Diversity of Quaternary Structures Regulates Nuclear Receptor Activities.

Nuclear receptors (NRs) form homo- and/or heterodimers as central scaffolds of multiprotein complexes, which activate or repress gene transcription to regulate development, homeostasis, and metabolism. Recent studies on NR quaternary structure reveal novel mechanisms of receptor dimerization, the existence of tetrameric chromatin-bound NRs, and previously unanticipated protein-protein/protein-DNA interactions.

Optimizing lactose hydrolysis by computer-guided modification of the catalytic site of a wild-type enzyme.

Lactose intolerance is a serious global health problem. A lactose hydrolysis enzyme, thermostable ß-galactosidase, BgaB (from Geobacillus stearothermophilus) has attracted the attention of industrial biologists because of its potential application in processing lactose-containing products. However, this enzyme experiences galactose product inhibition. Through homology modeling and molecular dynamics (MD) simulation, we have identified the galactose binding sites in the thermostable ß-galactosidase BgaB (BgaB). The binding sites are formed from Glu303, Asn310, Trp311, His354, Arg109, Phe341, Try272, Asn147, Glu148, and H354; these residues are all important for enzyme catalysis. A ligand-receptor binding model has been proposed to guide site-directed BgaB mutagenesis experiments. Based upon the model and the MD simulations, we recommend mutating Arg109, Phe341, Trp311, Asn147, Asn310, Try272, and His354 to reduce galactose product inhibition. In vitro site-directed mutagenesis experiments confirmed our predictions. The success rate for mutagenesis was 66.7 %. The best BgaB mutant, F341T, can hydrolyze lactose completely, and is the most promising enzyme for use by the dairy industry. Thus, our study is a successful example of optimizing enzyme catalytic chemical reaction by computer-guided modifying the catalytic site of a wild-type enzyme.

Chemical Structure Similarity Search for Ligand-based Virtual Screening: Methods and Computational Resources.

For many years the assumption that "Chemical compounds with similar structures may have similar activities" has been a foundation for lead identification. The similarity can be computed based upon topological, steric, electronic, and/or physical properties. The chemical structure similarity search differs from the chemical substructure search in that the former requires assessment of the properties of each compound and thus no filter can be applied for skipping structures before they are assessed to accelerate the computation. The latter can be accelerated by pre-screening compounds and omitting those that miss one (or more) specified fragments from the query. Moreover, three-dimensional similarity search requires superimposing many conformation pairs for each compound in the library. This makes 3-D similarity search algorithms time-consuming, and in general requires high performance computing (HPC) resources. This review will summarize recent progress in the techniques for HPC-supported two and three-dimensional chemical structure similarity search algorithms, and their applications in ligand-based virtual screening.

Sequence and structural analysis of cellular retinoic acid-binding proteins reveals a network of conserved hydrophobic interactions.

Proteins in the intracellular lipid-binding protein (iLBP) family show remarkably high structural conservation despite their low-sequence identity. A multiple-sequence alignment using 52 sequences of iLBP family members revealed 15 fully conserved positions, with a disproportionately high number of these (n=7) located in the relatively small helical region. The conserved positions displayed high structural conservation based on comparisons of known iLBP crystal structures. It is striking that the beta-sheet domain had few conserved positions, despite its high structural conservation. This observation prompted us to analyze pair-wise interactions within the beta-sheet region to ask whether structural information was encoded in interacting amino acid pairs. We conducted this analysis on the iLBP family member, cellular retinoic acid-binding protein I (CRABP I), whose folding mechanism is under study in our laboratory. Indeed, an analysis based on a simple classification of hydrophobic and polar amino acids revealed a network of conserved interactions in CRABP I that cluster spatially, suggesting a possible nucleation site for folding. Significantly, a small number of residues participated in multiple conserved interactions, suggesting a key role for these sites in the structure and folding of CRABP I. The results presented here correlate well with available experimental evidence on folding of CRABPs and their family members and suggest future experiments. The analysis also shows the usefulness of considering pair-wise conservation based on a simple classification of amino acids, in analyzing sequences and structures to find common core regions among homologues.

Derivation of class II force fields. VIII. Derivation of a general quantum mechanical force field for organic compounds.

A class II valence force field covering a broad range of organic molecules has been derived employing ab initio quantum mechanical "observables." The procedure includes selecting representative molecules and molecular structures, and systematically sampling their energy surfaces as described by energies and energy first and second derivatives with respect to molecular deformations. In this article the procedure for fitting the force field parameters to these energies and energy derivatives is briefly reviewed. The application of the methodology to the derivation of a class II quantum mechanical force field (QMFF) for 32 organic functional groups is then described. A training set of 400 molecules spanning the 32 functional groups was used to parameterize the force field. The molecular families comprising the functional groups and, within each family, the torsional angles used to sample different conformers, are described. The number of stationary points (equilibria and transition states) for these molecules is given for each functional group. This set contains 1324 stationary structures, with 718 minimum energy structures and 606 transition states. The quality of the fit to the quantum data is gauged based on the deviations between the ab initio and force field energies and energy derivatives. The accuracy with which the QMFF reproduces the ab initio molecular bond lengths, bond angles, torsional angles, vibrational frequencies, and conformational energies is then given for each functional group. Consistently good accuracy is found for these computed properties for the various types of molecules. This demonstrates that the methodology is broadly applicable for the derivation of force field parameters across widely differing types of molecular structures. Copyright 2001 John Wiley & Sons, Inc. J Comput Chem 22: 1782-1800, 2001

Allosteric mechanisms of nuclear receptors: insights from computational simulations.

The traditional structural view of allostery defines this key regulatory mechanism as the ability of one conformational event (allosteric site) to initiate another in a separate location (active site). In recent years computational simulations conducted to understand how this phenomenon occurs in nuclear receptors (NRs) has gained significant traction. These results have yield insights into allosteric changes and communication mechanisms that underpin ligand binding, coactivator binding site formation, post-translational modifications, and oncogenic mutations. Moreover, substantial efforts have been made in understanding the dynamic processes involved in ligand binding and coregulator recruitment to different NR conformations in order to predict cell/tissue-selective pharmacological outcomes of drugs. They also have improved the accuracy of in silico screening protocols so that nowadays they are becoming part of optimisation protocols for novel therapeutics. Here we summarise the important contributions that computational simulations have made towards understanding the structure/function relationships of NRs and how these can be exploited for rational drug design.

Generation of receptor structural ensembles for virtual screening using binding site shape analysis and clustering.

Accounting for protein flexibility is an essential yet challenging component of structure-based virtual screening. Whereas an ideal approach would account for full protein and ligand flexibility during the virtual screening process, this is currently intractable using available computational resources. An alternative is ensemble docking, where calculations are performed on a set of individual rigid receptor conformations and the results combined. The primary challenge associated with this approach is the choice of receptor structures to use for the docking calculations. In this work, we show that selection of a small set of structures based on clustering on binding site volume overlaps provides an efficient and effective way to account for protein flexibility in virtual screening. We first apply the method to crystal structures of cyclin-dependent kinase 2 and HIV protease and show that virtual screening for ensembles of four cluster representative structures yields consistently high enrichments and diverse actives. We then apply the method to a structural ensemble of the androgen receptor generated with molecular dynamics and obtain results that are in agreement with those from the crystal structures of cyclin-dependent kinase 2 and HIV protease. This work provides a step forward in the incorporation of protein flexibility into structure-based virtual screening.

Exploring protein flexibility: incorporating structural ensembles from crystal structures and simulation into virtual screening protocols.

The capacity of proteins to adapt their structure in response to various perturbations including covalent modifications, and interactions with ligands and other proteins plays a key role in biological processes. Here, we explore the ability of molecular dynamics (MD), replica exchange molecular dynamics (REMD), and a library of structures of crystal-ligand complexes, to sample the protein conformational landscape and especially the accessible ligand binding site geometry. The extent of conformational space sampled is measured by the diversity of the shapes of the ligand binding sites. Since our focus here is the effect of this plasticity on the ability to identify active compounds through virtual screening, we use the structures generated by these techniques to generate a small ensemble for further docking studies, using binding site shape hierarchical clustering to determine four structures for each ensemble. These are then assessed for their capacity to optimize enrichment and diversity in docking. We test these protocols on three different receptors: androgen receptor (AR), HIV protease, and CDK2. We show that REMD enhances structural sampling slightly as compared both to MD, and the distortions induced by ligand binding as reflected in the crystal structures. The improved sampling of the simulation methods does not translate directly into improved docking performance, however. The ensemble approach did improve enrichment and diversity, and the ensemble derived from the crystal structures performed somewhat better than those derived from the simulations.