Energetics of Base Pairs in B-DNA in Solution:  An Appraisal of Potential Functions and Dielectric Treatments

Arora, Nidhi; Jayaram, B.

doi:10.1021/jp9813692

Cited by 58 publications

(48 citation statements)

References 70 publications

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“…The force field we have selected is that of the assisted model building with energy refinement (AMBER) (Case et al 2005). AMBER has an established use in nucleic acid modeling to determine and compare the free energies of base pairs (Arora and Jayaram 1998;Giudice and Lavery 2003;Giudice et al 2003;Sanbonmatsu and Joseph 2003;Varnai et al 2004;Mathews and Case 2006;Rhodes et al 2006;Perez et al 2008). …”

Section: Resultsmentioning

confidence: 99%

Free energy calculation of modified base-pair formation in explicit solvent: A predictive model

Vendeix

Munoz²,

Agris³

2009

RNA

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The maturation of RNAs includes site-specific post-transcriptional modifications that contribute significantly to hydrogen bond formation within RNA and between different RNAs, especially in formation of mismatch base pairs. Thus, an understanding of the geometry and strength of the base-pairing of modified ribonucleoside 59-monophosphates, previously not defined, is applicable to investigations of RNA structure and function and of the design of novel RNAs. The geometry and free energies of base-pairings were calculated in aqueous solution under neutral conditions with AMBER force fields and molecular dynamics simulations (MDSs). For example, unmodified uridines were observed to bind to uridine and cytidine with significant stability, but the ribose C19-C19 distances were far short (;8.9 Å ) of distances observed for canonical A-form RNA helices. In contrast, 5-oxyacetic acid uridine, known to bind adenosine, wobble to guanosine, and form mismatch base pairs with uridine and cytidine, bound adenosine and guanosine with geometries and energies comparable to an unmodified uridine. However, the 5-oxyacetic acid uridine base paired to uridine and cytidine with a C19-C19 distance comparable to that of an A-form helix, ;11 Å , when a H 2 O molecule migrated between and stably hydrogen bonded to both bases. Even in formation of canonical base pairs, intermediate structures with a second energy minimum consisted of transient H 2 O molecules forming hydrogen bonded bridges between the two bases. Thus, MDS is predictive of the effects of modifications, H 2 O molecule intervention in the formation of base-pair geometry, and energies that are important for native RNA structure and function.

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Section: Resultsmentioning

confidence: 99%

Free energy calculation of modified base-pair formation in explicit solvent: A predictive model

Vendeix

Munoz²,

Agris³

2009

RNA

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“…The scoring function employed considers the non‐bonded energy of a protein–ligand complex as a sum of three energy terms – electrostatic, van der Waals and hydrophobic, termed here as Model I

E = \sum E_{normalel} + E_{normalvdw} + E_{normalhpb} .

Here, E is the total non‐bonded energy, E el is the electrostatic contribution to the energy, E vdw is the van der Waal term, E hpb is the hydrophobic contribution and the summation runs over all the atoms of the protein–ligand complex. Details of the function and individual terms are provided elsewhere ([28–32] and references therein). In a nutshell, the electrostatic contribution to the interaction energy is computed via Coulomb's law with a sigmoidal dielectric function.…”

Section: Theory and Methodologymentioning

confidence: 99%

An all atom energy based computational protocol for predicting binding affinities of protein–ligand complexes

Jain

Jayaram

2005

FEBS Letters

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We report here a computationally fast protocol for predicting binding affinities of non-metallo protein-ligand complexes. The protocol builds in an all atom energy based empirical scoring function comprising electrostatics, van der Waals, hydrophobicity and loss of conformational entropy of protein side chains upon ligand binding. The method is designed to ensure transferability across diverse systems and has been validated on a heterogenous dataset of 161 complexes consisting of 55 unique protein targets. The scoring function trained on a dataset of 61 complexes yielded a correlation of r = 0.92 for the predicted binding free energies against the experimental binding affinities. Model validation and parameter analysis studies ensure the predictive ability of the scoring function. When tested on the remaining 100 protein-ligand complexes a correlation of r = 0.92 was recovered. The high correlation obtained underscores the potential applicability of the methodology in drug design endeavors. The scoring function has been web enabled at www.scfbio-iitd.res.in/software/drugdesign/bappl.jsp as binding affinity prediction of protein-ligand (BAPPL) server.

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“…[46] After investigating the sensitivity to force field choice of the results on a heterogeneous dataset of 161 complexes, an empirical scoring function consisting of 25 independent variables (electrostatic, van der Waals, loss of conformational entropy and atom types for hydrophobicity) was developed. [43,44] NsLTP-LPC complexes are omitted because BAPPL failed to give binding energies for all of them (note that this lipid is the only positively charged ligand and all nsLTPs have net positive charge).…”

Section: Estimates Of Binding Free Energiesmentioning

confidence: 99%

“…It must be mentioned that neither experimental binding affinity data exist in the BindingDB (www.bindingdb.org) database [54] nor, to the best of our knowledge, any other binding affinities had been reported before for nsLTP-lipid complexes. We obtained estimates of DG bind with the BAPPL (Binding Affinity Prediction of Protein-Ligand) approach, [43,44] a computationally fast procedure for predicting binding affinities of nonmetal protein ligand complexes. This method is based upon an all- ) and p-values of observed solvation free energy gain upon formation of the interface (P int ) for nsLTP-lipid complexes.…”

Section: Estimates Of Binding Energies For Nsltps-lipid Complexesmentioning

confidence: 99%

Computational study of ligand binding in lipid transfer proteins: Structures, interfaces, and free energies of protein‐lipid complexes

et al. 2012

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Plant nonspecific lipid transfer proteins (nsLTPs) bind a wide variety of lipids, which allows them to perform disparate functions. Recent reports on their multifunctionality in plant growth processes have posed new questions on the versatile binding abilities of these proteins. The lack of binding specificity has been customarily explained in qualitative terms on the basis of a supposed structural flexibility and nonspecificity of hydrophobic protein-ligand interactions. We present here a computational study of protein-ligand complexes formed between five nsLTPs and seven lipids bound in two different ways in every receptor protein. After optimizing geometries in molecular dynamics calculations, we computed PoissonBoltzmann electrostatic potentials, solvation energies, properties of the protein-ligand interfaces, and estimates of binding free energies of the resulting complexes. Our results provide the first quantitative information on the ligand abilities of nsLTPs, shed new light into protein-lipid interactions, and reveal new features which supplement commonly held assumptions on their lack of binding specificity.

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Energetics of Base Pairs in B-DNA in Solution: An Appraisal of Potential Functions and Dielectric Treatments

Cited by 58 publications

References 70 publications

Free energy calculation of modified base-pair formation in explicit solvent: A predictive model

Free energy calculation of modified base-pair formation in explicit solvent: A predictive model

An all atom energy based computational protocol for predicting binding affinities of protein–ligand complexes

Computational study of ligand binding in lipid transfer proteins: Structures, interfaces, and free energies of protein‐lipid complexes

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