Search

Context: Given the elusive nature of Primary Amoebic Meningoencephalitis (PAM), caused by Naegleria fowleri, early detection is vital, yet challenging due to limited clinical indicators. This research leverages Indonesia’s rich biodiversity to explore novel sources of traditional medicine. Aims: To evaluate the potential compounds from Indonesian plants that possess antiamoebic and antifungal properties for inhibiting the N. fowleri CYP51 protein, crucial for cell integrity. Methods: Initially, 92 compounds were screened, and six were shortlisted following ADMETox evaluation. Subsequent steps encompassed QSAR analysis, molecular docking, and molecular dynamics simulations. Results: The QSAR analysis verified the activity potential of these six compounds, progressing them to molecular docking analysis. Among these, curcumenol from Curcuma longa emerged as a promising contender, displaying the lowest binding affinity at -9.2 kcal/mol, indicative of superior binding compared to other ligands. Molecular dynamics simulations underscored the stability of all compounds, with root mean square fluctuation (RMSF) values within 1-3 Å. Conclusions: Consequently, employing a comprehensive approach spanning ADMETox, QSAR, molecular docking, and dynamics simulations, curcumenol emerged as the prime candidate for inhibiting the N. fowleri CYP51 protein, suggesting its potential as a PAM therapeutic agent.

Critical assessment of structure prediction (CASP) conducts community experiments to determine the state of the art in computing protein structure from amino acid sequence. The process relies on the experimental community providing information about not yet public or about to be solved structures, for use as targets. For some targets, the experimental structure is not solved in time for use in CASP. Calculated structure accuracy improved dramatically in this round, implying that models should now be much more useful for resolving many sorts of experimental difficulties. To test this, selected models for seven unsolved targets were provided to the experimental groups. These models were from the AlphaFold2 group, who overall submitted the most accurate predictions in CASP14. Four targets were solved with the aid of the models, and, additionally, the structure of an already solved target was improved. An a posteriori analysis showed that, in some cases, models from other groups would also be effective. This paper provides accounts of the successful application of models to structure determination, including molecular replacement for X-ray crystallography, backbone tracing and sequence positioning in a cryo-electron microscopy structure, and correction of local features. The results suggest that, in future, there will be greatly increased synergy between computational and experimental approaches to structure determination.