Inverse Conformational Selection in Lipid-Protein Binding.

Interest in lipid interactions with proteins and other biomolecules is emerging not only in fundamental biochemistry but also in the field of nanobiotechnology where lipids are commonly used, for example, in carriers of mRNA vaccines. The outward-facing components of cellular membranes and lipid nanoparticles, the lipid headgroups, regulate membrane interactions with approaching substances, such as proteins, drugs, RNA, or viruses. Because lipid headgroup conformational ensembles have not been experimentally determined in physiologically relevant conditions, an essential question about their interactions with other biomolecules remains unanswered: Do headgroups exchange between a few rigid structures, or fluctuate freely across a practically continuous spectrum of conformations? Here, we combine solid-state NMR experiments and molecular dynamics simulations from the NMRlipids Project to resolve the conformational ensembles of headgroups of four key lipid types in various biologically relevant conditions. We find that lipid headgroups sample a wide range of overlapping conformations in both neutral and charged cellular membranes, and that differences in the headgroup chemistry manifest only in probability distributions of conformations. Furthermore, the analysis of 894 protein-bound lipid structures from the Protein Data Bank suggests that lipids can bind to proteins in a wide range of conformations, which are not limited by the headgroup chemistry. We propose that lipids can select a suitable headgroup conformation from the wide range available to them to fit the various binding sites in proteins. The proposed inverse conformational selection model will extend also to lipid binding to targets other than proteins, such as drugs, RNA, and viruses.

Heterogeneous dynamics in partially disordered proteins.

Importance of disordered protein regions is increasingly recognized in biology, but their characterization remains challenging due to the lack of suitable experimental and theoretical methods. NMR experiments can detect multiple timescale dynamics and structural details of disordered protein regions, but their detailed interpretation is often difficult. Here we combine protein backbone 15N spin relaxation data with molecular dynamics (MD) simulations to detect not only heterogeneous dynamics of large partially disordered proteins but also their conformational ensembles. We observed that the rotational dynamics of folded regions in partially disordered proteins is dominated by similar rigid body rotation as in globular proteins, thereby being largely independent of flexible disordered linkers. Disordered regions, on the other hand, exhibit complex rotational motions with multiple timescales below ∼30 ns which are difficult to detect from experimental data alone, but can be captured by MD simulations. Combining MD simulations and backbone 15N spin relaxation data, measured applying segmental isotopic labeling with salt-inducible split intein, we resolved the conformational ensemble and dynamics of partially disordered periplasmic domain of TonB protein from Helicobacter pylori containing 250 residues. To demonstrate the universality of our approach, it was applied also to the partially disordered region of chicken Engrailed 2. Our results pave the way in understanding how TonB transfers energy from inner membrane to the outer membrane receptors in Gram-negative bacteria, as well as the function of other proteins with disordered domains.

Overlay databank unlocks data-driven analyses of biomolecules for all.

Tools based on artificial intelligence (AI) are currently revolutionising many fields, yet their applications are often limited by the lack of suitable training data in programmatically accessible format. Here we propose an effective solution to make data scattered in various locations and formats accessible for data-driven and machine learning applications using the overlay databank format. To demonstrate the practical relevance of such approach, we present the NMRlipids Databank-a community-driven, open-for-all database featuring programmatic access to quality-evaluated atom-resolution molecular dynamics simulations of cellular membranes. Cellular membrane lipid composition is implicated in diseases and controls major biological functions, but membranes are difficult to study experimentally due to their intrinsic disorder and complex phase behaviour. While MD simulations have been useful in understanding membrane systems, they require significant computational resources and often suffer from inaccuracies in model parameters. Here, we demonstrate how programmable interface for flexible implementation of data-driven and machine learning applications, and rapid access to simulation data through a graphical user interface, unlock possibilities beyond current MD simulation and experimental studies to understand cellular membranes. The proposed overlay databank concept can be further applied to other biomolecules, as well as in other fields where similar barriers hinder the AI revolution.