Extensive benchmark of rDock as a peptide-protein docking tool.

Peptide-protein interactions are ubiquitous in living cells and essential to a wide range of biological processes, as well as pathologies such as cancer or cardiovascular disease. Yet, obtaining reliable binding mode predictions in peptide-protein docking remains a great challenge for most computational docking programs. The main goal of this study was to assess the performance of the small molecule docking program rDock in comparison to other widely used small molecule docking programs, using 100 peptide-protein systems with peptides ranging from 2 to 12 residues. As we used two large independent benchmark sets previously published for other small-molecule docking programs (AutoDockVina benchmark and LEADSPEP), the performance of rDock could directly be compared to the performances of AutoDockVina, Surflex, GOLD, and Glide, as well as to the peptide docking protocol PIPER-FlexPepDock and the webserver HPepDock. Our benchmark reveals that rDock can dock the 100 peptides with an overall backbone RMSD below 2.5 Å in 58.5% of the cases (76% for the 47 systems of the AutoDockVina benchmark set and 43% for the 53 systems of the LEADSPEP benchmark set). More specifically, rDock docks up to 11-residue peptides with a backbone RMSD below 2.5 Å in 60.75% of the cases. rDock displays higher accuracy than most available small molecule docking programs for 6-10-residue peptides and can sometimes perform similarly to the peptide docking tool, especially at a high level of exhaustiveness (100 or 150 runs). Its performance, as is the case for many other unguided small molecule docking tools, is compromised when the peptides adopt secondary structures upon binding. However, our analyses suggest that rDock could be used for predicting how medium-sized biologically relevant peptides bind to their respective protein targets when the latter bind in an extended mode.

Molecular dynamics study of CDC25BR492L mutant causing the activity decrease of CDC25B.

Cell division cycle 25B (CDC25B) was responsible for regulating the various stages of cell division in the cell cycle. R492L was one of the common types of CDC25B mutants. Researches showed that compared to CDC25BWT, CDC25BR492L mutant had a ∼100-fold reduction in the rate constant for forming phosphatase intermediate (k2). However, the molecular basis of how the CDC25BR492L mutant influenced the process of binding between CDC25B and CDK2/CyclinA was not yet known. Therefore, the optimizations of three-dimensional structure of the CDC25BWT-CDK2/CyclinA system and the CDC25BR492L-CDK2/CyclinA system were constructed by ZDOCK and RDOCK, and five methods were employed to verify the reasonability of the docking structure. Then the molecular dynamics simulations on the two systems were performed to explore the reason why CDC25BR492L mutant caused the weak interactions between CDC25BR492L and CDK2/CyclinA, respectively. The remote docking site (Arg488-Tyr497) and the second active site (Lys538-Arg544) of CDC25B were observed to have high fluctuations in the CDC25BR492L-CDK2/CyclinA system with post-analysis, where the high fluctuation of these two regions resulted in weak interactions between CD25B and CDK2. In addition, Asp38-Glu42 and Asp206-Asp210 of CDK2 showed the slightly descending fluctuation, and CDK2 revealed an enhanced the self-interaction, which made CDK2 keep a relatively stable state in the CDC25BR492L-CDK2/CyclinA system. Finally, Leu492 of CDC25B was speculated to be the key residue, which had great effects on the binding between CDC25BR492L and CDK2 in the CDC25BR492L-CDK2/CyclinA system. Consequently, overall analyses appeared in this study ultimately offered a helpful understanding of the weak interactions between CDC25BR492L and CDK2.

The design of novel inhibitors for treating cancer by targeting CDC25B through disruption of CDC25B-CDK2/Cyclin A interaction using computational approaches.

Cell division cycle 25B is a key cell cycle regulator and widely considered as potent clinical drug target for cancers. This research focused on identifying potential compounds in theory which are able to disrupt transient interactions between CDC25B and its CDK2/Cyclin A substrate.By using the method of ZDOCK and RDOCK, the most optimized 3D structure of CDK2/Cyclin A in complex with CDC25B was constructed and validated using two methods: 1) the superimposition of proteins; 2) analysis of the hydrogen bond distances of Arg 488(N1)-Asp 206(OD1), Arg 492(NE)-Asp 206(OD1), Arg 492(N1)-Asp 206(OD2) and Tyr 497(NE)-Asp 210(OD1). A series of new compounds was gained through searching the fragment database derived from ZINC based on the known inhibitor-compound 7 by the means of "replace fragment" technique. The compounds acquired via meeting the requirements of the absorption, distribution, metabolism, and excretion (ADME) predictions. Finally, 12 compounds with better binding affinity were identified. The comp#1, as a representative, was selected to be synthesized and assayed for their CDC25B inhibitory activities. The comp#1 exhibited mild inhibitory activities against human CDC25B with IC50 values at about 39.02 µM. Molecular Dynamic (MD) simulation revealed that the new inhibitor-comp#1 had favorable conformations for binding to CDC25B and disturbing the interactions between CDC25B and CDK2/Cyclin A.

Molecular basis for antagonistic activity of anifrolumab, an anti-interferon-α receptor 1 antibody.

Anifrolumab (anifrolumab) is an antagonist human monoclonal antibody that targets interferon α receptor 1 (IFNAR1). Anifrolumab has been developed to treat autoimmune diseases and is currently in clinical trials. To decipher the molecular basis of its mechanism of action, we engaged in multiple epitope mapping approaches to determine how it interacts with IFNAR1 and antagonizes the receptor. We identified the epitope of anifrolumab using enzymatic fragmentation, phage-peptide library panning and mutagenesis approaches. Our studies revealed that anifrolumab recognizes the SD3 subdomain of IFNAR1 with the critical residue R(279). Further, we solved the crystal structure of anifrolumab Fab to a resolution of 2.3 Å. Guided by our epitope mapping studies, we then used in silico protein docking of the anifrolumab Fab crystal structure to IFNAR1 and characterized the corresponding mode of binding. We find that anifrolumab sterically inhibits the binding of IFN ligands to IFNAR1, thus blocking the formation of the ternary IFN/IFNAR1/IFNAR2 signaling complex. This report provides the molecular basis for the mechanism of action of anifrolumab and may provide insights toward designing antibody therapies against IFNAR1.