The Energy Computation Paradox and ab initio Protein Folding

The routine prediction of three-dimensional protein structure from sequence remains a challenge in computational biochemistry. It has been intuited that calculated energies from physics-based scoring functions are able to distinguish native from nonnative folds based on previous performance with small proteins and that conformational sampling is the fundamental bottleneck to successful folding. We demonstrate that as protein size increases, errors in the computed energies become a significant problem. We show, by using error probability density functions, that physics-based scores contain significant systematic and random errors relative to accurate reference energies. These errors propagate throughout an entire protein and distort its energy landscape to such an extent that modern scoring functions should have little chance of success in finding the free energy minima of large proteins. Nonetheless, by understanding errors in physics-based score functions, they can be reduced in a post-hoc manner, improving accuracy in energy computation and fold discrimination

Effect of 28 days of creatine ingestion on muscle metabolism and performance of a simulated cycling road race

<p>Abstract</p> <p>Purpose</p> <p>The effects of creatine supplementation on muscle metabolism and exercise performance during a simulated endurance road race was investigated.</p> <p>Methods</p> <p>Twelve adult male (27.3 ± 1.0 yr, 178.6 ± 1.4 cm, 78.0 ± 2.5 kg, 8.9 ± 1.1 %fat) endurance-trained (53.3 ± 2.0 ml* kg^-1* min^-1, cycling ~160 km/wk) cyclists completed a simulated road race on a cycle ergometer (Lode), consisting of a two-hour cycling bout at 60% of peak aerobic capacity (VO_2peak) with three 10-second sprints performed at 110% VO_{2 peak}every 15 minutes. Cyclists completed the 2-hr cycling bout before and after dietary creatine monohydrate or placebo supplementation (3 g/day for 28 days). Muscle biopsies were taken at rest and five minutes before the end of the two-hour ride.</p> <p>Results</p> <p>There was a 24.5 ± 10.0% increase in resting muscle total creatine and 38.4 ± 23.9% increase in muscle creatine phosphate in the creatine group (<it>P </it>< 0.05). Plasma glucose, blood lactate, and respiratory exchange ratio during the 2-hour ride, as well as VO_{2 peak}, were not affected by creatine supplementation. Submaximal oxygen consumption near the end of the two-hour ride was decreased by approximately 10% by creatine supplementation (P < 0.05). Changes in plasma volume from pre- to post-supplementation were significantly greater in the creatine group (⁺14.0 ± 6.3%) than the placebo group (^-10.4 ± 4.4%; <it>P </it>< 0.05) at 90 minutes of exercise. The time of the final sprint to exhaustion at the end of the 2-hour cycling bout was not affected by creatine supplementation (creatine pre, 64.4 ± 13.5s; creatine post, 88.8 ± 24.6s; placebo pre, 69.0 ± 24.8s; placebo post 92.8 ± 31.2s: creatine vs. placebo not significant). Power output for the final sprint was increased by ~33% in both groups (creatine vs. placebo not significant).</p> <p>Conclusions</p> <p>It can be concluded that although creatine supplementation may increase resting muscle total creatine, muscle creatine phosphate, and plasma volume, and may lead to a reduction in oxygen consumption during submaximal exercise, creatine supplementation does not improve sprint performance at the end of endurance cycling exercise.</p

A mathematical and computational review of Hartree-Fock SCF methods in Quantum Chemistry

We present here a review of the fundamental topics of Hartree-Fock theory in Quantum Chemistry. From the molecular Hamiltonian, using and discussing the Born-Oppenheimer approximation, we arrive to the Hartree and Hartree-Fock equations for the electronic problem. Special emphasis is placed in the most relevant mathematical aspects of the theoretical derivation of the final equations, as well as in the results regarding the existence and uniqueness of their solutions. All Hartree-Fock versions with different spin restrictions are systematically extracted from the general case, thus providing a unifying framework. Then, the discretization of the one-electron orbitals space is reviewed and the Roothaan-Hall formalism introduced. This leads to a exposition of the basic underlying concepts related to the construction and selection of Gaussian basis sets, focusing in algorithmic efficiency issues. Finally, we close the review with a section in which the most relevant modern developments (specially those related to the design of linear-scaling methods) are commented and linked to the issues discussed. The whole work is intentionally introductory and rather self-contained, so that it may be useful for non experts that aim to use quantum chemical methods in interdisciplinary applications. Moreover, much material that is found scattered in the literature has been put together here to facilitate comprehension and to serve as a handy reference.Comment: 64 pages, 3 figures, tMPH2e.cls style file, doublesp, mathbbol and subeqn package

Combining Optimal Control Theory and Molecular Dynamics for Protein Folding

A new method to develop low-energy folding routes for proteins is presented. The novel aspect of the proposed approach is the synergistic use of optimal control theory with Molecular Dynamics (MD). In the first step of the method, optimal control theory is employed to compute the force field and the optimal folding trajectory for the atoms of a Coarse-Grained (CG) protein model. The solution of this CG optimization provides an harmonic approximation of the true potential energy surface around the native state. In the next step CG optimization guides the MD simulation by specifying the optimal target positions for the atoms. In turn, MD simulation provides an all-atom conformation whose positions match closely the reference target positions determined by CG optimization. This is accomplished by Targeted Molecular Dynamics (TMD) which uses a bias potential or harmonic restraint in addition to the usual MD potential. Folding is a dynamical process and as such residues make different contacts during the course of folding. Therefore CG optimization has to be reinitialized and repeated over time to accomodate these important changes. At each sampled folding time, the active contacts among the residues are recalculated based on the all-atom conformation obtained from MD. Using the new set of contacts, the CG potential is updated and the CG optimal trajectory for the atoms is recomputed. This is followed by MD. Implementation of this repetitive CG optimization - MD simulation cycle generates the folding trajectory. Simulations on a model protein Villin demonstrate the utility of the method. Since the method is founded on the general tools of optimal control theory and MD without any restrictions, it is widely applicable to other systems. It can be easily implemented with available MD software packages

Exploring the Universe of Protein Structures beyond the Protein Data Bank

It is currently believed that the atlas of existing protein structures is faithfully represented in the Protein Data Bank. However, whether this atlas covers the full universe of all possible protein structures is still a highly debated issue. By using a sophisticated numerical approach, we performed an exhaustive exploration of the conformational space of a 60 amino acid polypeptide chain described with an accurate all-atom interaction potential. We generated a database of around 30,000 compact folds with at least of secondary structure corresponding to local minima of the potential energy. This ensemble plausibly represents the universe of protein folds of similar length; indeed, all the known folds are represented in the set with good accuracy. However, we discover that the known folds form a rather small subset, which cannot be reproduced by choosing random structures in the database. Rather, natural and possible folds differ by the contact order, on average significantly smaller in the former. This suggests the presence of an evolutionary bias, possibly related to kinetic accessibility, towards structures with shorter loops between contacting residues. Beside their conceptual relevance, the new structures open a range of practical applications such as the development of accurate structure prediction strategies, the optimization of force fields, and the identification and design of novel folds

The inverted free energy landscape of an intrinsically disordered peptide by simulations and experiments

The free energy landscape theory has been very successful in rationalizing the folding behaviour of globular proteins, as this representation provides intuitive information on the number of states involved in the folding process, their populations and pathways of interconversion. We extend here this formalism to the case of the A\u3b240 peptide, a 40-residue intrinsically disordered protein fragment associated with Alzheimer's disease. By using an advanced sampling technique that enables free energy calculations to reach convergence also in the case of highly disordered states of proteins, we provide a precise structural characterization of the free energy landscape of this peptide. We find that such landscape has inverted features with respect to those typical of folded proteins. While the global free energy minimum consists of highly disordered structures, higher free energy regions correspond to a large variety of transiently structured conformations with secondary structure elements arranged in several different manners, and are not separated from each other by sizeable free energy barriers. From this peculiar structure of the free energy landscape we predict that this peptide should become more structured and not only more compact, with increasing temperatures, and we show that this is the case through a series of biophysical measurements

Characteristics of facilities with specialized programming for drinking drivers and for other criminal justice involved clients: analysis of a national database

<p>Abstract</p> <p>Background</p> <p>Offering specialized programming at substance abuse treatment facilities can help diversify clientele and funding sources, potentially enhancing the facilities' ability to survive and/or expand. Past research has shown that facilities only offering specialized programming for driving under the influence/driving while intoxicated offenders (DUI) are predominately private-for-profit owned. As criminal justice populations, both DUI and other criminal justice offenders, comprise a large proportion of those in community-based substance abuse treatment knowing facilities' characteristics would be important for administrators and policymakers to consider when updating programming, training staff or expanding capacity to ensure efficient use of scarce resources. However, while such characteristics are known for DUI programs, they are not known for facilities offering specialized programming for other criminal justice offenders.</p> <p>Methods</p> <p>Analysis of the 2004 US National Survey of Substance Abuse Treatment Facilities.</p> <p>Results</p> <p>Almost half the facilities (48.2%) offered either DUI or other criminal justice specialized programming. These facilities were divided between those offering DUI specialized programming (17.7%), other criminal justice specialized programming (16.6%) and both types of programming (13.9%). Certain characteristics were independently associated with offering DUI specialized programming (private ownership, rural location, for profit status) or other criminal justice specialized programming (receiving public funds, urban location, region of country).</p> <p>Conclusion</p> <p>Offering specialized programming for DUI or other criminal justice offenders was common and associated with distinct characteristics. These observed associations may reflect the positioning of the facility to increase visibility, or diversify clientele and possibly funding streams or the decision of policymakers. As the criminal justice populations show no sign of decreasing and resources are scarce, the efficient use of resources demands policymakers recognize the prevalence of these specialized programming, join forces to examine them for efficacy, and explicitly incorporate these characteristics into strategies for workforce training and plans for treatment expansion.</p

A probability-conserving cross-section biasing mechanism for variance reduction in Monte Carlo particle transport calculations

In Monte Carlo particle transport codes, it is often important to adjust reaction cross sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analogous Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross section change. This makes it possible to increase the cross section of nuclear reactions by factors exceeding 10^4 (in appropriate cases), without distorting the results of energy deposition calculations or coincidence rates. The procedure is also valid for bias factors less than unity, which is useful, for example, in problems that involve computation of particle penetration deep into a target, such as occurs in atmospheric showers or in shielding

Solution Structure and Dynamics of the I214V Mutant of the Rabbit Prion Protein

Background: The conformational conversion of the host-derived cellular prion protein (PrP C) into the disease-associated scrapie isoform (PrP Sc) is responsible for the pathogenesis of transmissible spongiform encephalopathies (TSEs). Various single-point mutations in PrP C s could cause structural changes and thereby distinctly influence the conformational conversion. Elucidation of the differences between the wild-type rabbit PrP C (RaPrP C) and various mutants would be of great help to understand the ability of RaPrP C to be resistant to TSE agents. Methodology/Principal Findings: We determined the solution structure of the I214V mutant of RaPrP C (91–228) and detected the backbone dynamics of its structured C-terminal domain (121–228). The I214V mutant displays a visible shift of surface charge distribution that may have a potential effect on the binding specificity and affinity with other chaperones. The number of hydrogen bonds declines dramatically. Urea-induced transition experiments reveal an obvious decrease in the conformational stability. Furthermore, the NMR dynamics analysis discloses a significant increase in the backbone flexibility on the pico- to nanosecond time scale, indicative of lower energy barrier for structural rearrangement. Conclusions/Significance: Our results suggest that both the surface charge distribution and the intrinsic backbone flexibility greatly contribute to species barriers for the transmission of TSEs, and thereby provide valuable hints fo

Hydrogen bond networks determine emergent mechanical and thermodynamic properties across a protein family

<p>Abstract</p> <p>Background</p> <p>Gram-negative bacteria use periplasmic-binding proteins (bPBP) to transport nutrients through the periplasm. Despite immense diversity within the recognized substrates, all members of the family share a common fold that includes two domains that are separated by a conserved hinge. The hinge allows the protein to cycle between open (apo) and closed (ligated) conformations. Conformational changes within the proteins depend on a complex interplay of mechanical and thermodynamic response, which is manifested as an increase in thermal stability and decrease of flexibility upon ligand binding.</p> <p>Results</p> <p>We use a distance constraint model (DCM) to quantify the give and take between thermodynamic stability and mechanical flexibility across the bPBP family. Quantitative stability/flexibility relationships (QSFR) are readily evaluated because the DCM links mechanical and thermodynamic properties. We have previously demonstrated that QSFR is moderately conserved across a mesophilic/thermophilic RNase H pair, whereas the observed variance indicated that different enthalpy-entropy mechanisms allow similar mechanical response at their respective melting temperatures. Our predictions of heat capacity and free energy show marked diversity across the bPBP family. While backbone flexibility metrics are mostly conserved, cooperativity correlation (long-range couplings) also demonstrate considerable amount of variation. Upon ligand removal, heat capacity, melting point, and mechanical rigidity are, as expected, lowered. Nevertheless, significant differences are found in molecular cooperativity correlations that can be explained by the detailed nature of the hydrogen bond network.</p> <p>Conclusion</p> <p>Non-trivial mechanical and thermodynamic variation across the family is explained by differences within the underlying H-bond networks. The mechanism is simple; variation within the H-bond networks result in altered mechanical linkage properties that directly affect intrinsic flexibility. Moreover, varying numbers of H-bonds and their strengths control the likelihood for energetic fluctuations as H-bonds break and reform, thus directly affecting thermodynamic properties. Consequently, these results demonstrate how unexpected large differences, especially within cooperativity correlation, emerge from subtle differences within the underlying H-bond network. This inference is consistent with well-known results that show allosteric response within a family generally varies significantly. Identifying the hydrogen bond network as a critical determining factor for these large variances may lead to new methods that can predict such effects.</p