Structural basis of Plasmodium vivax inhibition by antibodies binding to the circumsporozoite protein repeats

Malaria is a global health burden, with Plasmodium falciparum (Pf) and Plasmodium vivax (Pv) responsible for the majority of infections worldwide. Circumsporozoite protein (CSP) is the most abundant protein on the surface of Plasmodium sporozoites, and antibodies targeting the central repeat region of CSP can prevent parasite infection. Although much has been uncovered about the molecular basis of antibody recognition of the PfCSP repeats, data remains scarce for PvCSP. Here, we performed molecular dynamics simulations for peptides comprising the PvCSP repeats from strains VK210 and VK247 to reveal how the PvCSP central repeats are highly disordered, with minor propensities to adopt turn conformations. Next, we solved eight crystal structures to unveil the interactions of two inhibitory monoclonal antibodies (mAbs), 2F2 and 2E10.E9, with PvCSP repeats. Both antibodies can accommodate subtle sequence variances in the repeat motifs and recognize largely coiled peptide conformations that also contain isolated turns. Our structural studies uncover various degrees of Fab-Fab homotypic interactions upon recognition of the PvCSP central repeats by these two inhibitory mAbs, similar to potent mAbs against PfCSP. These findings augment our understanding of host-Plasmodium interactions, and contribute molecular details of Pv inhibition by mAbs to unlock structure-based engineering of PvCSP-based vaccines.

Structural basis of Plasmodium vivax inhibition by antibodies binding to the circumsporozoite protein repeats

Malaria is a global health burden, with Plasmodium falciparum (Pf) and Plasmodium vivax (Pv) responsible for the majority of infections worldwide. Circumsporozoite protein (CSP) is the most abundant protein on the surface of Plasmodium sporozoites, and antibodies targeting the central repeat region of CSP can prevent parasite infection. Although much has been uncovered about the molecular basis of antibody recognition of the PfCSP repeats, data remains scarce for PvCSP. Here, we performed molecular dynamics simulations for peptides comprising the PvCSP repeats from strains VK210 and VK247 to reveal how the PvCSP central repeats are highly disordered, with minor propensities to adopt turn conformations. Next, we solved eight crystal structures to unveil the interactions of two inhibitory monoclonal antibodies (mAbs), 2F2 and 2E10.E9, with PvCSP repeats. Both antibodies can accommodate subtle sequence variances in the repeat motifs and recognize largely coiled peptide conformations that also contain isolated turns. Our structural studies uncover various degrees of Fab-Fab homotypic interactions upon recognition of the PvCSP central repeats by these two inhibitory mAbs, similar to potent mAbs against PfCSP. These findings augment our understanding of host-Plasmodium interactions, and contribute molecular details of Pv inhibition by mAbs to unlock structure-based engineering of PvCSP-based vaccines.

Length Dependent Folding Kinetics of Alanine-Based Helical Peptides from Optimal Dimensionality Reduction

We present a computer simulation study of helix folding in alanine homopeptides (ALA)n of length n = 5, 8, 15, and 21 residues. Based on multi-microsecond molecular dynamics simulations at room temperature, we found helix populations and relaxation times increasing from about 6% and ~2 ns for ALA5 to about 60% and ~500 ns for ALA21, and folding free energies decreasing linearly with the increasing number of residues. The helix folding was analyzed with the Optimal Dimensionality Reduction method, yielding coarse-grained kinetic models that provided a detailed representation of the folding process. The shorter peptides, ALA5 and ALA8, tended to convert directly from coil to helix, while ALA15 and ALA21 traveled through several intermediates. Coarse-grained aggregate states representing the helix, coil, and intermediates were heterogeneous, encompassing multiple peptide conformations. The folding involved multiple pathways and interesting intermediate states were present on the folding paths, with partially formed helices, turns, and compact coils. Statistically, helix initiation was favored at both termini, and the helix was most stable in the central region. Importantly, we found the presence of underlying universal local dynamics in helical peptides with correlated transitions for neighboring hydrogen bonds. Overall, the structural and dynamical parameters extracted from the trajectories are in good agreement with experimental observables, providing microscopic insights into the complex helix folding kinetics.

InterPepRank: Assessment of Docked Peptide Conformations by a Deep Graph Network

MotivationPeptide-protein interactions between a smaller or disordered peptide stretch and a folded receptor make up a large part of all protein-protein interactions. A common approach for modelling such interactions is to exhaustively sample the conformational space by fast-fourier-transform docking, and then refine a top percentage of decoys. Commonly, methods capable of ranking the decoys for selection in short enough time for larger scale studies rely on first-principle energy terms such as electrostatics, Van der Waals forces, or on pre-calculated statistical pairwise potentials.ResultsWe present InterPepRank for peptide-protein complex scoring and ranking. InterPepRank is a machine-learning based method which encodes the structure of the complex as a graph; with physical pairwise interactions as edges and evolutionary and sequence features as nodes. The graph-network is trained to predict the LRMSD of decoys by using edge-conditioned graph convolutions on a large set of peptide-protein complex decoys. InterPepRank is tested on a massive independent test set with no targets sharing CATH annotation nor 30% sequence identity with any target in training or validation data. On this set, InterPepRank has a median AUC of 0.86 for finding coarse peptide-protein complexes with LRMSD<4Å. This is an improvement compared to other state-of-the-art ranking methods that have a median AUC of circa 0.69. When included as selection-method for selecting decoys for refinement in a previously established peptide docking pipeline, InterPepRank improves the number of Medium and High quality models produced by 80% and 40%, respectively.AvailabilityThe program is available from: http://wallnerlab.org/InterPepRankContactBjörn Wallner [email protected] informationSupplementary data are available at BioRxiv online.

Receptor-free Discrimination of Peptide Native Bound Conformations Suggests Limited Transferability of the “cen_std+score4l” Rosetta Energy Function From Proteins to Peptides

One of the strategies of peptide–protein docking is to pregenerate an ensemble of peptide conformations in the absence of the receptor, and then dock them as rigid bodies onto its surface. Success of this strategy requires that the scoring function that drives the pregeneration step be able to discriminate in favor of conformations that resemble the native bound conformation. Here we present a study on the discrimination of peptide native bound conformations as achieved without receptor by the “cen_std+score4L” Rosetta energy function, a low-resolution scoring function equivalent to one chosen for other tasks where the modeling of solvent effects is of special importance. The cen_std+score4L function was able to assign, on average, lower energies to native-like than to non-native decoy conformations for only 3 of our 18 test peptides; it also ranked one or more native-like decoys in the top 1% for only 2 peptides. However, by optimizing the weights of the energy terms that define the cen_std+score4L function, native discrimination improved substantially: Native-like decoys were assigned lower energies than non-native decoys for 16 peptides, with a discrimination signal larger than noise for 9 peptides, that is, 50% of the test set. And for 9 peptides, too, native-like decoys ranked in the top 1%. An ensuing energetic analysis of native-like versus non-native decoys suggests that native peptide conformations have solvation and non-local electrostatics that poorly recapitulate those of native protein conformations. Native peptide conformations are also characterized by few backbone–backbone H-bonds and by lack of compactness, presumably to optimize interaction with the receptor. Overall, this study lays groundwork for pregenerating dockable peptide conformations with Rosetta, whether the subsequent docking will be performed by Rosetta or some other software.

Towards Unraveling the Histone Code by Fragment Blind Docking

Histones serve as protein spools for winding the DNA in the nucleosome. High variability of their post-translational modifications result in a unique code system often responsible for the pathomechanisms of epigenetics-based diseases. Decoding is performed by reader proteins via complex formation with the N-terminal peptide tails of histones. Determination of structures of histone-reader complexes would be a key to unravel the histone code and the design of new drugs. However, the large number of possible histone complex variations imposes a true challenge for experimental structure determination techniques. Calculation of such complexes is difficult due to considerable size and flexibility of peptides and the shallow binding surfaces of the readers. Moreover, location of the binding sites is often unknown, which requires a blind docking search over the entire surface of the target protein. To accelerate the work in this field, a new approach is presented for prediction of the structure of histone H3 peptide tails docked to their targets. Using a fragmenting protocol and a systematic blind docking method, a collection of well-positioned fragments of the H3 peptide is produced. After linking the fragments, reconstitution of anchoring regions of the target-bound H3 peptide conformations was possible. As a first attempt of combination of blind and fragment docking approaches, our new method is named fragment blind docking (FBD).

Peptide conformation and oligomerization characteristics of surface-mediated assemblies revealed by molecular dynamics simulations and scanning tunneling microscopy

The characteristics of peptide conformations in both solution and surface-bound states, using poly-glycine as a model structure, are analyzed by using molecular dynamics (MD) simulations and scanning tunneling microscopy (STM).