An ultrafast and accurate scoring function for protein-protein docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12-6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein-protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein-protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge-charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein-protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein-protein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r(2) ∼ 0.9), and only 0.2-5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations. MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode. MM-ISMSA is distributed free of charge to nonprofit organizations.

The potential for microbes to overcome antibiotics of different classes before they reach bacterial cells is largely unexplored. Here we show that a soluble bacterial lipocalin produced by Burkholderia cenocepacia upon exposure to sublethal antibiotic concentrations increases resistance to diverse antibiotics in vitro and in vivo. These phenotypes were recapitulated by heterologous expression in B. cenocepacia of lipocalin genes from Pseudomonas aeruginosa, Mycobacterium tuberculosis, and methicillin-resistant Staphylococcus aureus. Purified lipocalin bound different classes of bactericidal antibiotics and contributed to bacterial survival in vivo. Experimental and X-ray crystal structure-guided computational studies revealed that lipocalins counteract antibiotic action by capturing antibiotics in the extracellular space. We also demonstrated that fat-soluble vitamins prevent antibiotic capture by binding bacterial lipocalin with higher affinity than antibiotics. Therefore, bacterial lipocalins contribute to antimicrobial resistance by capturing diverse antibiotics in the extracellular space at the site of infection, which can be counteracted by known vitamins.

An efficient chemoselective method for the creation of semisynthetic lipases by site-specific incorporation of tailor-made peptides on the lipase-lid site was developed. These new enzymes showed excellent improved specificity and regio-or enantioselectivity in different biotransformations.