QMOD: physically meaningful QSAR

Jain, Ajay N.

doi:10.1007/s10822-010-9379-8

Cited by 45 publications

(72 citation statements)

References 22 publications

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“…Já o programa Surflex-Dock, um dos módulos do pacote computacional SYBYL, da empresa Tripos, 73 adota uma estratégia de docagem que combina uma função de escore empírica (semelhante a do Hammerhead) 74 com métodos de similaridade morfológica, 75,76 gerando conformações aleatórias de fragmentos do ligante. Além disso, também implementa uma nova forma, mais rápida e precisa de reunir estes fragmentos.…”

Section: Triagem Virtual Baseada Na Estrutura Do Alvo Molecularunclassified

Virtual Screening Strategies in Drug Design

Rodrigues¹,

Mantoani²,

Almeida³

et al. 2012

Revista Virtual De Química

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Abstract:The development of virtual screening techniques represents a major advance in the current drug design era. Through several strategies, virtual screening is able to facilitate the selection of molecules with the desired chemical features to modulate the biological activity of the most attractive molecular targets currently available. From the simplest techniques, as the similarity search or molecular docking, to more complex strategies, including statistical methods and machine learning, the main goal of virtual screening is to improve the searching for molecules with the desired features required for becoming drug candidates, thus accelerating the continuous process of drug design. The aim of this review is to discuss the main virtual screening strategies and how they relate to the drug design process.Keywords: Virtual screening; drug design; molecular modeling. ResumoO desenvolvimento de técnicas de triagem virtual representa um dos maiores avanços na atual era de planejamento de fármacos. A triagem virtual, através de inúmeras estratégias distintas, é capaz de direcionar a seleção de moléculas com as características químicas desejadas para modular a atividade biológica dos mais diversos e atrativos alvos moleculares conhecidos na atualidade. Desde as técnicas mais simples, como a bus a po si ila idade ou do age molecular, até as estratégias mais complexas, que envolvem métodos estatísticos e de aprendizagem de máquinas, o objetivo principal da triagem virtual é aprimorar o processo de busca de novos candidatos a fármacos e acelerar o processo contínuo do seu planejamento. O objetivo desta revisão é discutir as principais técnicas de triagem virtual e como elas se relacionam com o desenvolvimento de novos fármacos.Palavras-chave: Triagem virtual; planejamento de fármacos; modelagem molecular.

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Section: Triagem Virtual Baseada Na Estrutura Do Alvo Molecularunclassified

Virtual Screening Strategies in Drug Design

Rodrigues¹,

Mantoani²,

Almeida³

et al. 2012

Revista Virtual De Química

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“…The amino acid residues involved in the LasR-OdDHL interactions are Trp 60, Tyr 56, Ser 129 and Asp 73. Compound 8 had a high similarity score of 0.660, 38 which is the best among the compounds except OdDHL itself. The introduction of an amide bond between the pyrone ring and the dodecanyl chain instead of the ether linkage might improve the binding affinity of compound 8 by creating a hydrogen-bonding interaction with Asp 73 which is observed in the crystal structure of the LasROdDHL complex.…”

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confidence: 96%

Design, synthesis and biological evaluation of 4-(alkyloxy)-6-methyl-2H-pyran-2-one derivatives as quorum sensing inhibitors

Park

Kim

et al. 2015

Bioorganic & Medicinal Chemistry Letters

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“…Conformations of each compound were created with Monte Carlo simulation (5000 trials) and flexible fit was selected. Within LigandFit, several scoring functions including LigScore1, LigScore2, 38) PLP1, PLP2, 39) Jain, 40) Ludi1, Ludi2, Ludi3, 41,42) PMF, 43) as well as a consensus score, 44) are available. Since there is no generally applicable scoring function so far, a solution to this problem is the calculation of a consensus score, which makes use of the merits of different scoring functions by combining their results.…”

Section: Methodsmentioning

confidence: 99%

Pharmacophore Modeling and Virtual Screening Studies of Checkpoint Kinase 1 Inhibitors

Chen

Liu

Yang

et al. 2009

CHEMICAL & PHARMACEUTICAL BULLETIN

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Checkpoint kinase 1 (Chk1), a serine/threonine kinase, plays a critical role in the regulation of the cell-cycle G2/M checkpoint.1-3) When DNA damage is detected in human cells, as a response, Chk1 is activated through ATM/ATR pathway. The activated Chk1 triggers the G2/M checkpoint, which arrests the cells in G2 to allow time for repairing their DNA. The inhibition of Chk1 kinase has been shown to result in abrogation of the G2/M checkpoint, which would permit premature mitotic entry in the presence of DNA damage, leading ultimately to cell death. [4][5][6] This suggests a potential therapeutic use of Chk1 inhibitors in cancer therapy; that is as sensitizing agents of DNA damaging drugs which are still a major component of cancer therapy.3,7-9) Indeed, several Chk1 inhibitors, including UCN-01 10) and SB-218078, 2,11) have been reported to be able to enhance the cytotoxicities of the standard DNA-damaging agents in vivo. In addition, selective Chk1 inhibitors are also helpful in the study of G2/M checkpoint signaling. 3,12) Therefore, development of Chk1 inhibitors has attracted much attention in recent years.Currently, many academic institutes and pharmaceutical companies have been involved in the development of Chk1 inhibitors. And a considerable number of compounds have been reported to have inhibitory potency against Chk1. Some compounds, such as PF-477736, AZD7762 and UCN-01, 9,12,13) have entered into clinical trials. Even so, discovering more potent Chk1 inhibitors with novel chemical structures are still needed and important in order to provide more lead candidates for the drug development.Quantitative structure-activity relationship (QSAR) methods, particularly three dimensional QSAR (3D-QSAR), have been demonstrated as an effective tool in discovering novel lead compounds.14,15) And pharmacophore modeling method is one of the best 3D-QSAR methods, which has been successfully applied to the drug discovery. [16][17][18][19][20] Thus, in this investigation, we shall first develop 3D pharmacophore models of Chk1 inhibitors based on the known Chk1 inhibitors. It is expected that the established pharmacophore models are able to correctly elucidate the QSAR of the Chk1 inhibitors. Then the best pharmacophore model obtained will be used to screen chemical libraries to identify new inhibitors against Chk1. ExperimentalPharmacophore Modeling All the pharmacophore modeling calculations were carried out by using CATALYST 4.11 software package (Accelrys, San Diego, U.S.A.).21) The common pharmacophore features necessary for potent Chk1 inhibitors were identified by HipHop program, and quantitative pharmacophore models were created by HypoRefine module within CATALYST.In pharmacophore modeling, the selection of training set compounds is critical to the quality of produced models. Each modeling algorithm has its own requirements that should be conformed to, particularly in the aspects of chemical structural diversity and bioactivity variation of the training set compounds. For the pharmacophore modeling algorithm ad...

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QMOD: physically meaningful QSAR

Cited by 45 publications

References 22 publications

Virtual Screening Strategies in Drug Design

Virtual Screening Strategies in Drug Design

Design, synthesis and biological evaluation of 4-(alkyloxy)-6-methyl-2H-pyran-2-one derivatives as quorum sensing inhibitors

Pharmacophore Modeling and Virtual Screening Studies of Checkpoint Kinase 1 Inhibitors

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