NMR-Based Configurational Assignments of Natural Products: Gibbs Sampling and Bayesian Inference Using Floating Chirality Distance Geometry Calculations.
Ontology highlight
ABSTRACT:
SUBMITTER: Immel S
PROVIDER: S-EPMC8781118 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The configurational analysis of complex natural products by NMR spectroscopy is still a challenging task. The assignment of the relative configuration is usually carried out by analysis of interproton distances from NOESY or ROESY spectra (qualitative or quantitative) and scalar (J) couplings. About 15 years ago, residual dipolar couplings (RDCs) were introduced as a tool for the configurational determination of small organic molecules. In contrast to NOEs/ROEs which are local parameters (distances up to 400 pm can be detected for small organic molecules), RDCs are global parameters which allow to obtain structural information also from long-range relationships. RDCs have the disadvantage that the sample needs a setup in an alignment medium in order to obtain the required anisotropic environment. Here, we will discuss the configurational analysis of five complex natural products: axinellamine A (1), tetrabromostyloguanidine (2), 3,7-epi-massadine chloride (3), tubocurarine (4), and vincristine (5). Compounds 1-3 are marine natural products whereas 4 and 5 are from terrestrial sources. The chosen examples will carefully work out the limitations of NOEs/ROEs in the configurational analysis of natural products and will also provide an outlook on the information obtained from RDCs.
| S-EPMC7344786 | biostudies-literature
Project description:Protein backbones have characteristic secondary structures, including alpha-helices and beta-sheets. Which structure is adopted locally is strongly biased by the local amino acid sequence of the protein. Accurate (probabilistic) mappings from sequence to structure are valuable for both secondary-structure prediction and protein design. For the case of alpha-helix caps, we test whether the information content of the sequence-structure mapping can be self-consistently improved by using a relaxed definition of the structure. We derive helix-cap sequence motifs using database helix assignments for proteins of known structure. These motifs are refined using Gibbs sampling in competition with a null motif. Then Gibbs sampling is repeated, allowing for frameshifts of +/-1 amino acid residue, in order to find sequence motifs of higher total information content. All helix-cap motifs were found to have good generalization capability, as judged by training on a small set of non-redundant proteins and testing on a larger set. For overall prediction purposes, frameshift motifs using all training examples yielded the best results. Frameshift motifs using a fraction of all training examples performed best in terms of true positives among top predictions. However, motifs without frameshifts also performed well, despite a roughly one-third lower total information content.
| S-EPMC1234247 | biostudies-literature
Project description:A 3D model of the transmembrane 7-alpha-bundle of rhodopsin-like G-protein-coupled receptors (GPCRs) was calculated using an iterative distance geometry refinement with an evolving system of hydrogen bonds, formed by intramembrane polar side chains in various proteins of the family and collectively applied as distance constraints. The alpha-bundle structure thus obtained provides H bonding of nearly all buried polar side chains simultaneously in the 410 GPCRs considered. Forty evolutionarily conserved GPCR residues form a single continuous domain, with an aliphatic "core" surrounded by six clusters of polar and aromatic side chains. The 7-alpha-bundle of a specific GPCR can be calculated using its own set of H bonds as distance constraints and the common "average" model to restrain positions of the helices. The bovine rhodopsin model thus determined is closely packed, but has a few small polar cavities, presumably filled by water, and has a binding pocket that is complementary to 11-cis (6-s-cis, 12-s-trans, C = N anti)-retinal or to all-trans-retinal, depending on conformations of the Lys296 and Trp265 side chains. A suggested mechanism of rhodopsin photoactivation, triggered by the cis-trans isomerization of retinal, involves rotations of Glu134, Tyr223, Trp265, Lys296, and Tyr306 side chains and rearrangement of their H bonds. The model is in agreement with published electron cryomicroscopy, mutagenesis, chemical modification, cross-linking, Fourier transform infrared spectroscopy, Raman spectroscopy, electron paramagnetic resonance spectroscopy, NMR, and optical spectroscopy data. The rhodopsin model and the published structure of bacteriorhodopsin have very similar retinal-binding pockets.
| S-EPMC1184393 | biostudies-other
Project description:A readily available stereodynamic and the electronic circular dichroism (ECD)-silent 2,5-di(1-naphthyl)-terephthalaldehyde-based probe has been applied for chirality sensing of primary amines. The chiral amine (the inductor) forces a change in the structure of the chromophore system through the point-to-axial chirality transmission mechanism. As a result, efficient induction of optical activity in the chromophoric system is observed. The butterflylike structure of the probe, with the terminal aryl groups acting as changeable "wings", allowed for the generation of exciton Cotton effects in the region of 1Bb electronic transition in the naphthalene chromophores. The sign of the exciton couplets observed for inductor-reporter systems might be correlated with an absolute configuration of the inductor, whereas the linear relationship between amplitudes of the specific Cotton effect and enantiomeric excess of the parent amine gives potentiality for quantitative chirality sensing. Despite the structural simplicity, the probe turned out to be unprecedentedly highly sensitive to even subtle differences in the inductor structure (i.e., O vs CH2).
| S-EPMC7458434 | biostudies-literature
Project description:A central problem in the bioinformatics of gene regulation is to find the binding sites for regulatory proteins. One of the most promising approaches toward identifying these short and fuzzy sequence patterns is the comparative analysis of orthologous intergenic regions of related species. This analysis is complicated by various factors. First, one needs to take the phylogenetic relationship between the species into account in order to distinguish conservation that is due to the occurrence of functional sites from spurious conservation that is due to evolutionary proximity. Second, one has to deal with the complexities of multiple alignments of orthologous intergenic regions, and one has to consider the possibility that functional sites may occur outside of conserved segments. Here we present a new motif sampling algorithm, PhyloGibbs, that runs on arbitrary collections of multiple local sequence alignments of orthologous sequences. The algorithm searches over all ways in which an arbitrary number of binding sites for an arbitrary number of transcription factors (TFs) can be assigned to the multiple sequence alignments. These binding site configurations are scored by a Bayesian probabilistic model that treats aligned sequences by a model for the evolution of binding sites and "background" intergenic DNA. This model takes the phylogenetic relationship between the species in the alignment explicitly into account. The algorithm uses simulated annealing and Monte Carlo Markov-chain sampling to rigorously assign posterior probabilities to all the binding sites that it reports. In tests on synthetic data and real data from five Saccharomyces species our algorithm performs significantly better than four other motif-finding algorithms, including algorithms that also take phylogeny into account. Our results also show that, in contrast to the other algorithms, PhyloGibbs can make realistic estimates of the reliability of its predictions. Our tests suggest that, running on the five-species multiple alignment of a single gene's upstream region, PhyloGibbs on average recovers over 50% of all binding sites in S. cerevisiae at a specificity of about 50%, and 33% of all binding sites at a specificity of about 85%. We also tested PhyloGibbs on collections of multiple alignments of intergenic regions that were recently annotated, based on ChIP-on-chip data, to contain binding sites for the same TF. We compared PhyloGibbs's results with the previous analysis of these data using six other motif-finding algorithms. For 16 of 21 TFs for which all other motif-finding methods failed to find a significant motif, PhyloGibbs did recover a motif that matches the literature consensus. In 11 cases where there was disagreement in the results we compiled lists of known target genes from the literature, and found that running PhyloGibbs on their regulatory regions yielded a binding motif matching the literature consensus in all but one of the cases. Interestingly, these literature gene lists had little overlap with the targets annotated based on the ChIP-on-chip data. The PhyloGibbs code can be downloaded from http://www.biozentrum.unibas.ch/~nimwegen/cgi-bin/phylogibbs.cgi or http://www.imsc.res.in/~rsidd/phylogibbs. The full set of predicted sites from our tests on yeast are available at http://www.swissregulon.unibas.ch.
| S-EPMC1309704 | biostudies-literature
Project description:Compared to fully flexible molecular dynamics, simulations of constrained systems can use larger time steps and focus kinetic energy on soft degrees of freedom. Achieving ergodic sampling from the Boltzmann distribution, however, has proven challenging. Using recent generalizations of the equipartition principle and Fixman potential, here we implement Hamiltonian Monte Carlo based on constrained molecular dynamics as a Gibbs sampling move. By mixing Hamiltonian Monte Carlo based on fully flexible and torsional dynamics, we are able to reproduce free energy landscapes of simple model systems and enhance sampling of macrocycles.
| S-EPMC5634954 | biostudies-literature
Project description:BackgroundEndangered plant species are an important resource for new chemistry. Lindera melissifolia is native to the Southeastern U.S. and scarcely populates the edges of lakes and ponds. Quantum mechanics (QM) used in combination with NMR/ECD is a powerful tool for the assignment of absolute configuration in lieu of X-ray crystallography.MethodsThe EtOAc extract of L. melissifolia was subject to chromatographic analysis by VLC and HPLC. Spin-spin coupling constant (SSCC) were calculated using DFT at the MPW1PW91/6-31G(d,p) level for all staggered rotamers. ECD calculations employed Amber* force fields followed by PM6 semi-empirical optimizations. Hetero- and homo-nuclear coupling constants were extracted from 1D (1)H, E.COSY and HETLOC experiments.ResultsTwo meroterpenoids, melissifolianes A (1) and B (2) were purified and their 2-D structures elucidated using NMR and HRESIMS. The relative configuration of 1 was established using the combination of NOE-based distance restraints and the comparisons of experimental and calculated SSCCs. The comparison of calculated and experimental ECD assigned the absolute configuration of 1. The relative configuration of a racemic mixture, melissifoliane B (2) was established utilizing J-based analysis combined with QM and NMR techniques.Conclusion Our study of the Lindera melissifolia metabolome exemplifies how new chemistry remains undiscovered among the numerous endangered plant species and demonstrates how analysis by ECD and NMR combined with various QM calculations is a sensible approach to support the stereochemical assignment of molecules with conformationally restricted conformations.General significanceQM-NMR/ECD combined approaches are of utility for unambiguous assignment of 3-D structures, especially with limited plant material and when a molecule is conformationally restricted. Conservation of an endangered plant species can be supported through identification of its new chemistry and utilization of that chemistry for commercial purposes.
| S-EPMC4139972 | biostudies-literature
Project description:To solve a long-standing problem of condensed matter physics with determining a proper description of the thermodynamic evolution of the time scale of molecular dynamics near the glass transition, we have extended the well-known Adam-Gibbs model to describe the temperature-volume dependence of structural relaxation times, τα(T, V). We also employ the thermodynamic scaling idea reflected in the density scaling power law, τα = f(T(-1)V(-γ)), recently acknowledged as a valid unifying concept in the glass transition physics, to differentiate between physically relevant and irrelevant attempts at formulating the temperature-volume representations of the Adam-Gibbs model. As a consequence, we determine a straightforward relation between the structural relaxation time τα and the configurational entropy SC, giving evidence that also SC(T, V) = g(T(-1)V(-γ)) with the exponent γ that enables to scale τα(T, V). This important findings have meaningful implications for the connection between thermodynamics and molecular dynamics near the glass transition, because it implies that τα can be scaled with SC.
| S-EPMC4568462 | biostudies-other
Project description:Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.
| S-EPMC4503633 | biostudies-literature
Project description:We present a new iterative algorithm for the molecular distance geometry problem with inaccurate and sparse data, which is based on the solution of linear systems, maximum cliques, and a minimization of nonlinear least-squares function. Computational results with real protein structures are presented in order to validate our approach.
| S-EPMC3698034 | biostudies-literature