DockIT: a tool for interactive molecular docking and molecular complex construction

Repeated local ellipsoid protrusion supplements HLA surface characterization

Allorecognition of donor HLA is a major risk factor for long-term kidney graft survival. Although several molecular matching algorithms have been proposed that compare physiochemical and structural features of the donors' and recipients' HLA proteins in order to predict their compatibility, the exact underlying mechanisms are still not fully understood. We hypothesized that the ElliPro approach of single ellipsoid fitting and protrusion ranking lacks sensitivity for the characteristic shape of HLA molecules and developed a prediction pipeline named Snowball that is fitting smaller ellipsoids iteratively to substructures. Aggregated protrusion ranks of locally fitted ellipsoids were calculated for 712 publicly available HLA structures and 78 predicted structures using AlphaFold 2. Amino-acid sequence and protrusion ranks were used to train deep neural network predictors to infer protrusion ranks for all known HLA sequences. Snowball protrusion ranks appear to be more sensitive than ElliPro scores in fine parts of the HLA such as the helix structures forming the HLA binding groove in particular when the ellipsoids are fitted to substructures considering atoms within a 15 Å radius. A cloud-based web service was implemented based on amino-acid matching considering both protein- and position-specific surface area and protrusion ranks extending the previously presented Snowflake prediction pipeline.

A Retrospective on the Development of Methods for the Analysis of Protein Conformational Ensembles

Analysing protein conformational ensembles whether from molecular dynamics (MD) simulation or other sources for functionally relevant conformational changes can be very challenging. In the nineteen nineties dimensional reduction methods were developed primarily for analysing MD trajectories to determine dominant motions with the aim of understanding their relationship to function. Coarse-graining methods were also developed so the conformational change between two structures could be described in terms of the relative motion of a small number of quasi-rigid regions rather than in terms of a large number of atoms. When these methods are combined, they can characterize the large-scale motions inherent in a conformational ensemble providing insight into possible functional mechanism. The dimensional reduction methods first applied to protein conformational ensembles were referred to as Quasi-Harmonic Analysis, Principal Component Analysis and Essential Dynamics Analysis. A retrospective on the origin of these methods is presented, the relationships between them explained, and more recent developments reviewed.

Interactive Flexible-Receptor Molecular Docking in Virtual Reality Using DockIT

Interactive docking enables the user to guide and control the docking of two biomolecules into a binding pose. It is of particular use when the binding site is known and is thought to be applicable to structure-based drug design (SBDD) and educating students about biomolecular interactions. For SBDD, it enables expertise and intuition to be brought to bear in the drug design process. In education, it can teach students about the most basic level of biomolecular function. Here, we introduce DockIT for virtual reality (VR) that uses a VR headset and hand-held controllers. Using the method of linear response on explicit solvent molecular dynamics simulations, DockIT can model both global and local conformational changes within the receptor due to forces of interaction with the ligand. It has real-time flexible molecular surface rendering and can show the real-time formation and breaking of hydrogen bonds, both between the ligand and receptor and within the receptor itself as it smoothly changes conformation.

UDock2: interactive real-time multi-body protein-protein docking software

MOTIVATION

Protein-protein docking aims at predicting the geometry of protein interactions to gain insights into the mechanisms underlying these processes and develop new strategies for drug discovery. Interactive and user-oriented manipulation tools can support this task complementary to automated software.

RESULTS

This article presents an interactive multi-body protein-protein docking software, UDock2, designed for research but also usable for teaching and popularization of science purposes due to its high usability. In UDock2, the users tackle the conformational space of protein interfaces using an intuitive real-time docking procedure with on-the-fly scoring. UDock2 integrates traditional computer graphics methods to facilitate the visualization and to provide better insight into protein surfaces, interfaces, and properties.

AVAILABILITY AND IMPLEMENTATION

UDock2 is open-source, cross-platform (Windows and Linux), and available at http://udock.fr. The code can be accessed at https://gitlab.com/Udock/Udock2.

The role of the half-turn in determining structures of Alzheimer's Aβ wild-type and mutants

Half-turns are shown to be the main determinants of many experimental Alzheimer's Aβ fibril structures. Fibril structures contain three half-turn types, βα_Rβ, βα_Lβ and βεβ which each result in a ∼90° bend in a β-strand. It is shown that only these half-turns enable cross-β stacking and thus the right-angle fold seen in fibrils is an intrinsic feature of cross-β. Encoding a strand as a conformational sequence in β, α_R, α_L and ε(β_L), pairwise combination rules for consecutive half-turns are used to decode this sequence to give the backbone path. This reveals how structures would be dramatically affected by a deletion. Using a wild-type Aβ(42) fibril structure and the pairwise combination rules, the Osaka deletion is predicted to result in exposure of surfaces that are mutually shielding from the solvent. Molecular dynamics simulations on an 11-mer β-sheet of Alzheimer's Aβ(40) of the Dutch (E22Q), Iowa (D23N), Arctic (E22G), and Osaka (E22Δ) mutants, show the crucial role glycine plays in the positioning of βα_Rβ half-turns. Their "in-phase" positions along the sequence in the wild-type, Dutch mutant and Iowa mutant means that the half-folds all fold to the same side creating the same closed structure. Their out-of-phase positions in Arctic and Osaka mutants creates a flatter structure in the former and an S-shape structure in the latter which, as predicted, exposes surfaces on the inside in the closed wild-type to the outside. This is consistent with the gain of interaction model and indicates how domain swapping might explain the Osaka mutant's unique properties.