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- Volume 18, Issue 31, 2018
Current Topics in Medicinal Chemistry - Volume 18, Issue 31, 2018
Volume 18, Issue 31, 2018
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Homology Modeling and Docking Studies of Bcl-2 and Bcl-xL with Small Molecule Inhibitors: Identification and Functional Studies
Authors: Abdul A. A. Salam, Upendra Nayek and Dhanya SunilApoptosis is a vital physiological process, which is observed in various biological events. The anti-apoptotic and pro-apoptotic members of Bcl-2 family are the most characterized proteins which are involved in the regulation of apoptotic cell death. The anti-apoptotic proteins such as Bcl-2 and Bcl-xL prevent apoptosis, whereas pro-apoptotic members like Bax and Bak, elicit the release of caspases from death antagonists inducing apoptosis. Thus, the Bcl-2 family of proteins play a vital role in controlling programmed cell death. Over expression of anti-apoptotic Bcl-2 proteins are often directly associated with various kinds of cancer. Developing suitable inhibitors for controlling the elevated levels of these proteins got much attention in last decade. Structural biology techniques such as Nuclear Magnetic Resonance (NMR) spectroscopy, X-ray crystallography, homology modeling and molecular docking play a significant role in identifying the key inhibitors of these proteins. The authors have developed and tested successfully, several series of indole pharmacore containing inhibitors for Bcl-2 and Bcl-xL proteins based on the homology modeling, docking and suitable biochemical and apoptosis assays. This review provides a summary of potential inhibitor molecules developed for Bcl-2 and Bcl-xL proteins, as well as the the key residues of these proteins interacting with potential drug molecules. The present appraisal also focuses on the role of computational algorithms in developing potential drug molecules,with more emphasis on the role of homology modeling and docking studies in developing inhibitors for Bcl- 2, and Bcl-xL proteins in cancer therapy.
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Structure Based Drug Design: Clinically Relevant HIV-1 Integrase Inhibitors
Authors: Maninder Kaur, Ravindra K. Rawal, Goutam Rath and Amit K. GoyalHIV-1 integrase, a member of a polynucleotidyl transferases superfamily, catalyzes the insertion of the viral DNA into the genome of host cells. It has emerged as a potential target for developing anti-HIV agents. In the last two decades, a number of integrase inhibitors have been developed as potential anti-HIV therapeutics. Several integrase inhibitors have reached later stages of clinical trials including S-1360, L870,810, L870,812 and BMS-707035. Into the bargain, Raltegravir, Elvitegravir and Dolutegravir have been approved by FDA as anti-HIV agents. This review article summarizes the structural insights required for the inhibition of the HIV1 integrase in the context of clinically relevant HIV1 integrase inhibitors. Additionally, the structural features required for overcoming HIV resistance have been discussed. These insights will update the ongoing design of novel antiviral inhibitors.
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Screening of Natural Lead Molecules Against Putative Molecular Targets of Drug-resistant Cryptococcus spp: An Insight from Computer-aided Molecular Design
Authors: Meghna Manjunath and Sinosh SkariyachanCryptococcosis is one of the major invasive fungal infections distributed worldwide with high mortality rate. C. neoformans and C. gattii are the major organisms that cause various types of infections. Anti-fungal resistances exhibited by the mentioned species of Cryptococcus threaten their effective prevention and treatment. There is limited information available on human to human transmission of the pathogen and virulent factors that are responsible for Cryptococcus mediated infections. Hence, there is high scope for understanding the mechanism, probable drug targets and scope of developing natural therapeutic agents that possess high relevance to pharmaceutical biotechnology and medicinal chemistry. The proposed review illustrates the role of computer-aided virtual screening for the screening of probable drug targets and identification of natural lead candidates as therapeutic remedies. The review initially focuses on the current perspectives on cryptococcosis, major metabolic pathways responsible for the pathogenesis, conventional therapies and associated drug resistance, challenges and scope of structure-based drug discovery. The review further illustrates various approaches for the prediction of unknown drug targets, molecular modeling works, screening of natural compounds by computational virtual screening with ideal drug likeliness and pharmacokinetic features, application of molecular docking studies and simulation. Thus, the present review probably provides AN insight into the role of medicinal chemistry and computational drug discovery to combat Cryptococcus infections and thereby open a new paradigm for the development of novel natural therapeutic against various drug targets for cryptococcal infections.
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Modern Computational Strategies for Designing Drugs to Curb Human Diseases: A Prospect
Drug discovery is an exhaustive and time-consuming process involving numerous stages like target identification, validation, lead optimization, preclinical trials, clinical trials and finally postmarketing vigilance for drug safety. The application of computer-aided drug designing (CADD) is an indispensable approach for developing safe and effective drugs. Previous methods based on combinatorial chemistry (CC) and high throughput screening (HTS) consumed a lot of time as well as expenditure. CADD based approaches including pharmacophore modeling (PM), molecular docking (MD), inverse docking, chemical similarity (CS), quantitative structure-activity relationship (QSAR), virtual screening (VS) and molecular dynamics simulations have been quite productive in predicting the therapeutic outcome of candidate drugs/compounds besides saving precious time. CADD tools exploit structural and other information available regarding the target (enzyme/receptor) and the ligands to identify the compounds with the ability to treat diseases notably cancer, neurodegenerative disorders, malaria, Ebola, HIV-AIDS and many more. Computational approaches have led to the discovery of many drugs that have passed preclinical and clinical trials and become novel therapeutics in the treatment of a variety of diseases. Some notable examples of CADD derived novel drugs include dorzolamide, saquinavir, ritonavir, indinavir, captopril and tirofiban. CADD plays important role in predicting absorption, distribution, metabolism, excretion and toxicity (ADME/T) of candidate drugs. Overall, CADD represents an effective and much-needed strategy for designing therapeutically effective drugs to combat human diseases.
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Role of 2-Dimensional Autocorrelation Descriptors in Predicting Antimalarial Activity of Artemisinin and its Aanalogues: A QSAR Study
Authors: Sourav Kalra, Gaurav Joshi, Raj Kumar and Anjana MunshiBackground: Malaria, one of the World's biggest billers' is on the schedule for biomedical research and public health policies. The introduction of the artemisinin, a Chinese traditional drug from Artemisia annua is a revolution in the treatment of malaria. Artemisinin-based combination treatment (ACT) is considered to be the best strategy for uncomplicated Falciparum malaria. The presence of 1,2,4-trioxane system in artemisinin is responsible for its antimalarial activity. Methods: In this study, twenty-nine analogues of artemisinin were taken into account for QSAR studies along with artemisinin. The most active analogue of artemisinin 21 was energy minimized. All the structures were prepared from the active conformer 21 and energy was minimized to the stable state using MMFF94 force field using ChemBioDraw-12. Genetic Algorithm is used to decide the descriptors best required for the model generation. The test set and training set division were done by using hierarchal clustering module available with NCSS statistical software. Results and Conclusion: The antimalarial activity of the artemisinin and its substituted analogues has been analyzed through the multiple linear regression (MLR) using various physiochemical and structural descriptors obtained from PADEL software. The models were prepared using the Sigma Plot version 11. The calculated 2D autocorrelation descriptors and the MLR model suggest that artemisinin and its analogues hold the scope in the optimization of antimalarial activity.
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Acetate Kinase (AcK) is Essential for Microbial Growth and Betel-derived Compounds Potentially Target AcK, PhoP and MDR Proteins in M. tuberculosis, V. cholerae and Pathogenic E. coli: An in silico and in vitro Study
Background: Mycobacterium tuberculosis, Vibrio cholerae, and pathogenic Escherichia coli are global concerns for public health. The emergence of multi-drug resistant (MDR) strains of these pathogens is creating additional challenges in controlling infections caused by these deadly bacteria. Recently, we reported that Acetate kinase (AcK) could be a broad-spectrum novel target in several bacteria including these pathogens. Methods: Here, using in silico and in vitro approaches we show that (i) AcK is an essential protein in pathogenic bacteria; (ii) natural compounds Chlorogenic acid and Pinoresinol from Piper betel and Piperidine derivative compound 6-oxopiperidine-3-carboxylic acid inhibit the growth of pathogenic E. coli and M. tuberculosis by targeting AcK with equal or higher efficacy than the currently used antibiotics; (iii) molecular modeling and docking studies show interactions between inhibitors and AcK that correlate with the experimental results; (iv) these compounds are highly effective even on MDR strains of these pathogens; (v) further, the compounds may also target bacterial two-component system proteins that help bacteria in expressing the genes related to drug resistance and virulence; and (vi) finally, all the tested compounds are predicted to have drug-like properties. Results and Conclusion: Suggesting that, these Piper betel derived compounds may be further tested for developing a novel class of broad-spectrum drugs against various common and MDR pathogens.
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Volumes & issues
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Volume 25 (2025)
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Volume (2025)
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Volume 24 (2024)
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Volume 23 (2023)
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Volume 22 (2022)
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Volume 21 (2021)
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Volume 20 (2020)
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Volume 19 (2019)
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Volume 18 (2018)
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Volume 17 (2017)
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Volume 16 (2016)
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Volume 15 (2015)
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Volume 14 (2014)
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Volume 13 (2013)
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Volume 12 (2012)
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Volume 11 (2011)
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Volume 10 (2010)
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Volume 9 (2009)
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Volume 8 (2008)
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Volume 7 (2007)
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Volume 6 (2006)
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Volume 5 (2005)
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Volume 4 (2004)
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Volume 3 (2003)
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Volume 2 (2002)
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Volume 1 (2001)
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