Data Driven Computational Design and Experimental Validation of Drugs for Accelerated Mitigation of Pandemic-like Scenarios.

Emerging pathogens are a historic threat to public health and economic stability. Current trial-and-error approaches to identify new therapeutics are often ineffective due to their inefficient exploration of the enormous small molecule design space. Here, we present a data-driven computational framework composed of hybrid evolutionary algorithms for evolving functional groups on existing drugs to improve their binding affinity toward the main protease (Mpro) of SARS-CoV-2. We show that combinations of functional groups and sites are critical to design drugs with improved binding affinity, which can be easily achieved using our framework by exploring a fraction of the available search space. Atomistic simulations and experimental validation elucidate that enhanced and prolonged interactions between functionalized drugs and Mpro residues result in their improved therapeutic value over that of the parental compound. Overall, this novel framework is extremely flexible and has the potential to rapidly design inhibitors for any protein with available crystal structures.

Examining the Drinking Motives Questionnaire-Revised Short Form among university students in Australia, New Zealand and Argentina.

INTRODUCTION: The Drinking Motives Questionnaire-Revised Short Form (DMQ-R-SF) is widely used among alcohol researchers studying adolescents and young adults. The psychometric properties of the DMQ-R-SF have been examined among university students in many countries, but to our knowledge, not in Australia, New Zealand or Argentina. We sought to examine the reliability and endorsement of the items on the DMQ-R-SF, and test the associations between the DMQ-R-SF subscales and alcohol use, and negative alcohol consequences between university students from Australia, New Zealand and Argentina. METHOD: University students (N = 820) in Australia (n = 315), New Zealand (n = 265) and Argentina (n = 240) completed a confidential online alcohol survey which included the DMQ-R-SF, the Daily Drinking Questionnaire and the Brief Young Adult Alcohol Consequences Questionnaire. RESULTS: Using the alignment method, support for the four-factor model on the DMQ-R-SF emerged and the factor loadings for 11 of the 12 items were invariant across sites. Most items (8 out of 12) on the DMQ-R-SF were fully invariant across all sites, but some small differences in item reliability for one item, and endorsement for three items emerged between the sites. Across the three countries, coping motives were positively correlated with negative alcohol consequences. Enhancement motives were positively associated with both alcohol use and negative alcohol consequences among students from Australia and New Zealand. DISCUSSION AND CONCLUSIONS: Most items on the DMQ-R-SF were comparably reliable among the university students sampled from Australia, New Zealand and Argentina. Our preliminary findings suggest that the DMQ-R-SF can be reliably used with university students from these countries.

Impact of Electronic Polarization on Preformed, ß-Strand Rich Homogenous and Heterogenous Amyloid Oligomers.

Amyloids are a subset of intrinsically disordered proteins (IDPs) that self-assemble into cross-ß oligomers and fibrils. The structural plasticity of amyloids leads to sampling of metastable, low-molecular-weight oligomers that contribute to cytotoxicity. Of interest are amyloid-ß (Aß) and islet amyloid polypeptide (IAPP), which are involved in the pathology of Alzheimer's disease and Type 2 Diabetes Mellitus, respectively. In addition to forming homogenous oligomers and fibrils, these species have been found to cross-aggregate in heterogeneous structures. Biophysical properties, including electronic effects, that are unique or conserved between homogenous and heterogenous amyloids oligomers are thus far unexplored. Here, we simulated homogenous and heterogenous amyloid oligomers of Aß16-22 and IAPP20-29 fragments using the Drude oscillator model to investigate the impact of electronic polarization on the structural morphology and stability of preformed hexamers. Upon simulation of preformed, ß-strand rich oligomers with Drude, structural rearrangement occurred causing some loss of ß-strand structure in favor of random coil content for all oligomers. Homogenous Aß16-22 was the most stable system, deriving stability from low polarization in hydrophobic residues and through salt bridge formation. Changes in polarization were observed primarily for Aß16-22 residues in heterogenous cross-amyloid systems, displaying a decrease in charged residue dipole moments and an increase in hydrophobic sidechain dipole moments. This work is the first study utilizing the Drude-2019 force field with amyloid oligomers, providing insight into the impact of electronic effects on oligomer structure and highlighting the importance of different microenvironments on amyloid oligomer stability.

Simulations of cross-amyloid aggregation of amyloid-ß and islet amyloid polypeptide fragments.

Amyloid-ß (Aß) and islet amyloid polypeptide (IAPP) are small peptides, classified as amyloids, that have the potential to self-assemble and form cytotoxic species, such as small soluble oligomers and large insoluble fibrils. The formation of Aß aggregates facilitates the progression of Alzheimer's disease (AD), while IAPP aggregates induce pancreatic ß-cell apoptosis, leading to exacerbation of type 2 diabetes (T2D). Cross-amyloid interactions between Aß and IAPP have been described both in vivo and in vitro, implying the role of Aß or IAPP as modulators of cytotoxic self-aggregation of each species, and suggesting that Aß-IAPP interactions are a potential molecular link between AD and T2D. Using molecular dynamics (MD) simulations, "hotspot" regions of the two peptides were studied to understand the formation of hexamers in a heterogeneous and homogeneous peptide-containing environment. Systems of only Aß(16-22) peptides formed antiparallel, ß-barrel-like structures, while systems of only IAPP(20-29) peptides formed stacked, parallel ß-sheets and had relatively unstable aggregation structures after 2 µs of simulation time. Systems containing both Aß and IAPP (1:1 ratio) hexamers showed antiparallel, ß-barrel-like structures, with an interdigitated arrangement of Aß(16-22) and IAPP(20-29). These ß-barrel structures have features of cytotoxic amyloid species identified in previous literature. Ultimately, this work seeks to provide atomistic insight into both the mechanism behind cross-amyloid interactions and structural morphologies of these toxic amyloid species.

Molecular Dynamics Simulations Indicate Aromaticity as a Key Factor in the Inhibition of IAPP(20-29) Aggregation.

Islet amyloid polypeptide (IAPP) is a 37-residue amyloidogenic hormone implicated in the progression of Type II Diabetes (T2D). T2D affects an estimated 422 million people yearly and is a comorbidity with numerous diseases. IAPP forms toxic oligomers and amyloid fibrils that reduce pancreatic ß-cell mass and exacerbate the T2D disease state. Toxic oligomer formation is attributed, in part, to the formation of interpeptide ß-strands comprised of residues 20-29 (IAPP(20-29)). Flavonoids, a class of polyphenolic natural products, have been found experimentally to inhibit IAPP aggregate formation. Many of these small flavonoids differ structurally only slightly; the influence of functional group placement on inhibiting the aggregation of the IAPP(20-29) has yet to be explored. To probe the role of small-molecule structural features that impede IAPP aggregation, molecular dynamics simulations were performed to observe trimer formation on a model fragment of IAPP(20-29) in the presence of morin, quercetin, dihydroquercetin, epicatechin, and myricetin. Contacts between Phe23 residues were critical to oligomer formation, and small-molecule contacts with Phe23 were a key predictor of ß-strand reduction. Structural properties influencing the ability of compounds to disrupt Phe23-Phe23 contacts included aromaticity and carbonyl and hydroxyl group placement. This work provides key information on design considerations for T2D therapeutics that target IAPP aggregation.