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.

The Convergence of the Hedgehog/Intein Fold in Different Protein Splicing Mechanisms.

Protein splicing catalyzed by inteins utilizes many different combinations of amino-acid types at active sites. Inteins have been classified into three classes based on their characteristic sequences. We investigated the structural basis of the protein splicing mechanism of class 3 inteins by determining crystal structures of variants of a class 3 intein from Mycobacterium chimaera and molecular dynamics simulations, which suggested that the class 3 intein utilizes a different splicing mechanism from that of class 1 and 2 inteins. The class 3 intein uses a bond cleavage strategy reminiscent of proteases but share the same Hedgehog/INTein (HINT) fold of other intein classes. Engineering of class 3 inteins from a class 1 intein indicated that a class 3 intein would unlikely evolve directly from a class 1 or 2 intein. The HINT fold appears as structural and functional solution for trans-peptidyl and trans-esterification reactions commonly exploited by diverse mechanisms using different combinations of amino-acid types for the active-site residues.

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.

Case-specific performance of MM-PBSA, MM-GBSA, and SIE in virtual screening.

In drug discovery the reliable prediction of binding free energies is of crucial importance. Methods that combine molecular mechanics force fields with continuum solvent models have become popular because of their high accuracy and relatively good computational efficiency. In this research we studied the performance of molecular mechanics generalized Born surface area (MM-GBSA), molecular mechanics Poisson-Boltzmann surface area (MM-PBSA), and solvated interaction energy (SIE) both in their virtual screening efficiency and their ability to predict experimentally determined binding affinities for five different protein targets. The protein-ligand complexes were derived with two different approaches important in virtual screening: molecular docking and ligand-based similarity search methods. The results show significant differences between the different binding energy calculation methods. However, the length of the molecular dynamics simulation was not of crucial importance for accuracy of results.

Comparison of virtual high-throughput screening methods for the identification of phosphodiesterase-5 inhibitors.

Reliable and effective virtual high-throughput screening (vHTS) methods are desperately needed to minimize the expenses involved in drug discovery projects. Here, we present an improvement to the negative image-based (NIB) screening: the shape, the electrostatics, and the solvation state of the target protein's ligand-binding site are included into the vHTS. Additionally, the initial vHTS results are postprocessed with molecular mechanics/generalized Born surface area (MMGBSA) calculations to estimate the favorability of ligand-protein interactions. The results show that docking produces very good early enrichment for phosphodiesterase-5 (PDE-5); however, in general, the NIB and the ligand-based screening performed better with or without the added electrostatics. Furthermore, the postprocessing of the NIB screening results using MMGBSA calculations improved the early enrichment for the PDE-5 considerably, thus, making hit discovery affordable.

Efficient virtual screening using multiple protein conformations described as negative images of the ligand-binding site.

The protein structure-based virtual screening is typically accomplished using a molecular docking procedure. However, docking is a fairly slow process that is limited by the available scoring functions that cannot reliably distinguish between active and inactive ligands. In contrast, the ligand-based screening methods that are based on shape similarity identify the active ligands with high accuracy. Here, we show that the usage of negative images of the ligand-binding site, together with shape comparison tools, which are typically used in ligand-based virtual screening, improve the discrimination of active molecules from inactives. In contrast to ligand-based shape comparison, the negative image of the binding site allows identification of compounds whose shape complements the shape of the ligand-binding cavity as closely as possible. Furthermore, the use of several target protein conformations allows the identification of active ligands whose shape is not optimal for crystallized protein conformation. Accordingly, the presented virtual screening method improves the identification of novel lead molecules by concentrating on the optimally shaped molecules for the flexible ligand binding site.

Immunogenicity of intrathecal plasmid gene delivery: cytokine release and effects on transgene expression.

BACKGROUND: One method for the delivery of therapeutic proteins to the spinal cord is to inject nonviral gene vectors including plasmid DNA into the cerebrospinal fluid (CSF) that surrounds the spinal cord (intrathecal space). This approach has produced therapeutic benefits in animal models of disease and several months of protein expression; however, there is little information available on the immune response to these treatments in the intrathecal space, the relevance of plasmid CpG sequences to any plasmid-induced immune response, or the effect of this immune response on transgene expression. METHODS: In the present study, coding or noncoding plasmids were delivered to the intrathecal space of the lumbar spinal region in rats. Lumbosacral CSF was then collected at various time points afterwards for monitoring of cytokines and transgene expression. RESULTS: This work demonstrates, for the first time, increased tumor necrosis factor-alpha and interleukin-1 in response to intrathecal plasmid vector injection and provides evidence indicating that this response is largely absent in a CpG-depleted vector. Transgene expression in the CSF is not significantly affected by this immune response. Expression after intrathecal plasmid injection is variable across rats but correlates with the amount of tissue associated plasmid and is increased by disrupting normal CSF flow. CONCLUSIONS: The data obtained in the present study indicate that plasmid immunogenicity may affect intrathecal plasmid gene therapy safety but not transgene expression in the CSF. Furthermore, the development of methods to prevent loss of plasmid via CSF flow out of the central nervous system through the injection hole and/or natural outflow routes may increase intrathecal plasmid gene delivery efficacy.