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NCBI: db=pubmed; Term=(Im, Wonpil[Author] AND Kansas) OR (Vakser, Ilya[Author]) OR (Karanicolas, John[Author] AND Kansas) OR (Deeds, Eric[Author]) OR (Ray, Christian[Author]) OR (Slusky, Joanna[Author]) OR (Ray JC[Author] AND Kansas)
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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]

The fungal natural product azaphilone-9 binds to HuR and inhibits HuR-RNA interaction in vitro.

Tue, 04/18/2017 - 09:07
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The fungal natural product azaphilone-9 binds to HuR and inhibits HuR-RNA interaction in vitro.

PLoS One. 2017;12(4):e0175471

Authors: Kaur K, Wu X, Fields JK, Johnson DK, Lan L, Pratt M, Somoza AD, Wang CCC, Karanicolas J, Oakley BR, Xu L, De Guzman RN

Abstract
The RNA-binding protein Hu antigen R (HuR) binds to AU-rich elements (ARE) in the 3'-untranslated region (UTR) of target mRNAs. The HuR-ARE interactions stabilize many oncogenic mRNAs that play important roles in tumorigenesis. Thus, small molecules that interfere with the HuR-ARE interaction could potentially inhibit cancer cell growth and progression. Using a fluorescence polarization (FP) competition assay, we identified the compound azaphilone-9 (AZA-9) derived from the fungal natural product asperbenzaldehyde, binds to HuR and inhibits HuR-ARE interaction (IC50 ~1.2 μM). Results from surface plasmon resonance (SPR) verified the direct binding of AZA-9 to HuR. NMR methods mapped the RNA-binding interface of HuR and identified the involvement of critical RNA-binding residues in binding of AZA-9. Computational docking was then used to propose a likely binding site for AZA-9 in the RNA-binding cleft of HuR. Our results show that AZA-9 blocks key RNA-binding residues of HuR and disrupts HuR-RNA interactions in vitro. This knowledge is needed in developing more potent AZA-9 derivatives that could lead to new cancer therapy.

PMID: 28414767 [PubMed - in process]

Gramicidin A Channel Formation Induces Local Lipid Redistribution II: A 3D Continuum Elastic Model.

Thu, 03/30/2017 - 11:09
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Gramicidin A Channel Formation Induces Local Lipid Redistribution II: A 3D Continuum Elastic Model.

Biophys J. 2017 Mar 28;112(6):1198-1213

Authors: Sodt AJ, Beaven AH, Andersen OS, Im W, Pastor RW

Abstract
To change conformation, a protein must deform the surrounding bilayer. In this work, a three-dimensional continuum elastic model for gramicidin A in a lipid bilayer is shown to describe the sensitivity to thickness, curvature stress, and the mechanical properties of the lipid bilayer. A method is demonstrated to extract the gramicidin-lipid boundary condition from all-atom simulations that can be used in the three-dimensional continuum model. The boundary condition affects the deformation dramatically, potentially much more than typical variations in the material stiffness do as lipid composition is changed. Moreover, it directly controls the sensitivity to curvature stress. The curvature stress and hydrophobic surfaces of the all-atom and continuum models are found to be in excellent agreement. The continuum model is applied to estimate the enrichment of hydrophobically matched lipids near the channel in a mixture, and the results agree with single-channel experiments and extended molecular dynamics simulations from the companion article by Beaven et al. in this issue of Biophysical Journal.

PMID: 28355547 [PubMed - in process]

Gramicidin A Channel Formation Induces Local Lipid Redistribution I: Experiment and Simulation.

Thu, 03/30/2017 - 11:09
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Gramicidin A Channel Formation Induces Local Lipid Redistribution I: Experiment and Simulation.

Biophys J. 2017 Mar 28;112(6):1185-1197

Authors: Beaven AH, Maer AM, Sodt AJ, Rui H, Pastor RW, Andersen OS, Im W

Abstract
Integral membrane protein function can be modulated by the host bilayer. Because biological membranes are diverse and nonuniform, we explore the consequences of lipid diversity using gramicidin A channels embedded in phosphatidylcholine (PC) bilayers composed of equimolar mixtures of di-oleoyl-PC and di-erucoyl-PC (dC18:1+dC22:1, respectively), di-palmitoleoyl-PC and di-nervonoyl-PC (dC16:1+dC24:1, respectively), and di-eicosenoyl-PC (pure dC20:1), all of which have the same average bilayer chain length. Single-channel lifetime experiments, molecular dynamics simulations, and a simple lipid compression model are used in tandem to gain insight into lipid redistribution around the channel, which partially alleviates the bilayer deformation energy associated with channel formation. The average single-channel lifetimes in the two-component bilayers (95 ± 10 ms for dC18:1+dC22:1 and 195 ± 20 ms for dC16:1+dC24:1) were increased relative to the single-component dC20:1 control bilayer (65 ± 10 ms), implying lipid redistribution. Using a theoretical treatment of thickness-dependent changes in channel lifetimes, the effective local enrichment of lipids around the channel was estimated to be 58 ± 4% dC18:1 and 66 ± 2% dC16:1 in the dC18:1+dC22:1 and dC16:1+dC24:1 bilayers, respectively. 3.5-μs molecular dynamics simulations show 66 ± 2% dC16:1 in the first lipid shell around the channel in the dC16:1+dC24:1 bilayer, but no significant redistribution (50 ± 4% dC18:1) in the dC18:1+dC22:1 bilayer; these simulated values are within the 95% confidence intervals of the experimental averages. The strong preference for the better matching lipid (dC16:1) near the channel in the dC16:1+dC24:1 mixture and lesser redistribution in the dC18:1+dC22:1 mixture can be explained by the energetic cost associated with compressing the lipids to match the channel's hydrophobic length.

PMID: 28355546 [PubMed - in process]

"Solvent hydrogen-bond occlusion": A new model of polar desolvation for biomolecular energetics.

Tue, 03/21/2017 - 06:10

"Solvent hydrogen-bond occlusion": A new model of polar desolvation for biomolecular energetics.

J Comput Chem. 2017 Mar 20;:

Authors: Bazzoli A, Karanicolas J

Abstract
Water engages in two important types of interactions near biomolecules: it forms ordered "cages" around exposed hydrophobic regions, and it participates in hydrogen bonds with surface polar groups. Both types of interaction are critical to biomolecular structure and function, but explicitly including an appropriate number of solvent molecules makes many applications computationally intractable. A number of implicit solvent models have been developed to address this problem, many of which treat these two solvation effects separately. Here, we describe a new model to capture polar solvation effects, called SHO ("solvent hydrogen-bond occlusion"); our model aims to directly evaluate the energetic penalty associated with displacing discrete first-shell water molecules near each solute polar group. We have incorporated SHO into the Rosetta energy function, and find that scoring protein structures with SHO provides superior performance in loop modeling, virtual screening, and protein structure prediction benchmarks. These improvements stem from the fact that SHO accurately identifies and penalizes polar groups that do not participate in hydrogen bonds, either with solvent or with other solute atoms ("unsatisfied" polar groups). We expect that in future, SHO will enable higher-resolution predictions for a variety of molecular modeling applications. © 2017 Wiley Periodicals, Inc.

PMID: 28318014 [PubMed - as supplied by publisher]


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