Abstract:Adequate initial configurations for molecular dynamics simulations consist of arrangements of molecules distributed in space in such a way to approximately represent the system's 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

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.

The analysis of structural mobility in molecular dynamics plays a key role in data interpretation, particularly in the simulation of biomolecules. The most common mobility measures computed from simulations are the Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuations (RMSF) of the structures. These are computed after the alignment of atomic coordinates in each trajectory step to a reference structure. This rigid-body alignment is not robust, in the sense that if a small portion of the structure is highly mobile, the RMSD and RMSF increase for all atoms, resulting possibly in poor quantification of the structural fluctuations and, often, to overlooking important fluctuations associated to biological function. The motivation of this work is to provide a robust measure of structural mobility that is practical, and easy to interpret. We propose a Low-Order-Value-Optimization (LOVO) strategy for the robust alignment of the least mobile substructures in a simulation. These substructures are automatically identified by the method. The algorithm consists of the iterative superposition of the fraction of structure displaying the smallest displacements. Therefore, the least mobile substructures are identified, providing a clearer picture of the overall structural fluctuations. Examples are given to illustrate the interpretative advantages of this strategy. The software for performing the alignments was named MDLovoFit and it is available as free-software at: http://leandro.iqm.unicamp.br/mdlovofit

Steered molecular dynamics simulations of ligand dissociation from Thyroid hormone receptors indicate that dissociation is favored via rearrangements in a mobile part of the LBD comprising H3, the loop between H1 and H2, and nearby beta-sheets, contrary to current models in which the H12 is mostly involved. Dissociation is facilitated in this path by the interaction of the hydrophilic part of the ligand with external water molecules, suggesting strategies to enhance ligand binding affinity.

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.

Nuclear receptor (NR) ligands occupy a pocket that lies within the core of the NR ligand-binding domain (LBD), and most NR LBDs lack obvious entry/exit routes upon the protein surface. Thus, significant NR conformational rearrangements must accompany ligand binding and release. The precise nature of these processes, however, remains poorly understood. Here, we utilize locally enhanced sampling (LES) molecular dynamics computer simulations to predict molecular motions of x-ray structures of thyroid hormone receptor (TR) LBDs and determine events that permit ligand escape. We find that the natural ligand 3,5,3'-triiodo-L-thyronine (T(3)) dissociates from the TRalpha1 LBD along three competing pathways generated through i), opening of helix (H) 12; ii), separation of H8 and H11 and the Omega-loop between H2 and H3; and iii), opening of H2 and H3, and the intervening beta-strand. Similar pathways are involved in dissociation of T(3) and the TRbeta-selective ligand GC24 from TRbeta; the TR agonist IH5 from the alpha- and beta-TR forms; and Triac from two natural human TRbeta mutants, A317T and A234T, but are detected with different frequencies in simulations performed with the different structures. Path I was previously suggested to represent a major pathway for NR ligand dissociation. We propose here that Paths II and III are also likely ligand escape routes for TRs and other NRs. We also propose that different escape paths are preferred in different situations, implying that it will be possible to design NR ligands that only associate stably with their cognate receptors in specific cellular contexts.

Estrogen Receptor (ER) is an important target for pharmaceutical design. Like other ligand-dependent transcription factors, hormone binding regulates ER transcriptional activity. Nevertheless, the mechanisms by which ligands enter and leave ERs and other nuclear receptors remain poorly understood. Here, we report results of locally enhanced sampling molecular dynamics simulations to identify dissociation pathways of two ER ligands [the natural hormone 17beta-estradiol (E(2)) and the selective ER modulator raloxifene (RAL)] from the human ERalpha ligand-binding domain in monomeric and dimeric forms. E(2) dissociation occurs via three different pathways in ER monomers. One resembles the mousetrap mechanism (Path I), involving repositioning of helix 12 (H12), others involve the separation of H8 and H11 (Path II), and a variant of this pathway at the bottom of the ligand-binding domain (Path II'). RAL leaves the receptor through Path I and a Path I variant in which the ligand leaves the receptor through the loop region between H11 and H12 (Path I'). Remarkably, ER dimerization strongly suppresses Paths II and II' for E(2) dissociation and modifies RAL escape routes. We propose that differences in ligand release pathways detected in the simulations for ER monomers and dimers provide an explanation for previously observed effects of ER quaternary state on ligand dissociation rates and suggest that dimerization may play an important, and hitherto unexpected, role in regulation of ligand dissociation rates throughout the nuclear receptor family.

Triac ͉ design ͉ mobility N uclear receptors (NRs) are conditional transcription factors with important roles in development and disease (1, 2). Although these proteins are targets for existing drugs and pharmaceutical development, structural relationships between subsets of these proteins mean that ligands that target one NR can cross-react with others. This is commonly observed when NRs exist in multiple subtypes, as for thyroid hormone (TH)