Comparison of Ligand-Based and Receptor-Based Virtual Screening of HIV Entry Inhibitors for the CXCR4 and CCR5 Receptors Using 3D Ligand Shape Matching and Ligand−Receptor Docking

Pérez‐Nueno, Violeta I.; Ritchie, David W.; Rabal, Obdulia; Pascual, Rosalía; Borrell, José I.; Teixidó, Jordi

doi:10.1021/ci700415g

Cited by 65 publications

(101 citation statements)

References 99 publications

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“…To evaluate the hits list and the precision of the applied methods the following metrics were used, typically applied in searches with pharmacophoric models (25). …”

Section: Obtaining and Hits Additionmentioning

confidence: 99%

VIRTUAL SCREENING: IDENTIFICATION OF COMPOUNDS WITH POSSIBLE QUORUM SENSING AGONISTIC ACTIVITY IN Pseudomonas aeruginosa

Vivas‐Reyes

Ahumedo

Velázquez

2017

Vitae

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Background: Quorum sensing (QS) is a cell density dependent mechanism that allows bacteria to regulate the expression of specific genes in response to changes in their population density, thus controlling their activities in order to produce a response as a unit multicellular. These responses include production of virulence factors, formation of biofilm, bioluminescence, sporulation, among other behavior. Objectives: The objective of this work was to obtain pharmacophore models able to filter and identify molecules with possible agonist activity of uorum sensing and to find possible candidates based on calculations of molecular docking. Methods: The structure of the receptor was taken from the Protein Data Bank (PDB). The program AutoDock 4.2 was used to perform docking calculations. The 3D structure of the ligand TP1 was extracted from the complex co-crystallized identified with the code PDB 3IX3. The geometries of ligands were optimized using the PM3 semiempirical method. Results: Two pharmacophoric models were designed, the first one was made using the most active compound (TP-1), highlighting the most important chemical characteristics for molecular recognition. The second model was based on the alignment of three of the most active ligands (TP-1, TP-3 and TP-4). These models were used as a filter in a screening on a database of conformations of several compounds with possible agonist activity of the main circuit of QS present in Pseudomonas aeruginosa. The pharmacophoric model based on alignment of the most active compounds showed greater capacity to select or identify compounds exhibiting significant structural and chemical characteristics to be considered possible hit. With this model, 22 compounds were identified. These compounds were subjected to a series of calculations of docking. The outcomes of the docking were used to identify interactions making a SAR analysis and were used as support to understand how chemically distinct compounds can be accommodated by a highly selective receptor, and provide the framework for the development of novel quorum-sensing regulators, utilizing the 2-benzamido(methyl) phenyl benzoate scaffold and to assess the possibility of synthetic routes, considering the structural similarity presenting between these compounds, generating in this way an alternative to find new compounds with modulating activity QS. These two strategies were used to select a list of potential modulators of quorum sensing or new pharmacophoric candidates.

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“…To evaluate the hits list and the precision of the applied methods the following metrics were used, typically applied in searches with pharmacophoric models (25). …”

Section: Obtaining and Hits Additionmentioning

confidence: 99%

VIRTUAL SCREENING: IDENTIFICATION OF COMPOUNDS WITH POSSIBLE QUORUM SENSING AGONISTIC ACTIVITY IN Pseudomonas aeruginosa

Vivas‐Reyes

Ahumedo

Velázquez

2017

Vitae

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“…A similar homology modeling study was also performed to construct homology models of CXCR4 and CCR5. The models were used for virtually screening a library consisting of 602 known CXCR4 and CCR5 inhibitors and some 4,700 similar, presumed inactive, molecules for comparison of ligand-based shape-matching searches and receptor-based docking methods (48). Although these studies described valuable trials in developing CXCR4 antagonists through computational methods, the revealed CXCR4 crystal structures are much different from the structures constructed by homology modeling.…”

Section: Cxcr4mentioning

confidence: 99%

Anti-HIV Drug Development Through Computational Methods

Zhang

Yuan

2014

AAPS J

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Abstract. Although highly active antiretroviral therapy (HAART) is effective in controlling the progression of AIDS, the emergence of drug-resistant strains increases the difficulty of successful treatment of patients with HIV infection. Increasing numbers of patients are facing the dilemma that comes with the running out of drug combinations for HAART. Computational methods play a key role in anti-HIV drug development. A substantial number of studies have been performed in anti-HIV drug development using various computational methods, such as virtual screening, QSAR, molecular docking, and homology modeling, etc. In this review, we summarize recent advances in the application of computational methods to anti-HIV drug development for five key targets as follows: reverse transcriptase, protease, integrase, CCR5, and CXCR4. We hope that this review will stimulate researchers from multiple disciplines to consider computational methods in the anti-HIV drug development process.

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“…In practice, because these rotations are not known a priori, the consensus shape is constructed iteratively as described previously [44]. We have shown that the consensus shapebased representation can be used to capture the essential 3D shape features of several known high-affinity ligands and to encode them in the form of a single representative pseudomolecule which can be used as a VS query [45][46][47][48].…”

Section: Equationmentioning

confidence: 99%

Predicting Drug Promiscuity Using Spherical Harmonic Surface Shape-Based Similarity Comparisons

Pérez‐Nueno¹

2011

TOPROCJ

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Polypharmacology is becoming an increasingly important aspect in drug design. Pharmaceutical companies are discovering more and more cases in which multiple drugs bind to a given target (promiscuous targets) and in which a given drug binds to more than one target (promiscuous ligands). These phenomena are clearly of great importance when considering drug side-effects. In the last 4 years, more than 30 drugs have been tested against more than 40 novel secondary targets based on promiscuity predictions. Current methods for predicting promiscuity typically aim to relate protein receptors according to their primary sequences, the similarity of their ligands, and more recently, the similarity of their ligand binding pockets.Here, we present a spherical harmonic (SH) surface shape-based approach to predict rapidly promiscuous ligands and targets by comparing sets of SH ligand and protein shapes, respectively. We present details of our approach applied to a wide range of PDB complexes comprising ligands in a selected subset of the MDL Drug Data Report (MDDR) database which are distributed over 249 diverse pharmacological targets. The shape similarity of each ligand to each target's ligand set is quantified and used to predict promiscuity. We also analyse the correlation between binding pocket and ligand shapes. We compare our promiscuity predictions with experimental activity values extracted from the BindingDB database.Consensus shapes, drug promiscuity, ligand shape space, protein pocket space, protein sequence space, shape similarity, spherical harmonic shapes.

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Comparison of Ligand-Based and Receptor-Based Virtual Screening of HIV Entry Inhibitors for the CXCR4 and CCR5 Receptors Using 3D Ligand Shape Matching and Ligand−Receptor Docking

Cited by 65 publications

References 99 publications

VIRTUAL SCREENING: IDENTIFICATION OF COMPOUNDS WITH POSSIBLE QUORUM SENSING AGONISTIC ACTIVITY IN Pseudomonas aeruginosa

VIRTUAL SCREENING: IDENTIFICATION OF COMPOUNDS WITH POSSIBLE QUORUM SENSING AGONISTIC ACTIVITY IN Pseudomonas aeruginosa

Anti-HIV Drug Development Through Computational Methods

Predicting Drug Promiscuity Using Spherical Harmonic Surface Shape-Based Similarity Comparisons

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