College of Liberal Arts & Sciences

An extensive simulation study of lipid bilayer properties with different head groups, acyl chain lengths, and chain saturations.

Recent Comp Bio Pubs - Fri, 10/27/2017 - 16:08
Related Articles

An extensive simulation study of lipid bilayer properties with different head groups, acyl chain lengths, and chain saturations.

Biochim Biophys Acta. 2016 12;1858(12):3093-3104

Authors: Zhuang X, Dávila-Contreras EM, Beaven AH, Im W, Klauda JB

Abstract
Previous MD simulations of six phosphocholine (PC) lipid bilayers demonstrated the accuracy of the CHARMM36 force field (C36FF) for PC bilayer simulation at varied temperatures (BBA-Biomembranes, 1838 (2014): 2520-2529). In this work, we further examine the accuracy of C36FF over a wide temperature range for a broader range of lipid types such as various head groups (phosphatidic acid (PA), PC, phosphoethanolamine (PE), phosphoglycerol (PG), and phosphoserine (PS)), and tails (saturated, mono-, mixed- and poly-unsaturated acyl chains with varied chain lengths). The structural properties (surface area per lipid (SA/lip), overall bilayer thickness, hydrophobic thickness, headgroup-to-headgroup thickness, deuterium order parameter (SCD), and spin-lattice relaxation time (T1)) obtained from simulations agree well with nearly all available experimental data. Our analyses indicate that PS lipids have the most inter-lipid hydrogen bonds, while PG lipids have the most intra-lipid hydrogen bonds, which play the main role in their low SA/lip in PS lipids and low thicknesses in PG lipids, respectively. PS, PE, and PA lipids have the largest contact clusters with on average 5-8 lipids per cluster, while PC and PG have clusters of 4 lipids based on a cutoff distance of 6.5Å. PS lipids have much slower lipid wobble (i.e., higher correlation time) than other head groups at a given temperature as the hydrogen bonded network significantly reduces a lipid's mobility, and the rate of lipid wobble increases dramatically as temperature increases. These in-depth analyses facilitate further understanding of lipid bilayers at the atomic level.

PMID: 27664502 [PubMed - indexed for MEDLINE]

Asymmetric Cryo-EM Structure of Anthrax Toxin Protective Antigen Pore with Lethal Factor N-Terminal Domain.

Recent Comp Bio Pubs - Sat, 09/23/2017 - 10:03

Asymmetric Cryo-EM Structure of Anthrax Toxin Protective Antigen Pore with Lethal Factor N-Terminal Domain.

Toxins (Basel). 2017 Sep 22;9(10):

Authors: Machen AJ, Akkaladevi N, Trecazzi C, O'Neil PT, Mukherjee S, Qi Y, Dillard R, Im W, Gogol EP, White TA, Fisher MT

Abstract
The anthrax lethal toxin consists of protective antigen (PA) and lethal factor (LF). Understanding both the PA pore formation and LF translocation through the PA pore is crucial to mitigating and perhaps preventing anthrax disease. To better understand the interactions of the LF-PA engagement complex, the structure of the LFN-bound PA pore solubilized by a lipid nanodisc was examined using cryo-EM. CryoSPARC was used to rapidly sort particle populations of a heterogeneous sample preparation without imposing symmetry, resulting in a refined 17 Å PA pore structure with 3 LFN bound. At pH 7.5, the contributions from the three unstructured LFN lysine-rich tail regions do not occlude the Phe clamp opening. The open Phe clamp suggests that, in this translocation-compromised pH environment, the lysine-rich tails remain flexible and do not interact with the pore lumen region.

PMID: 28937604 [PubMed - in process]

Modeling CAPRI Targets 110 - 120 by Template-Based and Free Docking Using Contact Potential and Combined Scoring Function.

Recent Comp Bio Pubs - Fri, 09/15/2017 - 16:08
Related Articles

Modeling CAPRI Targets 110 - 120 by Template-Based and Free Docking Using Contact Potential and Combined Scoring Function.

Proteins. 2017 Sep 14;:

Authors: Kundrotas PJ, Anishchenko I, Badal VD, Das M, Dauzhenka T, Vakser IA

Abstract
The paper presents analysis of our template-based and free docking predictions in the joint CASP12/CAPRI37 round. A new scoring function for template-based docking was developed, benchmarked on the Dockground resource, and applied to the targets. The results showed that the function successfully discriminates the incorrect docking predictions. In correctly predicted targets, the scoring function was complemented by other considerations, such as consistency of the oligomeric states among templates, similarity of the biological functions, biological interface relevance, etc. The scoring function still does not distinguish well biological from crystal packing interfaces, and needs further development for the docking of bundles of α-helices. In the case of the trimeric targets, sequence-based methods did not find common templates, despite similarity of the structures, suggesting complementary use of structure- and sequence-based alignments in comparative docking. The results showed that if a good docking template is found, an accurate model of the interface can be built even from largely inaccurate models of individual subunits. Free docking however is very sensitive to the quality of the individual models. However, our newly developed contact potential detected approximate locations of the binding sites. This article is protected by copyright. All rights reserved.

PMID: 28905425 [PubMed - as supplied by publisher]

Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores.

Recent Comp Bio Pubs - Wed, 09/13/2017 - 15:09
Related Articles

Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores.

Proteins. 2015 Dec;83(12):2293-306

Authors: Parente DJ, Ray JC, Swint-Kruse L

Abstract
As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for coevolution between pairs of positions. Coevolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of coevolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly-used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6-bisphosphate aldolase protein families as models. Calculations used unthresholded coevolution scores from which column-specific properties such as sequence entropy and random noise were subtracted; "central" positions were identified by calculating various network centrality scores. When compared among algorithms, network centrality methods, particularly eigenvector centrality, showed markedly better agreement than comparisons of the top pairwise scores. Positions with large centrality scores occurred at key structural locations and/or were functionally sensitive to mutations. Further, the top central positions often differed from those with top pairwise coevolution scores: instead of a few strong scores, central positions often had multiple, moderate scores. We conclude that eigenvector centrality calculations reveal a robust evolutionary pattern of constraints-detectable by divergent algorithms--that occur at key protein locations. Finally, we discuss the fact that multiple patterns coexist in evolutionary data that, together, give rise to emergent protein functions.

PMID: 26503808 [PubMed - indexed for MEDLINE]

Dockground: A comprehensive data resource for modeling of protein complexes.

Recent Comp Bio Pubs - Tue, 09/12/2017 - 14:10
Related Articles

Dockground: A comprehensive data resource for modeling of protein complexes.

Protein Sci. 2017 Sep 10;:

Authors: Kundrotas PJ, Anishchenko I, Dauzhenka T, Kotthoff I, Mnevets D, Copeland MM, Vakser IA

Abstract
Characterization of life processes at the molecular level requires structural details of protein interactions. The number of experimentally determined structures of protein-protein complexes accounts only for a fraction of known protein interactions. This gap in structural description of the interactome has to be bridged by modeling. An essential part of the development of structural modeling/docking techniques for protein interactions is databases of protein-protein complexes. They are necessary for studying protein interfaces, providing a knowledge base for docking algorithms, developing intermolecular potentials, search procedures, and scoring functions. Development of protein-protein docking techniques requires thorough benchmarking of different parts of the docking protocols on carefully curated sets of protein-protein complexes. We present a comprehensive description of the Dockground resource (http://dockground.compbio.ku.edu) for structural modeling of protein interactions, including previously unpublished unbound docking benchmark set 4, and the X-ray docking decoy set 2. The resource offers a variety of interconnected datasets of protein-protein complexes and other data for the development and testing of different aspects of protein docking methodologies. Based on protein-protein complexes extracted from the PDB biounit files, Dockground offers sets of X-ray unbound, simulated unbound, model, and docking decoy structures. All datasets are freely available for download, as a whole or selecting specific structures, through a user-friendly interface on one integrated website. This article is protected by copyright. All rights reserved.

PMID: 28891124 [PubMed - as supplied by publisher]

Identification of novel small molecule Beclin 1 mimetics activating autophagy.

Recent Comp Bio Pubs - Sat, 09/09/2017 - 13:03
Related Articles

Identification of novel small molecule Beclin 1 mimetics activating autophagy.

Oncotarget. 2017 Aug 01;8(31):51355-51369

Authors: Yu J, Lan L, Lewin SJ, Rogers SA, Roy A, Wu X, Gao P, Karanicolas J, Aubé J, Sun B, Xu L

Abstract
Anti-apoptotic proteins Bcl-2 and Bcl-xL could block autophagy by binding to Beclin 1 protein, an essential inducer of autophagy. Compounds mimicking Beclin 1 might be able to disrupt Bcl-xL/2-Beclin 1 interaction, free out Beclin 1, and thus trigger autophagy. In order to identify small molecule Beclin 1 mimetics, a fluorescence polarization-based high-throughput screening of 50,316 compounds was carried out with a Z' score of 0.82 ± 0.05, and an outcome of 58 hits. After the structure analysis, three acridine analogues were unveiled and confirmed using the fluorescence polarization assay and the surface plasmon resonance assay. Moreover, a set of 17 additional acridine analogues was prepared and tested. Compound 7 showed selectivity for Bcl-xL (KD = 6.5 μM) over Bcl-2 (KD = 160 μM) protein, and potent cytotoxicity (nanomolar scale) in PC-3, PC-3a and DU145 prostate cancer cells. Furthermore, induction of autophagy was also demonstrated in PC-3 and PC-3a cells treated with some acridine compounds by LC3 conversion immunoblotting and LC3 fluorescence microscopy. These Beclin 1 mimetics will be invaluable tools for developing novel autophagy inducers, better understanding the roles of autophagy in cancer, and will contribute to cancer therapy.

PMID: 28881653 [PubMed - in process]

Subscribe to Center for Computational Biology aggregator

One of 34 U.S. public institutions in the prestigious Association of American Universities
44 nationally ranked graduate programs.
—U.S. News & World Report
Top 50 nationwide for size of library collection.
—ALA
23rd nationwide for service to veterans —"Best for Vets," Military Times
KU Today