Most Accessed Articles | QSAR Analysis of Multimodal Antidepressants Vortioxetine Analogs Using Physicochemical Descriptors and MLR Modeling

Journal Name: Current Computer-Aided Drug Design

Author(s): David M. Rajathei*, Subbiah Parthasarathy, Samuel Selvaraj.

 

 

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Abstract:

Background: Vortioxetine is a multimodal antidepressant drug with combined effects on SERT as an inhibitor, 5-HT1A as agonist and 5-HT3A as an antagonist. Series of vortioxetine analogs have been reported as multi antidepressant compounds and they block serotonin transport into the neuronal cells, activate the postsynaptic 5-HT1A receptors and eliminate the low activity of 5-HT3A receptors.

Objective: To explore the important properties of vortioxetine analogs involved in antidepressant activity by developing 2D QSAR models.

Methods: Selections of significant descriptors were performed by Least Absolute Shrinkage and Selection Operator (LASSO) method and, the Multiple Linear Regression (MLR) method and All Subsets and GA algorithm included in QSARINS software were used for generating QSAR models. Further, the virtual screening was performed based on bioactivity and structure similarity using the PubChem database.

Results: The four descriptor model of complementary information content (CIC2), solubility (bcutp3), mass (bcutm8) and partial charge in van der Waals surface area (PEOEVSA7) of the molecules is obtained for SERT inhibition with the significant statistics of R2= 0.69, RMSEtr= 0.44, R2 ext= 0.62 and CCCext= 0.78. For 5-HT1A agonist, the two descriptor model of molecular shape (Kappm3) and van der Waals volume of the atoms (bcutv11) with R2= 0.78, RMSEtr= 0.33, R2 ext = 0.83, and CCCext= 0.87 is established. The three descriptor model of information content (IC3), solubility (bcutp9) and electronegativity (GATSe5) of the molecules with R2= 0.61, RMSEtr= 0.34, R2 ext= 0.69 and CCCext= 0.72 is obtained for 5-HT3A antagonist. The antidepressant activities of 16 virtual screened compounds were predicted using the developed models.

Conclusion: The developed QSAR models may be useful to predict antidepressant activity for the newly synthesized vortioxetine analogs. To read out more, please visit: http://www.eurekaselect.com/166166/article

Editors Choice Article | Rational Design of Colchicine Derivatives as anti-HIV Agents via QSAR and Molecular Docking

Journal Name: Medicinal Chemistry

Author(s): Apilak Worachartcheewan*, Napat Songtawee, Suphakit Siriwong, Supaluk Prachayasittikul*, Chanin Nantasenamat, Virapong Prachayasittikul.

 

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Background: Human immunodeficiency virus (HIV) is an infective agent that causes an acquired immunodeficiency syndrome (AIDS). Therefore, the rational design of inhibitors for preventing the progression of the disease is required.

Objective: This study aims to construct quantitative structure-activity relationship (QSAR) models, molecular docking and newly rational design of colchicine and derivatives with anti-HIV activity.

Methods: A data set of 24 colchicine and derivatives with anti-HIV activity were employed to develop the QSAR models using machine learning methods (e.g. multiple linear regression (MLR), artificial neural network (ANN) and support vector machine (SVM)), and to study a molecular docking.

Results: The significant descriptors relating to the anti-HIV activity included JGI2, Mor24u, Gm and R8p+ descriptors. The predictive performance of the models gave acceptable statistical qualities as observed by correlation coefficient (Q2) and root mean square error (RMSE) of leave-one out cross-validation (LOO-CV) and external sets. Particularly, the ANN method outperformed MLR and SVM methods that displayed LOO−CV 2 Q and RMSELOO-CV of 0.7548 and 0.5735 for LOOCV set, and Ext 2 Q of 0.8553 and RMSEExt of 0.6999 for external validation. In addition, the molecular docking of virus-entry molecule (gp120 envelope glycoprotein) revealed the key interacting residues of the protein (cellular receptor, CD4) and the site-moiety preferences of colchicine derivatives as HIV entry inhibitors for binding to HIV structure. Furthermore, newly rational design of colchicine derivatives using informative QSAR and molecular docking was proposed.

Conclusion: These findings serve as a guideline for the rational drug design as well as potential development of novel anti-HIV agents. To read out more, please visit: http://www.eurekaselect.com/165617/article

MOST ACCESSED ARTICLE – Therapeutic, Molecular and Computational Aspects of Novel Monoamine Oxidase (MAO) Inhibitors – Combinatorial Chemistry & High Throughput Screening

Journal: Combinatorial Chemistry & High Throughput Screening

Author(s): Muthusamy Ramesh , Yussif M. Dokurugu, Michael D. Thompson, Mahmoud E. Soliman

Abstract:

Background: Due to the limited number of MAO inhibitors in the clinics, several research efforts are aimed at the discovery of novel MAO inhibitors. At present, a high specificity and a reversible mode of inhibition of MAO-A/B are cited as desirable traits in drug discovery process. This will help to reduce the probability of causing target disruption and may increase the duration of action of drug.

Aim: Most of the existing MAO inhibitors lead to side effects due to the lack of affinity and selectivity. Therefore, there is an urgent need to design novel, potent, reversible and selective inhibitors for MAO-A/B. Selective inhibition of MAO-A results in the elevated level of serotonin and noradrenaline. Hence, MAO-A inhibitors can be used for improving the symptoms of depression. The selective MAO-B inhibitors are used with L-DOPA and/or dopamine agonists in the symptomatic treatment of Parkinson’s disease. The present study was aimed to describe the recently developed hits of MAO inhibitors.

Method: At present, CADD techniques are gaining an attention in rationale drug discovery of MAO inhibitors, and several research groups employed CADD approaches on various chemical scaffolds to identify novel MAO inhibitors. These computational techniques assisted in the development of lead molecules with improved pharmacodynamics / pharmacokinetic properties toward MAOs. Further, CADD techniques provided a better understanding of structural aspects of molecular targets and lead molecules.

Conclusions: The present review describes the importance of structural features of potential chemical scaffolds as well as the role of computational approaches like ligand docking, molecular dynamics, QSAR and pharmacophore modeling in the development of novel MAO inhibitors.

To access the article, please visit: http://www.eurekaselect.com/150823

 

Testimonial by Gjumrakch Aliev!

Gjumrakch Aliev

Contributed Article: “Application of Multi-Target Computer-Aided Methodologies In Molecular Design of CNS Drugs

Press Release for EurekAlert! Grid-based continual analysis of molecular interior for drug discovery, QSAR and QSPR

This article by Dr. Andrey V. Potemkin et al. is published in Current Drug Discovery Technologies, Volume 14, Issue 3, 2017

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A series of grid-based computational technologies for in silico virtual screening and molecular design of new drugs is proposed. The technologies are based on original CoMIn (Continual Molecular Interior analysis) software. The grid-based analysis is done by means of a lattice construction analogously to many other grid-based methods. Further continual elucidation of molecular structure is performed in various ways: (i) in the terms of intermolecular interactions potentials. This can be represented as a superposition of Coulomb, Van der Waals interactions and hydrogen bonds. All the potentials are well known continual functions and their values can be determined in all lattice points for a molecule. (ii) In the terms of quantum functions such as electron density distribution, Laplacian and Hamiltonian of electron density distribution, potential energy distribution, the highest occupied and the lowest unoccupied molecular orbitals distribution and their superposition. To reduce the time of calculations using quantum methods based on the first principles, an original quantum free-orbital approach AlteQ is proposed. All the functions can be calculated using a quantum approach at a sufficient level of theory and their values can be determined in all lattice points for a molecule. Then, the molecules of a dataset can be superimposed in the lattice for the maximal coincidence (or minimal deviations) of the potentials (i) or the quantum functions (ii). The methods and criteria of the superimposition are discussed. After that a functional relationship between biological activity or property and characteristics of potentials (i) or functions (ii) is created. The methods of the quantitative relationship construction are discussed. New approaches for rational virtual drug design based on intermolecular potentials and quantum functions are invented. All the invented methods are explained on the http://www.chemosophia.com website.

For more information about the article, please visit http://www.eurekaselect.com/149863

EurekAlert! – Two-way clustering method for QSAR modeling of diverse set of chemicals

The articles by Basak, Majumdar, and Grunwald developed in silico models for the estimation of potential mutagenicity of chemicals from their structure without the input of any other experimental data.

Toxicologists use a large number of tests to assess potential toxicity of chemicals to human and ecological health, a thorough analysis of one chemical requiring $2 to 4 million and a few years of time. One important toxicological property of chemicals is mutagenicity. Both drugs and environmental pollutants can be mutagenic. Gene mutilation related diseases have a major impact on human health. Some mutations may lead to increased susceptibility to some forms of heart disease, diabetes, or cancer. Laboratory bioassays used to assess the mutagenic potential of chemicals because the accumulation of mutations is prerequisite to tumor development. Therefore, testing a large number of chemical mutagens, both drug candidates in the discovery pipeline and environmental pollutants, can be expensive in terms of economic resources, testing facilities, and time.


Subhabrata Majumdar, Subhash C. Basak and Gregory D Grunwald.

Department of Chemistry & Biochemistry, University of Minnesota Duluth-Natural Resources Research Institute, Duluth, Minnesota, USA

Read more here: http://www.eurekalert.org/pub_releases/2016-02/bsp-tcm022916.php

Major Article Contributions by some of the Indian Authors of Bentham Science Publishers in the Journal: Medicinal Chemistry

Journal Name: Medicinal Chemistry

Article Title QSAR Study on a Series of Aryl Carboxylic Acid Amide Derivatives as Potential Inhibitors of Dihydroorotate Dehydrogenase (DHODH)

Author(s): Vivek K. Vyas and Manjunath Ghate

Abstract: QSAR study was performed on a series of aryl carboxylic acid amide derivatives (62 analogs) to establish structural features required for human dihydroorotate dehydrogenase (hDHODH) inhibition. Statistical significant QSAR models were developed for the prediction of hDHODH inhibitory activity by applying MLR analysis (r2 = 0.851 and q2 = 0.795), PCR analysis (r2 = 0.713 and q2 = 0.667) and PLS analysis (r2 = 0.848 and q2 = 0.802). QSAR study emphasized the importance of topological, estate number, hydrophobic and alignment independent descriptors for the prediction of hDHODH inhibitory activity. SaasCcount descriptor suggested the presence of carbon atoms in five member aryl ring system. Positive impact of alignment independent descriptors reveals the presence of carbonyl oxygen and chloro group in this series of compounds. DistTopo signifies basic connectivity of atoms in the molecules. High degree of predictability of the proposed QSAR models offers a great potential for the design and development of potent hDHODH inhibitors.

For more Details, visit: http://benthamscience.com/journal/abstracts.php?journalID=mc&articleID=106309

Article Title: QSAR and Docking Based Semi-synthesis and in vitro Evaluation of 18 β-glycyrrhetinic Acid Derivatives Against Human Lung Cancer Cell Line A-549

Author(s): Dharmendra Kumar Yadav, Komal Kalani, Feroz Khan and Santosh Kumar Srivastava

Abstract: For the prediction of anticancer activity of glycyrrhetinic acid (GA-1) analogs against the human lung cancer cell line (A-549), a QSAR model was developed by forward stepwise multiple linear regression methodology. The regression coefficient (r2) and prediction accuracy (rCV2) of the QSAR model were taken 0.94 and 0.82, respectively in terms of correlation. The QSAR study indicates that the dipole moments, size of smallest ring, amine counts, hydroxyl and nitro functional groups are correlated well with cytotoxic activity. The docking studies showed high binding affinity of the predicted active compounds against the lung cancer target EGFR. These active glycyrrhetinic acid derivatives were then semi-synthesized, characterized and in-vitro tested for anticancer activity. The experimental results were in agreement with the predicted values and the ethyl oxalyl derivative of GA-1 (GA-3) showed equal cytotoxic activity to that of standard anticancer drug paclitaxel.

For more details, visit: http://benthamscience.com/journal/abstracts.php?journalID=mc&articleID=116645

Article Title: Synthesis, Leptospirocidal Activity and QSAR Analysis of Novel Quinoxaline Derivatives

Author(s): Ayarivan Puratchikody, Ramalakshmi Natarajan, Mukesh Doble, Shanmugam Hema Iswarya and Raj Vijayabharathi

Abstract: A simple and efficient method has been developed for the synthesis of series of N-Mannich bases of (E)-3- (phenylimino/4-chlorophenylimino)-2,3-dihydro-1-[(N-substituted piperazinyl) methyl]quinoxaline-2-(1H)-one 3a-f and 4a-f. The requisite 2a and 2b were obtained by reactionbetween quinoxaline-2,3-dione 1 and aniline / p-chloroaniline. These compounds underwent NMannich reaction with various substituted piperazines to yield (title compounds 3a-f and 4a-f respectively. Structures of synthesized compounds were confirmed by spectral studies (IR, 1H NMR, 13C NMR and Mass) and elemental analysis. All the synthesized compounds were screened for in vitro leptospirocidal activty against Leptospira interrogans. The potent compounds 4a, 4b and 4c which showed maximum activity during in vitro studies were subjected to in vivo studies. The inhibitory activity of enzymes carboxypeptidase and transpeptidase, in leptospirosis by the synthesized compounds were determined. 3D-QSAR studies model developed showed the need for more hydrophobic and less steric groups as substituent groups to enhance the in vitro activity.

For more details, Visit: http://benthamscience.com/journal/abstracts.php?journalID=mc&articleID=106312

Major Article Contributions by Some of our Indian Authors in Bentham Science Publishers Journal: Medicinal Chemistry

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New Quinolinyl–1,3,4–Oxadiazoles: Synthesis, In Vitro Antibacterial, Antifungal and Antituberculosis Studies

Author(s): Rahul V. Patel, Premlata Kumari and Kishor H. Chikhalia

Affiliation: Department of Applied Chemistry, S. V. National Institute of Technology, Surat–395007, Gujarat, India.

Abstract

In order to generate hybrid antimicrobial remedies with novel mode of action, two series of quinoline based 1,3,4-oxadiazole derivatives condensed with N-aryl/benzothiazolyl acetamides were synthesized and the MIC values of the compounds towards eight reference bacterial strains (S. aureus, B. cereus, E. coli, P. aeruginosa, K. pneumoniae, S. typhi, P. vulgaris, S. flexneri), four fungi (A. niger, A. fumigatus, A. clavatus, C. albicans) and Mycobacterium tuberculosis H37Rv were assayed in vitro. Quinoline–6–carboxlic acid was treated with thionyl chloride in refluxing methanol to obtain the corresponding ester derivative to be hydrazinolyzed by 99% hydrazine hydrate in ethanol to produce carbohydrazide intermediate. The carbohydrazide precursor underwent cyclization by carbon disulfide and ethanolic KOH to construct 5–quinolinyl–6–yl–1,3,4–oxadiazol–2–thiol. Substituted 2–chloro–N–phenyl(benzothiazolyl)aceta-mide derivatives were then condensed to 1,3,4-oxadiazole nucleus via sulphur linkage to yield the desired products. Target products bearing N–benzothiazolyl–2–chloroacetamides displayed good inhibitory potential. The biological screening identified that many final analogues exhibited a significant inhibition of the growth of microorganisms at 3.12-25 μg/mL of MIC, which were comparable to control drugs. The influence of the presence of various functional groups to the phenyl/benzothiazolyl ring on activity profiles was investigated. The proposed structures of the newly prepared products were confirmed with the aid of IR, 1H NMR, 13C NMR spectroscopy and elemental analysis. These results may provide new insights in the design of a novel pool of bioactive templates.

A Combination of 3D-QSAR Modeling and Molecular Docking Approach for the Discovery of Potential HIF Prolyl Hydroxylase Inhibitors

Author(s): Mahesh Kumar Teli and Rajanikant Golgodu Krishnamurthy

Affiliation: School of Biotechnology Coordinator, Bioinformatics Centre National Institute of Technology Calicut Calicut – 673601, Kerala, India.

Abstract

Suppression of HIF prolyl hydroxylase (PHD) activity by small molecule inhibitors leads to the stabilization of HIF and offers a potential therapeutic option for treating ischemic disorders. In this study, pharmacophore based QSAR modeling, virtual screening and molecular docking approaches were concurrently used to identify target-specific PHD inhibitors with better ADME properties and to readily minimize false positives and false negatives. A 3D-QSAR based method was used to generate a pharmacophore hypothesis (AAAN). The obtained 3D-QSAR model has an excellent correlation coefficient value (r2 = 0.99), Fisher ratio (F = 386) and exhibited good predictive power (q2 = 0.64). The hypothesis was validated and utilized for chemical database screening and the retrieved compounds were subjected to molecular docking for further refinement. Quantitative AAAN hypothesis comprised three H-bond accepter and one negative ionizable group feature and it give good predictive ability because all the QSAR information it was providing matched with the active site information. The hypothesis was validated and used as a 3D query for database screening. After manual selection, molecular docking and further refinement, based on the molecular interactions of inhibitors with the essential amino acids residues, 12 candidates with good ADME and blood brain barrier permeability values were selected as potential PHD inhibitors.

Modeling of LIM-Kinase 2 Inhibitory Activity of Pyrrolopyrimidine Analogues: Useful in Treatment of Ocular Hypertension and Glaucoma

Author(s): Gagandip Singh, Manish K. Gupta, Viney Kumar and Yenamandra S. Prabhakar

Affiliation: Molecular Modeling and Pharmacoinformatics Lab, Department of Pharmaceutical Chemistry, ISF College of Pharmacy, Moga-142001, India.

Abstract

The LIM-Kinase 2 (LIMK2) inhibitory activity of a series of pyrrolopyrimidine analogs has been analyzed through combinatorial protocol in multiple linear regressions (CP-MLR) and partial least square (PLS) using different descriptors obtained from DRAGON software. The empirical, topological and charge descriptors have led to statistically significant QSAR models and showed good external predictivity as reflected in test set R2 values (0.782 to 0.888). The obtained structure-activity correlations underlined the significance of bulkiness and molecular polarizability in improving the activity. The topological descriptors suggested that open chain or branched substituents are favorable while cyclic /ring substituents are unfavorable for the activity. The descriptors identified in the study showed that pyrrolopyrimidine scaffold holds scope for modulating LIMK2 inhibitory activity. The study gives a direction for further exploration of chemical space of pyrrolopyrimidine analogs as LIMK2 inhibitors.

Variable Selection Based QSAR Modeling on Bisphenylbenzimidazole as Inhibitor of HIV-1 Reverse Transcriptase

Author(s): Surendra Kumar and Meena Tiwari

Affiliation: Computer Aided Drug Design Lab, Department of Pharmacy, Shri G. S. Institute of Technology and Science, 23, Park Road, Indore-452003, (M.P.), India.

Abstract

The emergence of mutant virus in drug therapy for HIV-1 infection has steadily risen in the last decade. Inhibition of reverse transcriptase enzyme has emerged as a novel target for the treatment of HIV infection. The aim to decipher the structural features that interact with receptor, we report a quantitative structure activity relationship (QSAR) study on a dataset of thirty seven compounds belonging to bisphenylbenzimidazoles (BPBIs) as reverse transcriptase inhibitors using enhanced replacement method (ERM), stepwise multiple linear regression (Stepwise-MLR) and genetic function approximation (GFA) method for selecting a subset of relevant descriptors, developing the best multiple linear regression model and defining the QSAR model applicability domain boundaries. The enhanced replacement method was found to give better results r2=0.8542, Q2(loo) = 0.7917, r2pred = 0.7812) at five variables as compared to stepwise MLR and GFA method, evidenced by internal and external validation parameters. The modified r2 (r2m) of the training set, test set and whole data set were calculated and are in agreement with the enhanced replacement method. The results of QSAR study rationalize the structural requirement for optimum binding of ligands. The developed QSAR model shows that hydrophobicity, flexibility, three dimensional surface area, volume and shape of molecule are important parameters to be considered for designing new compounds and to decipher reverse transcriptase enzyme inhibition activity of these compounds at molecular level. The applicability domain was defined to find the similar analogs with better prediction power.

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