An Open Drug Discovery Competition: Experimental Validation of Predictive Models in a Series of Novel Antimalarials.

The Open Source Malaria (OSM) consortium is developing compounds that kill the human malaria parasite, Plasmodium falciparum, by targeting PfATP4, an essential ion pump on the parasite surface. The structure of PfATP4 has not been determined. Here, we describe a public competition created to develop a predictive model for the identification of PfATP4 inhibitors, thereby reducing project costs associated with the synthesis of inactive compounds. Competition participants could see all entries as they were submitted. In the final round, featuring private sector entrants specializing in machine learning methods, the best-performing models were used to predict novel inhibitors, of which several were synthesized and evaluated against the parasite. Half possessed biological activity, with one featuring a motif that the human chemists familiar with this series would have dismissed as "ill-advised". Since all data and participant interactions remain in the public domain, this research project "lives" and may be improved by others.

Peptides in the presence of aqueous ionic liquids: tunable co-solutes as denaturants or protectants?

We studied the stability of a small ß-hairpin peptide under the influence of an aqueous 1-ethyl-3-methylimidazolium acetate ([EMIM](+)[ACE](-)) solution via all-atom molecular dynamics simulations in combination with metadynamics. Our free energy results indicate a denaturation of the peptide structure in the presence of the ionic liquid which is validated by a significant broadening of the end-to-end distance. The radial distribution functions between the ions and the peptide were used for the calculation of the preferential binding coefficients in terms of the Kirkwood-Buff theory. A significant structure dependent binding behavior of acetate to the peptide was found which can be interpreted as the main reason for the denaturation of the native conformation. The outcomes of our simulations allow us to propose a simple mechanism to explain the unfolding of the peptide with regard to the specific properties of ionic liquids. Our results are in good agreement with experimental findings and demonstrate the benefits of ionic liquids as tunable co-solutes with regard to their influence on protein structural properties.

Evaluating data mining algorithms using molecular dynamics trajectories.

Molecular dynamics simulations provide a sample of a molecule's conformational space. Experiments on the mus time scale, resulting in large amounts of data, are nowadays routine. Data mining techniques such as classification provide a way to analyse such data. In this work, we evaluate and compare several classification algorithms using three data sets which resulted from computer simulations, of a potential enzyme mimetic biomolecule. We evaluated 65 classifiers available in the well-known data mining toolkit Weka, using 'classification' errors to assess algorithmic performance. Results suggest that: (i) 'meta' classifiers perform better than the other groups, when applied to molecular dynamics data sets; (ii) Random Forest and Rotation Forest are the best classifiers for all three data sets; and (iii) classification via clustering yields the highest classification error. Our findings are consistent with bibliographic evidence, suggesting a 'roadmap' for dealing with such data.

Insights into the structure of the PmrD protein with molecular dynamics simulations.

Resistance to cationic antimicrobial peptide polymyxin B from Gram-negative bacteria is accomplished by two-component systems (TCSs), protein complexes PmrA/PmrB and PhoP/PhoQ. PmrD is the first protein identified to mediate the connectivity between two TCSs. The 3D structure of PmrD has been recently solved by NMR and its unique fold was revealed. Here, a molecular dynamics study is presented started from the NMR structure. Numerous hydrophobic and electrostatic interactions were identified to contribute to PmrD's 3D stability. Moreover, the mobility of the five loops that connect the protein's six beta-strands has been explored. Solvent-accessible surface area calculation revealed that a Leucine-rich hydrophobic cluster of the protein stabilized the protein's structure.

Molecular Dynamics as a pattern recognition tool: an automated process detects peptides that preserve the 3D arrangement of Trypsin's Active Site.

Recently, the synthesis of a molecule has been reported that belongs to a Lysine based, branched cyclic peptide class. This work explores the ability of such molecules to preserve the 3D geometry of the Trypsin's Active Site (TAS) by applying an integrated framework of automated computer procedures. The following four factors a) D/L chirality, b) different amino acids at different positions of the molecular scaffold's cyclic part, c) the application of AMBER and CHARMM force fields and d) different implicit solvation models were evaluated against TAS similarity. It was found that a number of molecules exhibit satisfactory geometric affinity to the TAS during extended Molecular Dynamics runs. We estimated that more than 2000 molecules (belonging to this class) could retain good similarity to the TAS arrangement.