ASD v3.0: unraveling allosteric regulation with structural mechanisms and biological networks.

Allosteric regulation, the most direct and efficient way of regulating protein function, is induced by the binding of a ligand at one site that is topographically distinct from an orthosteric site. Allosteric Database (ASD, available online at http://mdl.shsmu.edu.cn/ASD) has been developed to provide comprehensive information featuring allosteric regulation. With increasing data, fundamental questions pertaining to allostery are currently receiving more attention from the mechanism of allosteric changes in an individual protein to the entire effect of the changes in the interconnected network in the cell. Thus, the following novel features were added to this updated version: (i) structural mechanisms of more than 1600 allosteric actions were elucidated by a comparison of site structures before and after the binding of an modulator; (ii) 261 allosteric networks were identified to unveil how the allosteric action in a single protein would propagate to affect downstream proteins; (iii) two of the largest human allosteromes, protein kinases and GPCRs, were thoroughly constructed; and (iv) web interface and data organization were completely redesigned for efficient access. In addition, allosteric data have largely expanded in this update. These updates are useful for facilitating the investigation of allosteric mechanisms, dynamic networks and drug discoveries.

ASBench: benchmarking sets for allosteric discovery.

Allostery allows for the fine-tuning of protein function. Targeting allosteric sites is gaining increasing recognition as a novel strategy in drug design. The key challenge in the discovery of allosteric sites has strongly motivated the development of computational methods and thus high-quality, publicly accessible standard data have become indispensable. Here, we report benchmarking data for experimentally determined allosteric sites through a complex process, including a 'Core set' with 235 unique allosteric sites and a 'Core-Diversity set' with 147 structurally diverse allosteric sites. These benchmarking sets can be exploited to develop efficient computational methods to predict unknown allosteric sites in proteins and reveal unique allosteric ligand-protein interactions to guide allosteric drug design.

ASD v2.0: updated content and novel features focusing on allosteric regulation.

Allostery is the most direct and efficient way for regulation of biological macromolecule function and is induced by the binding of a ligand at an allosteric site topographically distinct from the orthosteric site. AlloSteric Database (ASD, http://mdl.shsmu.edu.cn/ASD) has been developed to provide comprehensive information on allostery. Owing to the inherent high receptor selectivity and lower target-based toxicity, allosteric regulation is expected to assume a more prominent role in drug discovery and bioengineering, leading to the rapid growth of allosteric findings. In this updated version, ASD v2.0 has expanded to 1286 allosteric proteins, 565 allosteric diseases and 22 008 allosteric modulators. A total of 907 allosteric site-modulator structural complexes and >200 structural pairs of orthosteric/allosteric sites in the allosteric proteins were constructed for researchers to develop allosteric site and pathway tools in response to community demands. Up-to-date allosteric pathways were manually curated in the updated version. In addition, both the front-end and the back-end of ASD have been redesigned and enhanced to allow more efficient access. Taken together, these updates are useful for facilitating the investigation of allosteric mechanisms, allosteric target identification and allosteric drug discovery.

Discovery of novel nonpeptide allosteric inhibitors interrupting the interaction of CDK2/cyclin A3 by virtual screening and bioassays.

Serine/threonine-specific cyclin-dependent kinases (CDKs) are key regulatory elements in eukaryotic cell cycle progression, and the dysregulation of CDKs has been implicated in cancers. Therefore, CDKs have been identified as anti-cancer targets for the development of small-molecule drugs. In this Letter, virtual screening and biological evaluation were performed to identify novel lead structures that allosterically disrupt the interaction between CDK2 and cyclin A3, which are directed toward a noncatalytic binding pocket of CDK2. Ultimately, B2 was identified as exhibiting superior CDK2/cyclin A3 inhibition activity. In addition, our results indicated that B2 exhibited antiproliferative activities against a broad spectrum of human cancer cell lines. Significantly, B2 certainly interrupted the interaction between CDK2 and cyclin A3 and exhibited a concentration-dependent trend. In summary, our results suggest that B2 is the first effective allosteric chemical small-molecule CDK2 inhibitor to be discovered, and further lead optimization may result in a series of novel anti-CDK2 agents.

Prediction of human clearance based on animal data and molecular properties.

Human clearance is often predicted prior to clinical study from in vivo preclinical data by virtue of interspecies allometric scaling methods. The aims of this study were to determine the important molecular descriptors for the extrapolation of animal data to human clearance and further to build a model to predict human clearance by combination of animal data and the selected molecular descriptors. These important molecular descriptors selected by genetic algorithm (GA) were from five classes: quantum mechanical, shadow indices, E-state keys, molecular properties, and molecular property counts. Although the data set contained many outliers determined by the conventional Mahmood method, the variation of most outliers was reduced significantly by our final support vector machine (SVM) model. The values of cross-validated correlation coefficient and root-mean-squared error (RMSE) for leave-one-out cross-validation (LOOCV) of the final SVM model were 0.783 and 0.305, respectively. Meanwhile, the reliability and consistency of the final model were also validated by an external test set. In conclusion, the SVM model based on the molecular descriptors selected by GA and animal data achieved better prediction performance than the Mahmood method. This approach can be applied as an improved interspecies allometric scaling method in drug research and development.

The mechanism of allosteric inhibition of protein tyrosine phosphatase 1B.

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.