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排序方式： 共有7874条查询结果，搜索用时 15 毫秒
981.
Amar Singh Taras Dauzhenka Petras J. Kundrotas Michael J. E. Sternberg Ilya A. Vakser 《Proteins》2020,88(9):1180-1188
Protein docking is essential for structural characterization of protein interactions. Besides providing the structure of protein complexes, modeling of proteins and their complexes is important for understanding the fundamental principles and specific aspects of protein interactions. The accuracy of protein modeling, in general, is still less than that of the experimental approaches. Thus, it is important to investigate the applicability of docking techniques to modeled proteins. We present new comprehensive benchmark sets of protein models for the development and validation of protein docking, as well as a systematic assessment of free and template-based docking techniques on these sets. As opposed to previous studies, the benchmark sets reflect the real case modeling/docking scenario where the accuracy of the models is assessed by the modeling procedure, without reference to the native structure (which would be unknown in practical applications). We also expanded the analysis to include docking of protein pairs where proteins have different structural accuracy. The results show that, in general, the template-based docking is less sensitive to the structural inaccuracies of the models than the free docking. The near-native docking poses generated by the template-based approach, typically, also have higher ranks than those produces by the free docking (although the free docking is indispensable in modeling the multiplicity of protein interactions in a crowded cellular environment). The results show that docking techniques are applicable to protein models in a broad range of modeling accuracy. The study provides clear guidelines for practical applications of docking to protein models. 相似文献
982.
Stephanie Jane Peacock Martin Krkošek Mark Alun Lewis Subhash Lele 《Ecology and evolution》2017,7(2):762-770
The statistical tools available to ecologists are becoming increasingly sophisticated, allowing more complex, mechanistic models to be fit to ecological data. Such models have the potential to provide new insights into the processes underlying ecological patterns, but the inferences made are limited by the information in the data. Statistical nonestimability of model parameters due to insufficient information in the data is a problem too‐often ignored by ecologists employing complex models. Here, we show how a new statistical computing method called data cloning can be used to inform study design by assessing the estimability of parameters under different spatial and temporal scales of sampling. A case study of parasite transmission from farmed to wild salmon highlights that assessing the estimability of ecologically relevant parameters should be a key step when designing studies in which fitting complex mechanistic models is the end goal. 相似文献
983.
Abstract The binding of the benzodioxolo-benzoquinolizine alkaloid, berberine chloride to natural and synthetic DNAs has been studied by intrinsic and extrinsic circular dichroic measurements. Binding of berberine causes changes in the circular dichroism spectrum of DNA as shown by the increase of molar ellipticity of the 270nm band, but with very little change of the 240nm band. The molar ellipticity at the saturation depends strongly on the base composition of DNA and also on salt concentration, but always larger for the AT rich DNA than the GC rich DNA The features in the circular dichroic spectral changes of berberine-synthetic DNA complexes were similar to that of native DNA but depends on the sequence of base pairs. On binding to DNA and polynucleotides, the alkaloid becomes optically active. The extrinsic circular dichroism developed in the visible absorption region (300–500nm) for the berberine-DNA complexes shows two broad spectral bands in the regions 425–440nm and 340–360nm with the maximum varying depending on base composition and sequence of DNA While the 425nm band shows less variation on the binding ratio, the 360nm band is remarkably dependent on the DNA/alkaloid ratio. The generation of the alkaloid associated extrinsic circular dichroic bands is not dependent on the base composition or sequence of base pairs, but the nature and magnitude of the bands are very much dependent on these two factors and also on the salt concentration. The interpretation of the results with respect to the modes of the alkaloid binding to DNA are presented. 相似文献
984.
Type 1 fimbriae are a known virulence factor in a number of pathogenic enterobacteriaceae, including Salmonella, Shigella and E. coli. Yet, they are also expressed by some commensal strains, notably of E. coli. One hypothesis of the role of fimbriae in commensals is that they evoke a small but tolerable host immune response in order to have the host release sialic acid, which is a valuable nutrient. Genetic evidence suggests that sialic acid down-regulates fimbriation. This has been believed to enable the cells to reduce virulence when the host response is increasing, thus avoiding a full activation of host defenses. In this article we assess the plausibility of this hypothesis using mathematical models. Our models lead us to two main conclusions: A slight activation of host defenses is only possible with a carefully tuned set of parameters, whereas under a wide range of parameters and assumptions, the model predicts the host defenses to be activated to at least half their potential in response to fimbriation. Secondly, the fact that fimbriation is suppressed by sialic acid seems irrelevant for the global qualitative properties. 相似文献
985.
Petraccone L Erra E Messere A Montesarchio D Piccialli G De Napoli L Barone G Giancola C 《Biopolymers》2004,73(4):434-442
Targeting double-stranded DNA with homopyrimidine PNAs results in strand displacement complexes PNA/DNA/PNA rather than PNA/DNA/DNA triplex structures. Not much is known about the binding properties of DNA-PNA chimeras. A 16-mer 5'-DNA-3'-p-(N)PNA(C) has been investigated for its ability to hybridize a complementary duplex DNA by DSC, CD, and molecular modeling studies. The obtained results showed the formation of a triplex structure having similar, if not slightly higher, stability compared to the same all-DNA complex. 相似文献
986.
Fairbrother WJ Gordon NC Humke EW O'Rourke KM Starovasnik MA Yin JP Dixit VM 《Protein science : a publication of the Protein Society》2001,10(9):1911-1918
PYRIN domains were identified recently as putative protein-protein interaction domains at the N-termini of several proteins thought to function in apoptotic and inflammatory signaling pathways. The approximately 95 residue PYRIN domains have no statistically significant sequence homology to proteins with known three-dimensional structure. Using secondary structure prediction and potential-based fold recognition methods, however, the PYRIN domain is predicted to be a member of the six-helix bundle death domain-fold superfamily that includes death domains (DDs), death effector domains (DEDs), and caspase recruitment domains (CARDs). Members of the death domain-fold superfamily are well established mediators of protein-protein interactions found in many proteins involved in apoptosis and inflammation, indicating further that the PYRIN domains serve a similar function. An homology model of the PYRIN domain of CARD7/DEFCAP/NAC/NALP1, a member of the Apaf-1/Ced-4 family of proteins, was constructed using the three-dimensional structures of the FADD and p75 neurotrophin receptor DDs, and of the Apaf-1 and caspase-9 CARDs, as templates. Validation of the model using a variety of computational techniques indicates that the fold prediction is consistent with the sequence. Comparison of a circular dichroism spectrum of the PYRIN domain of CARD7/DEFCAP/NAC/NALP1 with spectra of several proteins known to adopt the death domain-fold provides experimental support for the structure prediction. 相似文献
987.
The similarity between folding and binding led us to posit the concept that the number of protein-protein interface motifs in nature is limited, and interacting protein pairs can use similar interface architectures repeatedly, even if their global folds completely vary. Thus, known protein-protein interface architectures can be used to model the complexes between two target proteins on the proteome scale, even if their global structures differ. This powerful concept is combined with a flexible refinement and global energy assessment tool. The accuracy of the method is highly dependent on the structural diversity of the interface architectures in the template dataset. Here, we validate this knowledge-based combinatorial method on the Docking Benchmark and show that it efficiently finds high-quality models for benchmark complexes and their binding regions even in the absence of template interfaces having sequence similarity to the targets. Compared to \"classical\" docking, it is computationally faster; as the number of target proteins increases, the difference becomes more dramatic. Further, it is able to distinguish binders from nonbinders. These features allow performing large-scale network modeling. The results on an independent target set (proteins in the p53 molecular interaction map) show that current method can be used to predict whether a given protein pair interacts. Overall, while constrained by the diversity of the template set, this approach efficiently produces high-quality models of protein-protein complexes. We expect that with the growing number of known interface architectures, this type of knowledge-based methods will be increasingly used by the broad proteomics community. 相似文献
988.
989.
Georgios Makrygiorgos Aaron J. Berliner Fengzhe Shi Douglas S. Clark Adam P. Arkin Ali Mesbah 《Biotechnology and bioengineering》2023,120(3):803-818
Computational models are increasingly used to investigate and predict the complex dynamics of biological and biochemical systems. Nevertheless, governing equations of a biochemical system may not be (fully) known, which would necessitate learning the system dynamics directly from, often limited and noisy, observed data. On the other hand, when expensive models are available, systematic and efficient quantification of the effects of model uncertainties on quantities of interest can be an arduous task. This paper leverages the notion of flow-map (de)compositions to present a framework that can address both of these challenges via learning data-driven models useful for capturing the dynamical behavior of biochemical systems. Data-driven flow-map models seek to directly learn the integration operators of the governing differential equations in a black-box manner, irrespective of structure of the underlying equations. As such, they can serve as a flexible approach for deriving fast-to-evaluate surrogates for expensive computational models of system dynamics, or, alternatively, for reconstructing the long-term system dynamics via experimental observations. We present a data-efficient approach to data-driven flow-map modeling based on polynomial chaos Kriging. The approach is demonstrated for discovery of the dynamics of various benchmark systems and a coculture bioreactor subject to external forcing, as well as for uncertainty quantification of a microbial electrosynthesis reactor. Such data-driven models and analyses of dynamical systems can be paramount in the design and optimization of bioprocesses and integrated biomanufacturing systems. 相似文献
990.
The design of bioaffinity-based targeted delivery systems for biofilm inactivation may require a comprehensive understanding of physicochemical and biochemical properties of biobased antimicrobial particles and their interactions with biofilm. In this study, Escherichia coli biofilm inactivation by chlorine-charged yeast microparticles was numerically simulated, and the roles of chemical stability, binding affinity, and controlled release of this targeted delivery system were assessed using this numerical simulation. The simulation results were experimentally validated using two different types of yeast microparticles. The results of this study illustrate that chorine stability achieved by yeast microparticles was a key factor for improved biofilm inactivation in an organic-rich environment (>6 additional log reduction in 20 min compared to the free chlorine treatment). Moreover, the binding affinity of yeast microparticles to E. coli biofilms was another key factor for an enhanced inactivation of biofilm, as a 10-fold increase in binding rate resulted in a 4.2-fold faster inactivation. Overall, the mechanistic modeling framework developed in this study could guide the design and development of biobased particles for targeted inactivation of biofilms. 相似文献