scholarly journals Strong Ligand-Protein Interactions Derived from Diffuse Ligand Interactions with Loose Binding Sites

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Lorraine Marsh
Keyword(s):  
Ligand Binding ◽  
Protein Interactions ◽  
Computational Method ◽  
Test Cases ◽  
Carrier Proteins ◽  
Multidrug Transporters ◽  
Fine Grained ◽  
Ligand Interactions ◽  
Protein Binding Region ◽  
Multiple Conformations

Many systems in biology rely on binding of ligands to target proteins in a single high-affinity conformation with a favorableΔG. Alternatively, interactions of ligands with protein regions that allow diffuse binding, distributed over multiple sites and conformations, can exhibit favorableΔGbecause of their higher entropy. Diffuse binding may be biologically important for multidrug transporters and carrier proteins. A fine-grained computational method for numerical integration of total bindingΔGarising from diffuse regional interaction of a ligand in multiple conformations using a Markov Chain Monte Carlo (MCMC) approach is presented. This method yields a metric that quantifies the influence on overall ligand affinity of ligand binding to multiple, distinct sites within a protein binding region. This metric is essentially a measure of dispersion in equilibrium ligand binding and depends on both the number of potential sites of interaction and the distribution of their individual predicted affinities. Analysis of test cases indicates that, for some ligand/protein pairs involving transporters and carrier proteins, diffuse binding contributes greatly to total affinity, whereas in other cases the influence is modest. This approach may be useful for studying situations where “nonspecific” interactions contribute to biological function.

scholarly journals Evolution of (p)ppGpp-HPRT regulation through diversification of an allosteric oligomeric interaction

2019 ◽  
Author(s):  
Brent W. Anderson ◽  
Kuanqing Liu ◽  
Christine Wolak ◽  
Katarzyna Dubiel ◽  
Kenneth A. Satyshur ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Binding Site ◽  
Protein Interactions ◽  
Binding Motif ◽  
Protein Ligand Interactions ◽  
Protein Interfaces ◽  
Ligand Interactions ◽  
Binding Residues ◽  
The Common ◽  
Ligand Regulation

ABSTRACTThe signaling ligand (p)ppGpp binds diverse targets across bacteria, yet the mechanistic and evolutionary basis underlying these ligand-protein interactions remains poorly understood. Here we identify a novel (p)ppGpp binding motif in the enzyme HPRT, where (p)ppGpp shares identical binding residues for PRPP and nucleobase substrates to regulate purine homeostasis. Intriguingly, HPRTs across species share the conserved binding site yet strongly differ in ligand binding, from strong inhibition by basal (p)ppGpp levels to weak regulation at induced concentrations. Surprisingly, strong ligand binding requires an HPRT dimer-dimer interaction that allosterically opens the (p)ppGpp pocket. This dimer-dimer interaction is absent in the common ancestor but evolved to favor (p)ppGpp binding in the vast majority of bacteria. We propose that the evolutionary plasticity of oligomeric interfaces enables allosteric adjustment of ligand regulation, bypassing constraints of the ligand binding site. Since most ligands bind near protein-protein interfaces, this principle likely extends to other protein-ligand interactions.

Prediction of Disease Comorbidity Using HeteSim Scores based on Multiple Heterogeneous Networks

2019 ◽  
Vol 19 (4) ◽  
pp. 232-241 ◽  
Author(s):  
Xuegong Chen ◽  
Wanwan Shi ◽  
Lei Deng
Keyword(s):  
Protein Interactions ◽  
Experimental Studies ◽  
Treatment Strategies ◽  
Computational Method ◽  
Biological Information ◽  
Support Vector ◽  
Protein Protein Interactions ◽  
Efficient Treatment ◽  
Disease Associations ◽  
Previous State

Background: Accumulating experimental studies have indicated that disease comorbidity causes additional pain to patients and leads to the failure of standard treatments compared to patients who have a single disease. Therefore, accurate prediction of potential comorbidity is essential to design more efficient treatment strategies. However, only a few disease comorbidities have been discovered in the clinic. Objective: In this work, we propose PCHS, an effective computational method for predicting disease comorbidity. Materials and Methods: We utilized the HeteSim measure to calculate the relatedness score for different disease pairs in the global heterogeneous network, which integrates six networks based on biological information, including disease-disease associations, drug-drug interactions, protein-protein interactions and associations among them. We built the prediction model using the Support Vector Machine (SVM) based on the HeteSim scores. Results and Conclusion: The results showed that PCHS performed significantly better than previous state-of-the-art approaches and achieved an AUC score of 0.90 in 10-fold cross-validation. Furthermore, some of our predictions have been verified in literatures, indicating the effectiveness of our method.

scholarly journals Affinity Selection in Germinal Centers: Cautionary Tales and New Opportunities

Cells ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1040
Author(s):  
Jose Faro ◽  
Mario Castro
Keyword(s):  
T Cell ◽  
B Cell ◽  
Cell Receptor ◽  
Future Research ◽  
Mathematical Framework ◽  
Immune Synapse ◽  
Cell Receptors ◽  
3 Dimensional ◽  
Fine Grained ◽  
Ligand Interactions

Our current quantitative knowledge of the kinetics of antibody-mediated immunity is partly based on idealized experiments throughout the last decades. However, new experimental techniques often render contradictory quantitative outcomes that shake previously uncontroversial assumptions. This has been the case in the field of T-cell receptors, where recent techniques for measuring the 2-dimensional rate constants of T-cell receptor–ligand interactions exposed results contradictory to those obtained with techniques measuring 3-dimensional interactions. Recently, we have developed a mathematical framework to rationalize those discrepancies, focusing on the proper fine-grained description of the underlying kinetic steps involved in the immune synapse. In this perspective article, we apply this approach to unveil potential blind spots in the case of B-cell receptors (BCR) and to rethink the interactions between B cells and follicular dendritic cells (FDC) during the germinal center (GC) reaction. Also, we elaborate on the concept of “catch bonds” and on the recent observations that B-cell synapses retract and pull antigen generating a “retracting force”, and propose some testable predictions that can lead to future research.

scholarly journals Aryl hydrocarbon receptor (AHR) in the cnidarian Nematostella vectensis: comparative expression, protein interactions, and ligand binding

2013 ◽  
Vol 224 (1) ◽  
pp. 13-24 ◽  
Author(s):  
Adam M. Reitzel ◽  
Yale J. Passamaneck ◽  
Sibel I. Karchner ◽  
Diana G. Franks ◽  
Mark Q. Martindale ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Aryl Hydrocarbon Receptor ◽  
Protein Interactions ◽  
Nematostella Vectensis ◽  
Aryl Hydrocarbon ◽  
Cnidarian Nematostella Vectensis

Conformational dynamics and thermodynamics of protein–ligand binding studied by NMR relaxation

2012 ◽  
Vol 40 (2) ◽  
pp. 419-423 ◽  
Author(s):  
Mikael Akke
Keyword(s):  
Ligand Binding ◽  
Bound States ◽  
Conformational Dynamics ◽  
Nmr Relaxation ◽  
Titration Calorimetry ◽  
Conformational Entropy ◽  
Chain Order ◽  
Ligand Interactions ◽  
Galectin 3 ◽  
Relaxation Experiments

Protein conformational dynamics can be critical for ligand binding in two ways that relate to kinetics and thermodynamics respectively. First, conformational transitions between different substates can control access to the binding site (kinetics). Secondly, differences between free and ligand-bound states in their conformational fluctuations contribute to the entropy of ligand binding (thermodynamics). In the present paper, I focus on the second topic, summarizing our recent results on the role of conformational entropy in ligand binding to Gal3C (the carbohydrate-recognition domain of galectin-3). NMR relaxation experiments provide a unique probe of conformational entropy by characterizing bond-vector fluctuations at atomic resolution. By monitoring differences between the free and ligand-bound states in their backbone and side chain order parameters, we have estimated the contributions from conformational entropy to the free energy of binding. Overall, the conformational entropy of Gal3C increases upon ligand binding, thereby contributing favourably to the binding affinity. Comparisons with the results from isothermal titration calorimetry indicate that the conformational entropy is comparable in magnitude to the enthalpy of binding. Furthermore, there are significant differences in the dynamic response to binding of different ligands, despite the fact that the protein structure is virtually identical in the different protein–ligand complexes. Thus both affinity and specificity of ligand binding to Gal3C appear to depend in part on subtle differences in the conformational fluctuations that reflect the complex interplay between structure, dynamics and ligand interactions.

scholarly journals GA-Based Optimization Method for Mobile Crane Repositioning Route Planning

2021 ◽  
Vol 11 (13) ◽  
pp. 6010
Author(s):  
Han-Seong Gwak ◽  
Hong-Chul Lee ◽  
Byoung-Yoon Choi ◽  
Yirong Mi
Keyword(s):  
Operating Time ◽  
Route Planning ◽  
Optimal Solution ◽  
Optimization Method ◽  
Computational Method ◽  
Test Cases ◽  
Construction Sites ◽  
Productivity Improvement ◽  
Planning Optimization ◽  
Mobile Crane

Mobile cranes have been used extensively as essential equipment at construction sites. The productivity improvement of the mobile crane affects the overall productivity of the construction project. Hence, various studies have been conducted regarding mobile crane operation planning. However, studies on solving RCP (the repositioning mobile crane problem) are insufficient. This article presents a mobile crane reposition route planning optimization method (RPOS) that minimizes the total operating time of mobile crane. It converts the construction site into a mathematical model, determines feasible locations of the mobile crane, and identifies near-global optimal solution (s) (i.e., the placement point sequences of mobile crane) by implementing genetic algorithm and dijkstra’s algorithm. The study is of value to practitioners because RPOS provides an easy-to-use computerized tool that reduces the lengthy computations relative to data processing and Genetic Algorithms (GAs). Test cases verify the validity of the computational method.

Sloshing in Rectangular and Cylindrical Tanks

2002 ◽  
Vol 46 (03) ◽  
pp. 186-200 ◽  
Author(s):  
Pierre C. Sames ◽  
Delphine Marcouly ◽  
Thomas E. Schellin
Keyword(s):  
Free Surface ◽  
Finite Volume ◽  
Temporal Evolution ◽  
Numerical Study ◽  
Computational Method ◽  
Test Cases ◽  
Grid Refinement ◽  
Cylindrical Tank ◽  
Excitation Period ◽  
Cylindrical Tanks

To validate an existing finite volume computational method, featuring a novel scheme to capture the temporal evolution of the free surface, fluid motions in partially filled tanks were simulated. The purpose was to compare computational and experimental results for test cases where measurements were available. Investigations comprised sloshing in a rectangular tank with a baffle at 60% filling level and in a cylindrical tank at 50% filling level. The numerical study started with examining effects of systematic grid refinement and concluded with examining effects of three-dimensionality and effects of variation of excitation period and amplitude. Predicted time traces of pressures and forces compared favorably with measurements.

Structural studies of the phosphatidylinositol 3-kinase (PI3K) SH3 domain in complex with a peptide ligand: role of the anchor residue in ligand binding

2010 ◽  
Vol 391 (1) ◽  
Author(s):  
Renu Batra-Safferling ◽  
Joachim Granzin ◽  
Susanne Mödder ◽  
Silke Hoffmann ◽  
Dieter Willbold
Keyword(s):  
Crystal Structure ◽  
Ligand Binding ◽  
Protein Interactions ◽  
Intracellular Signaling ◽  
Sh3 Domain ◽  
Peptide Ligand ◽  
Type I ◽  
Phosphatidylinositol 3 Kinase ◽  
Anchor Residue ◽  
Phosphatidylinositol 3

Abstract Src homology 3 (SH3) domains are mediators of protein-protein interactions. They comprise approximately 60 amino acid residues and are found in many intracellular signaling proteins. Here, we present the crystal structure of the SH3 domain from phosphatidylinositol 3-kinase (PI3K) in complex with the 12-residue proline-rich peptide PD1R (HSKRPLPPLPSL). The crystal structure of the PI3K SH3-PD1R complex at a resolution of 1.7 Å reveals type I ligand orientation of the bound peptide with an extended conformation where the central portion forms a left-handed type II polyproline (PPII) helix. The overall structure of the SH3 domain shows minimal changes on ligand binding. In addition, we also attempted crystallization with another peptide ligand (PD1) where the residue at anchor position P-3 is a tyrosine. The crystals obtained did not contain the PD1 ligand; instead, the ligand binding site is partially occupied by residues Arg18 and Trp55 from the symmetry-related PI3K SH3 molecule. Considering these crystal structures of PI3K SH3 together with published reports, we provide a comparative analysis of protein-ligand interactions that has helped us identify the individual residues which play an important role in defining target specificity.

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