Predicting Multi-Epitope Peptide Cancer Vaccine from Novel TAA Topo48

Cancer is one of the most lethal diseases. Recently, cancer immunotherapy has a tremendous achievement in cancer treatment. A certain number of cancer based epitope vaccines with different moiety have been discovered. In japan, several clinical tests of cancer based epitope vaccine derived from tumor associated antigens (TAAs) are now ongoing or have recently been completed. a novel of TAAs potentially as cancer vaccine have been retrieved from a fragment weighed 48kDa derived from human DNA-topoisomerase 1 (TOP1) called Topo48. Therefore, it is still critical to discover a derived Topo48 epitope based cancer vaccine. Immuno-informatics considered as a methods noted to have better accuracy to design promising vaccine candidates. Here, continuous and discontinuous B-cell epitopes following with CTL epitopes and their docking interaction to major histocompatibility complex (MHC) class I Human Leukocyte Antigens (HLA)- A0201 were predicted. Kolaskar-Tongaonkar’s, Emini’s, Karpus-Schulz’s, and Parker’s methods were used to predict continuous B-cell epitopes while ElliPro was used for prediction of discontinued B-cell epitopes. Those considered methods marked to have better accuracy to design promising vaccine candidates. Similarly, CTL epitopes was also predicted by using NetCTL server and the best candidates were further investigated their binding affinity by mean of PEP-FOLD3, PatchDock rigid-body docking server, and FireDock server. Total 27 continuous epitopes and 7 discontinuous B-cell epitopes were predicted. In the other hand, 9 peptides were predicted as CTL epitopes. Whereas, three predicted CTL epitope in range 263MLDHEYTTK27, 755AIDMADEDY763, 715ALGTSKLNY724) exhibited good interactions to HLA-A0201. Moreover, we also found residues His266, Thr270, Ala755, Tyr723, Thr718, Ser719, Lys720 from Topo48 and residues Thr163, Asp757, His70, Glu63 from HLA- A0201 were indicated to be antigenic. Ultimately, our proposed continuous/discontinuous B-cell epitopes, and also CTL epitopes can be potential vaccines for cancer immunotherapy.

Integrative modeling of membrane-associated protein assemblies

Membrane proteins are among the most challenging systems to study with experimental structural biology techniques. The increased number of deposited structures of membrane proteins has opened the route to modeling their complexes by methods such as docking. Here, we present an integrative computational protocol for the modeling of membrane-associated protein assemblies. The information encoded by the membrane is represented by artificial beads, which allow targeting of the docking toward the binding-competent regions. It combines efficient, artificial intelligence-based rigid-body docking by LightDock with a flexible final refinement with HADDOCK to remove potential clashes at the interface. We demonstrate the performance of this protocol on eighteen membrane-associated complexes, whose interface lies between the membrane and either the cytosolic or periplasmic regions. In addition, we provide a comparison to another state-of-the-art docking software, ZDOCK. This protocol should shed light on the still dark fraction of the interactome consisting of membrane proteins.

Integrative Modeling of Membrane-associated Protein Assemblies

Historically, membrane protein systems have been considered as one of the most challenging systems to study with experimental structural biology techniques. Over the past years, increased number of experimental structures of membrane proteins have become available thanks in particular to advances in solid-state NMR spectroscopy and cryo-electron microscopy. This has opened the route to modeling the complexes that those membrane proteins form by methods such as docking. Most approaches developed to date are, however, not capable of incorporating the topological information provided by the membrane into the modeling process. Here, we present an integrative computational protocol for the modeling of membrane-associated protein assemblies, specifically complexes consisting of a membrane-embedded protein and a soluble partner. It combines efficient, artificial intelligence-based rigid-body docking by LightDock with a flexible final refinement with HADDOCK to remove potential clashes at the interface. We make use of an equilibrated coarse-grained lipid bilayer to represent the information encoded in the membrane in the form of artificial beads, which allows to target the docking towards the binding-competent regions. We demonstrate the performance of this membrane-driven protocol on eighteen membrane-associated complexes, whose interface lies between the membrane and either the cytosolic or periplasmic regions. In addition, we evaluate how different membrane definitions impact the performance of the docking protocol and provide a comparison, in terms of success rate, to another state-of-the-art docking software, ZDOCK. Finally, we discuss the quality of the generated models and propose possible future developments. Our membrane docking protocol should allow to shed light on the still rather dark fraction of the interactome consisting of membrane proteins.

High-resolution global peptide-protein docking using fragments-based PIPER-FlexPepDock

Peptide-protein interactions contribute a significant fraction of the protein-protein interactome. Accurate modeling of these interactions is challenging due to the vast conformational space associated with interactions of highly flexible peptides with large receptor surfaces. To address this challenge we developed a fragment based high-resolution peptide-protein docking protocol. By streamlining the Rosetta fragment picker for accurate peptide fragment ensemble generation, the PIPER docking algorithm for exhaustive fragment-receptor rigid-body docking and Rosetta FlexPepDock for flexible full-atom refinement of PIPER docked models, we successfully addressed the challenge of accurate and efficient global peptide-protein docking at high-resolution with remarkable accuracy. Validation on a representative set of solved peptide-protein complex structures demonstrates the accuracy and robustness of our approach, and opens up the way to high-resolution modeling of many more peptide-protein interactions and to the detailed study of peptide-protein association in general. PIPER-FlexPepDock is freely available to the academic community as a server at http://piperfpd.furmanlab.cs.huji.ac.il.

Structure of the lutein-binding domain of human StARD3 at 1.74 Å resolution and model of a complex with lutein

A crystal structure of the lutein-binding domain of human StARD3 (StAR-related lipid-transfer protein 3; also known as MLN64) has been refined to 1.74 Å resolution. A previous structure of the same protein determined to 2.2 Å resolution highlighted homology with StARD1 and shared cholesterol-binding character. StARD3 has since been recognized as a carotenoid-binding protein in the primate retina, where its biochemical function of binding lutein with specificity appears to be well suited to recruit this photoprotective molecule. The current and previous structures correspond closely to each other (r.m.s.d. of 0.25 Å), especially in terms of the helix-grip fold constructed around a solvent-filled cavity. Regions of interest were defined with alternate conformations in the current higher-resolution structure, including Arg351 found within the cavity and Ω1, a loop of four residues found just outside the cavity entrance. Models of the complex with lutein generated by rigid-body docking indicate that one of the ionone rings must protrude outside the cavity, and this insight has implications for molecular interactions with transport proteins and enzymes that act on lutein. Interestingly, models with the ∊-ionone ring characteristic of lutein pointing towards the bottom of the cavity were associated with fewer steric clashes, suggesting that steric complementarity and ligand asymmetry may play a role in discriminating lutein from the other ocular carotenoids zeaxanthin andmeso-zeaxanthin, which only have β-ionone rings.