scholarly journals Decrypting protein surfaces by combining evolution, geometry and molecular docking

2018 ◽  
Author(s):  
Chloé Dequeker ◽  
Elodie Laine ◽  
Alessandra Carbone
Keyword(s):  
Protein Interactions ◽  
Sources Of Information ◽  
Protein Surface ◽  
Protein Surfaces ◽  
Geometrical Properties ◽  
Cross Docking ◽  
Protein Interfaces ◽  
New Concepts ◽  
Physico Chemical ◽  
Computational Data

The growing body of experimental and computational data describing how proteins interact with each other has emphasized the multiplicity of protein interactions and the complexity underlying protein surface usage and deformability. In this work, we propose new concepts and methods toward deciphering such complexity. We introduce the notion of interacting region to account for the multiple usage of a protein's surface residues by several partners and for the variability of protein interfaces coming from molecular flexibility. We predict interacting patches by crossing evolutionary, physico-chemical and geometrical properties of the protein surface with information coming from complete cross-docking (CC-D) simulations. We show that our predictions match well interacting regions and that the dierent sources of information are complementary. We further propose an indicator of whether a protein has a few or many partners. Our prediction strategies are implemented in the dynJET2 algorithm and assessed on a new dataset of 262 protein on which we performed CC-D. The code and the data are available at: http://www.lcqb.upmc.fr/dynJET2/.

scholarly journals Water follows polar and nonpolar protein surface domains

2019 ◽  
Vol 116 (39) ◽  
pp. 19274-19281 ◽  
Author(s):  
Baofu Qiao ◽  
Felipe Jiménez-Ángeles ◽  
Trung Dac Nguyen ◽  
Monica Olvera de la Cruz
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Protein Interactions ◽  
Protein Solubility ◽  
Protein Surface ◽  
Protein Surfaces ◽  
Charged Amino Acids ◽  
Average Water ◽  
Surface Domains ◽  
Positively Charged

The conformation of water around proteins is of paramount importance, as it determines protein interactions. Although the average water properties around the surface of proteins have been provided experimentally and computationally, protein surfaces are highly heterogeneous. Therefore, it is crucial to determine the correlations of water to the local distributions of polar and nonpolar protein surface domains to understand functions such as aggregation, mutations, and delivery. By using atomistic simulations, we investigate the orientation and dynamics of water molecules next to 4 types of protein surface domains: negatively charged, positively charged, and charge-neutral polar and nonpolar amino acids. The negatively charged amino acids orient around 98% of the neighboring water dipoles toward the protein surface, and such correlation persists up to around 16 Å from the protein surface. The positively charged amino acids orient around 94% of the nearest water dipoles against the protein surface, and the correlation persists up to around 12 Å. The charge-neutral polar and nonpolar amino acids are also orienting the water neighbors in a quantitatively weaker manner. A similar trend was observed in the residence time of the nearest water neighbors. These findings hold true for 3 technically important enzymes (PETase, cytochrome P450, and organophosphorus hydrolase). Our results demonstrate that the water−amino acid degree of correlation follows the same trend as the amino acid contribution in proteins solubility, namely, the negatively charged amino acids are the most beneficial for protein solubility, then the positively charged amino acids, and finally the charge-neutral amino acids.

Protein Surface Functional Imaging

2012 ◽  
Vol 721 ◽  
pp. 319-324 ◽  
Author(s):  
Paul Dan Cristea ◽  
Octavian Arsene ◽  
Rodica Tuduce ◽  
Dan Nicolau
Keyword(s):  
Density Distribution ◽  
Functional Imaging ◽  
Protein Interactions ◽  
Functional Classification ◽  
Protein Surface ◽  
Protein Surfaces ◽  
Discrete Surface ◽  
Vector Description ◽  
Unit Vectors

The paper presents an image-oriented functional description of protein surfaces in terms of amphiphilicity (hydrophobicity / hydrophilicity) distribution. The actual discrete surface atom amphiphilicity distribution is replaced by an approximately equivalent amphiphilicity density distribution, computed in a standardized octagonal pattern around each atom. This representation is used to compute the resemblance of the neighborhoods of a pair of surface atoms – defined as the sum of the products of amphiphilicity densities of the corresponding patches (the pattern's central circles and the angular sectors in the same positions) in the two neighborhoods. The similitude and the interaction of a pair of atom neighborhoods are defined as their resemblance for parallel, respectively, anti-parallel orientations of the unit vectors perpendicular on the molecular surfaces in the points where the central atoms are located. These parameters, as well as the vector description of the neighborhoods, are used for the functional classification of surface atoms and for the study of protein interactions.

scholarly journals Multiple protein-DNA interfaces unravelled by evolutionary information, physico-chemical and geometrical properties

2019 ◽  
Author(s):  
F. Corsi ◽  
R. Lavery ◽  
E. Laine ◽  
A. Carbone
Keyword(s):  
Protein Structures ◽  
Chemical Properties ◽  
Structural Data ◽  
Evolutionary Information ◽  
Surface Geometry ◽  
Protein Surfaces ◽  
Geometrical Properties ◽  
Link Type ◽  
Physico Chemical ◽  
Multiple Protein

ABSTRACTThe usage made of protein surfaces by nucleic acids still remains largely unknown, due to the lack of available structural data and the inherent complexity associated to protein surface deformability and evolution. In this work, we present a method that contributes to decipher such complexity by predicting protein-DNA interfaces and characterizing their properties. It relies on three biologically and physically meaningful descriptors, namely evolutionary conservation, physico-chemical properties and surface geometry. We carefully assessed its performance on several hundreds of protein structures. We achieve a higher sensitivity compared to state-of-the-art methods, and similar precision. Importantly, we show that our method is able to unravel ‘hidden’ binding sites by applying it to unbound protein structures and to proteins binding to DNA via multiple sites and in different conformations. It is implemented as a fully automated tool, , freely accessible at: http://www.lcqb.upmc.fr/JET2DNA. We also provide a new reference dataset of 187 protein-DNA complex structures, representative of all types of protein-DNA interactions, along with a subset of associated unbound structures: http://www.lcqb.upmc.fr/PDNAbenchmarks.

scholarly journals Valorisation of Coffee Roasting By-Products: Recovery of Silverskin Fat By Supercritical CO2 Extraction

2021 ◽  
Author(s):  
Rita Nasti ◽  
Andrea Galeazzi ◽  
Stefania Marzorati ◽  
Federica Zaccheria ◽  
Nicoletta Ravasio ◽  
...  
Keyword(s):  
Scale Up ◽  
Added Value ◽  
Supercritical Co2 Extraction ◽  
Green Technologies ◽  
Coffee Silverskin ◽  
New Concepts ◽  
Physico Chemical ◽  
High Investment ◽  
Fat Yield ◽  
By Products

AbstractRecovery of agro and food-industrial waste and their valorisation via green technologies can help to outline new concepts of industrial strategies. In this contest, a fat enriched of added-value components was extracted from coffee silverskin by applying a supercritical fluid extraction technique (sc-CO2). An appropriate modulation of process parameters like temperature (T = 35, 50, 60 °C) and pressure (p = 200–300 bar) influences the fat yield and the chemical composition, opening the way for targeted extraction. The extraction time, the organic solvent use and the energy consume were reduced compared to Soxhlet. Moreover, a mathematical model was constructed based on the experimental data collected, employed apparatus, and physico-chemical characteristics of biomass, pointing to a possible industrial scale-up. The experimental results are accompanied by a preliminary cost of manufacturing (COM), highlighting how the high investment for the apparatus is compensated by several benefits. Graphic Abstract

scholarly journals Optimal Anchoring of a Urea-based Foldamer Inhibitor of ASF1 Histone Chaperone Through Backbone Plasticity

2020 ◽  
Author(s):  
Johanne Mbianda ◽  
May Bakail ◽  
Christophe André ◽  
Gwenaëlle Moal ◽  
Marie E. Perrin ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Histone Chaperone ◽  
Protein Protein Interactions ◽  
Protein Surface ◽  
Chromatin Dynamics ◽  
Correct Orientation ◽  
Surface Recognition ◽  
Binding Interface ◽  
Helical Peptide ◽  
Α Helix

<p><b>Sequence-specific oligomers with predictable folding patterns, i.e. foldamers provide new opportunities to mimic α-helical peptides and design inhibitors of protein-protein interactions. One major hurdle of this strategy is to retain the correct orientation of key side chains involved in protein surface recognition. Here, we show that the structural plasticity of a foldamer backbone may significantly contribute to the required spatial adjustment for optimal interaction with the protein surface. By using oligoureas as α-helix mimics, we designed a foldamer/peptide hybrid inhibitor of histone chaperone ASF1, a key regulator of chromatin dynamics. The crystal structure of its complex with ASF1 reveals a striking plasticity of the urea backbone, which adapts to the ASF1 surface to maintain the same binding interface. One additional benefit of generating ASF1 ligands with non-peptide oligourea segments is the resistance to proteolysis in human plasma which was highly improved compared to the cognate α-helical peptide. </b></p>

scholarly journals Computational design and experimental verification of a symmetric protein homodimer

2015 ◽  
Vol 112 (34) ◽  
pp. 10714-10719 ◽  
Author(s):  
Yun Mou ◽  
Po-Ssu Huang ◽  
Fang-Ciao Hsu ◽  
Shing-Jong Huang ◽  
Stephen L. Mayo
Keyword(s):  
Protein Interactions ◽  
De Novo ◽  
Computational Design ◽  
Atomic Level ◽  
Protein Interfaces ◽  
Unknown Structure ◽  
Α Helix ◽  
Distinct Features ◽  
Novel Protein

Homodimers are the most common type of protein assembly in nature and have distinct features compared with heterodimers and higher order oligomers. Understanding homodimer interactions at the atomic level is critical both for elucidating their biological mechanisms of action and for accurate modeling of complexes of unknown structure. Computation-based design of novel protein–protein interfaces can serve as a bottom-up method to further our understanding of protein interactions. Previous studies have demonstrated that the de novo design of homodimers can be achieved to atomic-level accuracy by β-strand assembly or through metal-mediated interactions. Here, we report the design and experimental characterization of a α-helix–mediated homodimer with C2 symmetry based on a monomeric Drosophila engrailed homeodomain scaffold. A solution NMR structure shows that the homodimer exhibits parallel helical packing similar to the design model. Because the mutations leading to dimer formation resulted in poor thermostability of the system, design success was facilitated by the introduction of independent thermostabilizing mutations into the scaffold. This two-step design approach, function and stabilization, is likely to be generally applicable, especially if the desired scaffold is of low thermostability.

scholarly journals Protein-assisted RNA fragment docking (RnaX) for modeling RNA–protein interactions using ModelX

2019 ◽  
Vol 116 (49) ◽  
pp. 24568-24573 ◽  
Author(s):  
Javier Delgado Blanco ◽  
Leandro G. Radusky ◽  
Damiano Cianferoni ◽  
Luis Serrano
Keyword(s):  
Conformational Changes ◽  
Protein Design ◽  
Protein Interactions ◽  
Rna Binding ◽  
Structural Information ◽  
Conformational Dynamics ◽  
Computational Cost ◽  
Regulation Of Transcription ◽  
Sequence Specificity ◽  
Protein Interfaces

RNA–protein interactions are crucial for such key biological processes as regulation of transcription, splicing, translation, and gene silencing, among many others. Knowing where an RNA molecule interacts with a target protein and/or engineering an RNA molecule to specifically bind to a protein could allow for rational interference with these cellular processes and the design of novel therapies. Here we present a robust RNA–protein fragment pair-based method, termed RnaX, to predict RNA-binding sites. This methodology, which is integrated into the ModelX tool suite (http://modelx.crg.es), takes advantage of the structural information present in all released RNA–protein complexes. This information is used to create an exhaustive database for docking and a statistical forcefield for fast discrimination of true backbone-compatible interactions. RnaX, together with the protein design forcefield FoldX, enables us to predict RNA–protein interfaces and, when sufficient crystallographic information is available, to reengineer the interface at the sequence-specificity level by mimicking those conformational changes that occur on protein and RNA mutagenesis. These results, obtained at just a fraction of the computational cost of methods that simulate conformational dynamics, open up perspectives for the engineering of RNA–protein interfaces.

scholarly journals NMR Spectroscopy of supramolecular chemistry on protein surfaces

2020 ◽  
Vol 16 ◽  
pp. 2505-2522
Author(s):  
Peter Bayer ◽  
Anja Matena ◽  
Christine Beuck
Keyword(s):  
Nmr Spectroscopy ◽  
Supramolecular Chemistry ◽  
Molecular Interactions ◽  
Protein Interactions ◽  
Atomic Resolution ◽  
Protein Protein Interactions ◽  
Protein Surfaces ◽  
Interaction Partners ◽  
Binding Pockets ◽  
Nmr Methods

As one of the few analytical methods that offer atomic resolution, NMR spectroscopy is a valuable tool to study the interaction of proteins with their interaction partners, both biomolecules and synthetic ligands. In recent years, the focus in chemistry has kept expanding from targeting small binding pockets in proteins to recognizing patches on protein surfaces, mostly via supramolecular chemistry, with the goal to modulate protein–protein interactions. Here we present NMR methods that have been applied to characterize these molecular interactions and discuss the challenges of this endeavor.

scholarly journals Elucidating the druggable interface of protein−protein interactions using fragment docking and coevolutionary analysis

2016 ◽  
Vol 113 (50) ◽  
pp. E8051-E8058 ◽  
Author(s):  
Fang Bai ◽  
Faruck Morcos ◽  
Ryan R. Cheng ◽  
Hualiang Jiang ◽  
José N. Onuchic
Keyword(s):  
Drug Design ◽  
Protein Interactions ◽  
Binding Sites ◽  
Hot Spots ◽  
Therapeutic Agents ◽  
Molecular Probes ◽  
Therapeutic Drug ◽  
Protein Protein Interactions ◽  
Protein Surface ◽  
Fragment Docking

Protein−protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein−protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

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