Javier Klett

MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

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.

Semisynthetic peptide-lipase conjugates for improved biotransformations.

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.

CRDOCK: An Ultrafast Multipurpose Protein–Ligand Docking Tool

An ultrafast docking and virtual screening program, CRDOCK, is presented that contains (1) a search engine that can use a variety of sampling methods and an initial energy evaluation function, (2) several energy minimization algorithms for fine tuning the binding poses, and (3) different scoring functions. This modularity ensures the easy configuration of custom-made protocols that can be optimized depending on the problem in hand. CRDOCK employs a precomputed library of ligand conformations that are initially generated from one-dimensional SMILES strings. Testing CRDOCK on two widely used benchmarks, the ASTEX diverse set and the Directory of Useful Decoys, yielded a success rate of ~75% in pose prediction and an average AUC of 0.66. A typical ligand can be docked, on average, in just ~13 s. Extension to a representative group of pharmacologically relevant G protein-coupled receptors that have been recently cocrystallized with some selective ligands allowed us to demonstrate the utility of this tool and also highlight some current limitations. CRDOCK is now included within VSDMIP, our integrated platform for drug discovery.

gCOMBINE: A graphical user interface to perform structure-based comparative binding energy (COMBINE) analysis on a set of ligand-receptor complexes†

We present gCOMBINE, a Java‐written graphical user interface (GUI) for performing comparative binding energy (COMBINE) analysis (Ortiz et al. J Med Chem 1995; 38:2681–2691) on a set of ligand‐receptor complexeswith the aim of deriving highly informative quantitative structure‐activity relationships. The essence of the method is to decompose the ligand‐receptor interaction energies into a series of terms, explore the origins of the variance within the set using Principal Component Analysis, and then assign weights to selected ligandresidue interactions using partial least squares analysis to correlate with the experimental activities or binding affinities. The GUI allows plenty of interactivity and provides multiple plots representing the energy descriptors entering the analysis, scores, loadings, experimental versus predicted regression lines, and the evolution of parameterssuch as r2 (correlation coefficient), q2 (cross‐validated r2), and prediction errors as the number of extracted latent variables increases. Other representative features include the implementation of a sigmoidal dielectric function for electrostatic energy calculations, alternative cross‐validation procedures (leave‐N‐out and random groups), drawing of confidence ellipses, and the possibility to carry out several additional tasks such as optional truncation of positive interaction energy values and generation of ready‐to‐use PDB files containing information related to the importance for activity of individual protein residues. This information can be displayed and color‐coded using a standard molecular graphics program such as PyMOL. It is expected that this user‐friendly tool will expand the applicability of the COMBINE analysis method and encourage more groups to use it in their drug design research programs. Proteins 2010.

Comparative binding energy (COMBINE) analysis supports a proposal for the binding mode of epothilones to β-tubulin.

The conformational preferences of epothilone A (EPA) and a 12,13‐cyclopropyl C12‐epimerized analogue were explored in aqueous solution using molecular dynamics simulations. The simulated conformers that provided an optimal fit in the paclitaxel binding site of mammalian β‐tubulin were then selected. The resulting modeled complexes were simulated before and after refinement of the M‐loop to improve the fitting and assess ligand stability within the binding pocket. The tubulin‐bound conformation of EPA was found to be unlike a previously reported solution obtained through mixed crystallographic/NMR/modeling studies. However, our conformation was in agreement with an NMR‐based proposal although the exact binding pose within the site was different. Molecular models were built for the complexes of 14 epothilone derivatives with β‐tubulin. A projection to latent structures regression method succeeded in providing a good prediction of the experimentally measured binding enthalpies for the whole set of ligands by assigning weights to a selection of interaction energy terms. These receptor‐based, quantitative structure–activity relationships support the proposed binding mode, help confirm and interpret previously acquired experimental data, shed additional light on the effect of several β‐tubulin mutations on ligand binding, and can potentially direct further experimental studies.

ALFA: Automatic Ligand Flexibility Assignment

ALFA is a fast computational tool for the conformational analysis of small molecules that uses a custom-made iterative algorithm to provide a set of representative conformers in an attempt to reproduce the diversity of states in which small molecules can exist, either isolated in solution or bound to a target. The results shown in this work prove that ALFA is fast enough to be integrated into massive high-throughput virtual screening protocols with the aim of incorporating ligand flexibility and also that ALFA reproduces crystallographic X-ray structures of bound ligands with great accuracy. Furthermore, the application includes a graphical user interface that allows its use through the popular molecular graphics program PyMOL to make it accessible to nonexpert users. ALFA is distributed free of charge upon request from the authors.

Antibiotic Capture by Bacterial Lipocalins Uncovers an Extracellular Mechanism of Intrinsic Antibiotic Resistance

ABSTRACT 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. IMPORTANCE Current research on antibiotic action and resistance focuses on targeting essential functions within bacterial cells. We discovered a previously unrecognized mode of general bacterial antibiotic resistance operating in the extracellular space, which depends on bacterial protein molecules called lipocalins. These molecules are highly conserved in most bacteria and have the ability to capture different classes of antibiotics outside bacterial cells. We also discovered that liposoluble vitamins, such as vitamin E, overcome in vitro and in vivo antibiotic resistance mediated by bacterial lipocalins, providing an unexpected new alternative to combat resistance by using this vitamin or its derivatives as antibiotic adjuvants. IMPORTANCE Current research on antibiotic action and resistance focuses on targeting essential functions within bacterial cells. We discovered a previously unrecognized mode of general bacterial antibiotic resistance operating in the extracellular space, which depends on bacterial protein molecules called lipocalins. These molecules are highly conserved in most bacteria and have the ability to capture different classes of antibiotics outside bacterial cells. We also discovered that liposoluble vitamins, such as vitamin E, overcome in vitro and in vivo antibiotic resistance mediated by bacterial lipocalins, providing an unexpected new alternative to combat resistance by using this vitamin or its derivatives as antibiotic adjuvants.

A structure-based design of new C2- and C13-substituted taxanes: tubulin binding affinities and extended quantitative structure-activity relationships using comparative binding energy (COMBINE) analysis.

Ten novel taxanes bearing modifications at the C2 and C13 positions of the baccatin core have been synthesized and their binding affinities for mammalian tubulin have been experimentally measured. The design strategy was guided by (i) calculation of interaction energy maps with carbon, nitrogen and oxygen probes within the taxane-binding site of β-tubulin, and (ii) the prospective use of a structure-based QSAR (COMBINE) model derived from an earlier series comprising 47 congeneric taxanes. The tubulin-binding affinity displayed by one of the new compounds (CTX63) proved to be higher than that of docetaxel, and an updated COMBINE model provided a good correlation between the experimental binding free energies and a set of weighted residue-based ligand-receptor interaction energies for 54 out of the 57 compounds studied. The remaining three outliers from the original training series have in common a large unfavourable entropic contribution to the binding free energy that we attribute to taxane preorganization in aqueous solution in a conformation different from that compatible with tubulin binding. Support for this proposal was obtained from solution NMR experiments and molecular dynamics simulations in explicit water. Our results shed additional light on the determinants of tubulin-binding affinity for this important class of antitumour agents and pave the way for further rational structural modifications.

Molecular Basis of the Functional Differences between Soluble Human Versus Murine MD-2: Role of Val135 in Transfer of Lipopolysaccharide from CD14 to MD-2.

Myeloid differentiation factor 2 (MD-2) is an extracellular protein, associated with the ectodomain of TLR4, that plays a critical role in the recognition of bacterial LPS. Despite high overall structural and functional similarity, human (h) and murine (m) MD-2 exhibit several species-related differences. hMD-2 is capable of binding LPS in the absence of TLR4, whereas mMD-2 supports LPS responsiveness only when mMD-2 and mTLR4 are coexpressed in the same cell. Previously, charged residues at the edge of the LPS binding pocket have been attributed to this difference. In this study, site-directed mutagenesis was used to explore the hydrophobic residues within the MD-2 binding pocket as the source of functional differences between hMD-2 and mMD-2. Whereas decreased hydrophobicity of residues 61 and 63 in the hMD-2 binding pocket retained the characteristics of wild-type hMD-2, a relatively minor change of valine to alanine at position 135 completely abolished the binding of LPS to the hMD-2 mutant. The mutant, however, retained the LPS binding in complex with TLR4 and also cell activation, resulting in a murine-like phenotype. These results were supported by the molecular dynamics simulation. We propose that the residue at position 135 of MD-2 governs the dynamics of the binding pocket and its ability to accommodate lipid A, which is allosterically affected by bound TLR4.

Glycolipid-based TLR4 Modulators and Fluorescent Probes: Rational Design, Synthesis, and Biological Properties.

The cationic glycolipid IAXO‐102, a potent TLR4 antagonist targeting both MD‐2 and CD14 co‐receptors, has been used as scaffold to design new potential TLR4 modulators and fluorescent labels for the TLR4 receptor complex (membrane TLR4.MD‐2 dimer and CD14). The primary amino group of IAXO‐102, not involved in direct interaction with MD‐2 and CD14 receptors, has been exploited to covalently attach a fluorescein (molecules 1 and 2) or to link two molecules of IAXO‐102 through diamine and diammonium spacers, obtaining ‘dimeric’ molecules 3 and 4. The structure‐based rational design of compounds 1‐4 was guided by the optimization of MD‐2 and CD14 binding. Compounds 1 and 2 inhibited TLR4 activation, in a concentration‐dependent manner, and signaling in HEK‐Blue TLR4 cells. The fluorescent labeling of murine macrophages by molecule 1 was inhibited by LPS and was also abrogated when cell surface proteins were digested by trypsin, thus suggesting an interaction of fluorescent probe 1 with membrane proteins of the TLR4 receptor system.