Carlos J. V. Simões

Potentially amyloidogenic conformational intermediates populate the unfolding landscape of transthyretin: Insights from molecular dynamics simulations

Protein aggregation into insoluble fibrillar structures known as amyloid characterizes several neurodegenerative diseases, including Alzheimers, Huntingtons and Creutzfeldt‐Jakob. Transthyretin (TTR), a homotetrameric plasma protein, is known to be the causative agent of amyloid pathologies such as FAP (familial amyloid polyneuropathy), FAC (familial amyloid cardiomiopathy) and SSA (senile systemic amyloidosis). It is generally accepted that TTR tetramer dissociation and monomer partial unfolding precedes amyloid fibril formation. To explore the TTR unfolding landscape and to identify potential intermediate conformations with high tendency for amyloid formation, we have performed molecular dynamics unfolding simulations of WT‐TTR and L55P‐TTR, a highly amyloidogenic TTR variant. Our simulations in explicit water allow the identification of events that clearly discriminate the unfolding behavior of WT and L55P‐TTR. Analysis of the simulation trajectories show that (i) the L55P monomers unfold earlier and to a larger extent than the WT; (ii) the single α‐helix in the TTR monomer completely unfolds in most of the L55P simulations while remain folded in WT simulations; (iii) L55P forms, early in the simulations, aggregation‐prone conformations characterized by full displacement of strands C and D from the main β‐sandwich core of the monomer; (iv) L55P shows, late in the simulations, severe loss of the H‐bond network and consequent destabilization of the CBEF β‐sheet of the β‐sandwich; (v) WT forms aggregation‐compatible conformations only late in the simulations and upon extensive unfolding of the monomer. These results clearly show that, in comparison with WT, L55P‐TTR does present a much higher probability of forming transient conformations compatible with aggregation and amyloid formation.

Toward the discovery of functional transthyretin amyloid inhibitors: application of virtual screening methods.

Inhibition of amyloid fibril formation by stabilization of the native form of the protein transthyretin (TTR) is a viable approach for the treatment of familial amyloid polyneuropathy that has been gaining momentum in the field of amyloid research. The TTR stabilizer molecules discovered to date have shown efficacy at inhibiting fibrilization in vitro but display impairing issues of solubility, affinity for TTR in the blood plasma and/or adverse effects. In this study we present a benchmark of four protein- and ligand-based virtual screening (VS) methods for identifying novel TTR stabilizers: (i) two-dimensional (2D) similarity searches with chemical hashed, pharmacophore, and UNITY fingerprints, (ii) 3D searches based on shape, chemical, and electrostatic similarity, (iii) LigMatch, a new ligand-based method which uses multiple templates and combines 3D geometric hashing with a 2D preselection process, and (iv) molecular docking to consensus X-ray crystal structures of TTR. We illustrate the potential of the best-performing VS protocols to retrieve promising new leads by ranking a tailored library of 2.3 million commercially available compounds. Our predictions show that the top-scoring molecules possess distinctive features from the known TTR binders, holding better solubility, fraction of halogen atoms, and binding affinity profiles. To the best of our knowledge, this is the first attempt to rationalize the utilization of a large battery of in silico screening techniques toward the identification of a new generation of TTR amyloid inhibitors.

Predicting hydrophobic solvation by molecular simulation: 1. testing united-atom alkane models

We present a systematic test of the performance of three popular united‐atom force fields—OPLS‐UA, GROMOS and TraPPE—at predicting hydrophobic solvation, more precisely at describing the solvation of alkanes in alkanes. Gibbs free energies of solvation were calculated for 52 solute/solvent pairs from Molecular Dynamics simulations and thermodynamic integration making use of the IBERCIVIS volunteer computing platform. Our results show that all force fields yield good predictions when both solute and solvent are small linear or branched alkanes (up to pentane). However, as the size of the alkanes increases, all models tend to increasingly deviate from experimental data in a systematic fashion. Furthermore, our results confirm that specific interaction parameters for cyclic alkanes in the united‐atom representation are required to account for the additional excluded volume within the ring. Overall, the TraPPE model performs best for all alkanes, but systematically underpredicts the magnitude of solvation free energies by about 6% (RMSD of 1.2 kJ/mol). Conversely, both GROMOS and OPLS‐UA systematically overpredict solvation free energies (by ∼13% and 15%, respectively). The systematic trends suggest that all models can be improved by a slight adjustment of their Lennard‐Jones parameters.

Assessing the Effect of 2D Fingerprint Filtering on ILP-Based Structure-Activity Relationships Toxicity Studies in Drug Design

The rational development of new drugs is a complex and expensive process. A myriad of factors affect the activity of putative candidate molecules in vivo and the propensity for causing adverse and toxic effects is recognised as the major hurdle behind the current “target-rich, lead-poor” scenario.