Xianqiang Sun

Accuracy Assessment of Protein-Based Docking Programs against RNA Targets

Ribonucleic acid (RNA) molecules play central roles in a variety of biological processes and, hence, are attractive targets for therapeutic intervention. In recent years, molecular docking techniques have become one of the most popular and successful approaches in drug discovery; however, almost all docking programs are protein based. The adaptability of popular docking programs in RNA world has not been systematically evaluated. This paper describes the comprehensive evaluation of two widely used protein-based docking programs--GOLD and Glide--for their docking and virtual screening accuracies against RNA targets. Using multiple docking strategies, both GOLD 4.0 and Glide 5.0 successfully reproduced most binding modes of the 60 tested RNA complexes. Applying different docking/scoring combinations, significant enrichments from the simulated virtual and fragment screening experiments were achieved against tRNA decoding A site of 16S rRNA (rRNA A-site). Our study demonstrated that current protein-based docking programs can fulfill general docking tasks against RNA, and these programs are very helpful in RNA-based drug discovery and design.

Residues remote from the binding pocket control the antagonist selectivity towards the corticotropin-releasing factor receptor-1

The corticotropin releasing factors receptor-1 and receptor-2 (CRF1R and CRF2R) are therapeutic targets for treating neurological diseases. Antagonists targeting CRF1R have been developed for the potential treatment of anxiety disorders and alcohol addiction. It has been found that antagonists targeting CRF1R always show high selectivity, although CRF1R and CRF2R share a very high rate of sequence identity. This has inspired us to study the origin of the selectivity of the antagonists. We have therefore built a homology model for CRF2R and carried out unbiased molecular dynamics and well-tempered metadynamics simulations for systems with the antagonist CP-376395 in CRF1R or CRF2R to address this issue. We found that the side chain of Tyr6.63 forms a hydrogen bond with the residue remote from the binding pocket, which allows Tyr6.63 to adopt different conformations in the two receptors and results in the presence or absence of a bottleneck controlling the antagonist binding to or dissociation from the receptors. The rotameric switch of the side chain of Tyr3566.63 allows the breaking down of the bottleneck and is a perquisite for the dissociation of CP-376395 from CRF1R.

Structure-based ensemble-QSAR model : a novel approach to the study of the EGFR tyrosine kinase and its inhibitors

Aim:To develop a novel 3D-QSAR approach for study of the epidermal growth factor receptor tyrosine kinase (EGFR TK) and its inhibitors.Methods:One hundred thirty nine EGFR TK inhibitors were classified into 3 clusters. Ensemble docking of these inhibitors with 19 EGFR TK crystal structures was performed. Three protein structures that showed the best recognition of each cluster were selected based on the docking results. Then, a novel QSAR (ensemble-QSAR) building method was developed based on the ligand conformations determined by the corresponding protein structures.Results:Compared with the 3D-QSAR model, in which the ligand conformations were determined by a single protein structure, ensemble-QSAR exhibited higher R2 (0.87) and Q2 (0.78) values and thus appeared to be a more reliable and better predictive model. Ensemble-QSAR was also able to more accurately describe the interactions between the target and the ligands.Conclusion:The novel ensemble-QSAR model built in this study outperforms the traditional 3D-QSAR model in rationality, and provides a good example of selecting suitable protein structures for docking prediction and for building structure-based QSAR using available protein structures.

Molecular switches of the κ opioid receptor triggered by 6′-GNTI and 5′-GNTI

The κ opioid receptor (κOR) is a member of G-protein-coupled receptors, and is considered as a promising drug target for treating neurological diseases. κOR selective 6′-GNTI was proved to be a G-protein biased agonist, whereas 5′-GNTI acts as an antagonist. To investigate the molecular mechanism of how these two ligands induce different behaviors of the receptor, we built two systems containing the 5′-GNTI-κOR complex and the 6′-GNTI-κOR complex, respectively, and performed molecular dynamics simulations of the two systems. We observe that transmembrane (TM) helix 6 of the κOR rotates about 4.6o on average in the κOR-6′-GNTI complex. Detailed analyses of the simulation results indicate that E2976.58 and I2946.55 play crucial roles in the rotation of TM6. In the simulation of the κOR-5′-GNTI system, it is revealed that 5′-GNTI can stabilize TM6 in the inactive state form. In addition, the kink of TM7 is stabilized by a hydrogen bond between S3247.47 and the residue V691.42 on TM1.

Propagation of the Allosteric Modulation Induced by Sodium in the δ-Opioid Receptor

Allosteric sodium in the helix bundle of a G protein-coupled receptor (GPCR) can modulate the receptor activation on the intracellular side. This phenomenon has confounded the GPCR community for decades. In this work, we present a theoretical model that reveals the mechanism of the allosteric modulation induced by sodium in the δ-opioid receptor. We found that the allosteric sodium ion exploits a distinct conformation of the key residue Trp2746.48 to propagate the modulation to helices 5 and 6, which further transmits along the helices and regulates their positions on the intracellular side. This mechanism is supported by subsequent functional assays. Remarkably, our results highlight the contrast between the allosteric effects towards two GPCR partners, the G protein and β-arrestin, as indicated by the fact that the allosteric modulation initiated by the sodium ion significantly affects the β-arrestin recruitment, while it alters the G protein signaling only moderately. We believe that the mechanism revealed in this work can be used to explain allosteric effects initiated by sodium in other GPCRs since the allosteric sodium is highly conserved across GPCRs.

Computational investigation of the interaction mechanism between the estrogen related receptor α and its agonists

Estrogen related receptor alpha (ERRα), the first identified orphan nuclear receptor, participates in the metabolism of body and adjusts some diseases such as breast cancer, osteoporosis and diabetes. Recent experiments have identified several ligands such as 7a, 7b, DK1 and DK3 toward ERRα as agonists, to have a therapeutic ability in reducing blood glucose, and impact the activity of ERRα receptor. Nevertheless, the detailed interaction modes between the agonists and the ERRα have not been fully understood, which will hinder the design and development of more potent agonists targeting ERRα for the treatment of diabetes. To address this issue, molecular docking and molecular dynamic simulation (MD) were performed to study how the four agonists regulate the behavior of ERRα. It was found that a proved residue Phe232 and some others such as Arg276, Phe286, His398 and Phe399 were the key residues in the ligand binding pocket. Hydrogen bonds between agonists and residues Arg276 and His398 and the pi–pi interactions between agonists and Phe232/Phe286/Phe399 both play important roles for agonist–ERRα binding. Interestingly, we observed that the agonists kept the binding of ERRα and its coactivator PGC-1α by stabilizing the site of helix12 (H12). All these findings are not only beneficial to understand the interaction mechanism between ERRα and its agonists, but also provide clues for designing novel and potent agonists of ERRα for the treatment of diabetes.