Leandro Martínez

PACKMOL: A package for building initial configurations for molecular dynamics simulations

Adequate initial configurations for molecular dynamics simulations consist of arrangements of molecules distributed in space in such a way to approximately represent the systems overall structure. In order that the simulations are not disrupted by large van der Waals repulsive interactions, atoms from different molecules must keep safe pairwise distances. Obtaining such a molecular arrangement can be considered a packing problem: Each type molecule must satisfy spatial constraints related to the geometry of the system, and the distance between atoms of different molecules must be greater than some specified tolerance. We have developed a code able to pack millions of atoms, grouped in arbitrarily complex molecules, inside a variety of three‐dimensional regions. The regions may be intersections of spheres, ellipses, cylinders, planes, or boxes. The user must provide only the structure of one molecule of each type and the geometrical constraints that each type of molecule must satisfy. Building complex mixtures, interfaces, solvating biomolecules in water, other solvents, or mixtures of solvents, is straightforward. In addition, different atoms belonging to the same molecule may also be restricted to different spatial regions, in such a way that more ordered molecular arrangements can be built, as micelles, lipid double‐layers, etc. The packing time for state‐of‐the‐art molecular dynamics systems varies from a few seconds to a few minutes in a personal computer. The input files are simple and currently compatible with PDB, Tinker, Molden, or Moldy coordinate files. The package is distributed as free software and can be downloaded from http://www.ime.unicamp.br/∼martinez/packmol/.

Packing optimization for automated generation of complex system's initial configurations for molecular dynamics and docking

Molecular Dynamics is a powerful methodology for the comprehension at molecular level of many chemical and biochemical systems. The theories and techniques developed for structural and thermodynamic analyses are well established, and many software packages are available. However, designing starting configurations for dynamics can be cumbersome. Easily generated regular lattices can be used when simple liquids or mixtures are studied. However, for complex mixtures, polymer solutions or solid adsorbed liquids (for example) this approach is inefficient, and it turns out to be very hard to obtain an adequate coordinate file. In this article, the problem of obtaining an adequate initial configuration is treated as a “packing” problem and solved by an optimization procedure. The initial configuration is chosen in such a way that the minimum distance between atoms of different molecules is greater than a fixed tolerance. The optimization uses a well‐known algorithm for box‐constrained minimization. Applications are given for biomolecule solvation, many‐component mixtures, and interfaces. This approach can reduce the work of designing starting configurations from days or weeks to few minutes or hours, in an automated fashion. Packing optimization is also shown to be a powerful methodology for space search in docking of small ligands to proteins. This is demonstrated by docking of the thyroid hormone to its nuclear receptor.

Medium Chain Fatty Acids Are Selective Peroxisome Proliferator Activated Receptor (PPAR) γ Activators and Pan-PPAR Partial Agonists

Thiazolidinediones (TZDs) act through peroxisome proliferator activated receptor (PPAR) γ to increase insulin sensitivity in type 2 diabetes (T2DM), but deleterious effects of these ligands mean that selective modulators with improved clinical profiles are needed. We obtained a crystal structure of PPARγ ligand binding domain (LBD) and found that the ligand binding pocket (LBP) is occupied by bacterial medium chain fatty acids (MCFAs). We verified that MCFAs (C8–C10) bind the PPARγ LBD in vitro and showed that they are low-potency partial agonists that display assay-specific actions relative to TZDs; they act as very weak partial agonists in transfections with PPARγ LBD, stronger partial agonists with full length PPARγ and exhibit full blockade of PPARγ phosphorylation by cyclin-dependent kinase 5 (cdk5), linked to reversal of adipose tissue insulin resistance. MCFAs that bind PPARγ also antagonize TZD-dependent adipogenesis in vitro. X-ray structure B-factor analysis and molecular dynamics (MD) simulations suggest that MCFAs weakly stabilize C-terminal activation helix (H) 12 relative to TZDs and this effect is highly dependent on chain length. By contrast, MCFAs preferentially stabilize the H2-H3/β-sheet region and the helix (H) 11-H12 loop relative to TZDs and we propose that MCFA assay-specific actions are linked to their unique binding mode and suggest that it may be possible to identify selective PPARγ modulators with useful clinical profiles among natural products.

Gaining ligand selectivity in thyroid hormone receptors via entropy.

Nuclear receptors are important targets for pharmaceuticals, but similarities between family members cause difficulties in obtaining highly selective compounds. Synthetic ligands that are selective for thyroid hormone (TH) receptor β (TRβ) vs. TRα reduce cholesterol and fat without effects on heart rate; thus, it is important to understand TRβ-selective binding. Binding of 3 selective ligands (GC-1, KB141, and GC-24) is characterized at the atomic level; preferential binding depends on a nonconserved residue (Asn-331β) in the TRβ ligand-binding cavity (LBC), and GC-24 gains extra selectivity from insertion of a bulky side group into an extension of the LBC that only opens up with this ligand. Here we report that the natural TH 3,5,3′-triodothyroacetic acid (Triac) exhibits a previously unrecognized mechanism of TRβ selectivity. TR x-ray structures reveal better fit of ligand with the TRα LBC. The TRβ LBC, however, expands relative to TRα in the presence of Triac (549 Å3 vs. 461 Å3), and molecular dynamics simulations reveal that water occupies the extra space. Increased solvation compensates for weaker interactions of ligand with TRβ and permits greater flexibility of the Triac carboxylate group in TRβ than in TRα. We propose that this effect results in lower entropic restraint and decreases free energy of interactions between Triac and TRβ, explaining subtype-selective binding. Similar effects could potentially be exploited in nuclear receptor drug design.

Only subtle protein conformational adaptations are required for ligand binding to thyroid hormone receptors: simulations using a novel multipoint steered molecular dynamics approach.

Thyroid hormone receptors (TR) are hormone-dependent transcription regulators that play a major role in human health, development, and metabolic functions. The thyroid hormone resistance syndrome, diabetes, obesity, and some types of cancer are just a few examples of important diseases that are related to TR malfunctioning, particularly impaired hormone binding. Ligand binding to and dissociation from the receptor ultimately control gene transcription and, thus, detailed knowledge of binding and release mechanisms are fundamental for the comprehension of the receptors biological function and development of pharmaceuticals. In this work, we present the first computational study of ligand entry into the ligand binding domain (LBD) of a nuclear receptor. We report molecular dynamics simulations of ligand binding to TRs using a generalization of the steered molecular dynamics technique designed to perform single-molecule pulling simulations along arbitrarily nonlinear driving pathways. We show that only gentle protein movements and conformational adaptations are required for ligand entry into the LBDs and that the magnitude of the forces applied to assist ligand binding are of the order of the forces involved in ligand dissociation. Our simulations suggest an alternative view for the mechanisms ligand binding and dissociation of ligands from nuclear receptors in which ligands can simply diffuse through the protein surface to reach proper positioning within the binding pocket. The proposed picture indicates that the large-amplitude protein motions suggested by the apo- and holo-RXRalpha crystallographic structures are not required, reconciling conformational changes of LBDs required for ligand entry with other nuclear receptors apo-structures that resemble the ligand-bound LBDs.

Convergent algorithms for protein structural alignment

BackgroundMany algorithms exist for protein structural alignment, based on internal protein coordinates or on explicit superposition of the structures. These methods are usually successful for detecting structural similarities. However, current practical methods are seldom supported by convergence theories. In particular, although the goal of each algorithm is to maximize some scoring function, there is no practical method that theoretically guarantees score maximization. A practical algorithm with solid convergence properties would be useful for the refinement of protein folding maps, and for the development of new scores designed to be correlated with functional similarity.ResultsIn this work, the maximization of scoring functions in protein alignment is interpreted as a Low Order Value Optimization (LOVO) problem. The new interpretation provides a framework for the development of algorithms based on well established methods of continuous optimization. The resulting algorithms are convergent and increase the scoring functions at every iteration. The solutions obtained are critical points of the scoring functions. Two algorithms are introduced: One is based on the maximization of the scoring function with Dynamic Programming followed by the continuous maximization of the same score, with respect to the protein position, using a smooth Newtonian method. The second algorithm replaces the Dynamic Programming step by a fast procedure for computing the correspondence between Cα atoms. The algorithms are shown to be very effective for the maximization of the STRUCTAL score.ConclusionThe interpretation of protein alignment as a LOVO problem provides a new theoretical framework for the development of convergent protein alignment algorithms. These algorithms are shown to be very reliable for the maximization of the STRUCTAL score, and other distance-dependent scores may be optimized with same strategy. The improved score optimization provided by these algorithms provide means for the refinement of protein fold maps and also for the development of scores designed to match biological function. The LOVO strategy may be also used for more general structural superposition problems such as flexible or non-sequential alignments. The package is available on-line at http://www.ime.unicamp.br/~martinez/lovoalign.

Analysis of Agonist and Antagonist Effects on Thyroid Hormone Receptor Conformation by Hydrogen/Deuterium Exchange

Thyroid hormone receptors (TRs) are ligand-gated transcription factors with critical roles in development and metabolism. Although x-ray structures of TR ligand-binding domains (LBDs) with agonists are available, comparable structures without ligand (apo-TR) or with antagonists are not. It remains important to understand apo-LBD conformation and the way that it rearranges with ligands to develop better TR pharmaceuticals. In this study, we conducted hydrogen/deuterium exchange on TR LBDs with or without agonist (T(3)) or antagonist (NH3). Both ligands reduce deuterium incorporation into LBD amide hydrogens, implying tighter overall folding of the domain. As predicted, mass spectroscopic analysis of individual proteolytic peptides after hydrogen/deuterium exchange reveals that ligand increases the degree of solvent protection of regions close to the buried ligand-binding pocket. However, there is also extensive ligand protection of other regions, including the dimer surface at H10-H11, providing evidence for allosteric communication between the ligand-binding pocket and distant interaction surfaces. Surprisingly, C-terminal activation helix H12, which is known to alter position with ligand, remains relatively protected from solvent in all conditions suggesting that it is packed against the LBD irrespective of the presence or type of ligand. T(3), but not NH3, increases accessibility of the upper part of H3-H5 to solvent, and we propose that TR H12 interacts with this region in apo-TR and that this interaction is blocked by T(3) but not NH3. We present data from site-directed mutagenesis experiments and molecular dynamics simulations that lend support to this structural model of apo-TR and its ligand-dependent conformational changes.

Enzyme Microheterogeneous Hydration and Stabilization in Supercritical Carbon Dioxide

Supercritical carbon dioxide is a promising green-chemistry solvent for many enzyme-catalyzed chemical reactions, yet the striking stability of some enzymes in such unconventional environments is not well understood. Here, we investigate the stabilization of the Candida antarctica Lipase B (CALB) in supercritical carbon dioxide-water biphasic systems using molecular dynamics simulations. The preservation of the enzyme structure and optimal activity depend on the presence of small amounts of water in the supercritical dispersing medium. When the protein is at least partially hydrated, water molecules bind to specific sites on the enzyme surface and prevent carbon dioxide from penetrating its catalytic core. Strikingly, water and supercritical carbon dioxide cover the protein surface quite heterogeneously. In the first solvation layer, the hydrophilic residues at the surface of the protein are able to pin down patches of water, whereas carbon dioxide solvates preferentially hydrophobic surface residues. In the outer solvation shells, water molecules tend to cluster predominantly on top of the larger water patches of the first solvation layer instead of spreading evenly around the remainder of the protein surface. For CALB, this exposes the substrate-binding region of the enzyme to carbon dioxide, possibly facilitating diffusion of nonpolar substrates into the catalytic funnel. Therefore, by means of microheterogeneous solvation, enhanced accessibility of hydrophobic substrates to the active site can be achieved, while preserving the functional structure of the enzyme. Our results provide a molecular picture on the nature of the stability of proteins in nonaqueous media.

Synthesis, characterization and catalytic properties of sol–gel derived mixed oxides

Abstract Alumina and 1:1 mixed oxides of Al2O3–ZrO2, Al2O3–TiO2, SiO2–TiO2 and ZrO2–TiO2 were synthesized via a sol–gel process by the so-called neutral amine route, followed by calcination at 600 °C. The mixed oxides were characterized before calcination by X-ray diffraction, revealing ordered hexagonal (Al2O3, Al2O3–ZrO2, ZrO2–TiO2) and lamellar (SiO2–TiO2, Al2O3–TiO2) structures. After calcination, all samples exhibited amorphous structures. Surface areas and pore characteristics of all materials were determined by nitrogen adsorption isotherms. The calcined oxides are active catalysts in the epoxidation of cyclooctene with tert-butyl hydroperoxide as oxidant. Epoxide yields from 14 to 45% were found for reaction times of 24 h. The titanium oxide containing catalysts are the most active and selective ones. On the other hand, the poisoning of acidic centers yields a decreasing activity while increasing selectivity.

Globally convergent trust-region methods for self-consistent field electronic structure calculations

As far as more complex systems are being accessible for quantum chemical calculations, the reliability of the algorithms used becomes increasingly important. Trust-region strategies comprise a large family of optimization algorithms that incorporates both robustness and applicability for a great variety of problems. The objective of this work is to provide a basic algorithm and an adequate theoretical framework for the application of globally convergent trust-region methods to electronic structure calculations. Closed shell restricted Hartree-Fock calculations are addressed as finite-dimensional nonlinear programming problems with weighted orthogonality constraints. A Levenberg-Marquardt-like modification of a trust-region algorithm for constrained optimization is developed for solving this problem. It is proved that this algorithm is globally convergent. The subproblems that ensure global convergence are easy-to-compute projections and are dependent only on the structure of the constraints, thus being extendable to other problems. Numerical experiments are presented, which confirm the theoretical predictions. The structure of the algorithm is such that accelerations can be easily associated without affecting the convergence properties.