3D-QSAR Approaches in Drug Design: Perspectives to Generate Reliable CoMFA Models

Melo-Filho, Cleber C.; Braga, Rodolpho C.; Andrade, Carolina Horta

doi:10.2174/1573409910666140410111043

Cited by 48 publications

(23 citation statements)

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“…Two steps are critical for the development of CoMFA and CoMSIA models: the partial atomic charge assignment and structural alignment ( Doweyko, 2004 ; Melo-Filho et al, 2014 ). In this study, two different charges (Gasteiger-Hückel and AM1-BCC) and three different molecular alignment approaches (morphological similarity function on Surflex-Sim, shape-based superposition on ROCS and alignment accessed by molecular docking) were evaluated.…”

Section: Resultsmentioning

confidence: 99%

QSAR-Driven Design and Discovery of Novel Compounds With Antiplasmodial and Transmission Blocking Activities

et al. 2018

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Malaria is a life-threatening infectious disease caused by parasites of the genus Plasmodium, affecting more than 200 million people worldwide every year and leading to about a half million deaths. Malaria parasites of humans have evolved resistance to all current antimalarial drugs, urging for the discovery of new effective compounds. Given that the inhibition of deoxyuridine triphosphatase of Plasmodium falciparum (PfdUTPase) induces wrong insertions in plasmodial DNA and consequently leading the parasite to death, this enzyme is considered an attractive antimalarial drug target. Using a combi-QSAR (quantitative structure-activity relationship) approach followed by virtual screening and in vitro experimental evaluation, we report herein the discovery of novel chemical scaffolds with in vitro potency against asexual blood stages of both P. falciparum multidrug-resistant and sensitive strains and against sporogonic development of P. berghei. We developed 2D- and 3D-QSAR models using a series of nucleosides reported in the literature as PfdUTPase inhibitors. The best models were combined in a consensus approach and used for virtual screening of the ChemBridge database, leading to the identification of five new virtual PfdUTPase inhibitors. Further in vitro testing on P. falciparum multidrug-resistant (W2) and sensitive (3D7) parasites showed that compounds LabMol-144 and LabMol-146 demonstrated fair activity against both strains and presented good selectivity versus mammalian cells. In addition, LabMol-144 showed good in vitro inhibition of P. berghei ookinete formation, demonstrating that hit-to-lead optimization based on this compound may also lead to new antimalarials with transmission blocking activity.

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Section: Resultsmentioning

confidence: 99%

QSAR-Driven Design and Discovery of Novel Compounds With Antiplasmodial and Transmission Blocking Activities

et al. 2018

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“…Typical alignment methods include the analysis of molecular fields, structural shapes, or pharmacophores. Pharmacophore generation for ligand alignment is more favorable as it aligns compounds based on feature similarity rather than chemical substructure [246]. As with similarity-based methods, QSAR makes use of molecular descriptors with dimensionality depending on the information available.…”

Section: Similarity-based and Quantitative Structure-activity/propertmentioning

confidence: 99%

“…Pharmacophore modelling have already demonstrated its value in ligand-based drug discovery studies. Ligand substructures required for optimal bioactivity can be aligned and characterized as a spatial arrangement of features in 3D space, which can be directly used for screening or applied to 3D-QSAR modeling [169,170,246]. Several software and webservers (Table 1) are available for the generation of ligand-based pharmacophores.…”

Section: Ligand-based Pharmacophore Modelingmentioning

confidence: 99%

In Silico Strategies in Tuberculosis Drug Discovery

et al. 2020

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Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic. In silico strategies can be applied at multiple stages of the drug discovery paradigm to expedite the identification of novel anti-TB therapeutics. In this paper, we discuss the current TB treatment, emergence of drug resistance, and the effective application of computational tools to the different stages of TB drug discovery when combined with traditional biochemical methods. We will also highlight the strengths and points of improvement in in silico TB drug discovery research, as well as possible future perspectives in this field.

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“…Computer-aided drug design (CADD) has become an integral part of the drug discovery process in both academia and pharma companies [13,14]. Elucidation of quantitative structure-activity relationships (QSAR) is one of the main approaches of CADD [15–18]. QSAR modeling has been widely used for identification of novel anti-TB agents.…”

Section: Introductionmentioning

confidence: 99%

QSAR-driven design, synthesis and discovery of potent chalcone derivatives with antitubercular activity

Gomes

Braga

Grzelak

et al. 2017

European Journal of Medicinal Chemistry

104

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New anti-tuberculosis (anti-TB) drugs are urgently needed to battle drug-resistant Mycobacterium tuberculosis strains and to shorten the current 6–12-month treatment regimen. In this work, we have continued the efforts to develop chalcone-based anti-TB compounds by using an in silico design and QSAR-driven approach. Initially, we developed SAR rules and binary QSAR models using literature data for targeted design of new chalcone-like compounds with anti-TB activity. Using these models, we prioritized 33 compounds for synthesis and biological evaluation. As a result, 10 chalcones-like compounds (4, 8, 9, 11, 13, 17–20, and 23) were found to exhibit nanomolar activity against replicating micobacteria, low micromolar activity against nonreplicating bacteria, and nanomolar and micromolar against rifampin (RMP) and isoniazid (INH) monoresistant strains (rRMP and rINH) (<1 µM and <10 µM, respectively). The series also show low activity against commensal bacteria and generally show good selectivity toward M. tuberculosis, with very low cytotoxicity against Vero cells (SI = 11–545). Our results suggest that our designed chalcone-like compounds, due to their high potency and selectivity, are promising anti-TB agents.

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3D-QSAR Approaches in Drug Design: Perspectives to Generate Reliable CoMFA Models

Cited by 48 publications

References 0 publications

QSAR-Driven Design and Discovery of Novel Compounds With Antiplasmodial and Transmission Blocking Activities

QSAR-Driven Design and Discovery of Novel Compounds With Antiplasmodial and Transmission Blocking Activities

In Silico Strategies in Tuberculosis Drug Discovery

QSAR-driven design, synthesis and discovery of potent chalcone derivatives with antitubercular activity

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