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Comparative Characterization of Crofelemer Samples using Data Mining and Machine Learning Approaches with Analytical Stability Data Sets.

Thu, 07/27/2017 - 13:13
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Comparative Characterization of Crofelemer Samples using Data Mining and Machine Learning Approaches with Analytical Stability Data Sets.

J Pharm Sci. 2017 Jul 22;:

Authors: Nariya MK, Kim JH, Xiong J, Kleindl PA, Hewarathna A, Fisher AC, Joshi SB, Schöneich C, Forrest ML, Middaugh CR, Volkin DB, Deeds EJ

Abstract
There is growing interest in generating physicochemical and biological analytical data sets to compare complex mixture drugs, for example products from different manufacturers. In this work, we compare various crofelemer samples prepared from a single lot by filtration with varying molecular weight cut-offs combined with incubation for different times at different temperatures. The two preceding manuscripts describe experimental data sets generated from analytical characterization of fractionated and degraded crofelemer samples. In this work, we use data mining techniques such as principal component analysis and mutual information scores to help visualize the data and determine discriminatory regions within these large data sets. The mutual information score identifies chemical signatures that differentiate crofelemer samples. These signatures, in many cases, would likely be missed by traditional data analysis tools. We also found that supervised learning classifiers robustly discriminate samples with around 99% classification accuracy, indicating that mathematical models of these physicochemical data sets are capable of identifying even subtle differences in crofelemer samples. Data mining and machine learning techniques can thus identify fingerprint-type attributes of complex mixture drugs that may be used for comparative characterization of products.

PMID: 28743607 [PubMed - as supplied by publisher]

The botanical drug substance crofelemer as a model system for comparative characterization of complex mixture drugs.

Thu, 07/27/2017 - 13:13
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The botanical drug substance crofelemer as a model system for comparative characterization of complex mixture drugs.

J Pharm Sci. 2017 Jul 22;:

Authors: Kleindl PA, Xiong J, Hewarathna A, Mozziconacci O, Nariya MK, Fisher AC, Deeds EJ, Joshi SB, Middaugh CR, Schöneich C, Volkin DB, Forrest ML

Abstract
Crofelemer is a botanical polymeric proanthocyanidin that inhibits chloride channel activity and is used clinically for treating HIV-associated secretory diarrhea. Crofelemer lots may exhibit significant physicochemical variation due to the natural source of the raw material. A variety of physical, chemical, and biological assays were utilized to identify potential critical quality attributes (CQAs) of crofelemer, which may be useful in characterizing differently sourced and/or processed drug products. Crofelemer drug substance was extracted from tablets of one commerical drug product lot, fractionated, and subjected to accelerated thermal degradation studies to produce derivative lots with variations in chemical and physical composition potentially representative of manufacturing and raw material variation. Liquid chromatography, UV absorbance spectroscopy, mass spectrometry, and NMR analysis revealed substantial changes in the composition of derivative lots. A chloride channel inhibition cell-based bioassay suggested that substantial changes in crofelemer composition did not necessarily result in major changes to bioactivity. In two companion papers, machine learning and data mining approaches were applied to the analytical and biological data sets presented herein, along with chemical stability data sets derived from forced degradation studies, to develop an integrated mathematical model that can identify CQAs which are most relevent in distinguishing between different populations of crofelemer.

PMID: 28743606 [PubMed - as supplied by publisher]

Modeling complexes of modeled proteins.

Tue, 07/25/2017 - 12:14
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Modeling complexes of modeled proteins.

Proteins. 2017 Mar;85(3):470-478

Authors: Anishchenko I, Kundrotas PJ, Vakser IA

Abstract
Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C(α) RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc.

PMID: 27701777 [PubMed - indexed for MEDLINE]

Structural quality of unrefined models in protein docking.

Tue, 07/25/2017 - 12:14
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Structural quality of unrefined models in protein docking.

Proteins. 2017 Jan;85(1):39-45

Authors: Anishchenko I, Kundrotas PJ, Vakser IA

Abstract
Structural characterization of protein-protein interactions is essential for understanding life processes at the molecular level. However, only a fraction of protein interactions have experimentally resolved structures. Thus, reliable computational methods for structural modeling of protein interactions (protein docking) are important for generating such structures and understanding the principles of protein recognition. Template-based docking techniques that utilize structural similarity between target protein-protein interaction and cocrystallized protein-protein complexes (templates) are gaining popularity due to generally higher reliability than that of the template-free docking. However, the template-based approach lacks explicit penalties for intermolecular penetration, as opposed to the typical free docking where such penalty is inherent due to the shape complementarity paradigm. Thus, template-based docking models are commonly assumed to require special treatment to remove large structural penetrations. In this study, we compared clashes in the template-based and free docking of the same proteins, with crystallographically determined and modeled structures. The results show that for the less accurate protein models, free docking produces fewer clashes than the template-based approach. However, contrary to the common expectation, in acceptable and better quality docking models of unbound crystallographically determined proteins, the clashes in the template-based docking are comparable to those in the free docking, due to the overall higher quality of the template-based docking predictions. This suggests that the free docking refinement protocols can in principle be applied to the template-based docking predictions as well. Proteins 2016; 85:39-45. © 2016 Wiley Periodicals, Inc.

PMID: 27756103 [PubMed - indexed for MEDLINE]

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment.

Tue, 07/25/2017 - 12:14
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Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment.

Proteins. 2016 Sep;84 Suppl 1:323-48

Authors: Lensink MF, Velankar S, Kryshtafovych A, Huang SY, Schneidman-Duhovny D, Sali A, Segura J, Fernandez-Fuentes N, Viswanath S, Elber R, Grudinin S, Popov P, Neveu E, Lee H, Baek M, Park S, Heo L, Rie Lee G, Seok C, Qin S, Zhou HX, Ritchie DW, Maigret B, Devignes MD, Ghoorah A, Torchala M, Chaleil RA, Bates PA, Ben-Zeev E, Eisenstein M, Negi SS, Weng Z, Vreven T, Pierce BG, Borrman TM, Yu J, Ochsenbein F, Guerois R, Vangone A, Rodrigues JP, van Zundert G, Nellen M, Xue L, Karaca E, Melquiond AS, Visscher K, Kastritis PL, Bonvin AM, Xu X, Qiu L, Yan C, Li J, Ma Z, Cheng J, Zou X, Shen Y, Peterson LX, Kim HR, Roy A, Han X, Esquivel-Rodriguez J, Kihara D, Yu X, Bruce NJ, Fuller JC, Wade RC, Anishchenko I, Kundrotas PJ, Vakser IA, Imai K, Yamada K, Oda T, Nakamura T, Tomii K, Pallara C, Romero-Durana M, Jiménez-García B, Moal IH, Férnandez-Recio J, Joung JY, Kim JY, Joo K, Lee J, Kozakov D, Vajda S, Mottarella S, Hall DR, Beglov D, Mamonov A, Xia B, Bohnuud T, Del Carpio CA, Ichiishi E, Marze N, Kuroda D, Roy Burman SS, Gray JJ, Chermak E, Cavallo L, Oliva R, Tovchigrechko A, Wodak SJ

Abstract
We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323-348. © 2016 Wiley Periodicals, Inc.

PMID: 27122118 [PubMed - indexed for MEDLINE]

Using Homology Modeling to Interrogate Binding Affinity in Neutralization of Ricin Toxin by a Family of Single Domain Antibodies.

Wed, 07/19/2017 - 22:04
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Using Homology Modeling to Interrogate Binding Affinity in Neutralization of Ricin Toxin by a Family of Single Domain Antibodies.

Proteins. 2017 Jul 18;:

Authors: Bazzoli A, Vance DJ, Rudolph MJ, Rong Y, Angalakurthi SK, Toth RT, Middaugh CR, Volkin DB, Weis DD, Karanicolas J, Mantis NJ

Abstract
In this report we investigated, within a group of closely related single domain camelid antibodies (VH Hs), the relationship between binding affinity and neutralizing activity as it pertains to ricin, a fast-acting toxin and biothreat agent. The V1C7-like VH Hs (V1C7, V2B9, V2E8, and V5C1) are similar in amino acid sequence, but differ in their binding affinities and toxin-neutralizing activities. Using the X-ray crystal structure of V1C7 in complex with ricin's enzymatic subunit (RTA) as a template, Rosetta-based homology modeling coupled with energetic decomposition led us to predict that a single pairwise interaction between Arg29 on V5C1 and Glu67 on RTA was responsible for the difference in ricin toxin binding affinity between V1C7, a weak neutralizer, and V5C1, a moderate neutralizer. This prediction was borne out experimentally: substitution of Arg for Gly at position 29 enhanced V1C7's binding affinity for ricin, whereas the reverse (i.e., Gly for Arg at position 29) diminished V5C1's binding affinity by >10 fold. As expected, the V5C1R29G mutant was largely devoid of toxin-neutralizing activity. However, the toxin-neutralizing activity of the V1C7G29R mutant was not correspondingly improved, indicating that in the V1C7 family binding affinity alone does not account for differences in antibody function. V1C7 and V5C1, as well as their respective point mutants, recognized indistinguishable epitopes on RTA, at least at the level of sensitivity afforded by hydrogen-deuterium mass spectrometry. The results of this study have implications for engineering therapeutic antibodies because they demonstrate that even subtle differences in epitope specificity can account for important differences in antibody function. This article is protected by copyright. All rights reserved.

PMID: 28718923 [PubMed - as supplied by publisher]

Crosstalk and the evolvability of intracellular communication.

Tue, 07/11/2017 - 18:04
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Crosstalk and the evolvability of intracellular communication.

Nat Commun. 2017 Jul 10;8:16009

Authors: Rowland MA, Greenbaum JM, Deeds EJ

Abstract
Metazoan signalling networks are complex, with extensive crosstalk between pathways. It is unclear what pressures drove the evolution of this architecture. We explore the hypothesis that crosstalk allows different cell types, each expressing a specific subset of signalling proteins, to activate different outputs when faced with the same inputs, responding differently to the same environment. We find that the pressure to generate diversity leads to the evolution of networks with extensive crosstalk. Using available data, we find that human tissues exhibit higher levels of diversity between cell types than networks with random expression patterns or networks with no crosstalk. We also find that crosstalk and differential expression can influence drug activity: no protein has the same impact on two tissues when inhibited. In addition to providing a possible explanation for the evolution of crosstalk, our work indicates that consideration of cellular context will likely be crucial for targeting signalling networks.

PMID: 28691706 [PubMed - in process]

Chemical stability of the botanical drug substance Crofelemer: a model system for comparative characterization of complex mixture drugs.

Mon, 07/10/2017 - 05:04

Chemical stability of the botanical drug substance Crofelemer: a model system for comparative characterization of complex mixture drugs.

J Pharm Sci. 2017 Jul 05;:

Authors: Hewarathna A, Mozziconacci O, Nariya MK, Kleindl PA, Xiong J, Fisher AC, Joshi SB, Middaugh CR, Forrest ML, Volkin DB, Deeds EJ, Schöneich C

Abstract
As the second of a three part series of articles in this issue concerning the development of a mathematical model for comparative characterization of complex mixture drugs using Crofelemer (CF) as a model compound, this work focuses on the evaluation of the chemical stability profile of CF. CF is a biopolymer containing a mixture of proanthocyanidin oligomers which are primarily composed of gallocatechin with a small contribution from catechin. CF extracted from drug product was subjected to molecular weight-based fractionation and thiolysis. Temperature stress and metal-catalyzed oxidation were selected for accelerated and forced degradation studies. Stressed-CF samples were size fractionated, thiolyzed, and analyzed with a combination of negative-ion electrospray ionization mass spectrometry (ESI-MS) and reversed-phase high pressure liquid chromatography (RP-HPLC) with UV absorption and fluorescence detection. We further analyzed the chemical stability data sets for various CF samples generated from RP-HPLC-UV and ESI-MS using data-mining and machine learning approaches. In particular, calculations based on mutual information of over 800,000 data points in the ESI-MS analytical data set revealed specific CF cleavage and degradation products that were differentially generated under specific storage/degradation conditions, which were not initially identified using traditional analysis of the ESI-MS results.

PMID: 28688843 [PubMed - as supplied by publisher]

The Structure of a Sugar Transporter of the Glucose EIIC Superfamily Provides Insight into the Elevator Mechanism of Membrane Transport.

Sat, 07/01/2017 - 12:17
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The Structure of a Sugar Transporter of the Glucose EIIC Superfamily Provides Insight into the Elevator Mechanism of Membrane Transport.

Structure. 2016 Jun 07;24(6):956-64

Authors: McCoy JG, Ren Z, Stanevich V, Lee J, Mitra S, Levin EJ, Poget S, Quick M, Im W, Zhou M

Abstract
The phosphoenolpyruvate:carbohydrate phosphotransferase systems are found in bacteria, where they play central roles in sugar uptake and regulation of cellular uptake processes. Little is known about how the membrane-embedded components (EIICs) selectively mediate the passage of carbohydrates across the membrane. Here we report the functional characterization and 2.55-Å resolution structure of a maltose transporter, bcMalT, belonging to the glucose superfamily of EIIC transporters. bcMalT crystallized in an outward-facing occluded conformation, in contrast to the structure of another glucose superfamily EIIC, bcChbC, which crystallized in an inward-facing occluded conformation. The structures differ in the position of a structurally conserved substrate-binding domain that is suggested to play a central role in sugar transport. In addition, molecular dynamics simulations suggest a potential pathway for substrate entry from the periplasm into the bcMalT substrate-binding site. These results provide a mechanistic framework for understanding substrate recognition and translocation for the glucose superfamily EIIC transporters.

PMID: 27161976 [PubMed - indexed for MEDLINE]

Bilayer Properties of Lipid A from Various Gram-Negative Bacteria.

Tue, 06/27/2017 - 11:07
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Bilayer Properties of Lipid A from Various Gram-Negative Bacteria.

Biophys J. 2016 Oct 18;111(8):1750-1760

Authors: Kim S, Patel DS, Park S, Slusky J, Klauda JB, Widmalm G, Im W

Abstract
Lipid A is the lipid anchor of a lipopolysaccharide in the outer leaflet of the outer membrane of Gram-negative bacteria. In general, lipid A consists of two phosphorylated N-acetyl glucosamine and several acyl chains that are directly linked to the two sugars. Depending on the bacterial species and environments, the acyl chain number and length vary, and lipid A can be chemically modified with phosphoethanolamine, aminoarabinose, or glycine residues, which are key to bacterial pathogenesis. In this work, homogeneous lipid bilayers of 21 distinct lipid A types from 12 bacterial species are modeled and simulated to investigate the differences and similarities of their membrane properties. In addition, different neutralizing ion types (Ca(2+), K(+), and Na(+)) are considered to examine the ion's influence on the membrane properties. The trajectory analysis shows that (1) the area per lipid is mostly correlated to the acyl chain number, and the area per lipid increases as a function of the acyl chain number; (2) the hydrophobic thickness is mainly determined by the average acyl chain length with slight dependence on the acyl chain number, and the hydrophobic thickness generally increases with the average acyl chain length; (3) a good correlation is observed among the area per lipid, hydrophobic thickness, and acyl chain order; and (4) although the influence of neutralizing ion types on the area per lipid and hydrophobic thickness is minimal, Ca(2+) stays longer on the membrane surface than K(+) or Na(+), consequently leading to lower lateral diffusion and a higher compressibility modulus, which agrees well with available experiments.

PMID: 27760361 [PubMed - indexed for MEDLINE]

DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites.

Tue, 06/27/2017 - 11:07
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DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites.

J Med Chem. 2016 May 12;59(9):4152-70

Authors: Gowthaman R, Miller SA, Rogers S, Khowsathit J, Lan L, Bai N, Johnson DK, Liu C, Xu L, Anbanandam A, Aubé J, Roy A, Karanicolas J

Abstract
Protein-protein interactions represent an exciting and challenging target class for therapeutic intervention using small molecules. Protein interaction sites are often devoid of the deep surface pockets presented by "traditional" drug targets, and crystal structures reveal that inhibitors typically engage these sites using very shallow binding modes. As a consequence, modern virtual screening tools developed to identify inhibitors of traditional drug targets do not perform as well when they are instead deployed at protein interaction sites. To address the need for novel inhibitors of important protein interactions, here we introduce an alternate docking strategy specifically designed for this regime. Our method, termed DARC (Docking Approach using Ray-Casting), matches the topography of a surface pocket "observed" from within the protein to the topography "observed" when viewing a potential ligand from the same vantage point. We applied DARC to carry out a virtual screen against the protein interaction site of human antiapoptotic protein Mcl-1 and found that four of the top-scoring 21 compounds showed clear inhibition in a biochemical assay. The Ki values for these compounds ranged from 1.2 to 21 μM, and each had ligand efficiency comparable to promising small-molecule inhibitors of other protein-protein interactions. These hit compounds do not resemble the natural (protein) binding partner of Mcl-1, nor do they resemble any known inhibitors of Mcl-1. Our results thus demonstrate the utility of DARC for identifying novel inhibitors of protein-protein interactions.

PMID: 26126123 [PubMed - indexed for MEDLINE]

Dynamical predictors of an imminent phenotypic switch in bacteria.

Sat, 06/10/2017 - 14:03
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Dynamical predictors of an imminent phenotypic switch in bacteria.

Phys Biol. 2017 Jun 09;:

Authors: Wang H, Ray C

Abstract
Single cells can stochastically switch across thresholds imposed by regulatory networks. Such thresholds can act as a tipping point, drastically changing global phenotypic states. In ecology and economics, imminent transitions across such tipping points can be predicted using dynamical early warning indicators. A typical example is "flickering" of a fast variable, predicting a longer-lasting switch from a low to a high state or vice versa. Considering the different timescales between metabolite and protein fluctuations in bacteria, we hypothesized that metabolic early warning indicators predict imminent transitions across a network threshold caused by enzyme saturation. We used stochastic simulations to determine if flickering predicts phenotypic transitions, accounting for a variety of molecular physiological parameters, including enzyme affinity, burstiness of enzyme gene expression, homeostatic feedback, and rates of metabolic precursor influx. In most cases, we found that metabolic flickering rates are robustly peaked near the enzyme saturation threshold. The degree of fluctuation was amplified by product inhibition of the enzyme. We conclude that sensitivity to flickering in fast variables may be a possible natural or synthetic strategy to prepare physiological states for an imminent transition.

PMID: 28597843 [PubMed - as supplied by publisher]

BamA POTRA Domain Interacts with a Native Lipid Membrane Surface.

Sat, 06/10/2017 - 14:03
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BamA POTRA Domain Interacts with a Native Lipid Membrane Surface.

Biophys J. 2016 Jun 21;110(12):2698-709

Authors: Fleming PJ, Patel DS, Wu EL, Qi Y, Yeom MS, Sousa MC, Fleming KG, Im W

Abstract
The outer membrane of Gram-negative bacteria is an asymmetric membrane with lipopolysaccharides on the external leaflet and phospholipids on the periplasmic leaflet. This outer membrane contains mainly β-barrel transmembrane proteins and lipidated periplasmic proteins (lipoproteins). The multisubunit protein β-barrel assembly machine (BAM) catalyzes the insertion and folding of the β-barrel proteins into this membrane. In Escherichia coli, the BAM complex consists of five subunits, a core transmembrane β-barrel with a long periplasmic domain (BamA) and four lipoproteins (BamB/C/D/E). The BamA periplasmic domain is composed of five globular subdomains in tandem called POTRA motifs that are key to BAM complex formation and interaction with the substrate β-barrel proteins. The BAM complex is believed to undergo conformational cycling while facilitating insertion of client proteins into the outer membrane. Reports describing variable conformations and dynamics of the periplasmic POTRA domain have been published. Therefore, elucidation of the conformational dynamics of the POTRA domain in full-length BamA is important to understand the function of this molecular complex. Using molecular dynamics simulations, we present evidence that the conformational flexibility of the POTRA domain is modulated by binding to the periplasmic surface of a native lipid membrane. Furthermore, membrane binding of the POTRA domain is compatible with both BamB and BamD binding, suggesting that conformational selection of different POTRA domain conformations may be involved in the mechanism of BAM-facilitated insertion of outer membrane β-barrel proteins.

PMID: 27332128 [PubMed - indexed for MEDLINE]

Challenges in structural approaches to cell modeling.

Sat, 06/10/2017 - 14:03
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Challenges in structural approaches to cell modeling.

J Mol Biol. 2016 Jul 31;428(15):2943-64

Authors: Im W, Liang J, Olson A, Zhou HX, Vajda S, Vakser IA

Abstract
Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field.

PMID: 27255863 [PubMed - indexed for MEDLINE]

Identification of novel small molecule Beclin 1 mimetics activating autophagy.

Thu, 06/08/2017 - 13:03
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Identification of novel small molecule Beclin 1 mimetics activating autophagy.

Oncotarget. 2017 May 18;:

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: 28591707 [PubMed - as supplied by publisher]

Fundamental trade-offs between information flow in single cells and cellular populations.

Sun, 05/14/2017 - 10:12
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Fundamental trade-offs between information flow in single cells and cellular populations.

Proc Natl Acad Sci U S A. 2017 May 12;:

Authors: Suderman R, Bachman JA, Smith A, Sorger PK, Deeds EJ

Abstract
Signal transduction networks allow eukaryotic cells to make decisions based on information about intracellular state and the environment. Biochemical noise significantly diminishes the fidelity of signaling: networks examined to date seem to transmit less than 1 bit of information. It is unclear how networks that control critical cell-fate decisions (e.g., cell division and apoptosis) can function with such low levels of information transfer. Here, we use theory, experiments, and numerical analysis to demonstrate an inherent trade-off between the information transferred in individual cells and the information available to control population-level responses. Noise in receptor-mediated apoptosis reduces information transfer to approximately 1 bit at the single-cell level but allows 3-4 bits of information to be transmitted at the population level. For processes such as eukaryotic chemotaxis, in which single cells are the functional unit, we find high levels of information transmission at a single-cell level. Thus, low levels of information transfer are unlikely to represent a physical limit. Instead, we propose that signaling networks exploit noise at the single-cell level to increase population-level information transfer, allowing extracellular ligands, whose levels are also subject to noise, to incrementally regulate phenotypic changes. This is particularly critical for discrete changes in fate (e.g., life vs. death) for which the key variable is the fraction of cells engaged. Our findings provide a framework for rationalizing the high levels of noise in metazoan signaling networks and have implications for the development of drugs that target these networks in the treatment of cancer and other diseases.

PMID: 28500273 [PubMed - as supplied by publisher]

Computational screening and design for compounds that disrupt protein-protein interactions.

Wed, 05/10/2017 - 08:12
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Computational screening and design for compounds that disrupt protein-protein interactions.

Curr Top Med Chem. 2017 May 08;:

Authors: Johnson DK, Karanicolas J

Abstract
Protein-protein interactions play key roles in all biological processes, motivating numerous campaigns to seek small-molecule disruptors of therapeutically relevant interactions. Two decades ago, the prospect of developing small-molecule inhibitors was thought to be perhaps impossible due to the potentially undruggable nature of the protein surfaces involved; this viewpoint was reinforced by the limited successes provided from traditional high-throughput screens. To date, however, refinement of new experimental approaches has led to a multitude of inhibitors against many different targets. Having thus established the feasibility of attaining success in this valuable and diverse target space, attention now turns to incorporating computational techniques that might assist during various stages of drug design and optimization. Here we review cases in which computational approaches - virtual screening, docking, and ligand optimization - have contributed to discovery of new inhibitors of protein-protein interactions. We conclude by providing an outlook into the upcoming challenges and recent advances likely to shape this field moving forward.

PMID: 28482793 [PubMed - as supplied by publisher]

Chaperonin-Based Biolayer Interferometry To Assess the Kinetic Stability of Metastable, Aggregation-Prone Proteins.

Wed, 05/10/2017 - 08:12
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Chaperonin-Based Biolayer Interferometry To Assess the Kinetic Stability of Metastable, Aggregation-Prone Proteins.

Biochemistry. 2016 Sep 06;55(35):4885-908

Authors: Lea WA, O'Neil PT, Machen AJ, Naik S, Chaudhri T, McGinn-Straub W, Tischer A, Auton MT, Burns JR, Baldwin MR, Khar KR, Karanicolas J, Fisher MT

Abstract
Stabilizing the folded state of metastable and/or aggregation-prone proteins through exogenous ligand binding is an appealing strategy for decreasing disease pathologies caused by protein folding defects or deleterious kinetic transitions. Current methods of examining binding of a ligand to these marginally stable native states are limited because protein aggregation typically interferes with analysis. Here, we describe a rapid method for assessing the kinetic stability of folded proteins and monitoring the effects of ligand stabilization for both intrinsically stable proteins (monomers, oligomers, and multidomain proteins) and metastable proteins (e.g., low Tm) that uses a new GroEL chaperonin-based biolayer interferometry (BLI) denaturant pulse platform. A kinetically controlled denaturation isotherm is generated by exposing a target protein, immobilized on a BLI biosensor, to increasing denaturant concentrations (urea or GuHCl) in a pulsatile manner to induce partial or complete unfolding of the attached protein population. Following the rapid removal of the denaturant, the extent of hydrophobic unfolded/partially folded species that remains is detected by an increased level of GroEL binding. Because this kinetic denaturant pulse is brief, the amplitude of binding of GroEL to the immobilized protein depends on the duration of the exposure to the denaturant, the concentration of the denaturant, wash times, and the underlying protein unfolding-refolding kinetics; fixing all other parameters and plotting the GroEL binding amplitude versus denaturant pulse concentration result in a kinetically controlled denaturation isotherm. When folding osmolytes or stabilizing ligands are added to the immobilized target proteins before and during the denaturant pulse, the diminished population of unfolded/partially folded protein manifests as a decreased level of GroEL binding and/or a marked shift in these kinetically controlled denaturation profiles to higher denaturant concentrations. This particular platform approach can be used to identify small molecules and/or solution conditions that can stabilize or destabilize thermally stable proteins, multidomain proteins, oligomeric proteins, and, most importantly, aggregation-prone metastable proteins.

PMID: 27505032 [PubMed - indexed for MEDLINE]

Replacing Arginine 33 for Alanine in the Hemophore HasA from Pseudomonas aeruginosa Causes Closure of the H32 Loop in the Apo-Protein.

Sun, 04/30/2017 - 16:03
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Replacing Arginine 33 for Alanine in the Hemophore HasA from Pseudomonas aeruginosa Causes Closure of the H32 Loop in the Apo-Protein.

Biochemistry. 2016 May 10;55(18):2622-31

Authors: Kumar R, Qi Y, Matsumura H, Lovell S, Yao H, Battaile KP, Im W, Moënne-Loccoz P, Rivera M

Abstract
Previous characterization of hemophores from Serratia marcescens (HasAs), Pseudomonas aeruginosa (HasAp), and Yersinia pestis (HasAyp) showed that hemin binds between two loops, where it is axially coordinated by H32 and Y75. The Y75 loop is structurally conserved in all three hemophores and harbors conserved ligand Y75. The other loop contains H32 in HasAs and HasAp, but a noncoordinating Q32 in HasAyp. The H32 loop in apo-HasAs and apo-HasAp is in an open conformation, which places H32 about 30 Å from the hemin-binding site. Hence, hemin binding onto the Y75 loop of HasAs or HasAp triggers a large relocation of the H32 loop from an open- to a closed-loop conformation and enables coordination of the hemin-iron by H32. In comparison, the Q32 loop in apo-HasAyp is in the closed conformation, and hemin binding occurs with minimal reorganization and without coordinative interactions with the Q32 loop. Studies in crystallo and in solution have established that the open H32 loop in apo-HasAp and apo-HasAs is well structured and minimally affected by conformational dynamics. In this study we address the intriguing issue of the stability of the H32 loop in apo-HasAp and how hemin binding triggers its relocation. We address this question with a combination of NMR spectroscopy, X-ray crystallography, and molecular dynamics simulations and find that R33 is critical to the stability of the open H32 loop. Replacing R33 with A causes the H32 loop in R33A apo-HasAp to adopt a conformation similar to that of holo-HasAp. Finally, stopped-flow absorption and resonance Raman analyses of hemin binding to apo-R33A HasAp indicate that the closed H32 loop slows down the insertion of the heme inside the binding pocket, presumably as it obstructs access to the hydrophobic platform on the Y75 loop, but accelerates the completion of the heme iron coordination.

PMID: 27074415 [PubMed - indexed for MEDLINE]


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