325 research outputs found
Detection of unrealistic molecular environments in protein structures based on expected electron densities
Understanding the relationship between protein structure and biological function is a central theme in structural biology. Advances are severely hampered by errors in experimentally determined protein structures. Detection and correction of such errors is therefore of utmost importance. Electron densities in molecular structures obey certain rules which depend on the molecular environment. Here we present and discuss a new approach that relates electron densities computed from a structural model to densities expected from prior observations on identical or closely related molecular environments. Strong deviations of computed from expected densities reveal unrealistic molecular structures. Most importantly, structure analysis and error detection are independent of experimental data and hence may be applied to any structural model. The comparison to state-of-the-art methods reveals that our approach is able to identify errors that formerly remained undetected. The new technique, called RefDens, is accessible as a public web service at http://refdens.services.came.sbg.ac.at
Pyrido- and benzisothiazolones as inhibitors of histone acetyltransferases (HATs)
Histone acetyltransferases (HATs) are interesting targets for the treatment of cancer and HIV infections but reports on selective inhibitors are very limited. Here we report structure–activity studies of pyrido- and benzisothiazolones in the in vitro inhibition of histone acetyltransferases, namely PCAF, CBP, Gcn5 and p300 using a heterogeneous assay with antibody mediated quantitation of the acetylation of a peptidic substrate. Dependent on the chemical structure distinct subtype selectivity profiles can be obtained. While N-aryl derivatives usually are rather pan-HAT inhibitors, N-alkyl derivatives show mostly a preference for CBP/p300. Selected compounds were also shown to be inhibitors of MOF. The best inhibitors show submicromolar inhibition of CBP. Selected compounds affect growth of HL-60 leukemic cells and LNCaP prostate carcinoma cells with higher potency on the leukemic cells. Target engagement was shown with reduction of histone acetylation in LNCaP cells
Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized
Understanding protein structure is of crucial importance in science, medicine
and biotechnology. For about two decades, knowledge based potentials based on
pairwise distances -- so-called "potentials of mean force" (PMFs) -- have been
center stage in the prediction and design of protein structure and the
simulation of protein folding. However, the validity, scope and limitations of
these potentials are still vigorously debated and disputed, and the optimal
choice of the reference state -- a necessary component of these potentials --
is an unsolved problem. PMFs are loosely justified by analogy to the reversible
work theorem in statistical physics, or by a statistical argument based on a
likelihood function. Both justifications are insightful but leave many
questions unanswered. Here, we show for the first time that PMFs can be seen as
approximations to quantities that do have a rigorous probabilistic
justification: they naturally arise when probability distributions over
different features of proteins need to be combined. We call these quantities
reference ratio distributions deriving from the application of the reference
ratio method. This new view is not only of theoretical relevance, but leads to
many insights that are of direct practical use: the reference state is uniquely
defined and does not require external physical insights; the approach can be
generalized beyond pairwise distances to arbitrary features of protein
structure; and it becomes clear for which purposes the use of these quantities
is justified. We illustrate these insights with two applications, involving the
radius of gyration and hydrogen bonding. In the latter case, we also show how
the reference ratio method can be iteratively applied to sculpt an energy
funnel. Our results considerably increase the understanding and scope of energy
functions derived from known biomolecular structures
Deriving amino acid contact potentials from their frequencies of occurence in proteins: a lattice model study
The possibility of deriving the contact potentials between amino acids from
their frequencies of occurence in proteins is discussed in evolutionary terms.
This approach allows the use of traditional thermodynamics to describe such
frequencies and, consequently, to develop a strategy to include in the
calculations correlations due to the spatial proximity of the amino acids and
to their overall tendency of being conserved in proteins. Making use of a
lattice model to describe protein chains and defining a "true" potential, we
test these strategies by selecting a database of folding model sequences,
deriving the contact potentials from such sequences and comparing them with the
"true" potential. Taking into account correlations allows for a markedly better
prediction of the interaction potentials
Global Optimization by Energy Landscape Paving
We introduce a novel heuristic global optimization method, energy landscape
paving (ELP), which combines core ideas from energy surface deformation and
tabu search. In appropriate limits, ELP reduces to existing techniques. The
approach is very general and flexible and is illustrated here on two protein
folding problems. For these examples, the technique gives faster convergence to
the global minimum than previous approaches.Comment: to appear in Phys. Rev. Lett. (2002
Numerical comparison of two approaches for the study of phase transitions in small systems
We compare two recently proposed methods for the characterization of phase
transitions in small systems. The validity and usefulness of these approaches
are studied for the case of the q=4 and q=5 Potts model, i.e. systems where a
thermodynamic limit and exact results exist. Guided by this analysis we discuss
then the helix-coil transition in polyalanine, an example of structural
transitions in biological molecules.Comment: 16 pages and 7 figure
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