Allosite: a method for predicting allosteric sites

Huang, Wenkang; Lu, Shaoyong; Huang, Zhimin; Liu, Xin-Yi; Mou, Linkai; Luo, Yu; Zhao, Yang; Liu, Yaqin; Chen, Zhongjie; Hou, Tingjun; Zhang, Jian

doi:10.1093/bioinformatics/btt399

Cited by 155 publications

(124 citation statements)

References 7 publications

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“…Contrary to similar studies (Panjkovich and Daura, 2012, Huang et al., 2013) the smallest biological assembly of the protein is used, rather than only the chain containing the allosteric modulator. Hetero atom records, including the allosteric modulators, are removed.…”

Section: Methodscontrasting

confidence: 87%

“…Whether the drug will activate or inhibit the protein is difficult to predict, and in many cases the location of allosteric sites is unknown. Existing approaches for allosteric site prediction include using changes in flexibility on ligand binding (Mitternacht and Berezovsky, 2011, Panjkovich and Daura, 2012, Greener and Sternberg, 2015), machine learning on pocket features (Huang et al., 2013, Cimermancic et al., 2016) and structural conservation (Panjkovich and Daura, 2010). …”

Section: Introductionmentioning

confidence: 99%

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Predicting Protein Dynamics and Allostery Using Multi-Protein Atomic Distance Constraints

2017

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SummaryThe related concepts of protein dynamics, conformational ensembles and allostery are often difficult to study with molecular dynamics (MD) due to the timescales involved. We present ExProSE (Exploration of Protein Structural Ensembles), a distance geometry-based method that generates an ensemble of protein structures from two input structures. ExProSE provides a unified framework for the exploration of protein structure and dynamics in a fast and accessible way. Using a dataset of apo/holo pairs it is shown that existing coarse-grained methods often cannot span large conformational changes. For T4-lysozyme, ExProSE is able to generate ensembles that are more native-like than tCONCOORD and NMSim, and comparable with targeted MD. By adding additional constraints representing potential modulators, ExProSE can predict allosteric sites. ExProSE ranks an allosteric pocket first or second for 27 out of 58 allosteric proteins, which is similar and complementary to existing methods. The ExProSE source code is freely available.

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Section: Methodscontrasting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Predicting Protein Dynamics and Allostery Using Multi-Protein Atomic Distance Constraints

2017

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“…The open conformation of the WPD loop is unable to engage in the dephosphorylation reaction, thereby eliminating its catalytic activity. As the key structural features along the allosteric pathway are highly conserved in the PTP family, the PTP1B allosteric pathway may provide insights for other enzymes in the PTP family and contribute to the next generation of PTP1B allosteric drug discovery [53]–[59].…”

Section: Discussionmentioning

confidence: 99%

The Mechanism of Allosteric Inhibition of Protein Tyrosine Phosphatase 1B

Zhang

et al. 2014

PLoS ONE

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As the prototypical member of the PTP family, protein tyrosine phosphatase 1B (PTP1B) is an attractive target for therapeutic interventions in type 2 diabetes. The extremely conserved catalytic site of PTP1B renders the design of selective PTP1B inhibitors intractable. Although discovered allosteric inhibitors containing a benzofuran sulfonamide scaffold offer fascinating opportunities to overcome selectivity issues, the allosteric inhibitory mechanism of PTP1B has remained elusive. Here, molecular dynamics (MD) simulations, coupled with a dynamic weighted community analysis, were performed to unveil the potential allosteric signal propagation pathway from the allosteric site to the catalytic site in PTP1B. This result revealed that the allosteric inhibitor compound-3 induces a conformational rearrangement in helix α7, disrupting the triangular interaction among helix α7, helix α3, and loop11. Helix α7 then produces a force, pulling helix α3 outward, and promotes Ser190 to interact with Tyr176. As a result, the deviation of Tyr176 abrogates the hydrophobic interactions with Trp179 and leads to the downward movement of the WPD loop, which forms an H-bond between Asp181 and Glu115. The formation of this H-bond constrains the WPD loop to its open conformation and thus inactivates PTP1B. The discovery of this allosteric mechanism provides an overall view of the regulation of PTP1B, which is an important insight for the design of potent allosteric PTP1B inhibitors.

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“…This highly efficient model uses different algorithms to predict the locations of allosteric sites in proteins, such as pocket-based analysis (analysis based on the Bdruggable^cavities referring to target proteins where small drug-like molecules have been shown to bind) and support vector machine (SVM) classifiers. Twenty-one site descriptors best suited to delineate the characteristics of typical allosteric sites were selected by a discriminated feature selection method (61). Several software packages, including a novel geometry-based pocket-based algorithm named Fpocket (60), were chosen as an initial pocket to detect the cavities and covered all known allosteric sites.…”

Section: Structure-based Methodsmentioning

confidence: 99%

Computational Advances for the Development of Allosteric Modulators and Bitopic Ligands in G Protein-Coupled Receptors

Feng

et al. 2015

AAPS J

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Abstract. Allosteric modulators of G protein-coupled receptors (GPCRs), which target at allosteric sites, have significant advantages against the corresponding orthosteric compounds including higher selectivity, improved chemical tractability or physicochemical properties, and reduced risk of receptor oversensitization. Bitopic ligands of GPCRs target both orthosteric and allosteric sites. Bitopic ligands can improve binding affinity, enhance subtype selectivity, stabilize receptors, and reduce side effects. Discovering allosteric modulators or bitopic ligands for GPCRs has become an emerging research area, in which the design of allosteric modulators is a key step in the detection of bitopic ligands. Radioligand binding and functional assays ([ 35 S]GTPγS and ERK1/2 phosphorylation) are used to test the effects for potential modulators or bitopic ligands. High-throughput screening (HTS) in combination with disulfide trapping and fragment-based screening are used to aid the discovery of the allosteric modulators or bitopic ligands of GPCRs. When used alone, these methods are costly and can often result in too many potential drug targets, including false positives. Alternatively, low-cost and efficient computational approaches are useful in drug discovery of novel allosteric modulators and bitopic ligands to help refine the number of targets and reduce the false-positive rates. This review summarizes the state-of-the-art computational methods for the discovery of modulators and bitopic ligands. The challenges and opportunities for future drug discovery are also discussed.

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Allosite: a method for predicting allosteric sites

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 155 publications

References 7 publications

Predicting Protein Dynamics and Allostery Using Multi-Protein Atomic Distance Constraints

Predicting Protein Dynamics and Allostery Using Multi-Protein Atomic Distance Constraints

The Mechanism of Allosteric Inhibition of Protein Tyrosine Phosphatase 1B

Computational Advances for the Development of Allosteric Modulators and Bitopic Ligands in G Protein-Coupled Receptors

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