Functional and structural consequences of TBK1 missense variants in frontotemporal lobar degeneration and amyotrophic lateral sclerosis.

Mutations in the Tank-binding kinase 1 (TBK1) gene were identified in 2015 in individuals with frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS). They account for ∼3-4% of cases. To date, over 100 distinct mutations, including missense, nonsense, deletion, insertion, duplication, and splice-site mutations have been reported. While nonsense mutations are predicted to cause disease via haploinsufficiency, the mechanisms underlying disease pathogenesis with missense mutations is not fully elucidated. TBK1 is a kinase involved in neuroinflammation, which is commonly observed in these diseases. TBK1 also phosphorylates key autophagy mediators, thereby regulating proteostasis, a pathway that is dysregulated in ALS-FTLD. Recently, several groups have characterised various missense mutations with respect to their effects on the phosphorylation of known TBK1 substrates, TBK1 homodimerization, interaction with optineurin, and the regulation of autophagy and neuroinflammatory pathways. Further, the effects of either global or conditional heterozygous knock-out of Tbk1, or the heterozygous or homozygous knock-in of ALS-FTLD associated mutations, alone or when crossed with the SOD1G93A classical ALS mouse model or a TDP-43 mouse model, have been reported. In this review we summarise the known functional effects of TBK1 missense mutations. We also present novel modelling data that predicts the structural effects of missense mutations and discuss how they correlate with the known functional effects of these mutations.

Characterisation of the Structure and Oligomerisation of Islet Amyloid Polypeptides (IAPP): A Review of Molecular Dynamics Simulation Studies.

Human islet amyloid polypeptide (hIAPP) is a naturally occurring, intrinsically disordered protein whose abnormal aggregation into amyloid fibrils is a pathological feature in type 2 diabetes, and its cross-aggregation with amyloid beta has been linked to an increased risk of Alzheimer's disease. The soluble, oligomeric forms of hIAPP are the most toxic to ß-cells in the pancreas. However, the structure of these oligomeric forms is difficult to characterise because of their intrinsic disorder and their tendency to rapidly aggregate into insoluble fibrils. Experimental studies of hIAPP have generally used non-physiological conditions to prevent aggregation, and they have been unable to describe its soluble monomeric and oligomeric structure at physiological conditions. Molecular dynamics (MD) simulations offer an alternative for the detailed characterisation of the monomeric structure of hIAPP and its aggregation in aqueous solution. This paper reviews the knowledge that has been gained by the use of MD simulations, and its relationship to experimental data for both hIAPP and rat IAPP. In particular, the influence of the choice of force field and water models, the choice of initial structure, and the configurational sampling method used, are discussed in detail. Characterisation of the solution structure of hIAPP and its mechanism of oligomerisation is important to understanding its cellular toxicity and its role in disease states, and may ultimately offer new opportunities for therapeutic interventions.

Characterization of the Conformations of Amyloid Beta 42 in Solution That May Mediate Its Initial Hydrophobic Aggregation.

Intrinsically disordered peptides, such as amyloid ß42 (Aß42), lack a well-defined structure in solution. Aß42 can undergo abnormal aggregation and amyloidogenesis in the brain, forming fibrillar plaques, a hallmark of Alzheimer's disease. The insoluble fibrillar forms of Aß42 exhibit well-defined, cross ß-sheet structures at the molecular level and are less toxic than the soluble, intermediate disordered oligomeric forms. However, the mechanism of initial interaction of monomers and subsequent oligomerization is not well understood. The structural disorder of Aß42 adds to the challenges of determining the structural properties of its monomers, making it difficult to understand the underlying molecular mechanism of pathogenic aggregation. Certain regions of Aß42 are known to exhibit helical propensity in different physiological conditions. NMR spectroscopy has shown that the Aß42 monomer at lower pH can adopt an α-helical conformation and as the pH is increased, the peptide switches to ß-sheet conformation and aggregation occurs. CD spectroscopy studies of aggregation have shown the presence of an initial spike in the amount of α-helical content at the start of aggregation. Such an increase in α-helical content suggests a mechanism wherein the peptide can expose critical non-polar residues for interaction, leading to hydrophobic aggregation with other interacting peptides. We have used molecular dynamics simulations to characterize in detail the conformational landscape of monomeric Aß42 in solution to identify molecular properties that may mediate the early stages of oligomerization. We hypothesized that conformations with α-helical structure have a higher probability of initiating aggregation because they increase the hydrophobicity of the peptide. Although random coil conformations were found to be the most dominant, as expected, α-helical conformations are thermodynamically accessible, more so than ß-sheet conformations. Importantly, for the first time α-helical conformations are observed to increase the exposure of aromatic and hydrophobic residues to the aqueous solvent, favoring their hydrophobically driven interaction with other monomers to initiate aggregation. These findings constitute a first step toward characterizing the mechanism of formation of disordered, low-order oligomers of Aß42.

Loss of a water-mediated network results in reduced agonist affinity in a ß2-adrenergic receptor clinical variant.

The ß2-adrenergic receptor (ß2AR) is a member of the G protein-coupled receptor (GPCR) family that is an important drug target for asthma and COPD. Clinical studies coupled with biochemical data have identified a critical receptor variant, Thr164Ile, to have a reduced response to agonist-based therapy, although the molecular mechanism underlying this seemingly "non-deleterious" substitution is not clear. Here, we couple molecular dynamics simulations with network analysis and free-energy calculations to identify the molecular determinants underlying the differential drug response. We are able to identify hydration sites in the transmembrane domain that are essential to maintain the integrity of the binding site but are absent in the variant. The loss of these hydration sites in the variant correlates with perturbations in the intra-protein interaction network and rearrangements in the orthosteric ligand binding site. In conjunction, we observe an altered binding and reduced free energy of a series of agonists, in line with experimental trends. Our work identifies a functional allosteric pathway connected by specific hydration sites in ß2AR that has not been reported before and provides insight into water-mediated networks in GPCRs in general. Overall, the work is one of the first step towards developing variant-specific potent and selective agonists.

TryTransDB: A web-based resource for transport proteins in Trypanosomatidae.

TryTransDB is a web-based resource that stores transport protein data which can be retrieved using a standalone BLAST tool. We have attempted to create an integrated database that can be a one-stop shop for the researchers working with transport proteins of Trypanosomatidae family. TryTransDB (Trypanosomatidae Transport Protein Database) is a web based comprehensive resource that can fire a BLAST search against most of the transport protein sequences (protein and nucleotide) from Trypanosomatidae family organisms. This web resource further allows to compute a phylogenetic tree by performing multiple sequence alignment (MSA) using CLUSTALW suite embedded in it. Also, cross-linking to other databases helps in gathering more information for a certain transport protein in a single website.

Characterizing clinically relevant natural variants of GPCRs using computational approaches.

G protein-coupled receptors (GPCRs) are an important class of drug targets owing to their physiological role. A large number of clinically relevant single nucleotide polymorphisms (SNPs) have been observed in GPCRs that are linked to disease susceptibility and adverse drug response. It is therefore important to characterize the variants in order to improve GPCR therapeutics. Here, we discuss computational methods coupling molecular dynamics simulations with docking and free energy calculations to characterize the functional differences in GPCR variants. The hallmark of this approach is the explicit incorporation of receptor and membrane dynamics that allows us to analyze short- and long-range effects in the variant receptors. We use the SNPs reported in ß2-adrenergic receptor (ß2AR) as a test case and highlight the recent successes in analyzing structural and dynamic differences in a series of population variants. The computational approach we discuss here has a twofold benefit: it helps to unravel the molecular mechanisms underlying hypo- or hyperfunctionality of variant receptors as well as prioritizing novel variants that must be experimentally tested.