The Most Severe Test for Hydrophobicity Scales: Two Proteins with 88% Sequence Identity but Different Structure and Function

Protein-protein interactions (protein functionalities) are mediated by water, which compacts individual proteins and promotes close and temporarily stable large-area protein-protein interfaces. In their classic paper Kyte and Doolittle (KD) concluded that the "simplicity and graphic nature of hydrophobicity scales make them very useful tools for the evaluation of protein structures". In practice, however, attempts to develop hydrophobicity scales (for example, compatible with classical force fields (CFF) in calculating the energetics of protein folding) have encountered many difficulties. Here we suggest an entirely different approach, based on the idea that proteins are self-organized networks, subject to finite-scale criticality (like some network glasses). We test this proposal against two small proteins that are delicately balanced between alpha and alpha/beta structures, with different functions encoded with only 12% of their amino acids. This example explains why protein structure prediction is so challenging, and it provides a severe test for the accuracy and content of hydrophobicity scales. The new method confirms KD's evaluation, and at the same time suggests that protein structure, dynamics and function can be best discussed without using CFF

QTL for feed intake and associated traits

The document attached has been archived with permission from the World Congress on Genetics Applied to Livestock Production.In typical beef cattle production systems, the breeding herd accounts for 65-85% of the total feed requirements (Ferrell and Jenkins, 1984 ; Montaldo-Bermudez et al., 1990) and 65-75% of this is used for maintenance. Primarily, the very large maintenance requirement is because cattle are a large, slowly maturing species with a low annual reproductive rate. Furthermore, only a single product is harvested (meat). Any improvement in the efficiency with which breeding cows maintain body weight, will result in an increase in total meat production for a given amount of feed. The key to selection for increased efficiency is to be able to accurately measure feed intake, a trait that is both difficult and expensive to measure. A less expensive alternative would be to use a DNA test for markers of genes affecting intake. This approach has the potential to significantly reduce the generation interval. The aim of this project is to locate regions (quantitative trait loci, QTL) in the cattle genome that contain genes affecting intake.W.S. Pitchford, M.L. Fenton, A.J. Kister and C.D.K. Bottem

Effectors of hemoglobin. Separation of allosteric and affinity factors

The relative contributions of the allosteric and affinity factors toward the change in p50 have been calculated for a series of effectors of hemoglobin (Hb). Shifts in the ligand affinity of deoxy Hb and the values for 50% ligand saturation (p50) were obtained from oxygen equilibrium data. Because the high-affinity parameters (liganded conformation) are poorly determined from the equilibrium curves, they were determined from kinetic measurements of the association and dissociation rates with CO as ligand. The CO on-rates were obtained by flash photolysis measurements. The off-rates were determined from the rate of oxidation of HbCO by ferricyanide, or by replacement of CO with NO. The partition function of fully liganded hemoglobin for oxygen and CO is only slightly changed by the effectors. Measurements were made in the presence of the effectors 2,3-diphosphoglycerate (DPG), inositol hexakisphosphate (IHP), bezafibrate (Bzf), and two recently synthesized derivatives of Bzf (LR16 and L35). Values of p50 change by over a factor of 60; the on-rates decrease by nearly a factor of 8, with little change in the off-rates for the liganded conformation. The data indicate that both allosteric and affinity parameters are changed by the effectors; the changes in ligand affinity represent the larger contribution toward shifts in p50

Machine Learning Analysis of τRAMD Trajectories to Decipher Molecular Determinants of Drug-Target Residence Times

Drug-target residence times can impact drug efficacy and safety, and are therefore increasingly being considered during lead optimization. For this purpose, computational methods to predict residence times, τ, for drug-like compounds and to derive structure-kinetic relationships are desirable. A challenge for approaches based on molecular dynamics (MD) simulation is the fact that drug residence times are typically orders of magnitude longer than computationally feasible simulation times. Therefore, enhanced sampling methods are required. We recently reported one such approach: the τRAMD procedure for estimating relative residence times by performing a large number of random acceleration MD (RAMD) simulations in which ligand dissociation occurs in times of about a nanosecond due to the application of an additional randomly oriented force to the ligand. The length of the RAMD simulations is used to deduce τ. The RAMD simulations also provide information on ligand egress pathways and dissociation mechanisms. Here, we describe a machine learning approach to systematically analyze protein-ligand binding contacts in the RAMD trajectories in order to derive regression models for estimating τ and to decipher the molecular features leading to longer τ values. We demonstrate that the regression models built on the protein-ligand interaction fingerprints of the dissociation trajectories result in robust estimates of τ for a set of 94 drug-like inhibitors of heat shock protein 90 (HSP90), even for the compounds for which the length of the RAMD trajectories does not provide a good estimation of τ. Thus, we find that machine learning helps to overcome inaccuracies in the modeling of protein-ligand complexes due to incomplete sampling or force field deficiencies. Moreover, the approach facilitates the identification of features important for residence time. In particular, we observed that interactions of the ligand with the sidechain of F138, which is located on the border between the ATP binding pocket and a hydrophobic transient sub-pocket, play a key role in slowing compound dissociation. We expect that the combination of the τRAMD simulation procedure with machine learning analysis will be generally applicable as an aid to target-based lead optimization

Syzygies in equivariant cohomology for non-abelian Lie groups

We extend the work of Allday-Franz-Puppe on syzygies in equivariant cohomology from tori to arbitrary compact connected Lie groups G. In particular, we show that for a compact orientable G-manifold X the analogue of the Chang-Skjelbred sequence is exact if and only if the equivariant cohomology of X is reflexive, if and only if the equivariant Poincare pairing for X is perfect. Along the way we establish that the equivariant cohomology modules arising from the orbit filtration of X are Cohen-Macaulay. We allow singular spaces and introduce a Cartan model for their equivariant cohomology. We also develop a criterion for the finiteness of the number of infinitesimal orbit types of a G-manifold.Comment: 28 pages; minor change

GRAVITY: metrology

GRAVITY is a second generation VLTI instrument, combining the light of four telescopes and two objects simultaneously. The main goal is to obtain astrometrically accurate information. Besides correctly measured stellar phases this requires the knowledge of the instrumental differential phase, which has to be measured optically during the astronomical observations. This is the purpose of a dedicated metrology system. The GRAVITY metrology covers the full optical path, from the beam combiners up to the reference points in the beam of the primary telescope mirror, minimizing the systematic uncertainties and providing a proper baseline in astrometric terms. Two laser beams with a fixed phase relation travel backward the whole optical chain, creating a fringe pattern in any plane close to a pupil. By temporal encoding the phase information can be extracted at any point by means of flux measurements with photo diodes. The reference points chosen sample the pupil at typical radii, eliminating potential systematics due differential focus. We present the final design and the performance estimate, which is in accordance with the overall requirements for GRAVITY.Comment: Proceedings of SPIE, Vol. 8445, Paper No. 8445-58, 201

Characteristics of transposable element exonization within human and mouse

Insertion of transposed elements within mammalian genes is thought to be an important contributor to mammalian evolution and speciation. Insertion of transposed elements into introns can lead to their activation as alternatively spliced cassette exons, an event called exonization. Elucidation of the evolutionary constraints that have shaped fixation of transposed elements within human and mouse protein coding genes and subsequent exonization is important for understanding of how the exonization process has affected transcriptome and proteome complexities. Here we show that exonization of transposed elements is biased towards the beginning of the coding sequence in both human and mouse genes. Analysis of single nucleotide polymorphisms (SNPs) revealed that exonization of transposed elements can be population-specific, implying that exonizations may enhance divergence and lead to speciation. SNP density analysis revealed differences between Alu and other transposed elements. Finally, we identified cases of primate-specific Alu elements that depend on RNA editing for their exonization. These results shed light on TE fixation and the exonization process within human and mouse genes.Comment: 11 pages, 4 figure