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

Feng, Zhiwei; Hu, Guanxing; Ma, Shifan; Xie, Xiang‐Qun

doi:10.1208/s12248-015-9776-y

Cited by 30 publications

(39 citation statements)

References 100 publications

(101 reference statements)

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“…However, above experimental approaches while powerful, are relatively costly and time-consuming compared to any extensive analysis performed in silico . Computational approaches for finding the allosteric sites can be broadly classified as sequence-based and structure-based methods [ 3 , 4 , 27 ]. Sequence-based techniques utilize sequence homology inferred from the multiple sequence alignment to identify the co-evolving amino acids that constitute catalytic and allosteric sites [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

Reversing allosteric communication: From detecting allosteric sites to inducing and tuning targeted allosteric response

2018

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The omnipresence of allosteric regulation together with the fundamental role of structural dynamics in this phenomenon have initiated a great interest to the detection of regulatory exosites and design of corresponding effectors. However, despite a general consensus on the key role of dynamics most of the earlier efforts on the prediction of allosteric sites are heavily crippled by the static nature of the underlying methods, which are either structure-based approaches seeking for deep surface pockets typical for “traditional” orthosteric drugs or sequence-based techniques exploiting the conservation of protein sequences. Because of the critical role of global protein dynamics in allosteric signaling, we investigate the hypothesis of reversibility in allosteric communication, according to which allosteric sites can be detected via the perturbation of the functional sites. The reversibility is tested here using our structure-based perturbation model of allostery, which allows one to analyze the causality and energetics of allosteric communication. We validate the “reverse perturbation” hypothesis and its predictive power on a set of classical allosteric proteins, then, on the independent extended benchmark set. We also show that, in addition to known allosteric sites, the perturbation of the functional sites unravels rather extended protein regions, which can host latent regulatory exosites. These protein parts that are dynamically coupled with functional sites can also be used for inducing and tuning allosteric communication, and an exhaustive exploration of the per-residue contributions to allosteric effects can eventually lead to the optimal modulation of protein activity. The site-effector interactions necessary for a specific mode and level of allosteric communication can be fine-tuned by adjusting the site’s structure to an available effector molecule and by the design or selection of an appropriate ligand.

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Section: Introductionmentioning

confidence: 99%

Reversing allosteric communication: From detecting allosteric sites to inducing and tuning targeted allosteric response

2018

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“…The GPCR superfamily, comprised more than 800 receptors, can be further categorized into four different classes, classes A, B, C, and F (Frizzled), according to their sequence homology (1,2). As essential receptors associated with a variety of physiological processes, including neurotransmission, immune defense, and cell growth, over 30% of currently marketed drugs are using GPCRs as their targets (3,4). …”

Section: Introductionmentioning

confidence: 99%

Integrated In Silico Fragment-Based Drug Design: Case Study with Allosteric Modulators on Metabotropic Glutamate Receptor 5

Bian

Feng

Yang

et al. 2017

AAPS J

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GPCR allosteric modulators target at the allosteric binding pockets of G protein-coupled receptors (GPCRs) with indirect influence on the effects of an orthosteric ligand. Such modulators exhibit significant advantages compared to the corresponding orthosteric ligands, including better chemical tractability or physicochemical properties, improved selectivity, and reduced risk of oversensitization towards their receptors. Metabotropic glutamate receptor 5 (mGlu5), a member of class C GPCRs, is a promising therapeutic target for treating many central nervous system diseases. The crystal structure of mGlu5 in the complex with the negative allosteric modulator mavoglurant was recently reported, providing a fundamental model for designing new allosteric modulators. Computational fragment-based drug discovery represents a powerful scaffold-hopping and lead structure-optimization tool for drug design. In the present work, a set of integrated computational methodologies was first used, such as fragment library generation and retrosynthetic combinatorial analysis procedure (RECAP) for novel compound generation. Then, the compounds generated were assessed by benchmark dataset verification, docking studies, and QSAR model simulation. Subsequently, structurally diverse compounds, with reported or unreported scaffolds, can be observed from top 20 in silico synthesized compounds, which were predicted to be potential mGlu5 modulators. In silico compounds with reported scaffolds may fill SAR holes in known, patented series of mGlu5 modulators. And the generation of compounds without reported tests on mGluR indicates that our approach is doable for exploring and designing novel compounds. Our case study of designing allosteric modulators on mGlu5 demonstrated that the established computational fragment-based approach is a useful methodology for facilitating new compound design in the future.

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“…Allosteric control has since been recognized as playing a critical role in feedback mechanisms, such as in the CAP transcription factor [ 7 – 9 ], signal transduction cascades [ 10 ], G protein-coupled receptors [ 11 , 12 ], ion channels [ 13 ] and enzymes [ 14 – 18 ] and many other functions involving conformational changes in the dynamic structure of proteins [ 19 ]. Understanding the allosteric signaling mechanism in greater detail is not only promising for elucidating protein specific knowledge, but also in developing allosteric drugs with a rational design approach rather than an empirical screen [ 20 – 22 ].…”

Section: Introductionmentioning

confidence: 99%

Dependence of prevalence of contiguous pathways in proteins on structural complexity

2017

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Allostery is a regulatory mechanism in proteins where an effector molecule binds distal from an active site to modulate its activity. Allosteric signaling may occur via a continuous path of residues linking the active and allosteric sites, which has been suggested by large conformational changes evident in crystal structures. An alternate possibility is that the signal occurs in the realm of ensemble dynamics via an energy landscape change. While the latter was first proposed on theoretical grounds, increasing evidence suggests that such a control mechanism is plausible. A major difficulty for testing the two methods is the ability to definitively determine that a residue is directly involved in allosteric signal transduction. Statistical Coupling Analysis (SCA) is a method that has been successful at predicting pathways, and experimental tests involving mutagenesis or domain substitution provide the best available evidence of signaling pathways. However, ascertaining energetic pathways which need not be contiguous is far more difficult. To date, simple estimates of the statistical significance of a pathway in a protein remain to be established. The focus of this work is to estimate such benchmarks for the statistical significance of contiguous pathways for the null model of selecting residues at random. We found that when 20% of residues in proteins are randomly selected, contiguous pathways at the 6 Å cutoff level were found with success rates of 51% in PDZ, 30% in p53, and 3% in MutS. The results suggest that the significance of pathways may have system specific factors involved. Furthermore, the possible existence of false positives for contiguous pathways implies that signaling could be occurring via alternate routes including those consistent with the energetic landscape model.

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

Cited by 30 publications

References 100 publications

Reversing allosteric communication: From detecting allosteric sites to inducing and tuning targeted allosteric response

Reversing allosteric communication: From detecting allosteric sites to inducing and tuning targeted allosteric response

Integrated In Silico Fragment-Based Drug Design: Case Study with Allosteric Modulators on Metabotropic Glutamate Receptor 5

Dependence of prevalence of contiguous pathways in proteins on structural complexity

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