Wang-Landau molecular dynamics technique to search for low-energy conformational space of proteins

Multicanonical molecular dynamics (MD) is a powerful technique for sampling conformations on rugged potential surfaces such as protein. However, it is notoriously difficult to estimate the multicanonical temperature effectively. Wang and Landau developed a convenient method for estimating the density of states based on a multicanonical Monte Carlo method. In their method, the density of states is calculated autonomously during a simulation. In this paper we develop a set of techniques to effectively apply the Wang-Landau method to MD simulations. In the multicanonical MD, the estimation of the derivative of the density of states is critical. In order to estimate it accurately, we devise two original improvements. First, the correction for the density of states is made smooth by using the Gaussian distribution obtained by a short canonical simulation. Second, an approximation is applied to the derivative, which is based on the Gaussian distribution and the multiple weighted histogram technique. A test of this method was performed with small polypeptides, Met-enkephalin and Trp-cage, and it is demonstrated that Wang-Landau MD is consistent with replica exchange MD but can sample much larger conformational space.Comment: 8 pages, 7 figures, accepted for publication in Physical Review

An effective all-atom potential for proteins

We describe and test an implicit solvent all-atom potential for simulations of protein folding and aggregation. The potential is developed through studies of structural and thermodynamic properties of 17 peptides with diverse secondary structure. Results obtained using the final form of the potential are presented for all these peptides. The same model, with unchanged parameters, is furthermore applied to a heterodimeric coiled-coil system, a mixed alpha/beta protein and a three-helix-bundle protein, with very good results. The computational efficiency of the potential makes it possible to investigate the free-energy landscape of these 49--67-residue systems with high statistical accuracy, using only modest computational resources by today's standards

Identification of five fundamental implicit theories underlying cognitive distortions in child abusers : a preliminary study

Qualitative analysis of interviews with 22 child abusers found strong evidence for Ward and Keenan\u27s (1999) proposal that there are five implicit theories in child abusers that account for the majority of their cognitive distortions/thinking errors. These implicit theories are: Child as a sexual being where children are perceived as being able to and wanting to engage in sexual activity with adults and also are not be harmed by such sexual contact; Nature of harm where the offender perceives that sexual activity does not cause harm (and may in fact be beneficial) to the child; Entitlement where the child abuser perceives that he is superior and more important than others: and hence is able to have sex with whoever, and whenever, he wants; Dangerous world where the offender perceives that that others are abusive and rejecting and he must fight to regain control; and Uncontrollable where the offender perceives the world as uncontrollable and hence he believes that circumstances are outside of his control. There was no evidence for any other type of implicit theory. Results of the study also indicated that there was a significant difference in terms of the endorsement of the Dangerous world implicit theory between participants reporting a history of child sexual abuse and those who did not. Offenders against male victims were significantly more likely to endorse the Child as a sexual being and Dangerous world implicit theories compared to men who had offended against female children

A Natural Love of Natural Products

Recent research on the chemistry of natural products from the author’s group that led to the receipt of the ACS Ernest Guenther Award in the Chemistry of Natural Products is reviewed. REDOR NMR and synthetic studies established the T-taxol conformation as the bioactive tubulin-binding conformation, and these results were confirmed by the synthesis of compounds which clearly owed their activity or lack of activity to whether or not they could adopt the T-taxol conformation. Similar studies with the epothilones suggest that the current tubulin-binding model needs to be modified. Examples of natural products discovery and biodiversity conservation in Suriname and Madagascar are also presented, and it is concluded that natural products chemistry will continue to make significant contributions to drug discovery. My first real exposure to natural products chemistry came in my third and final year as an undergraduate at Cambridge University, when I attended a course of lectures on the chemistry of natural products by the Nobel Prize-winning chemist Sir Alexander Todd (later to become Lord Todd). The lectures included many references to his own work in the field, with stories of his early work on the structure of cholesterol, th

An enhanced partial order curve comparison algorithm and its application to analyzing protein folding trajectories

<p>Abstract</p> <p>Background</p> <p>Understanding how proteins fold is essential to our quest in discovering how life works at the molecular level. Current computation power enables researchers to produce a huge amount of folding simulation data. Hence there is a pressing need to be able to interpret and identify novel folding features from them.</p> <p>Results</p> <p>In this paper, we model each folding trajectory as a multi-dimensional curve. We then develop an effective multiple curve comparison (MCC) algorithm, called the <it>enhanced partial order (EPO) </it>algorithm, to extract features from a set of diverse folding trajectories, including both successful and unsuccessful simulation runs. The EPO algorithm addresses several new challenges presented by comparing high dimensional curves coming from folding trajectories. A detailed case study on miniprotein Trp-cage <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> demonstrates that our algorithm can detect similarities at rather low level, and extract biologically meaningful folding events.</p> <p>Conclusion</p> <p>The EPO algorithm is general and applicable to a wide range of applications. We demonstrate its generality and effectiveness by applying it to aligning multiple protein structures with low similarities. For user's convenience, we provide a web server for the algorithm at <url>http://db.cse.ohio-state.edu/EPO</url>.</p

Multiscale Coarse-Graining of the Protein Energy Landscape

A variety of coarse-grained (CG) models exists for simulation of proteins. An outstanding problem is the construction of a CG model with physically accurate conformational energetics rivaling all-atom force fields. In the present work, atomistic simulations of peptide folding and aggregation equilibria are force-matched using multiscale coarse-graining to develop and test a CG interaction potential of general utility for the simulation of proteins of arbitrary sequence. The reduced representation relies on multiple interaction sites to maintain the anisotropic packing and polarity of individual sidechains. CG energy landscapes computed from replica exchange simulations of the folding of Trpzip, Trp-cage and adenylate kinase resemble those of other reduced representations; non-native structures are observed with energies similar to those of the native state. The artifactual stabilization of misfolded states implies that non-native interactions play a deciding role in deviations from ideal funnel-like cooperative folding. The role of surface tension, backbone hydrogen bonding and the smooth pairwise CG landscape is discussed. Ab initio folding aside, the improved treatment of sidechain rotamers results in stability of the native state in constant temperature simulations of Trpzip, Trp-cage, and the open to closed conformational transition of adenylate kinase, illustrating the potential value of the CG force field for simulating protein complexes and transitions between well-defined structural states

Detection of Functional Modes in Protein Dynamics

Proteins frequently accomplish their biological function by collective atomic motions. Yet the identification of collective motions related to a specific protein function from, e.g., a molecular dynamics trajectory is often non-trivial. Here, we propose a novel technique termed “functional mode analysis” that aims to detect the collective motion that is directly related to a particular protein function. Based on an ensemble of structures, together with an arbitrary “functional quantity” that quantifies the functional state of the protein, the technique detects the collective motion that is maximally correlated to the functional quantity. The functional quantity could, e.g., correspond to a geometric, electrostatic, or chemical observable, or any other variable that is relevant to the function of the protein. In addition, the motion that displays the largest likelihood to induce a substantial change in the functional quantity is estimated from the given protein ensemble. Two different correlation measures are applied: first, the Pearson correlation coefficient that measures linear correlation only; and second, the mutual information that can assess any kind of interdependence. Detecting the maximally correlated motion allows one to derive a model for the functional state in terms of a single collective coordinate. The new approach is illustrated using a number of biomolecules, including a polyalanine-helix, T4 lysozyme, Trp-cage, and leucine-binding protein

Calculation of the Free Energy and Cooperativity of Protein Folding

Calculation of the free energy of protein folding and delineation of its pre-organization are of foremost importance for understanding, predicting and designing biological macromolecules. Here, we introduce an energy smoothing variant of parallel tempering replica exchange Monte Carlo (REMS) that allows for efficient configurational sampling of flexible solutes under the conditions of molecular hydration. Its usage to calculate the thermal stability of a model globular protein, Trp cage TC5b, achieves excellent agreement with experimental measurements. We find that the stability of TC5b is attained through the coupled formation of local and non-local interactions. Remarkably, many of these structures persist at high temperature, concomitant with the origin of native-like configurations and mesostates in an otherwise macroscopically disordered unfolded state. Graph manifold learning reveals that the conversion of these mesostates to the native state is structurally heterogeneous, and that the cooperativity of their formation is encoded largely by the unfolded state ensemble. In all, these studies establish the extent of thermodynamic and structural pre-organization of folding of this model globular protein, and achieve the calculation of macromolecular stability ab initio, as required for ab initio structure prediction, genome annotation, and drug design