of structural scaffolds and compositions. The model was made to meet OECD standards, and all of its validation parameters have values that are higher than the minimum requirements (R2 tr = 0.89, Q2 LMO = 0.86, and R2 ex = 0.85). The present QSAR study linked structural factors to arginase-I inhibitory action, including the proximity of lipophilic atoms to the molecule's centre of mass (within 3A), the position of the donor to the ring nitrogen (exactly 3 bonds away), and the surface area ratio. As OAT-1746 and two others are the only arginase-I inhibitors in development at the time, we have performed a QSAR-based virtual screening with 1650 FDA compounds taken from the zinc database. In this screening, 112 potential hit compounds were found to have a PIC50 value of less than 10 nm against the arginase-I receptor. The created QSAR model's application domain was evaluated in relation to the most active hit molecules identified using QSAR-based virtual screening, utilising a training set of 149 compounds and a prediction set of 112 hit molecules. As shown in the Williams plot, the top hit molecule, ZINC000252286875, has a low leverage value of HAT i/i h* = 0.140, placing it towards the boundary of the usable range. Furthermore, one of 112 hit molecules with a docking score of -10.891 kcal/mol (PIC50 = 10.023 M) was isolated from a study of arginase-I using molecular docking. Protonated ZINC000252286875-linked arginase-1 showed 2.9 RMSD, whereas non-protonated had 1.8. RMSD plots illustrate protein stability in protonated and non-protonated ZINC000252286875-bound states. Protonated-ZINC000252286875-bound proteins contain 25 Rg. The non-protonated protein-ligand combination exhibits a 25.2-Rg, indicating compactness. Protonated and non-protonated ZINC000252286875 stabilised protein targets in binding cavities posthumously. Significant root mean square fluctuations (RMSF) were seen in the arginase-1 protein at a small number of residues for a time function of 500 ns in both the protonated and unprotonated states. Protonated and non-protonated ligands interacted with proteins throughout the simulation. ZINC000252286875 bound Lys64, Asp124, Ala171, Arg222, Asp232, and Gly250. Aspartic acid residue 232 exhibited 200% ionic contact. 500-ns simulations-maintained ions. Salt bridges for ZINC000252286875 aided docking. ZINC000252286875 created six ionic bonds with Lys68, Asp117, His126, Ala171, Lys224, and Asp232 residues. Asp117, His126, and Lys224 showed 200% ionic interactions. In protonated and deprotonated states, GbindvdW, GbindLipo, and GbindCoulomb energies played crucial role. Moreover, ZINC000252286875 meets all of the ADMET standards to serve as a drug. As a result, the current analyses were successful in locating a novel and potent hit molecule that inhibits arginase-I effectively at nanomolar concentrations. The results of this investigation can be used to develop brand-new arginase I inhibitors as an alternative immune-modulating cancer therapy.
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Affiliation(s)
- Magdi E. A. Zaki
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
- *Correspondence: Magdi E. A. Zaki, ; Rahul D. Jawarkar,
| | - Sami A. Al-Hussain
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | - Aamal A. Al-Mutairi
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | - Abdul Samad
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tishk International University, Erbil, Kurdistan Region, Iraq
| | - Arabinda Ghosh
- Microbiology Division, Department of Botany, Gauhati University, Guwahati, India
| | - Somdatta Chaudhari
- Department of Pharmaceutical Chemistry, Progressive Education Society’s Modern College of Pharmacy, Pune, India
| | - Pravin N. Khatale
- Department of Medicinal Chemistry, Dr Rajendra Gode Institute of Pharmacy, Amravati, Maharashtra, India
| | - Prashant Ajmire
- Department of Medicinal Chemistry, Dr Rajendra Gode Institute of Pharmacy, Amravati, Maharashtra, India
| | - Rahul D. Jawarkar
- Department of Medicinal Chemistry, Dr Rajendra Gode Institute of Pharmacy, Amravati, Maharashtra, India
- *Correspondence: Magdi E. A. Zaki, ; Rahul D. Jawarkar,
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Rep Kaulić V, Racané L, Leventić M, Šubarić D, Rastija V, Glavaš-Obrovac L, Raić-Malić S. Synthesis, Antiproliferative Evaluation and QSAR Analysis of Novel Halogen- and Amidino-Substituted Benzothiazoles and Benzimidazoles. Int J Mol Sci 2022; 23:ijms232415843. [PMID: 36555479 PMCID: PMC9785280 DOI: 10.3390/ijms232415843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 12/08/2022] [Accepted: 12/09/2022] [Indexed: 12/15/2022] Open
Abstract
Syntheses of 6-halogen-substituted benzothiazoles were performed by condensation of 4-hydroxybenzaldehydes and 2-aminotiophenoles and subsequent O-alkylation with appropriate halides, whereas 6-amidino-substituted benzothiazoles were synthesized by condensation of 5-amidino-2-aminothiophenoles and corresponding benzaldehydes. While most of the compounds from non-substituted and halogen-substituted benzothiazole series showed marginal antiproliferative activity on tested tumor cell lines, amidino benzazoles exhibited stronger inhibitory activity. Generally, imidazolyl benzothiazoles showed pronounced and nonselective activity, with the exception of 36c which had a strong inhibitory effect on HuT78 cells (IC50 = 1.6 µM) without adverse cytotoxicity on normal BJ cells (IC50 >100 µM). Compared to benzothiazoles, benzimidazole structural analogs 45a−45c and 46c containing the 1,2,3-triazole ring exhibited pronounced and selective antiproliferative activity against HuT78 cells with IC50 < 10 µM. Moreover, compounds 45c and 46c containing the methoxy group at the phenoxy unit were not toxic to normal BJ cells. Of all the tested compounds, benzimidazole 45a with the unsubstituted phenoxy central core showed the most pronounced cell growth inhibition on THP1 cells in the nanomolar range (IC50 = 0.8 µM; SI = 70). QSAR models of antiproliferative activity for benzazoles on T-cell lymphoma (HuT78) and non-tumor MDCK-1 cells elucidated the effects of the substituents at position 6 of benzazoles, demonstrating their dependence on the topological and spatial distribution of atomic mass, polarizability, and van der Waals volumes. A notable cell cycle perturbation with higher accumulation of cells in the G2/M phase, and a significant cell increase in subG0/G1 phase were found in HuT78 cells treated with 36c, 42c, 45a−45c and 46c. Apoptotic morphological changes, an externalization of phosphatidylserine, and changes in the mitochondrial membrane potential of treated cells were observed as well.
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Affiliation(s)
- Valentina Rep Kaulić
- Department of Organic Chemistry, Faculty of Chemical Engineering and Technology, University of Zagreb, Marulićev trg 20, 10000 Zagreb, Croatia
| | - Livio Racané
- Department of Applied Chemistry, Faculty of Textile Technology, University of Zagreb, Prilaz Baruna Filipovića 28, 10000 Zagreb, Croatia
| | - Marijana Leventić
- Department of Medicinal Chemistry, Biochemistry and Laboratory Medicine, Faculty of Medicine Osijek, University Josip Juraj Strossmayer of Osijek, Josipa Huttlera 4, 31000 Osijek, Croatia
| | - Domagoj Šubarić
- Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia
| | - Vesna Rastija
- Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia
| | - Ljubica Glavaš-Obrovac
- Department of Medicinal Chemistry, Biochemistry and Laboratory Medicine, Faculty of Medicine Osijek, University Josip Juraj Strossmayer of Osijek, Josipa Huttlera 4, 31000 Osijek, Croatia
- Correspondence: (L.G.-O.); (S.R.-M.)
| | - Silvana Raić-Malić
- Department of Organic Chemistry, Faculty of Chemical Engineering and Technology, University of Zagreb, Marulićev trg 20, 10000 Zagreb, Croatia
- Correspondence: (L.G.-O.); (S.R.-M.)
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8
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Masand VH, Al-Hussain SA, Rathore MM, Thakur SD, Akasapu S, Samad A, Al-Mutairi AA, Zaki MEA. Pharmacophore Synergism in Diverse Scaffold Clinches in Aurora Kinase B. Int J Mol Sci 2022; 23:ijms232314527. [PMID: 36498857 PMCID: PMC9739353 DOI: 10.3390/ijms232314527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/01/2022] [Accepted: 11/11/2022] [Indexed: 11/23/2022] Open
Abstract
Aurora kinase B (AKB) is a crucial signaling kinase with an important role in cell division. Therefore, inhibition of AKB is an attractive approach to the treatment of cancer. In the present work, extensive quantitative structure-activity relationships (QSAR) analysis has been performed using a set of 561 structurally diverse aurora kinase B inhibitors. The Organization for Economic Cooperation and Development (OECD) guidelines were used to develop a QSAR model that has high statistical performance (R2tr = 0.815, Q2LMO = 0.808, R2ex = 0.814, CCCex = 0.899). The seven-variable-based newly developed QSAR model has an excellent balance of external predictive ability (Predictive QSAR) and mechanistic interpretation (Mechanistic QSAR). The QSAR analysis successfully identifies not only the visible pharmacophoric features but also the hidden features. The analysis indicates that the lipophilic and polar groups-especially the H-bond capable groups-must be present at a specific distance from each other. Moreover, the ring nitrogen and ring carbon atoms play important roles in determining the inhibitory activity for AKB. The analysis effectively captures reported as well as unreported pharmacophoric features. The results of the present analysis are also supported by the reported crystal structures of inhibitors bound to AKB.
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Affiliation(s)
- Vijay H. Masand
- Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati 444602, Maharashtra, India
- Correspondence: (V.H.M.); (M.E.A.Z.)
| | - Sami A. Al-Hussain
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 11623, Saudi Arabia
| | - Mithilesh M. Rathore
- Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati 444602, Maharashtra, India
| | - Sumer D. Thakur
- Department of Chemistry, RDIK and NKD College, Badnera, Amravati 444701, Maharashtra, India
| | | | - Abdul Samad
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tishk International University, Erbil 44001, Iraq
| | - Aamal A. Al-Mutairi
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 11623, Saudi Arabia
| | - Magdi E. A. Zaki
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 11623, Saudi Arabia
- Correspondence: (V.H.M.); (M.E.A.Z.)
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9
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Veríssimo GC, Serafim MSM, Kronenberger T, Ferreira RS, Honorio KM, Maltarollo VG. Designing drugs when there is low data availability: one-shot learning and other approaches to face the issues of a long-term concern. Expert Opin Drug Discov 2022; 17:929-947. [PMID: 35983695 DOI: 10.1080/17460441.2022.2114451] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Modern drug discovery generally is accessed by useful information from previous large databases or uncovering novel data. The lack of biological and/or chemical data tends to slow the development of scientific research and innovation. Here, approaches that may help provide solutions to generate or obtain enough relevant data or improve/accelerate existing methods within the last five years were reviewed. AREAS COVERED One-shot learning (OSL) approaches, structural modeling, molecular docking, scoring function space (SFS), molecular dynamics (MD), and quantum mechanics (QM) may be used to amplify the amount of available data to drug design and discovery campaigns, presenting methods, their perspectives, and discussions to be employed in the near future. EXPERT OPINION Recent works have successfully used these techniques to solve a range of issues in the face of data scarcity, including complex problems such as the challenging scenario of drug design aimed at intrinsically disordered proteins and the evaluation of potential adverse effects in a clinical scenario. These examples show that it is possible to improve and kickstart research from scarce available data to design and discover new potential drugs.
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Affiliation(s)
- Gabriel C Veríssimo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Mateus Sá M Serafim
- Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Thales Kronenberger
- Department of Medical Oncology and Pneumology, Internal Medicine VIII, University Hospital of Tübingen, Tübingen, Germany.,School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Rafaela S Ferreira
- Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Kathia M Honorio
- Escola de Artes, Ciências e Humanidades, Universidade de São Paulo (USP), São Paulo, Brazil.,Centro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André, Brazil
| | - Vinícius G Maltarollo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
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10
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Jawarkar RD, Sharma P, Jain N, Gandhi A, Mukerjee N, Al-Mutairi AA, Zaki MEA, Al-Hussain SA, Samad A, Masand VH, Ghosh A, Bakal RL. QSAR, Molecular Docking, MD Simulation and MMGBSA Calculations Approaches to Recognize Concealed Pharmacophoric Features Requisite for the Optimization of ALK Tyrosine Kinase Inhibitors as Anticancer Leads. Molecules 2022; 27:molecules27154951. [PMID: 35956900 PMCID: PMC9370430 DOI: 10.3390/molecules27154951] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 07/15/2022] [Accepted: 07/22/2022] [Indexed: 12/04/2022] Open
Abstract
ALK tyrosine kinase ALK TK is an important target in the development of anticancer drugs. In the present work, we have performed a QSAR analysis on a dataset of 224 molecules in order to quickly predict anticancer activity on query compounds. Double cross validation assigns an upward plunge to the genetic algorithm−multi linear regression (GA-MLR) based on robust univariate and multivariate QSAR models with high statistical performance reflected in various parameters like, fitting parameters; R2 = 0.69−0.87, F = 403.46−292.11, etc., internal validation parameters; Q2LOO = 0.69−0.86, Q2LMO = 0.69−0.86, CCCcv = 0.82−0.93, etc., or external validation parameters Q2F1 = 0.64−0.82, Q2F2 = 0.63−0.82, Q2F3 = 0.65−0.81, R2ext = 0.65−0.83 including RMSEtr < RMSEcv. The present QSAR evaluation successfully identified certain distinct structural features responsible for ALK TK inhibitory potency, such as planar Nitrogen within four bonds from the Nitrogen atom, Fluorine atom within five bonds beside the non-ring Oxygen atom, lipophilic atoms within two bonds from the ring Carbon atoms. Molecular docking, MD simulation, and MMGBSA computation results are in consensus with and complementary to the QSAR evaluations. As a result, the current study assists medicinal chemists in prioritizing compounds for experimental detection of anticancer activity, as well as their optimization towards more potent ALK tyrosine kinase inhibitor.
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Affiliation(s)
- Rahul D. Jawarkar
- Faculty of Pharmacy, Oriental University, Indore 453555, Madhya Pradesh, India; (P.S.); (N.J.)
- Correspondence: (R.D.J.); (M.E.A.Z.); Tel.: +91-7385178762 (R.D.J.)
| | - Praveen Sharma
- Faculty of Pharmacy, Oriental University, Indore 453555, Madhya Pradesh, India; (P.S.); (N.J.)
| | - Neetesh Jain
- Faculty of Pharmacy, Oriental University, Indore 453555, Madhya Pradesh, India; (P.S.); (N.J.)
| | - Ajaykumar Gandhi
- Department of Chemistry, Government College of Arts and Science, Aurangabad 431004, Maharashtra, India;
| | - Nobendu Mukerjee
- Department of Microbiology, Ramakrishna Mission Vivekananda Centenary College, Kolkata 700118, West Bengal, India;
| | - Aamal A. Al-Mutairi
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia; (A.A.A.-M.); (S.A.A.-H.)
| | - Magdi E. A. Zaki
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia; (A.A.A.-M.); (S.A.A.-H.)
- Correspondence: (R.D.J.); (M.E.A.Z.); Tel.: +91-7385178762 (R.D.J.)
| | - Sami A. Al-Hussain
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia; (A.A.A.-M.); (S.A.A.-H.)
| | - Abdul Samad
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tishk International University, Erbil 44001, Kurdistan Region, Iraq;
| | - Vijay H. Masand
- Department of Chemistry, Vidyabharati Mahavidyalalya, Camp Road, Amravati 444602, Maharashtra, India;
| | - Arabinda Ghosh
- Microbiology Division, Department of Botany, Gauhati University, Guwahati 781014, Assam, India;
| | - Ravindra L. Bakal
- Department of Medicinal Chemistry, Dr. Rajendra Gode Institute of Pharmacy, University-Mardi Road, Amravati 444603, Maharashtra, India;
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QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSA. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27154758. [PMID: 35897936 PMCID: PMC9332886 DOI: 10.3390/molecules27154758] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 07/11/2022] [Accepted: 07/19/2022] [Indexed: 12/05/2022]
Abstract
Using 84 structurally diverse and experimentally validated LSD1/KDM1A inhibitors, quantitative structure–activity relationship (QSAR) models were built by OECD requirements. In the QSAR analysis, certainly significant and understated pharmacophoric features were identified as critical for LSD1 inhibition, such as a ring Carbon atom with exactly six bonds from a Nitrogen atom, partial charges of lipophilic atoms within eight bonds from a ring Sulphur atom, a non-ring Oxygen atom exactly nine bonds from the amide Nitrogen, etc. The genetic algorithm–multi-linear regression (GA-MLR) and double cross-validation criteria were used to create robust QSAR models with high predictability. In this study, two QSAR models were developed, with fitting parameters like R2 = 0.83–0.81, F = 61.22–67.96, internal validation parameters such as Q2LOO = 0.79–0.77, Q2LMO = 0.78–0.76, CCCcv = 0.89–0.88, and external validation parameters such as, R2ext = 0.82 and CCCex = 0.90. In terms of mechanistic interpretation and statistical analysis, both QSAR models are well-balanced. Furthermore, utilizing the pharmacophoric features revealed by QSAR modelling, molecular docking experiments corroborated with the most active compound’s binding to the LSD1 receptor. The docking results are then refined using Molecular dynamic simulation and MMGBSA analysis. As a consequence, the findings of the study can be used to produce LSD1/KDM1A inhibitors as anticancer leads.
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Bukhari SNA, Elsherif MA, Junaid K, Ejaz H, Alam P, Samad A, Jawarkar RD, Masand VH. Perceiving the Concealed and Unreported Pharmacophoric Features of the 5-Hydroxytryptamine Receptor Using Balanced QSAR Analysis. Pharmaceuticals (Basel) 2022; 15:ph15070834. [PMID: 35890133 PMCID: PMC9316833 DOI: 10.3390/ph15070834] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 06/12/2022] [Accepted: 06/25/2022] [Indexed: 02/04/2023] Open
Abstract
The 5-hydroxytryptamine receptor 6 (5-HT6) has gained attention as a target for developing therapeutics for Alzheimer’s disease, schizophrenia, cognitive dysfunctions, anxiety, and depression, to list a few. In the present analysis, a larger and diverse dataset of 1278 molecules covering a broad chemical and activity space was used to identify visual and concealed structural features associated with binding affinity for 5-HT6. For this, quantitative structure–activity relationships (QSAR) and molecular docking analyses were executed. This led to the development of a statistically robust QSAR model with a balance of excellent predictivity (R2tr = 0.78, R2ex = 0.77), the identification of unreported aspects of known features, and also novel mechanistic interpretations. Molecular docking and QSAR provided similar as well as complementary results. The present analysis indicates that the partial charges on ring carbons present within four bonds from a sulfur atom, the occurrence of sp3-hybridized carbon atoms bonded with donor atoms, and a conditional occurrence of lipophilic atoms/groups from nitrogen atoms, which are prominent but unreported pharmacophores that should be considered while optimizing a molecule for 5-HT6. Thus, the present analysis led to identification of some novel unreported structural features that govern the binding affinity of a molecule. The results could be beneficial in optimizing the molecules for 5-HT6.
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Affiliation(s)
- Syed Nasir Abbas Bukhari
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jouf University, Sakaka 72388, Saudi Arabia
| | | | - Kashaf Junaid
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Sakaka 72388, Saudi Arabia
| | - Hasan Ejaz
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Sakaka 72388, Saudi Arabia
| | - Pravej Alam
- Department of Biology, College of Science and Humanities, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
| | - Abdul Samad
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tishk International University, Erbil 44001, Iraq
| | - Rahul D Jawarkar
- Department of Medicinal Chemistry, Dr. Rajendra Gode Institute of Pharmacy, University-Mardi Road, Amravati 444603, Maharashtra, India
| | - Vijay H Masand
- Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati 444602, Maharashtra, India
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13
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Mechanistic Analysis of Chemically Diverse Bromodomain-4 Inhibitors Using Balanced QSAR Analysis and Supported by X-ray Resolved Crystal Structures. Pharmaceuticals (Basel) 2022; 15:ph15060745. [PMID: 35745664 PMCID: PMC9231298 DOI: 10.3390/ph15060745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 06/07/2022] [Accepted: 06/07/2022] [Indexed: 11/17/2022] Open
Abstract
Bromodomain-4 (BRD-4) is a key enzyme in post-translational modifications, transcriptional activation, and many other cellular processes. Its inhibitors find their therapeutic usage in cancer, acute heart failure, and inflammation to name a few. In the present study, a dataset of 980 molecules with a significant diversity of structural scaffolds and composition was selected to develop a balanced QSAR model possessing high predictive capability and mechanistic interpretation. The model was built as per the OECD (Organisation for Economic Co-operation and Development) guidelines and fulfills the endorsed threshold values for different validation parameters (R2tr = 0.76, Q2LMO = 0.76, and R2ex = 0.76). The present QSAR analysis identified that anti-BRD-4 activity is associated with structural characters such as the presence of saturated carbocyclic rings, the occurrence of carbon atoms near the center of mass of a molecule, and a specific combination of planer or aromatic nitrogen with ring carbon, donor, and acceptor atoms. The outcomes of the present analysis are also supported by X-ray-resolved crystal structures of compounds with BRD-4. Thus, the QSAR model effectively captured salient as well as unreported hidden pharmacophoric features. Therefore, the present study successfully identified valuable novel pharmacophoric features, which could be beneficial for the future optimization of lead/hit compounds for anti-BRD-4 activity.
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14
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Ghosh A, Mukerjee N, Sharma B, Pant A, Kishore Mohanta Y, Jawarkar RD, Bakal RL, Terefe EM, Batiha GES, Mostafa-Hedeab G, Aref Albezrah NK, Dey A, Baishya D. Target Specific Inhibition of Protein Tyrosine Kinase in Conjunction With Cancer and SARS-COV-2 by Olive Nutraceuticals. Front Pharmacol 2022; 12:812565. [PMID: 35356629 PMCID: PMC8959131 DOI: 10.3389/fphar.2021.812565] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 12/24/2021] [Indexed: 12/18/2022] Open
Abstract
The fact that viruses cause human cancer dates back to the early 1980s. By reprogramming cellular signaling pathways, viruses encoded protein that can regulate altered control of cell cycle events. Viruses can interact with a superfamily of membrane bound protein, receptor tyrosine kinase to modulate their activity in order to increase virus entrance into cells and promotion of viral replication within the host. Therefore, our study aimed at screening of inhibitors of tyrosine kinase using natural compounds from olive. Protein tyrosine kinase (PTK) is an important factor for cancer progression and can be linked to coronavirus. It is evident that over expression of Protein tyrosine kinase (PTK) enhance viral endocytosis and proliferation and the use of tyrosine kinase inhibitors reduced the period of infection period. Functional network studies were carried out using two major PTKs viz. Anaplastic lymphoma kinase (ALK) and B-lymphocytic kinase (BTK). They are associated with coronavirus in regulation of cell signaling proteins for cellular processes. We virtually screened for 161 library of natural compounds from olive found overexpressed in ALK and BTK in metastatic as well as virus host cells. We have employed both ligand and target-based approach for drug designing by high throughput screening using Multilinear regression model based QSAR and docking. The QSAR based virtual screening of 161 olive nutraceutical compounds has successfully identified certain new hit; Wedelosin, in which, the descriptor rsa (ratio of molecular surface area to the solvent accessible surface area) plays crucial role in deciding Wedelosin’s inhibitory potency. The best-docked olive nutraceuticals further investigated for the stability and effectivity of the BTK and ALK during in 150 ns molecular dynamics and simulation. Post simulation analysis and binding energy estimation in MMGBSA further revealed the intensive potential of the olive nutraceuticals in PTK inhibition. This study is therefore expected to widen the use of nutraceuticals from olive in cancer as well as SARS-CoV2 alternative therapy.
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Affiliation(s)
- Arabinda Ghosh
- Microbiology Division, Department of Botany, Gauhati University, Guwahati, India
| | - Nobendu Mukerjee
- Department of Microbiology, Ramakrishna Mission Vivekananda Centenary College, Kolkata, India
| | - Bhavdeep Sharma
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala, India
| | - Anushree Pant
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala, India
| | - Yugal Kishore Mohanta
- Department of Applied Biology, University of Science and Technology Meghalaya, Ri Bhoi, India
| | - Rahul D Jawarkar
- Department of Medicinal Chemistry, Dr. Rajendra Gode Institute of Pharmacy, Amravati, India
| | - Ravindrakumar L Bakal
- Department of Medicinal Chemistry, Dr. Rajendra Gode Institute of Pharmacy, Amravati, India
| | - Ermias Mergia Terefe
- Department of Pharmacology and Pharmacognosy, School of Pharmacy and Health Sciences, United states International University-Africa, Nairobi, Kenya
| | - Gaber El-Saber Batiha
- Department of Pharmacology and Therapeutics, Faculty of Veterinary Medicine, Damanhour University, Damanhour, Egypt
| | - Gomaa Mostafa-Hedeab
- Pharmacology Department & Health Research Unit-Medical College-Jouf University, Sakakah, Saudi Arabia.,Pharmacology Department, Faculty of Medicine, Beni-Suef University, Beni-Suef, Egypt
| | | | - Abhijit Dey
- Department of Life Sciences, Presidency University, Kolkata, India
| | - Debabrat Baishya
- Department of Bioengineering, Gauhati University, Guwahati, India
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15
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Jawarkar R, Bakal RL, Zaki ME, Al-Hussain S, Ghosh A, Gandhi A, Mukerjee N, Samad A, Masand VH, Lewaa I. QSAR based virtual screening derived identification of a novel hit as a SARS CoV-229E 3CL pro Inhibitor: GA-MLR QSAR modeling supported by molecular Docking, molecular dynamics simulation and MMGBSA calculation approaches. ARAB J CHEM 2022; 15:103499. [PMID: 34909066 PMCID: PMC8524701 DOI: 10.1016/j.arabjc.2021.103499] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 10/10/2021] [Indexed: 12/26/2022] Open
Abstract
Congruous coronavirus drug targets and analogous lead molecules must be identified as quickly as possible to produce antiviral therapeutics against human coronavirus (HCoV SARS 3CLpro) infections. In the present communication, we bear recognized a HIT candidate for HCoV SARS 3CLpro inhibition. Four Parametric GA-MLR primarily based QSAR model (R2:0.84, R2adj:0.82, Q2loo: 0.78) was once promoted using a dataset over 37 structurally diverse molecules along QSAR based virtual screening (QSAR-VS), molecular docking (MD) then molecular dynamic simulation (MDS) analysis and MMGBSA calculations. The QSAR-based virtual screening was utilized to find novel lead molecules from an in-house database of 100 molecules. The QSAR-vS successfully offered a hit molecule with an improved PEC50 value from 5.88 to 6.08. The benzene ring, phenyl ring, amide oxygen and nitrogen, and other important pharmacophoric sites are revealed via MD and MDS studies. Ile164, Pro188, Leu190, Thr25, His41, Asn46, Thr47, Ser49, Asn189, Gln191, Thr47, and Asn141 are among the key amino acid residues in the S1 and S2 pocket. A stable complex of a lead molecule with the HCoV SARS 3CLpro was discovered using MDS. MM-GBSA calculations resulted from MD simulation results well supported with the binding energies calculated from the docking results. The results of this study can be exploited to develop a novel antiviral target, such as an HCoV SARS 3CLpro Inhibitor.
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Key Words
- 3CLpro, 3C like Protease
- FDA, Food and Drug Administration
- GA-MLR
- GA-MLR, Genetic Algorithm Multilinear Regression
- HCoV SARS 3CLpro
- HCoV-HKU1, Human coronavirus HKU1
- HCoV-NL63, Human coronavirus NL63
- HCoVs, human coronaviruses
- Lead
- MD, Molecular Docking
- MDS, molecular dynamic simulation
- MERS, Middle East Respiratory Syndrome
- MMGBSA calculations
- MMGBSA, Molecular Mechanics Generalized Born and Surface Area
- Molecular docking and MD simulation
- OECD, Organization for Economic Corporation and Development
- QSAR based virtual screening
- QSAR, Quantitative Structure Activity Relationship
- RNA, Ribo-nucleic acid
- SARS, severe acute respiratory sign
- VS, Virtual Screening
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Affiliation(s)
- R.D. Jawarkar
- Department of Medicinal Chemistry, Dr. Rajendra Gode Institute of Pharmacy, University-Mardi Road, Amravati, Maharashtra, 444603, India,Corresponding authors at: Department of Medicinal Chemistry, Dr. Rajendra Gode College of Pharmacy, Mardi Road, Amravati, Maharashtra, India and (Rahul D. Jawarkar). Department of Chemistry, Faculty of Science, Al-Imam Mohammad Ibn Saud Islamic university, Riyadh 13318, Saudi Arabia (Magdi E.A. Zaki)
| | - Ravindrakumar L. Bakal
- Department of Medicinal Chemistry, Dr. Rajendra Gode Institute of Pharmacy, University-Mardi Road, Amravati, Maharashtra, 444603, India
| | - Magdi E.A. Zaki
- Department of Chemistry, Faculty of Science, Al-Imam Mohammad Ibn Saud Islamic university, Riyadh 13318, Saudi Arabia
| | - Sami Al-Hussain
- Department of Chemistry, Faculty of Science, Al-Imam Mohammad Ibn Saud Islamic university, Riyadh 13318, Saudi Arabia,Corresponding authors at: Department of Medicinal Chemistry, Dr. Rajendra Gode College of Pharmacy, Mardi Road, Amravati, Maharashtra, India and (Rahul D. Jawarkar). Department of Chemistry, Faculty of Science, Al-Imam Mohammad Ibn Saud Islamic university, Riyadh 13318, Saudi Arabia (Magdi E.A. Zaki)
| | - Arabinda Ghosh
- Microbiology Division, Department of Botany, Gauhati University, Guwahati, Assam 781014, India
| | - Ajaykumar Gandhi
- Department of Chemistry, Government College of Arts and Science, Aurangabad, Maharashtra 431 004, India
| | - Nobendu Mukerjee
- Department of Microbiology; Ramakrishna Mission Vivekananda Centenary College, Akhil Mukherjee Rd, Chowdhary Para, Rahara, Khardaha, Kolkata, West Bengal 700118, India
| | - Abdul Samad
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tishk International University, Erbil, Kurdistan Region, Iraq
| | - Vijay H. Masand
- Department of Chemistry, Vidyabharti Mahavidyalaya, Camp Road, Amravati Maharashtra, India
| | - Israa Lewaa
- Department of Business Administration, Faculty of Business Administration, Economics & Political Science, The British University in Egypt (BUE), Cairo, Egypt
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16
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Pan T, Geng Y, Hao J, He X, Li J, Gao Y, Shang S, Song Z. Taking Advantage of the Renewable Forest Bioresource Turpentine to Prepare α,β-Unsaturated Compounds as Highly Efficient Fungicidal Candidates. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2021; 69:12985-12993. [PMID: 34723535 DOI: 10.1021/acs.jafc.1c05364] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
In a continuous study on the high-value-added exploration of a renewable forest bioresource turpentine in modern organic agriculture, two series of α-pinene derivatives containing amide and α,β-unsaturated ketone pharmacophores were prepared. Through an in-depth fungicidal activity study, the title compounds presented excellent inhibitory activity against common crop fungi, especially Sclerotinia sclerotiorum, and the notable EC50 values of α,β-unsaturated compounds 3u (funan containing) and 3v (thiophene containing) were 1.657 and 1.749 μg/mL, respectively. Further physiological and biochemical studies on S. sclerotiorum revealed that compounds 3u and 3v reduced the ergosterol content in the cell membrane and increased the permeability of the cell membrane. In combination with their effect on mycelial morphology, the title compounds might have inhibitory effects on the biosynthesis of ergosterol, which is a paramount component of the target cell membrane. Moreover, quantitative structure-activity relationship (QSAR) and SAR studies revealed that the charge distribution of α,β-unsaturated carbonyl ketone derivatives played an important role in the observed fungicidal activity. In summary, this study highlights the design and development of novel high-efficacy turpentine-based antifungal agents.
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Affiliation(s)
- Tingmin Pan
- College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Yuanxiao Geng
- College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Jin Hao
- College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Xiaohua He
- College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Jian Li
- College of Forestry, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Yanqing Gao
- College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Shibin Shang
- Institute of Chemical Industry of Forest Products, Chinese Academy of Forestry, Nanjing, Jiangsu 210042, People's Republic of China
| | - Zhanqian Song
- Institute of Chemical Industry of Forest Products, Chinese Academy of Forestry, Nanjing, Jiangsu 210042, People's Republic of China
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Masand VH, Zaki MEA, Al-Hussain SA, Ghorbal AB, Akasapu S, Lewaa I, Ghosh A, Jawarkar RD. Identification of concealed structural alerts using QSTR modeling for Pseudokirchneriella subcapitata. AQUATIC TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2021; 239:105962. [PMID: 34525418 DOI: 10.1016/j.aquatox.2021.105962] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 08/10/2021] [Accepted: 09/01/2021] [Indexed: 06/13/2023]
Abstract
In the present work, QSTR modeling was conducted for microalga Pseudokirchneriella subcapitata using a data set of 271 molecules belonging to different types of chemical classes for the prediction of EC50 for 72 hr based assays. The balanced QSTR model encompasses seven easily interpretable molecular descriptors and possesses statistical robustness with high predictive ability. This Genetic Algorithm Multi-linear regression (GA-MLR) model was subjected to internal validation, Y-randomization test, applicability domain analysis, and external validation as per the recommended OECD guidelines. The newly developed model fulfilled the threshold values for more than 20 recommended validation parameters including R2 = 0.72, Q2LOO = 0.70, etc. The developed QSTR model was successful in identifying the type of hybridization or specific type of atoms of previously reported and newer structural alerts. Thus, the model could be useful for data gap filling and expanding mechanistic interpretation of toxicity for different chemicals.
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Affiliation(s)
- Vijay H Masand
- Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati, Maharashtra, 444 602, India
| | - Magdi E A Zaki
- Department of Chemistry, Faculty of Science, College of Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi Arabia.
| | - Sami A Al-Hussain
- Department of Chemistry, Faculty of Science, College of Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi Arabia.
| | - Anis Ben Ghorbal
- Department of Mathematics and Statistics, Faculty of Science, College of Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi Arabia.
| | | | - Israa Lewaa
- Assistant Lecturer of Statistics, Faculty of Business Administration, Department of Business Administration, Economics and Political Science, The British University in Egypt, Cairo, Egypt.
| | - Arabinda Ghosh
- Microbiology Division, Department of Botany, Gauhati University, Guwahati, Assam, 781014, India
| | - Rahul D Jawarkar
- Department of Medicinal Chemistry, Dr. Rajendra Gode Institute of Pharmacy, Amravati, Maharashtra, India
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18
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Gandhi A, Masand V, Zaki MEA, Al-Hussain SA, Ghorbal AB, Chapolikar A. QSAR analysis of sodium glucose co-transporter 2 (SGLT2) inhibitors for anti-hyperglycaemic lead development. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2021; 32:731-744. [PMID: 34494464 DOI: 10.1080/1062936x.2021.1971295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 08/18/2021] [Indexed: 06/13/2023]
Abstract
QSAR (Quantitative Structure Activity Relationship) modelling was performed on a dataset of 90 sodium-dependent glucose cotransporter 2 (SGLT2) inhibitors. The quantitative and explicative evaluations revealed some of the subtle and distinguished structural features that are responsible for the inhibitory potency of these compounds against SGLT2, such as less possible number of ring carbons at 8 Å from the lipophilic atoms in the molecule (fringClipo8A) and more possible value for the sum of the partial charges of the lipophilic atoms present within seven bonds from the donor atoms (lipo_don_7Bc). Multivariate GA-MLR (genetic algorithm-multi linear regression) and thorough validation methodology out-turned a statistically robust QSAR model with a very high predictability shown from various statistical parameters. A QSAR model with r2 = 0.83, F = 51.54, Q2LOO = 0.79, Q2LMO = 0.79, CCCcv = 0.88, Q2Fn = 0.76-0.81, r2ext = 0.77, CCCext = 0.85, and with RMSEtr < RMSEcv was proposed. This QSAR model will assist synthetic chemists in the development of the SGLT2 inhibitors as the antidiabetic leads.
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Affiliation(s)
- A Gandhi
- Department of Chemistry, Government College of Arts and Science, Aurangabad, Maharashtra, India
| | - V Masand
- Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati, Maharashtra, India
| | - M E A Zaki
- Department of Chemistry, College of Science, Al-Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | - S A Al-Hussain
- Department of Chemistry, College of Science, Al-Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | - A Ben Ghorbal
- Department of Mathematics and Statistics, College of Sciences, Al-Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | - A Chapolikar
- Department of Chemistry, Government College of Arts and Science, Aurangabad, Maharashtra, India
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19
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Gandhi A, Masand V, Zaki MEA, Al-Hussain SA, Ghorbal AB, Chapolikar A. Quantitative Structure-Activity Relationship Evaluation of MDA-MB-231 Cell Anti-Proliferative Leads. Molecules 2021; 26:molecules26164795. [PMID: 34443383 PMCID: PMC8401583 DOI: 10.3390/molecules26164795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 07/30/2021] [Accepted: 08/03/2021] [Indexed: 11/23/2022] Open
Abstract
In the present endeavor, for the dataset of 219 in vitro MDA-MB-231 TNBC cell antagonists, a (QSAR) quantitative structure–activity relationships model has been carried out. The quantitative and explicative assessments were performed to identify inconspicuous yet pre-eminent structural features that govern the anti-tumor activity of these compounds. GA-MLR (genetic algorithm multi-linear regression) methodology was employed to build statistically robust and highly predictive multiple QSAR models, abiding by the OECD guidelines. Thoroughly validated QSAR models attained values for various statistical parameters well above the threshold values (i.e., R2 = 0.79, Q2LOO = 0.77, Q2LMO = 0.76–0.77, Q2-Fn = 0.72–0.76). Both de novo QSAR models have a sound balance of descriptive and statistical approaches. Decidedly, these QSAR models are serviceable in the development of MDA-MB-231 TNBC cell antagonists.
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Affiliation(s)
- Ajaykumar Gandhi
- Department of Chemistry, Government College of Arts and Science, Aurangabad 431 004, Maharashtra, India;
- Correspondence: (A.G.); (M.E.A.Z.)
| | - Vijay Masand
- Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati 444 602, Maharashtra, India;
| | - Magdi E. A. Zaki
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia;
- Correspondence: (A.G.); (M.E.A.Z.)
| | - Sami A. Al-Hussain
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia;
| | - Anis Ben Ghorbal
- Department of Mathematics and Statistics, College of Sciences, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia;
| | - Archana Chapolikar
- Department of Chemistry, Government College of Arts and Science, Aurangabad 431 004, Maharashtra, India;
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20
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Mechanistic and Predictive QSAR Analysis of Diverse Molecules to Capture Salient and Hidden Pharmacophores for Anti-Thrombotic Activity. Int J Mol Sci 2021; 22:ijms22158352. [PMID: 34361118 PMCID: PMC8348508 DOI: 10.3390/ijms22158352] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 07/24/2021] [Accepted: 07/31/2021] [Indexed: 12/02/2022] Open
Abstract
Thrombosis is a life-threatening disease with a high mortality rate in many countries. Even though anti-thrombotic drugs are available, their serious side effects compel the search for safer drugs. In search of a safer anti-thrombotic drug, Quantitative Structure-Activity Relationship (QSAR) could be useful to identify crucial pharmacophoric features. The present work is based on a larger data set comprising 1121 diverse compounds to develop a QSAR model having a balance of acceptable predictive ability (Predictive QSAR) and mechanistic interpretation (Mechanistic QSAR). The developed six parametric model fulfils the recommended values for internal and external validation along with Y-randomization parameters such as R2tr = 0.831, Q2LMO = 0.828, R2ex = 0.783. The present analysis reveals that anti-thrombotic activity is found to be correlated with concealed structural traits such as positively charged ring carbon atoms, specific combination of aromatic Nitrogen and sp2-hybridized carbon atoms, etc. Thus, the model captured reported as well as novel pharmacophoric features. The results of QSAR analysis are further vindicated by reported crystal structures of compounds with factor Xa. The analysis led to the identification of useful novel pharmacophoric features, which could be used for future optimization of lead compounds.
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21
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Biological Activities Related to Plant Protection and Environmental Effects of Coumarin Derivatives: QSAR and Molecular Docking Studies. Int J Mol Sci 2021; 22:ijms22147283. [PMID: 34298898 PMCID: PMC8303553 DOI: 10.3390/ijms22147283] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 07/01/2021] [Accepted: 07/02/2021] [Indexed: 01/31/2023] Open
Abstract
The aim was to study the inhibitory effects of coumarin derivatives on the plant pathogenic fungi, as well as beneficial bacteria and nematodes. The antifungal assay was performed on four cultures of phytopathogenic fungi by measuring the radial growth of the fungal colonies. Antibacterial activity was determined by the broth microdilution method performed on two beneficial soil organisms. Nematicidal activity was tested on two entomopathogenic nematodes. The quantitative structure-activity relationship (QSAR) model was generated by genetic algorithm, and toxicity was estimated by T.E.S.T. software. The mode of inhibition of enzymes related to the antifungal activity is elucidated by molecular docking. Coumarin derivatives were most effective against Macrophomina phaseolina and Sclerotinia sclerotiorum, but were not harmful against beneficial nematodes and bacteria. A predictive QSAR model was obtained for the activity against M. phaseolina (R2tr = 0.78; R2ext = 0.67; Q2loo = 0.67). A QSAR study showed that multiple electron-withdrawal groups, especially at position C-3, enhanced activities against M. phaseolina, while the hydrophobic benzoyl group at the pyrone ring, and –Br, –OH, –OCH3, at the benzene ring, may increase inhibition of S. sclerotiourum. Tested compounds possibly act inhibitory against plant wall-degrading enzymes, proteinase K. Coumarin derivatives are the potentially active ingredient of environmentally friendly plant-protection products.
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Chukwuemeka PO, Umar HI, Iwaloye O, Oretade OM, Olowosoke CB, Oretade OJ, Elabiyi MO. Predictive hybrid paradigm for cytotoxic activity of 1,3,4-thiadiazole derivatives as CDK6 inhibitors against human (MCF-7) breast cancer cell line and its structural modifications: rational for novel cancer therapeutics. J Biomol Struct Dyn 2021; 40:8518-8537. [PMID: 33890551 DOI: 10.1080/07391102.2021.1913231] [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: 10/21/2022]
Abstract
The dysregulation of cyclin-CDK6 interactions has been implicated in human breast cancer, providing a rationale for more therapeutic options. Recently, ATP-competitive inhibitors have been employed for managing breast cancer. These molecules, like most natural CDKs inhibitors, potently bind in the ATP-binding site of CDK6 to regulate trans-activation. Nonetheless, only a few numbers of these molecules are approved to mitigate breast cancer, thus, ensuring that the search for more selective inhibitors continues. In this study, we attempted to establish the selective predictive models for identifying potent CDK6 inhibitors against a human breast cancer cell-line using a dataset of fifty-two 1,3,4-thiadiazole derivatives. The significant eight descriptor hybrid QSAR models generated exhibited encouraging statistical attributes including R2> 0.70, Q2LOO > 0.70, Q2LMO > 0.60, Qfn2 > 0.6. Furthermore, the study designed new compounds based on the activity and structural basis for selectivity of compounds for CDK6. While demonstrating good potency and modest selectivity, the compound C16, which showed significantly high activity of 5.5607 µM and binding energy value of -9.0 Kcal/mol, was used as template for compounds design to generate 10 novel series of 1,3,4-thiadiazole analogues containing benzisoselenazolone scaffolds, with significant pharmacological activity and better selectivity for CDK6. By our rationale, four of the designed compounds (C16b, C16h, C16i, and C16j) with activity values of 6.2584 µM, 6.7812 µM, 6.4717 µM, and 6.2666 µM respectively, and binding affinities of -10.0 kcal/mol, -9.9 kcal/mol, -9.9 kcal/mol, and -9.9 kcal/mol respectively, may emerge as therapeutic options for breast cancer treatment after extensive in vitro and in vivo studies.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Prosper Obed Chukwuemeka
- Department of Biotechnology, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
| | - Haruna Isiyaku Umar
- Department of Biochemistry, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
| | - Opeyemi Iwaloye
- Bioinformatics and Molecular Biology Unit, Department of Biochemistry, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
| | - Oluwaseyi Matthew Oretade
- Department of Biotechnology, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
| | | | - Oyeyemi Janet Oretade
- Department of Physiology, College of Health Science (CHS), Osun State University, Osogbo, Nigeria
| | - Michael Omoniyi Elabiyi
- Department of Microbiology, School of Sciences (SOS), Federal University of Technology Akure, Akure, Nigeria
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23
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Masand VH, Patil MK, El-Sayed NNE, Zaki ME, Almarhoon Z, Al-Hussain SA. Balanced QSAR analysis to identify the structural requirements of ABBV-075 (Mivebresib) analogues as bromodomain and extraterminal domain (BET) family bromodomain inhibitor. J Mol Struct 2021. [DOI: 10.1016/j.molstruc.2020.129597] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
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Zaki MEA, Al-Hussain SA, Masand VH, Akasapu S, Lewaa I. QSAR and Pharmacophore Modeling of Nitrogen Heterocycles as Potent Human N-Myristoyltransferase (Hs-NMT) Inhibitors. Molecules 2021; 26:molecules26071834. [PMID: 33805223 PMCID: PMC8038050 DOI: 10.3390/molecules26071834] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 03/12/2021] [Accepted: 03/19/2021] [Indexed: 11/24/2022] Open
Abstract
N-myristoyltransferase (NMT) is an important eukaryotic monomeric enzyme which has emerged as an attractive target for developing a drug for cancer, leishmaniasis, ischemia-reperfusion injury, malaria, inflammation, etc. In the present work, statistically robust machine leaning models (QSAR (Quantitative Structure–Activity Relationship) approach) for Human NMT (Hs-NMT) inhibitory has been performed for a dataset of 309 Nitrogen heterocycles screened for NMT inhibitory activity. Hundreds of QSAR models were derived. Of these, the model 1 and 2 were chosen as they not only fulfil the recommended values for a good number of validation parameters (e.g., R2 = 0.77–0.79, Q2LMO = 0.75–0.76, CCCex = 0.86–0.87, Q2-F3 = 0.74–0.76, etc.) but also provide useful insights into the structural features that sway the Hs-NMT inhibitory activity of Nitrogen heterocycles. That is, they have an acceptable equipoise of descriptive and predictive qualities as per Organisation for Economic Co-operation and Development (OECD) guidelines. The developed QSAR models identified a good number of molecular descriptors like solvent accessible surface area of all atoms having specific partial charge, absolute surface area of Carbon atoms, etc. as important features to be considered in future optimizations. In addition, pharmacophore modeling has been performed to get additional insight into the pharmacophoric features, which provided additional results.
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Affiliation(s)
- Magdi E. A. Zaki
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia;
- Correspondence: (M.E.A.Z.); (V.H.M.)
| | - Sami A. Al-Hussain
- Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia;
| | - Vijay H. Masand
- Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati 444 602, Maharashtra, India
- Correspondence: (M.E.A.Z.); (V.H.M.)
| | | | - Israa Lewaa
- Department of Business Administration, Faculty of Business Administration, Economics and Political Science, British University in Egypt, Cairo 11837, Egypt;
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25
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Masand VH, Akasapu S, Gandhi A, Rastija V, Patil MK. Structure features of peptide-type SARS-CoV main protease inhibitors: Quantitative structure activity relationship study. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS : AN INTERNATIONAL JOURNAL SPONSORED BY THE CHEMOMETRICS SOCIETY 2020; 206:104172. [PMID: 33518858 PMCID: PMC7833253 DOI: 10.1016/j.chemolab.2020.104172] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Revised: 09/09/2020] [Accepted: 10/02/2020] [Indexed: 05/12/2023]
Abstract
In the present work, an extensive QSAR (Quantitative Structure Activity Relationships) analysis of a series of peptide-type SARS-CoV main protease (MPro) inhibitors following the OECD guidelines has been accomplished. The analysis was aimed to identify salient and concealed structural features that govern the MPro inhibitory activity of peptide-type compounds. The QSAR analysis is based on a dataset of sixty-two peptide-type compounds which resulted in the generation of statistically robust and highly predictive multiple models. All the developed models were validated extensively and satisfy the threshold values for many statistical parameters (for e.g. R2 = 0.80-0.82, Q2 loo = 0.74-0.77, Q 2 LMO = 0.66-0.67). The developed QSAR models identified number of sp2 hybridized Oxygen atoms within seven bonds from aromatic Carbon atoms, the presence of Carbon and Nitrogen atoms at a topological distance of 3 and other interrelations of atom pairs as important pharmacophoric features. Hence, the present QSAR models have a good balance of Qualitative (Descriptive QSARs) and Quantitative (Predictive QSARs) approaches, therefore useful for future modifications of peptide-type compounds for anti- SARS-CoV activity.
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Key Words
- ADMET, Absorption, Distribution, Metabolism, Excretion and Toxicity
- COVID-19
- GA, Genetic algorithm
- MLR, Multiple linear Regression
- OECD, Organisation for Economic Co-operation and Development
- OFS, Objective Feature Selection
- OLS, Ordinary Least Square
- Peptide-type compounds
- QSAR
- QSAR, Quantitative structure-activity analysis
- QSARINS, QSAR Insubria
- SARS-CoV
- SARS-CoV-2
- SFS, Subjective Feature Selection
- SMILES, Simplified molecular-Input Line-Entry System
- WHO, World health organization
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Affiliation(s)
- Vijay H Masand
- Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati, Maharashtra, 444 602, India
| | | | - Ajaykumar Gandhi
- Department of Chemistry, Government College of Arts and Science, Aurangabad, Maharashtra, 431 004, India
| | - Vesna Rastija
- Department of Agroecology and Environmental Protection, Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
| | - Meghshyam K Patil
- Department of Chemistry, Osmanabad Sub-Centre Dr. Babasaheb Ambedkar Marathwada University, Osmanabad, Maharashtra, India
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26
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Masand VH, Rastija V, Patil MK, Gandhi A, Chapolikar A. Extending the identification of structural features responsible for anti-SARS-CoV activity of peptide-type compounds using QSAR modelling. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2020; 31:643-654. [PMID: 32847369 DOI: 10.1080/1062936x.2020.1784271] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 06/15/2020] [Indexed: 06/11/2023]
Abstract
A quantitative structure-activity relationship (QSAR) model was built from a dataset of 54 peptide-type compounds as SARS-CoV inhibitors. The analysis was executed to identify prominent and hidden structural features that govern anti-SARS-CoV activity. The QSAR model was derived from the genetic algorithm-multi-linear regression (GA-MLR) methodology. This resulted in the generation of a statistically robust and highly predictive model. In addition, it satisfied the OECD principles for QSAR validation. The model was validated thoroughly and fulfilled the threshold values of a battery of statistical parameters (e.g. r 2 = 0.87, Q 2 loo = 0.82). The derived model is successful in identifying many atom-pairs as important structural features that govern the anti-SARS-CoV activity of peptide-type compounds. The newly developed model has a good balance of descriptive and statistical approaches. Consequently, the present work is useful for future modifications of peptide-type compounds for SARS-CoV and SARS-CoV-2 activity.
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Affiliation(s)
- V H Masand
- Department of Chemistry, Vidya Bharati Mahavidyalaya , Amravati, India
| | - V Rastija
- Department of Chemistry, Faculty of Agrobiotechnical Sciences, Josip Juraj Strossmayer University of Osijek , Osijek, Croatia
| | - M K Patil
- Department of Chemistry, Dr. Babasaheb Ambedkar Marathwada University , Aurangabad, India
| | - A Gandhi
- Department of Chemistry, Government College of Arts and Science , Aurangabad, India
| | - A Chapolikar
- Department of Chemistry, Government College of Arts and Science , Aurangabad, India
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27
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Lončarić M, Strelec I, Pavić V, Šubarić D, Rastija V, Molnar M. Lipoxygenase Inhibition Activity of Coumarin Derivatives-QSAR and Molecular Docking Study. Pharmaceuticals (Basel) 2020; 13:ph13070154. [PMID: 32709129 PMCID: PMC7408124 DOI: 10.3390/ph13070154] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 07/13/2020] [Accepted: 07/15/2020] [Indexed: 01/10/2023] Open
Abstract
Lipoxygenases (LOXs) are a family of enzymes found in plants, mammals, and microorganisms. In animals and plants, the enzyme has the capability for the peroxidation of unsaturated fatty acids. Although LOXs participate in the plant defense system, the enzyme’s metabolites can have numerous negative effects on human health. Therefore, many types of research are searching for compounds that can inhibit LOXs. The best quantitative structure–activity relationship (QSAR) model was obtained using a Genetic Algorithm (GA). Molecular docking was performed with iGEMDOCK. The inhibition of lipoxygenase was in the range of 7.1 to 96.6%, and the inhibition of lipid peroxidation was 7.0–91.0%. Among the synthesized compounds, the strongest inhibitor of soybean LOX-3 (96.6%) was found to be 3-benzoyl-7-(benzyloxy)-2H-chromen-2-one. A lipid peroxidation inhibition of 91.0% was achieved with ethyl 7-methoxy-2-oxo-2H-chromene-3-carboxylate. The docking scores for the soybean LOX-3 and human 5-LOX also indicated that this compound has the best affinity for these LOX enzymes. The best multiple linear QSAR model contains the atom-centered fragment descriptors C-06, RDF035p, and HATS8p. QSAR and molecular docking studies elucidated the structural features important for the enhanced inhibitory activity of the most active compounds, such as the presence of the benzoyl ring at the 3-position of coumarin’s core. Compounds with benzoyl substituents are promising candidates as potent lipoxygenase inhibitors.
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Affiliation(s)
- Melita Lončarić
- Faculty of Food Faculty Osijek, Josip Juraj Strossmayer University, 31000 Osijek, Croatia; (M.L.); (I.S.)
| | - Ivica Strelec
- Faculty of Food Faculty Osijek, Josip Juraj Strossmayer University, 31000 Osijek, Croatia; (M.L.); (I.S.)
| | - Valentina Pavić
- Department of Biology, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia;
| | - Domagoj Šubarić
- Department of Agroecology and Environmental Protection, Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (D.Š.); (V.R.)
| | - Vesna Rastija
- Department of Agroecology and Environmental Protection, Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (D.Š.); (V.R.)
| | - Maja Molnar
- Faculty of Food Faculty Osijek, Josip Juraj Strossmayer University, 31000 Osijek, Croatia; (M.L.); (I.S.)
- Correspondence: ; Tel.: +385-31-224-342
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28
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Drug design by machine-trained elastic networks: predicting Ser/Thr-protein kinase inhibitors' activities. Mol Divers 2020; 25:899-909. [PMID: 32222890 DOI: 10.1007/s11030-020-10074-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 03/11/2020] [Indexed: 12/23/2022]
Abstract
An elastic network model (ENM) represents a molecule as a matrix of pairwise atomic interactions. Rich in coded information, ENMs are hereby proposed as a novel tool for the prediction of the activity of series of molecules, with widely different chemical structures, but a common biological activity. The new approach is developed and tested using a set of 183 inhibitors of serine/threonine-protein kinase enzyme (Plk3) which is an enzyme implicated in the regulation of cell cycle and tumorigenesis. The elastic network (EN) predictive model is found to exhibit high accuracy and speed compared to descriptor-based machine-trained modeling. EN modeling appears to be a highly promising new tool for the high demands of industrial applications such as drug and material design.
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29
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Toropov AA, Toropova AP. QSPR/QSAR: State-of-Art, Weirdness, the Future. Molecules 2020; 25:E1292. [PMID: 32178379 PMCID: PMC7143984 DOI: 10.3390/molecules25061292] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 03/06/2020] [Accepted: 03/10/2020] [Indexed: 12/15/2022] Open
Abstract
Ability of quantitative structure-property/activity relationships (QSPRs/QSARs) to serve for epistemological processes in natural sciences is discussed. Some weirdness of QSPR/QSAR state-of-art is listed. There are some contradictions in the research results in this area. Sometimes, these should be classified as paradoxes or weirdness. These points are often ignored. Here, these are listed and briefly commented. In addition, hypotheses on the future evolution of the QSPR/QSAR theory and practice are suggested. In particular, the possibility of extending of the QSPR/QSAR problematic by searching for the "statistical similarity" of different endpoints is suggested and illustrated by an example for relatively "distanced each from other" endpoints, namely (i) mutagenicity, (ii) anticancer activity, and (iii) blood-brain barrier.
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Affiliation(s)
| | - Alla P. Toropova
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Science, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milano, Italy;
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30
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Brahmbhatt H, Molnar M, Pavić V, Rastija V. Synthesis, Characterization, Antibacterial and Antioxidant Potency of NSubstituted- 2-Sulfanylidene-1,3-Thiazolidin-4-one Derivatives and QSAR Study. Med Chem 2019; 15:840-849. [PMID: 30520381 DOI: 10.2174/1573406415666181205163052] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 11/17/2018] [Accepted: 11/27/2018] [Indexed: 11/22/2022]
Abstract
BACKGROUND Rhodanine is known for its potential and important role in the medicinal chemistry since its derivatives exhibit a wide range of pharmacological activities such as antibacterial, antifungal, antidiabetic, antitubercular, anti-HIV, antiparasitic, antioxidant, anticancer, antiproliferative and anthelmintic agents. OBJECTIVES Since N-substituted rhodanine synthons are rarely commercially available, it is desirable to develop a straightforward synthetic approach for the synthesis of these key building blocks. The objective was to synthesize a series of rhodanine derivatives and to investigate their antimicrobial and antioxidant activity. Also, in order to obtain an insight into their structure-activity relationship, QSAR studies on the antioxidant activity were performed. METHODS 1H and 13C FTNMR spectra were recorded on Bruker Avance 600 MHz NMR Spectrometer, mass analysis was carried out on ESI+ mode by LC-MS/MS API 2000. 2,2-Diphenyl-1- picrylhydrazyl radical scavenging activity (% DPPH) was determined in dimethylsulfoxide (DMSO) as a solvent. The antibacterial activity was assessed against Bacillus subtilis, Staphylococcus aureus (Gram positive) and Escherichia coli, Pseudomonas aeruginosa (Gram negative) bacteria in terms of the minimum inhibitory concentrations (MICs) by a modified broth microdilution method. RESULTS A series of N-substituted-2-sulfanylidene-1,3-thiazolidin-4-ones were synthesized and characterized by 1H NMR, 13C NMR, FTIR, GC MS, LCMS/MS and C,H,N,S elemental analysis. Most of the synthesized compounds showed moderate to excellent antibacterial activity (MIC values from 125 μg/ml to 15.62 μg/mL) and DPPH scavenging activity (from 3.60% to 94.40%). Compound 2-thioxo-3- (4-(trifluoromethyl)-phenyl)thiazolidin-4-one showed the most potent activity against Escherichia coli (3.125 μg/mL), equivalent to antibiotic Amikacin sulphate and against Staphylococcus aureus (0.097 μg/ml), 100 times superior then antibiotic Amikacin sulphate. It has also shown a potent antioxidant activity (95% DPPH scavenging). Two best QSAR models, obtained by GETAWAY descriptor R7p+, Balabans molecular connectivity topological index and Narumi harmonic topological index (HNar), suggest that the enhanced antioxidant activity is related to the presence of pairs of atoms higher polarizability at the topological distance 7, substituted benzene ring and longer saturated aliphatic chain in N-substituents. CONCLUSION A series of novel N-substituted-2-thioxothiazolidin-4-one derivatives were designed, synthesized, characterized and evaluated for their antibacterial and antioxidant activity in vitro. Majority of the compounds showed excellent antibacterial activity compared to ampicillin and few of them have an excellent activity as compared to Chloramphenicol standard antibacterial drug. The QSAR study has clarified the importance of presenting a pairs of atoms higher polarizability, such as Cl and S at the specific distance, as well as the substituted benzene ring and a long saturated aliphatic chain in N-substituents for the enhanced antioxidant activity of 2-sulfanylidene-1,3- thiazolidin-4-one derivatives.
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Affiliation(s)
- Harshad Brahmbhatt
- Department of Applied Chemistry and Ecology, Faculty of Food Technology Osijek, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
| | - Maja Molnar
- Department of Applied Chemistry and Ecology, Faculty of Food Technology Osijek, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
| | - Valentina Pavić
- The Department of Biology, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
| | - Vesna Rastija
- Faculty of Agrobiotehnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
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Toropova AP, Toropov AA. Whether the Validation of the Predictive Potential of Toxicity Models is a Solved Task? Curr Top Med Chem 2019; 19:2643-2657. [PMID: 31702504 DOI: 10.2174/1568026619666191105111817] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 09/02/2019] [Accepted: 09/04/2019] [Indexed: 12/23/2022]
Abstract
Different kinds of biological activities are defined by complex biochemical interactions, which are termed as a "mathematical function" not only of the molecular structure but also for some additional circumstances, such as physicochemical conditions, interactions via energy and information effects between a substance and organisms, organs, cells. These circumstances lead to the great complexity of prediction for biochemical endpoints, since all "details" of corresponding phenomena are practically unavailable for the accurate registration and analysis. Researchers have not a possibility to carry out and analyse all possible ways of the biochemical interactions, which define toxicological or therapeutically attractive effects via direct experiment. Consequently, a compromise, i.e. the development of predictive models of the above phenomena, becomes necessary. However, the estimation of the predictive potential of these models remains a task that is solved only partially. This mini-review presents a collection of attempts to be used for the above-mentioned task, two special statistical indices are proposed, which may be a measure of the predictive potential of models. These indices are (i) Index of Ideality of Correlation; and (ii) Correlation Contradiction Index.
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Affiliation(s)
- Alla P Toropova
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via La Masa 19, 20156 Milano, Italy
| | - Andrey A Toropov
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via La Masa 19, 20156 Milano, Italy
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Masand VH, Elsayed NN, Thakur SD, Gawhale N, Rathore MM. Quinoxalinones Based Aldose Reductase Inhibitors: 2D and 3D-QSAR Analysis. Mol Inform 2019; 38:e1800149. [PMID: 31131980 DOI: 10.1002/minf.201800149] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2018] [Accepted: 05/07/2019] [Indexed: 11/08/2022]
Abstract
In the present work, 2D- and 3D-quantitative structure-activity relationship (QSAR) analysis has been employed for a diverse set of eighty-nine quinoxalinones to identify the pharmacophoric features with significant correlation with the aldose reductase inhibitory activity. Using genetic algorithm (GA) as a variable selection method, multivariate linear regression (MLR) models were derived using a pool of molecular descriptors. All the six-descriptor based GA-MLR QSAR models are statistically robust with coefficient of determination (R2 )>0.80 and cross-validated R2 >0.77. The derived GA-MLR models were thoroughly validated using internal and external and Y-scrambling techniques. The CoMFA like model, which is based on a combination of steric and electrostatic effects and graphically inferred using contour plots, is highly robust with R2 >0.93 and cross-validated R2 >0.73. The established QSAR and CoMFA like models are proficient in identify key pharmacophoric features that govern the aldose reductase inhibitory activity of quinoxalinones.
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Affiliation(s)
- Vijay H Masand
- Department of Chemistry, Vidya Bharati College, Camp, Amravati, Maharashtra, 444 602, India
| | - Nahed N Elsayed
- Department of Chemistry, College of Science, "Girls Section", King Saud University, PO Box 22452, Riyadh, 11495, Saudi Arabia.,National Organization for Drug Control and Research (NODCAR), 51 Wezaret El-Zerra St., Giza, 35521, Egypt
| | - Sumersingh D Thakur
- Department of Chemistry, RDIK and NKD College, Badnera-Amravati, Maharashtra, India
| | - Nandkishor Gawhale
- Department of Chemistry, G. S. Tompe College, Chandur Bazaar, Amravati, Maharashtra, India
| | - Mithilesh M Rathore
- Department of Chemistry, Vidya Bharati College, Camp, Amravati, Maharashtra, 444 602, India
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Masand VH, El-Sayed NN, Bambole MU, Patil VR, Thakur SD. Multiple quantitative structure-activity relationships (QSARs) analysis for orally active trypanocidal N-myristoyltransferase inhibitors. J Mol Struct 2019. [DOI: 10.1016/j.molstruc.2018.07.080] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Molnar M, Brahmbhatt H, Rastija V, Pavić V, Komar M, Karnaš M, Babić J. Environmentally Friendly Approach to Knoevenagel Condensation of Rhodanine in Choline Chloride: Urea Deep Eutectic Solvent and QSAR Studies on Their Antioxidant Activity. Molecules 2018; 23:E1897. [PMID: 30060629 PMCID: PMC6222480 DOI: 10.3390/molecules23081897] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 07/16/2018] [Accepted: 07/27/2018] [Indexed: 12/22/2022] Open
Abstract
A series of rhodanine derivatives was synthesized in the Knoevenagel condensation of rhodanine and different aldehydes using choline chloride:urea (1:2) deep eutectic solvent. This environmentally friendly and catalyst free approach was very effective in the condensation of rhodanine with commercially available aldehydes, as well as the ones synthesized in our laboratory. All rhodanine derivatives were subjected to 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) scavenging activity investigation and quantitative structure-activity relationship (QSAR) studies were performed to elucidate their structure-activity relationship. The best multiple linear QSAR model demonstrate a stability in the internal validation and Y-randomization (R² = 0.81; F = 24.225; Q²loo = 0.72; R²Yscr = 0.148). Sphericity of the molecule, ratio of symmetric atoms enhanced atomic mass along the principle axes in regard to total number of atoms in molecule, and 3D distribution of the atoms higher electronegativity (O, N, and S) in molecules are important characteristic for antioxidant ability of rhodanine derivatives. Molecular docking studies were carried out in order to explain in silico antioxidant studies, a specific protein tyrosine kinase (2HCK). The binding interactions of the most active compound have shown strong hydrogen bonding and van der Waals interactions with the target protein.
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Affiliation(s)
- Maja Molnar
- Faculty of Food Technology Osijek, Josip Juraj Strossmayer University of Osijek, Franje Kuhaca 20, 31000 Osijek, Croatia.
| | - Harshad Brahmbhatt
- Faculty of Food Technology Osijek, Josip Juraj Strossmayer University of Osijek, Franje Kuhaca 20, 31000 Osijek, Croatia.
| | - Vesna Rastija
- Faculty of Agriculture, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia.
| | - Valentina Pavić
- Department of Biology, Josip Juraj Strossmayer University of Osijek, Cara Hadrijana 8/A, 31000 Osijek, Croatia.
| | - Mario Komar
- Faculty of Food Technology Osijek, Josip Juraj Strossmayer University of Osijek, Franje Kuhaca 20, 31000 Osijek, Croatia.
| | - Maja Karnaš
- Faculty of Agriculture, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia.
| | - Jurislav Babić
- Faculty of Food Technology Osijek, Josip Juraj Strossmayer University of Osijek, Franje Kuhaca 20, 31000 Osijek, Croatia.
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Multiple QSAR models, pharmacophore pattern and molecular docking analysis for anticancer activity of α, β-unsaturated carbonyl-based compounds, oxime and oxime ether analogues. J Mol Struct 2018. [DOI: 10.1016/j.molstruc.2017.12.045] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Taraji M, Haddad PR, Amos RIJ, Talebi M, Szucs R, Dolan JW, Pohl CA. Chemometric-assisted method development in hydrophilic interaction liquid chromatography: A review. Anal Chim Acta 2017; 1000:20-40. [PMID: 29289311 DOI: 10.1016/j.aca.2017.09.041] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Revised: 09/22/2017] [Accepted: 09/24/2017] [Indexed: 02/09/2023]
Abstract
With an enormous growth in the application of hydrophilic interaction liquid chromatography (HILIC), there has also been significant progress in HILIC method development. HILIC is a chromatographic method that utilises hydro-organic mobile phases with a high organic content, and a hydrophilic stationary phase. It has been applied predominantly in the determination of small polar compounds. Theoretical studies in computer-aided modelling tools, most importantly the predictive, quantitative structure retention relationship (QSRR) modelling methods, have attracted the attention of researchers and these approaches greatly assist the method development process. This review focuses on the application of computer-aided modelling tools in understanding the retention mechanism, the classification of HILIC stationary phases, prediction of retention times in HILIC systems, optimisation of chromatographic conditions, and description of the interaction effects of the chromatographic factors in HILIC separations. Additionally, what has been achieved in the potential application of QSRR methodology in combination with experimental design philosophy in the optimisation of chromatographic separation conditions in the HILIC method development process is communicated. Developing robust predictive QSRR models will undoubtedly facilitate more application of this chromatographic mode in a broader variety of research areas, significantly minimising cost and time of the experimental work.
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Affiliation(s)
- Maryam Taraji
- Australian Centre for Research on Separation Science (ACROSS), School of Physical Sciences-Chemistry, University of Tasmania, Private Bag 75, Hobart 7001, Australia
| | - Paul R Haddad
- Australian Centre for Research on Separation Science (ACROSS), School of Physical Sciences-Chemistry, University of Tasmania, Private Bag 75, Hobart 7001, Australia.
| | - Ruth I J Amos
- Australian Centre for Research on Separation Science (ACROSS), School of Physical Sciences-Chemistry, University of Tasmania, Private Bag 75, Hobart 7001, Australia
| | - Mohammad Talebi
- Australian Centre for Research on Separation Science (ACROSS), School of Physical Sciences-Chemistry, University of Tasmania, Private Bag 75, Hobart 7001, Australia
| | - Roman Szucs
- Pfizer Global Research and Development, CT13 9NJ, Sandwich, UK
| | - John W Dolan
- LC Resources, 1795 NW Wallace Rd., McMinnville, OR 97128, USA
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Deep Eutectic Solvents as Convenient Media for Synthesis of Novel Coumarinyl Schiff Bases and Their QSAR Studies. Molecules 2017; 22:molecules22091482. [PMID: 28872604 PMCID: PMC6151826 DOI: 10.3390/molecules22091482] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 08/29/2017] [Accepted: 09/02/2017] [Indexed: 11/17/2022] Open
Abstract
Deep eutectic solvents, as green and environmentally friendly media, were utilized in the synthesis of novel coumarinyl Schiff bases. Novel derivatives were synthesized from 2-((4-methyl-2-oxo-2H-chromen-7-yl)oxy)acetohydrazide and corresponding aldehyde in choline chloride:malonic acid (1:1) based deep eutectic solvent. In these reactions, deep eutectic solvent acted as a solvent and catalyst as well. Novel Schiff bases were synthesized in high yields (65–75%) with no need for further purification, and their structures were confirmed by mass spectra, 1H and 13C NMR. Furthermore, their antioxidant activity was determined and compared to antioxidant activity of previously synthesized derivatives, thus investigating their structure–activity relationship utilizing quantitative structure-activity relationship QSAR studies. Calculation of molecular descriptors has been performed by DRAGON software. The best QSAR model (Rtr = 0.636; Rext = 0.709) obtained with three descriptors (MATS3m, Mor22u, Hy) implies that the pairs of atoms higher mass at the path length 3, three-dimensional arrangement of atoms at scattering parameter s = 21 Å−1, and higher number of hydrophilic groups (-OH, -NH) enhanced antioxidant activity. Electrostatic potential surface of the most active compounds showed possible regions for donation of electrons to 1,1-diphenyl-2-picryhydrazyl (DPPH) radicals.
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Jukić M, Rastija V, Opačak-Bernardi T, Stolić I, Krstulović L, Bajić M, Glavaš-Obrovac L. Antitumor activity of 3,4-ethylenedioxythiophene derivatives and quantitative structure-activity relationship analysis. J Mol Struct 2017. [DOI: 10.1016/j.molstruc.2016.11.074] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Masand VH, El-Sayed NNE, Mahajan DT, Rastija V. QSAR analysis for 6-arylpyrazine-2-carboxamides as Trypanosoma brucei inhibitors. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2017; 28:165-177. [PMID: 28235390 DOI: 10.1080/1062936x.2017.1292407] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2016] [Accepted: 02/04/2017] [Indexed: 06/06/2023]
Abstract
Human African trypanosomiasis (HAT) is prevalent in African countries, covering 37 countries, mostly sub-Saharan. A limited number of drugs are available to cure this neglected disease. In the present work, quantitative structure-activity (toxicity) relationships (QSA(T)R) analysis has been performed for a dataset of 54 6-arylpyrazine-2-carboxamides as Trypanosoma brucei inhibitors to identify the important structural features required for future optimization of lead candidates. The QSA(T)R models satisfy OECD guidelines and have high statistical robustness. The QSA(T)R models are based on easily interpretable molecular descriptors. The QSA(T)R models indicate that Trypanosoma brucei inhibitory activity of 6-arylpyrazine-2-carboxamides has correlation with the presence of N-sec-butylformamide and substituted benzene. The results could be beneficial for further optimization of 6-arylpyrazine-2-carboxamides as Trypanosoma brucei inhibitors. Some potential candidate molecules have been proposed.
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Affiliation(s)
- V H Masand
- a Department of Chemistry , Vidya Bharati College , Camp, Amravati , Maharashtra , India
| | - N N E El-Sayed
- b Department of Chemistry , College of Science, "Girls Section", King Saud University , Riyadh Saudi Arabia
- c National Organization for Drug Control and Research , Giza , Egypt
| | - D T Mahajan
- a Department of Chemistry , Vidya Bharati College , Camp, Amravati , Maharashtra , India
| | - V Rastija
- d Department of Chemistry, Faculty of Agriculture , Josip Juraj Strossmayer University of P. Svacica 1d , Osijek , Croatia
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QSAR modeling for anti-human African trypanosomiasis activity of substituted 2-Phenylimidazopyridines. J Mol Struct 2017. [DOI: 10.1016/j.molstruc.2016.11.012] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Masand VH, Mahajan DT, Maldhure AK, Rastija V. Quantitative structure–activity relationships (QSARs) and pharmacophore modeling for human African trypanosomiasis (HAT) activity of pyridyl benzamides and 3-(oxazolo[4,5-b]pyridin-2-yl)anilides. Med Chem Res 2016. [DOI: 10.1007/s00044-016-1664-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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