Three‐Dimensional Holographic Vector of Atomic Interaction Field Applied in QSAR of Anti‐HIV HEPT Analogues

Tong, Jianbo; Liu, Shilin

doi:10.1002/qsar.200710076

Cited by 9 publications

(1 citation statement)

References 44 publications

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“…The key residues of TPH1: Met124, Tyr125, Tyr235, Arg257, Thr265, Glu267, Asp269, Thr370, Cys271, His272, Glu317, Ser336 and Ile369 were chosen for mutating. However, due to the significant difference in backbone conformations between proline and alanine, the Pro238 from the active site of TPH1 was not selected [37–39]. …”

Section: Methodsmentioning

confidence: 99%

Molecular Dynamics Simulation of Tryptophan Hydroxylase-1: Binding Modes and Free Energy Analysis to Phenylalanine Derivative Inhibitors

Huang

Peng

et al. 2013

IJMS

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Serotonin is a neurotransmitter that modulates many central and peripheral functions. Tryptophan hydroxylase-1 (TPH1) is a key enzyme of serotonin synthesis. In the current study, the interaction mechanism of phenylalanine derivative TPH1 inhibitors was investigated using molecular dynamics (MD) simulations, free energy calculations, free energy decomposition analysis and computational alanine scanning. The predicted binding free energies of these complexes are consistent with the experimental data. The analysis of the individual energy terms indicates that although the van der Waals and electrostatics interaction contributions are important in distinguishing the binding affinities of these inhibitors, the electrostatic contribution plays a more crucial role in that. Moreover, it is observed that different configurations of the naphthalene substituent could form different binding patterns with protein, yet lead to similar inhibitory potency. The combination of different molecular modeling techniques is an efficient way to interpret the interaction mechanism of inhibitors and our work could provide valuable information for the TPH1 inhibitor design in the future.

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Section: Methodsmentioning

confidence: 99%

Molecular Dynamics Simulation of Tryptophan Hydroxylase-1: Binding Modes and Free Energy Analysis to Phenylalanine Derivative Inhibitors

Huang

Peng

et al. 2013

IJMS

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Evolution of PLS for Modeling SAR and omics Data

Hasegawa¹,

Funatsu

2012

Molecular Informatics

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In quantitative structure-activity relationship (QSAR), multivariate statistical methods are commonly used for data analysis. Partial least squares (PLS) is of particular interest because it can analyze data with strongly collinear, noisy and numerous X variables, and also simultaneously models several activity variables Y. PLS provides several prediction regions and diagnostic plots as statistical measures. PLS has evolved for coping with the severe demands imposed by complex data structures. In this review article, we outline the algorithms of five advanced PLS techniques and provide some representative examples of each. The selected models are Nonlinear PLS, Multiway PLS, Hierarchical PLS, Orthogonal PLS, and Bi-modal PLS. Studies of particular aspects of living cells (such as the set of genes or proteins in the cell and their interactions) are collectively known as the -omics fields. Omics integrate heterogeneous scientific disciplines and include chemogenomics, proteomics, and metabolomics. The datasets produced within the omics fields are numerous, megavariate and extremely complex. The data structures are frequently incomplete, noisy, nonlinear and collinear demanding modern and powerful multivariate data analysis methods. In particular, the omics technologies have steered biology towards the adoption of orthogonal PLS. We also describe future prospects for the use of PLS algorithms in the omics fields.

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QSAR Studies of HEPT Derivatives Using Support Vector Machines

et al. 2009

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Human Immunodeficiency Virus type 1 reverse transcriptase is an important target for chemotherapeutic agents against the AIDS disease. 1-[2-Hydroxyethoxy-methyl]-6-(phenylthio) thymine] derivatives are potent nonnucleoside reverse transcriptase inhibitors. In the present work, quantitative structure-activity relationship analysis for a set of 79 HEPT derivatives has been investigated by means of support vector machines. The relationships between structure and activity were examined quantitatively using descriptors encoding the steric, hydrophobic, electronic and structural features of 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine] derivatives. The performance and predictive capability of support vector machines method are investigated and compared with other methods such as artificial neural network and multiple linear regression methods. The obtained results indicate that the support vector machines model with the kernel radial basis function can be employed as a forceful tool for quantitative structureactivity relationship studies. The contribution of each descriptor to the structure-activity relationships was evaluated.

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Three‐Dimensional Holographic Vector of Atomic Interaction Field Applied in QSAR of Anti‐HIV HEPT Analogues

Cited by 9 publications

References 44 publications

Molecular Dynamics Simulation of Tryptophan Hydroxylase-1: Binding Modes and Free Energy Analysis to Phenylalanine Derivative Inhibitors

Molecular Dynamics Simulation of Tryptophan Hydroxylase-1: Binding Modes and Free Energy Analysis to Phenylalanine Derivative Inhibitors

Evolution of PLS for Modeling SAR and omics Data

QSAR Studies of HEPT Derivatives Using Support Vector Machines

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