Computer assisted simulations and molecular graphics methods in molecular design 2. Proteinases and receptor and transport proteins

Stamato, F. M. L. G.; Paulino, Margot; Garratt, R.C.; Soares, Cláudio M.; Tapia, O.

doi:10.1007/bf01019470

Cited by 3 publications

(1 citation statement)

References 148 publications

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“…These ideas has gone a long way since then, and the basic concept of the calculation of FD magnitude of the “candidate zones” for protein–protein or protein–ligand interactions was established (Arteca and Mezey, ; Bryant et al ., ) in the context of characterization of surface complexity. A comprehensive (but old) review (Stamato et al ., ) describes the influence of the Aqvist–Tapia work on the then contemporary protein surface studies. A recent work (Bera and Ray, ), banking on the work of Aqvist and Tapia () and employing SAFD methodology (Pettit and Bowie, ), has investigated interfaces of obligate and nonobligate protein–protein complexes.…”

Section: An Overview Of Successful Application Of Protein Surface Framentioning

confidence: 99%

Fractal nature of protein surface roughness: a note on quantification of change of surface roughness in active sites, before and after binding

Banerji

Navare²

2013

J of Molecular Recognition

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Year 2010 marked the 25th year since we came to know that roughness of a protein surface has fractal symmetry. Ever since the publication of Lewis and Rees' paper, hundreds of works from a spectrum of perspectives have established that fractal dimension (FD) can be considered as a reliable marker that describes roughness of protein surface objectively. In this article, we introduce readers to the fundamentals of fractals and present categorical biophysical and geometrical reasons as to why FD-based constructs can describe protein surface roughness more accurately. We then review the commonality (and the lack of it) between numerous approaches that have attempted to investigate protein surface with fractal measures, before exploring the patterns in the results that they have produced. Apart from presenting the genealogy of approaches and results, we present an analysis that quantifies the difference in surface roughness in stretches of protein surface containing the active site, before and after binding to ligands, to underline the utility of FD-based measures further. It has been found that surface stretches containing the active site, in general, undergo a significant increment in its roughness after binding. After presenting the entire repertoire of FD-based surface roughness studies, we talk about two yet-unexplored problems where application of FD-based techniques can help in deciphering underlying patterns of surface interactions. Finally, we list the limitations of FD-based constructs and put down several precautions that one must take while working with them.

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Section: An Overview Of Successful Application Of Protein Surface Framentioning

confidence: 99%

Fractal nature of protein surface roughness: a note on quantification of change of surface roughness in active sites, before and after binding

Banerji

Navare²

2013

J of Molecular Recognition

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Modelling of H2 antagonists and tridimensional modelling of H2 receptor interactions. Part 2

Olea‐Azar

Parra-Mouchet

Lunt

1996

Mol Eng

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The interactions between the H2 antagonists cimetidine, ranitidine and famotidine with a basic molecular model for the histamine H2 receptor have been analyzed. The calculated potential energies of the antagonist-H2 receptor complexes follow an order consistent with the published binding data, indicating that famotidine is the best H2 receptor ligand. Comparison with the interactions found for histamine and this H2 receptor model suggests that the protonated imidazole moiety of cimetidine, the dimethylammonio moiety of protonated ranitidine and the protonated guanidinyl moiety of famotidine are bioisosteric with the protonated aliphatic amine group of histamine. Asp 98 in helix 3 appears to be the main residue for antagonist recognition, but some residues in helix 5 may be involved, apparently by serving to guide the antagonist into the binding pocket.

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A molecular modeling study of the urease active site

Manunza

Deiana

Pintore

et al. 1997

Journal of Molecular Structure: THEOCHEM

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Computer assisted simulations and molecular graphics methods in molecular design 2. Proteinases and receptor and transport proteins

Cited by 3 publications

References 148 publications

Fractal nature of protein surface roughness: a note on quantification of change of surface roughness in active sites, before and after binding

Fractal nature of protein surface roughness: a note on quantification of change of surface roughness in active sites, before and after binding

Modelling of H2 antagonists and tridimensional modelling of H2 receptor interactions. Part 2

A molecular modeling study of the urease active site

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