scholarly journals The Identification of Metal Ion Ligand-Binding Residues by Adding the Reclassified Relative Solvent Accessibility

2020 ◽  
Vol 11 ◽  
Author(s):  
Xiuzhen Hu ◽  
Zhenxing Feng ◽  
Xiaojin Zhang ◽  
Liu Liu ◽  
Shan Wang
Keyword(s):  
Ligand Binding ◽  
Metal Ion ◽  
Solvent Accessibility ◽  
Relative Solvent Accessibility ◽  
Binding Residues

Comprehensive review and empirical analysis of hallmarks of DNA-, RNA- and protein-binding residues in protein chains

2017 ◽  
Vol 20 (4) ◽  
pp. 1250-1268 ◽  
Author(s):  
Jian Zhang ◽  
Zhiqiang Ma ◽  
Lukasz Kurgan
Keyword(s):  
Nucleic Acid ◽  
Ligand Binding ◽  
Protein Binding ◽  
Large Scale ◽  
Rna Binding ◽  
Solvent Accessibility ◽  
Residue Level ◽  
Relative Solvent Accessibility ◽  
Data Set ◽  
Binding Residues

Abstract Proteins interact with a variety of molecules including proteins and nucleic acids. We review a comprehensive collection of over 50 studies that analyze and/or predict these interactions. While majority of these studies address either solely protein–DNA or protein–RNA binding, only a few have a wider scope that covers both protein–protein and protein–nucleic acid binding. Our analysis reveals that binding residues are typically characterized with three hallmarks: relative solvent accessibility (RSA), evolutionary conservation and propensity of amino acids (AAs) for binding. Motivated by drawbacks of the prior studies, we perform a large-scale analysis to quantify and contrast the three hallmarks for residues that bind DNA-, RNA-, protein- and (for the first time) multi-ligand-binding residues that interact with DNA and proteins, and with RNA and proteins. Results generated on a well-annotated data set of over 23 000 proteins show that conservation of binding residues is higher for nucleic acid- than protein-binding residues. Multi-ligand-binding residues are more conserved and have higher RSA than single-ligand-binding residues. We empirically show that each hallmark discriminates between binding and nonbinding residues, even predicted RSA, and that combining them improves discriminatory power for each of the five types of interactions. Linear scoring functions that combine these hallmarks offer good predictive performance of residue-level propensity for binding and provide intuitive interpretation of predictions. Better understanding of these residue-level interactions will facilitate development of methods that accurately predict binding in the exponentially growing databases of protein sequences.

scholarly journals Recognition of Metal Ion Ligand-Binding Residues by Adding Correlation Features and Propensity Factors

2022 ◽  
Vol 12 ◽  
Author(s):  
Shuang Xu ◽  
Xiuzhen Hu ◽  
Zhenxing Feng ◽  
Jing Pang ◽  
Kai Sun ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Metal Ion ◽  
Biological Function ◽  
Structural Information ◽  
Basic Feature ◽  
Improved Method ◽  
Binding Residue ◽  
Protein Functions ◽  
Binding Residues ◽  
Correlation Information

The realization of many protein functions is inseparable from the interaction with ligands; in particular, the combination of protein and metal ion ligands performs an important biological function. Currently, it is a challenging work to identify the metal ion ligand-binding residues accurately by computational approaches. In this study, we proposed an improved method to predict the binding residues of 10 metal ion ligands (Zn2+, Cu2+, Fe2+, Fe3+, Co2+, Mn2+, Ca2+, Mg2+, Na+, and K+). Based on the basic feature parameters of amino acids, and physicochemical and predicted structural information, we added another two features of amino acid correlation information and binding residue propensity factors. With the optimized parameters, we used the GBM algorithm to predict metal ion ligand-binding residues. In the obtained results, the Sn and MCC values were over 10.17% and 0.297, respectively. Besides, the Sn and MCC values of transition metals were higher than 34.46% and 0.564, respectively. In order to test the validity of our model, another method (Random Forest) was also used in comparison. The better results of this work indicated that the proposed method would be a valuable tool to predict metal ion ligand-binding residues.

Computational Biology Tools for Identifying Specific Ligand Binding Residues for Novel Agrochemical and Drug Design

2015 ◽  
Vol 16 (8) ◽  
pp. 701-717 ◽  
Author(s):  
Izabella Pena Neshich ◽  
Leticia Nishimura ◽  
Fabio de Moraes ◽  
Jose Salim ◽  
Fabian Villalta-Romero ◽  
...  
Keyword(s):  
Drug Design ◽  
Computational Biology ◽  
Ligand Binding ◽  
Binding Residues ◽  
Specific Ligand

scholarly journals Bridging the gap between structure and kinetics of human SGLT1

2012 ◽  
Vol 302 (9) ◽  
pp. C1293-C1305 ◽  
Author(s):  
Monica Sala-Rabanal ◽  
Bruce A. Hirayama ◽  
Donald D. F. Loo ◽  
Vincent Chaptal ◽  
Jeff Abramson ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Binding Site ◽  
Sugar Transport ◽  
Gene Families ◽  
Structural Studies ◽  
Sugar Binding ◽  
Substituted Cysteine Accessibility ◽  
Biochemical Assays ◽  
Functional Consequences ◽  
Binding Residues

The Na+-glucose cotransporter hSGLT1 is a member of a class of membrane proteins that harness Na+ electrochemical gradients to drive uphill solute transport. Although hSGLT1 belongs to one gene family (SLC5), recent structural studies of bacterial Na+ cotransporters have shown that Na+ transporters in different gene families have the same structural fold. We have constructed homology models of hSGLT1 in two conformations, the inward-facing occluded (based on vSGLT) and the outward open conformations (based on Mhp1), mutated in turn each of the conserved gates and ligand binding residues, expressed the SGLT1 mutants in Xenopus oocytes, and determined the functional consequences using biophysical and biochemical assays. The results establish that mutating the ligand binding residues produces profound changes in the ligand affinity (the half-saturation concentration, K0.5); e.g., mutating sugar binding residues increases the glucose K0.5 by up to three orders of magnitude. Mutation of the external gate residues increases the Na+ to sugar transport stoichiometry, demonstrating that these residues are critical for efficient cotransport. The changes in phlorizin inhibition constant ( Ki) are proportional to the changes in sugar K0.5, except in the case of F101C, where phlorizin Ki increases by orders of magnitude without a change in glucose K0.5. We conclude that glucose and phlorizin occupy the same binding site and that F101 is involved in binding to the phloretin group of the inhibitor. Substituted-cysteine accessibility methods show that the cysteine residues at the position of the gates and sugar binding site are largely accessible only to external hydrophilic methanethiosulfonate reagents in the presence of external Na+, demonstrating that the external sugar (and phlorizin) binding vestibule is opened by the presence of external Na+ and closes after the binding of sugar and phlorizin. Overall, the present results provide a bridge between kinetics and structural studies of cotransporters.

scholarly journals SphereCon—a method for precise estimation of residue relative solvent accessible area from limited structural information

2020 ◽  
Vol 36 (11) ◽  
pp. 3372-3378
Author(s):  
Alexander Gress ◽  
Olga V Kalinina
Keyword(s):  
Protein Function ◽  
Structural Information ◽  
Solvent Accessibility ◽  
Three Dimensional ◽  
Structural Data ◽  
Supplementary Information ◽  
Dimensional Structure ◽  
Relative Solvent Accessibility ◽  
Precise Measure ◽  
The Impact

Abstract Motivation In proteins, solvent accessibility of individual residues is a factor contributing to their importance for protein function and stability. Hence one might wish to calculate solvent accessibility in order to predict the impact of mutations, their pathogenicity and for other biomedical applications. A direct computation of solvent accessibility is only possible if all atoms of a protein three-dimensional structure are reliably resolved. Results We present SphereCon, a new precise measure that can estimate residue relative solvent accessibility (RSA) from limited data. The measure is based on calculating the volume of intersection of a sphere with a cone cut out in the direction opposite of the residue with surrounding atoms. We propose a method for estimating the position and volume of residue atoms in cases when they are not known from the structure, or when the structural data are unreliable or missing. We show that in cases of reliable input structures, SphereCon correlates almost perfectly with the directly computed RSA, and outperforms other previously suggested indirect methods. Moreover, SphereCon is the only measure that yields accurate results when the identities of amino acids are unknown. A significant novel feature of SphereCon is that it can estimate RSA from inter-residue distance and contact matrices, without any information about the actual atom coordinates. Availability and implementation https://github.com/kalininalab/spherecon. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

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