Enhancing the Intrinsic Antiplasmodial Activity and Improving the Stability and Selectivity of a Tunable Peptide Scaffold Derived from Human Platelet Factor 4.

The control of malaria, a disease caused by Plasmodium parasites that kills over half a million people every year, is threatened by the continual emergence and spread of drug resistance. Therefore, new molecules with different mechanisms of action are needed in the antimalarial drug development pipeline. Peptides developed from host defense molecules are gaining traction as anti-infectives due to theood of inducing drug resistance. Human platelet factor 4 (PF4) has intrinsic activity against P. falciparum, and a macrocyclic helix-loop-helix peptide derived from its active domain recapitulates this activity. In this study, we used a stepwise approach to optimize first-generation PF4-derived internalization peptides (PDIPs) by producing analogues with substitutions to charged and hydrophobic amino acid residues or with modifications to terminal residues including backbone cyclization. We evaluated the in vitro activity of PDIP analogues against P. falciparum compared to their overall helical structure, resistance to breakdown by serum proteases, selective binding to negatively charged membranes, and hemolytic activity. Next, we combined antiplasmodial potency-enhancing substitutions that retained favorable membrane and cell-selective properties onto the most stable scaffold to produce a backbone cyclic PDIP analogue with four-fold improved activity against P. falciparum compared to first-generation peptides. These studies demonstrate the ability to modify PDIP to select for and combine desirable properties and further validate the suitability of this unique peptide scaffold for developing a new molecule class that is distinct from existing antimalarial drugs.

Estimating statistical power for ERP studies using the auditory N1, Tb, and P2 components.

The N1, Tb, and P2 components of the event-related potential (ERP) are thought to reflect the sequential processing of auditory stimuli in the human brain. Despite their extensive use in biological, cognitive, and clinical neuroscience, there are no guidelines for how to appropriately power ERP studies using these components. In the present study, we investigated how the number of trials, number of participants, effect magnitude, and study design influenced statistical power. Using Monte Carlo simulations of ERP data from a passive listening task, we determined the probability of finding a statistically significant effect in 58,900 experiments repeated 1,000 times each. We found that as the number of trials, number of participants, and effect magnitude increased, so did statistical power. We also found that increasing the number of trials had a bigger effect on statistical power for within-subject designs than for between-subject designs, and that within-subject designs required a smaller number of trials and participants to provide the same level of statistical power for a given effect magnitude than between-subject designs. These results show that it is important to carefully consider these factors when designing ERP studies, rather than relying on tradition or anecdotal evidence. To improve the robustness and reproducibility of ERP research, we have built an online statistical power calculator (https://bradleynjack.shinyapps.io/ErpPowerCalculator), which we hope will allow researchers to estimate the statistical power of previous studies, as well as help them design appropriately-powered studies in the future.