Loopholes and missing links in protein modeling

This paper provides an unbiased comparison of four commercially available programs for loop sampling, Prime, Modeler, ICM, and Sybyl, each of which uses a different modeling protocol. The study assesses the quality of results and examines the relative strengths and weaknesses of each method. The set of loops to be modeled varied in length from 4-12 amino acids. The approaches used for loop modeling can be classified into two methodologies: ab initio loop generation (Modeler and Prime) and database searches (Sybyl and ICM). Comparison of the modeled loops to the native structures was used to determine the accuracy of each method. All of the protocols returned similar results for short loop lengths (four to six residues), but as loop length increased, the quality of the results varied among the programs. Prime generated loops with RMSDs <2.5 A for loops up to 10 residues, while the other three methods met the 2.5 A criteria at seven-residue loops. Additionally, the ability of the software to utilize disulfide bonds and X-ray crystal packing influenced the quality of the results. In the final analysis, the top-ranking loop from each program was rarely the loop with the lowest RMSD with respect to the native template, revealing a weakness in all programs to correctly rank the modeled loops.     

蛋白质结构与功能研究中的分子模拟技术

分子模拟技术为蛋白质的研究提供了一种崭新的手段,在理论上解决了结构预测和功能分析以及蛋白质工程实施方面所面临的难题。它在蛋白质的结构预测和模建工作中占有举足轻重的地位,实现了生物技术与计算机技术的完美结合。本文简要阐述了该技术的基本步骤和工作原理,并以目前应用最广的生物大分子领域的商品化分子模拟软件Accelrys公司基于Linux系统开发的InsightII为例,介绍了相关程序模块的功能和作用,同时结合该技术在蛋白质的结构预测和模建、结构与功能关系分析、分子设计等过程中的开发与应用,加以具体说明和展望。     

Combined finite-element and rigid-body analysis of human jaw joint dynamics

The jaw joint plays a crucial role in human mastication. It acts as a guidance for jaw movements and as a fulcrum for force generation. The joint is subjected to loading which causes tensions and deformations in its cartilaginous structures. These are assumed to be a major determinant for development, maintenance and also degeneration of the joint. To analyze the distribution of tensions and deformations in the cartilaginous structures of the jaw joint during jaw movement, a dynamical model of the human masticatory system has been constructed. Its movements are controlled by muscle activation. The articular cartilage layers and articular disc were included as finite-element (FE) models. As this combination of rigid-body and FE modeling had not been applied to musculoskeletal systems yet, its benefits and limitations were assessed by simulating both unloaded and loaded jaw movements. It was demonstrated that joint loads increase with muscle activation, irrespective of the external loads. With increasing joint load, the size of the stressed area of the articular surfaces was enlarged, whereas the peak stresses were much less affected. The results suggest that the articular disc enables distribution of local contact stresses over a much wider area of the very incongruent articular surfaces by transforming compressive principal stress into shear stress.     

Comparison of Composer and ORCHESTRAR

Although the number of known protein structures is increasing, the number of protein sequences without determined structures is still much larger. Three-dimensional (3D) protein structure information helps in the understanding of functional mechanisms, but solving structures by X-ray crystallography or NMR is often a lengthy and difficult process. A relatively fast way of determining a protein's 3D structure is to construct a computer model using homologous sequence and structure information. Much work has gone into algorithms that comprise the ORCHESTRAR homology modeling program in the SYBYL software package. This novel homology modeling tool combines algorithms for modeling conserved cores, variable regions, and side chains. The paradigm of using existing knowledge from multiple templates and the underlying protein environment knowledgebase is used in all of these algorithms, and will become even more powerful as the number of experimentally derived protein structures increases. To determine how ORCHESTRAR compares to Composer (a broadly used, but an older tool), homology models of 18 proteins were constructed using each program so that a detailed comparison of each step in the modeling process could be carried out. Proteins modeled include kinases, dihydrofolate reductase, HIV protease, and factor Xa. In almost all cases ORCHESTRAR produces models with lower root-mean-squared deviation (RMSD) values when compared with structures determined by X-ray crystallography or NMR. Moreover, ORCHESTRAR produced a homology model for three target sequences where Composer failed to produce any. Data for RMSD comparisons between structurally conserved cores, structurally variable regions, side-chain conformations are presented, as well as analyses of active site and protein-protein interface configurations.     

The biomechanical model of the long finger extensor mechanism and its parametric identification

The extensor mechanism of the finger is a structure transmitting the forces from several muscles to the finger joints. Force transmission in the extensor mechanism is usually modeled by equations with constant coefficients which are determined experimentally only for finger extension posture. However, the coefficient values change with finger flexion because of the extensor mechanism deformation. This induces inaccurate results for any other finger postures. We proposed a biomechanical model of the extensor mechanism represented as elastic strings. The model includes the main tendons and ligaments. The parametric identification of the model in extension posture was performed to match the distribution of the forces among the tendons to experimental data. The parametrized model was used to simulate three degrees of flexion. Furthermore, the ability of the model to reproduce how the force distribution in simulated extensor mechanism changes according to the muscle forces was also demonstrated. The proposed model could be used to simulate the extensor mechanism for any physiological finger posture for which the coefficients involved in the equations are unknown.     

Optimization of control strategies for epidemics in heterogeneous populations with symmetric and asymmetric transmission

There is growing interest in incorporating economic factors into epidemiological models in order to identify optimal strategies for disease control when resources are limited. In this paper we consider how to optimize the control of a pathogen that is capable of infecting multiple hosts with different rates of transmission within and between species. Our objective is to find control strategies that maximize the discounted number of healthy individuals. We consider two classes of host-pathogen system, comprising two host species and a common pathogen, one with asymmetrical and the other with symmetrical transmission rates, applicable to a wide range of SI (susceptible-infected) epidemics of plant and animal pathogens. We motivate the analyses with an example of sudden oak death in California coastal forests, caused by Phytophthora ramorum, in communities dominated by bay laurel (Umbellularia californica) and tanoak (Lithocarpus densiflorus). We show for the asymmetric case that it is optimal to give priority in treating disease to the more infectious species, and to treat the other species only when there are resources left over. For the symmetric case, we show that although a switching strategy is an optimum, in which preference is first given to the species with the lower level of susceptibles and then to the species with the higher level of susceptibles, a simpler strategy that favors treatment of infected hosts for the more susceptible species is a robust alternative for practical application when the optimal switching time is unknown. Finally, since transmission rates are notoriously difficult to estimate, we analyze the robustness of the strategies when the true state with respect to symmetry or otherwise is unknown but one or other is assumed.     

STRUCTFAST: protein sequence remote homology detection and alignment using novel dynamic programming and profile-profile scoring

STRUCTFAST is a novel profile-profile alignment algorithm capable of detecting weak similarities between protein sequences. The increased sensitivity and accuracy of the STRUCTFAST method are achieved through several unique features. First, the algorithm utilizes a novel dynamic programming engine capable of incorporating important information from a structural family directly into the alignment process. Second, the algorithm employs a rigorous analytical formula for profile-profile scoring to overcome the limitations of ad hoc scoring functions that require adjustable parameter training. Third, the algorithm employs Convergent Island Statistics (CIS) to compute the statistical significance of alignment scores independently for each pair of sequences. STRUCTFAST routinely produces alignments that meet or exceed the quality obtained by an expert human homology modeler, as evidenced by its performance in the latest CAFASP4 and CASP6 blind prediction benchmark experiments.     

Homology modeling of histidine-containing phosphocarrier protein and eosinophil-derived neurotoxin: Construction of models and comparison with experiment

Homology modeling methods have been used to construct models of two proteins—the histidine-containing phosphocarrier protein (HPr) from Mycoplasma capricolum and human eosinophil-derived neurotoxin (EDN). Comparison of the models with the subsequently determined X-ray crystal structures indicates that the core regions of both proteins are reasonably well reproduced, although the template structures are closer to the X-ray structures in these regions—possible enhancements are discussed. The conformations of most of the side chains in the core of HPr are well reproduced in the modeled structure. As expected, the conformations of surface side chains in this protein differ significantly from the X-ray structure. The loop regions of EDN were incorrectly modeled—reasons for this and possible enhancements are discussed. © 1995 Wiley-Liss, Inc.     

Subject-specific geometry affects acetabular contact pressure during gait more than subject-specific loading patterns

Abstract

Finite element modeling (FEM) can predict hip cartilage contact mechanics. This study investigated how subject-specific boundary conditions and joint geometry affect acetabular cartilage contact mechanics using a multi-scale workflow. For two healthy subjects, musculoskeletal models calculated subject-specific hip kinematics and loading, which were used as boundary conditions for FEM. Cartilage contact mechanics were predicted using either generic or subject-specific FEM and boundary conditions. A subject-specific mesh resulted in a more lateral contact. Effects of subject-specific boundary conditions varied between both subjects. Results highlight the complex interplay between loading and kinematics and their effect on cartilage contact mechanics.     

Modeling of microalgal shear‐induced flocculation and sedimentation using a coupled CFD‐population balance approach

In this study, shear‐induced flocculation modeling of Chlorella sp. microalgae was conducted by combination of population balance modeling and CFD. The inhomogeneous Multiple Size Group (MUSIG) and the Euler–Euler two fluid models were coupled via Ansys‐CFX‐15 software package to achieve both fluid and particle dynamics during the flocculation. For the first time, a detailed model was proposed to calculate the collision frequency and breakage rate during the microalgae flocculation by means of the response surface methodology as a tool for optimization. The particle size distribution resulted from the model was in good agreement with that of the jar test experiment. Furthermore, the subsequent sedimentation step was also examined by removing the shear rate in both simulations and experiments. Consequently, variation in the shear rate and its effects on the flocculation behavior, sedimentation rate and recovery efficiency were evaluated. Results indicate that flocculation of Chlorella sp. microalgae under shear rates of 37, 182, and 387 s^?1 is a promising method of pre‐concentration which guarantees the cost efficiency of the subsequent harvesting process by recovering more than 90% of the biomass. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 34:160–174, 2018     

Integrating coalescent and ecological niche modeling in comparative phylogeography

Understanding the factors that contribute to the formation of population genetic structure is a central goal of phylogeographic research, but achieving this goal can be complicated by the stochastic variance inherent to genetic processes. Statistical approaches to testing phylogeographic hypotheses accommodate this stochasticity by evaluating competing models of putative historical population structure, often by simulating null distributions of the expected variance. The effectiveness of these tests depends on the biological realism of the models. Information from the fossil record can aid in reconstructing the historical distributions of some taxa. However, for the majority of taxa, which lack sufficient fossils, paleodistributional modeling can provide valuable spatial-geographic data concerning ancestral distributions. Paleodistributional models are generated by projecting ecological niche models, which predict the current distribution of each species, onto a model of past climatic conditions. Here, we generate paleodistributional models describing the suitable habitat during the last glacial maximum for lineages from the mesic forests of the Pacific Northwest of North America, and use these models to generate alternative phylogeographic hypotheses. Coalescent simulations are then used to test these hypotheses to improve our understanding of the historical events that promoted the formation of population genetic structure in this ecosystem. Results from Pacific Northwest mesic forest organisms demonstrate the utility of these combined approaches. Paleodistribution models and population genetic structure are congruent across three amphibian lineages, suggesting that they have responded in a concerted manner to environmental change. Two other species, a willow and a water vole, despite being currently codistributed and having similar population genetic structure, were predicted by the paleodistributional model to have had markedly different distributions during the last glacial maximum. This suggests that congruent phylogeographic patterns can arise from incongruent ancestral distributions. Paleodistributional models introduce a much-needed spatial-geographic perspective to statistical phylogeography. In conjunction with coalescent models of population genetic structure, they have the potential to improve our understanding of the factors that promote population divergence and ultimately produce regional patterns of biodiversity.     

Cardiac myocytes and local signaling in nano-domains

It is well known that calcium-induced calcium-release in cardiac myocytes takes place in spatially restricted regions known as dyads, where discrete patches of junctional sarcoplasmic reticulum tightly associate with the t-tubule membrane. The dimensions of a dyad are so small that it contains only a few Ca²⁺ ions at any given time. Ca²⁺ signaling in the dyad is therefore noisy, and dominated by the Brownian motion of Ca²⁺ ions in a potential field. Remarkably, from this complexity emerges the integrated behavior of the myocyte in which, under normal conditions, precise control of Ca²⁺ release and muscle contraction is maintained over the life of the cell. This is but one example of how signal processing within the cardiac myocyte and other cells often occurs in small “nano-domains” where proteins and protein complexes interact at spatial dimensions on the order of ∼1-10 nm and at time-scales on the order of nanoseconds to perform the functions of the cell. In this article, we will review several examples of local signaling in nano-domains, how it contributes to the integrative behavior of the cardiac myocyte, and present computational methods for modeling signal processing within these domains across differing spatio-temporal scales.     

Data collection and capture systems for microbial modeling

Summary Microbial modeling experiments require an integrated and efficient design to overcome constraints on time and human resources. The choice of an experimental system is effected by first determining the goals and scope of the model to be constructed. Kinetic studies, for example, require a different approach from single end-point models, such as time to toxin detection or growth probability. Studies have been conducted in liquid broth tubes or batch culture, agar plates, and food matrices. These traditional systems are labor intensive, however, which constrains experimental size, and thus, a model's scope and validity. To maximize experimental size, experimental systems should be automated and linked to electronic data manipulation, analysis, and presentation. Microbial modelers should also consider the relationship between the experimental environmental factors, such as pH,a _w, or temperature, and their impact on growth, virulence or toxigenesis determinants. Attaining these goals will increase the probability that the model will accurately predict microbial responses in food systems.     

Climate change‐induced distributional change of medicinal and aromatic plants in the Nepal Himalaya

Medicinal and aromatic plants (MAPs) contribute to human well‐being via health and economic benefits. Nepal has recorded 2331 species of MAPs, of which around 300 species are currently under trade. Wild harvested MAPs in Nepal are under increasing pressure from overexploitation for trade and the effects of climate change and development. Despite some localized studies to examine the impact of climate change on MAPs, a consolidated understanding is lacking on how the distribution of major traded species of MAPs will change with future climate change. This study identifies the potential distribution of 29 species of MAPs in Nepal under current and future climate using an ensemble modeling and hotspot approach. Future climate change will reduce climatically suitable areas of two‐third of the studied species and decrease climatically suitable hotspots across elevation, physiography, ecoregions, federal states, and protected areas in Nepal. Reduction in climatically suitable areas for MAPs might have serious consequences for the livelihood of people that depend on the collection and trade of MAPs as well as Nepal''s national economy. Therefore, it is imperative to consider the threats that future climate change may have on distribution of MAPs while designing protected areas and devising environmental conservation and climate adaptation policies.     

Simulation of planar soft tissues using a structural constitutive model: Finite element implementation and validation

Computational implementation of physical and physiologically realistic constitutive models is critical for numerical simulation of soft biological tissues in a variety of biomedical applications. It is well established that the highly nonlinear and anisotropic mechanical behaviors of soft tissues are an emergent behavior of the underlying tissue microstructure. In the present study, we have implemented a structural constitutive model into a finite element framework specialized for membrane tissues. We noted that starting with a single element subjected to uniaxial tension, the non-fibrous tissue matrix must be present to prevent unrealistic tissue deformations. Flexural simulations were used to set the non-fibrous matrix modulus because fibers have little effects on tissue deformation under three-point bending. Multiple deformation modes were simulated, including strip biaxial, planar biaxial with two attachment methods, and membrane inflation. Detailed comparisons with experimental data were undertaken to insure faithful simulations of both the macro-level stress–strain insights into adaptations of the fiber architecture under stress, such as fiber reorientation and fiber recruitment. Results indicated a high degree of fidelity and demonstrated interesting microstructural adaptions to stress and the important role of the underlying tissue matrix. Moreover, we apparently resolve a discrepancy in our 1997 study (Billiar and Sacks, 1997. J. Biomech. 30 (7), 753–756) where we observed that under strip biaxial stretch the simulated fiber splay responses were not in good agreement with the experimental results, suggesting non-affine deformations may have occurred. However, by correctly accounting for the isotropic phase of the measured fiber splay, good agreement was obtained. While not the final word, these simulations suggest that affine fiber kinematics for planar collagenous tissues is a reasonable assumption at the macro level. Simulation tools such as these are imperative in the design and simulation of native and engineered tissues.     

Pyrazolo-triazolo-pyrimidines as adenosine receptor antagonists: Effect of the N-5 bond type on the affinity and selectivity at the four adenosine receptor subtypes

In the last few years, many efforts have been made to search for potent and selective human A₃ adenosine antagonists. In particular, one of the most promising human A₃ adenosine receptor antagonists is represented by the pyrazolo-triazolo-pyrimidine family. This class of compounds has been strongly investigated from the point of view of structure-activity relationships. In particular, it has been observed that fundamental requisites for having both potency and selectivity at the human A₃ adenosine receptors are the presence of a small substituent at the N⁸ position and an unsubstitued phenyl carbamoyl moiety at the N⁵ position. In this study, we report the role of the N⁵-bond type on the affinity and selectivity at the four adenosine receptor subtypes. The observed structure-activity relationships of this class of antagonists are also exhaustively rationalized using the recently published ligand-based homology modeling approach.     

A kinetic model of Escherichia coli core metabolism satisfying multiple sets of mutant flux data

In contrast to stoichiometric-based models, the development of large-scale kinetic models of metabolism has been hindered by the challenge of identifying kinetic parameter values and kinetic rate laws applicable to a wide range of environmental and/or genetic perturbations. The recently introduced ensemble modeling (EM) procedure provides a promising remedy to address these challenges by decomposing metabolic reactions into elementary reaction steps and incorporating all phenotypic observations, upon perturbation, in its model parameterization scheme. Here, we present a kinetic model of Escherichia coli core metabolism that satisfies the fluxomic data for wild-type and seven mutant strains by making use of the EM concepts. This model encompasses 138 reactions, 93 metabolites and 60 substrate-level regulatory interactions accounting for glycolysis/gluconeogenesis, pentose phosphate pathway, TCA cycle, major pyruvate metabolism, anaplerotic reactions and a number of reactions in other parts of the metabolism. Parameterization is performed using a formal optimization approach that minimizes the discrepancies between model predictions and flux measurements. The predicted fluxes by the model are within the uncertainty range of experimental flux data for 78% of the reactions (with measured fluxes) for both the wild-type and seven mutant strains. The remaining flux predictions are mostly within three standard deviations of reported ranges. Converting the EM-based parameters into a Michaelis–Menten equivalent formalism revealed that 35% of K_m and 77% of k_cat parameters are within uncertainty range of the literature-reported values. The predicted metabolite concentrations by the model are also within uncertainty ranges of metabolomic data for 68% of the metabolites. A leave-one-out cross-validation test to evaluate the flux prediction performance of the model showed that metabolic fluxes for the mutants located in the proximity of mutations used for training the model can be predicted more accurately. The constructed model and the parameterization procedure presented in this study pave the way for the construction of larger-scale kinetic models with more narrowly distributed parameter values as new metabolomic/fluxomic data sets are becoming available for E. coli and other organisms.     

Refinement of protein structures by iterative comparative modeling and CryoEM density fitting

We developed a method for structure characterization of assembly components by iterative comparative protein structure modeling and fitting into cryo-electron microscopy (cryoEM) density maps. Specifically, we calculate a comparative model of a given component by considering many alternative alignments between the target sequence and a related template structure while optimizing the fit of a model into the corresponding density map. The method relies on the previously developed Moulder protocol that iterates over alignment, model building, and model assessment. The protocol was benchmarked using 20 varied target-template pairs of known structures with less than 30% sequence identity and corresponding simulated density maps at resolutions from 5A to 25A. Relative to the models based on the best existing sequence profile alignment methods, the percentage of C(alpha) atoms that are within 5A of the corresponding C(alpha) atoms in the superposed native structure increases on average from 52% to 66%, which is half-way between the starting models and the models from the best possible alignments (82%). The test also reveals that despite the improvements in the accuracy of the fitness function, this function is still the bottleneck in reducing the remaining errors. To demonstrate the usefulness of the protocol, we applied it to the upper domain of the P8 capsid protein of rice dwarf virus that has been studied by cryoEM at 6.8A. The C(alpha) root-mean-square deviation of the model based on the remotely related template, bluetongue virus VP7, improved from 8.7A to 6.0A, while the best possible model has a C(alpha) RMSD value of 5.3A. Moreover, the resulting model fits better into the cryoEM density map than the initial template structure. The method is being implemented in our program MODELLER for protein structure modeling by satisfaction of spatial restraints and will be applicable to the rapidly increasing number of cryoEM density maps of macromolecular assemblies.