Determination of an empirical energy function for protein conformational analysis by energy embedding
It is quite easy to propose an empirical potential for conformational analysis such that given crystal structures lie near local minima. What is much more difficult, is to devise a function such that the native structure lies near a relatively deep local minimum, at least in some neighborhood of the...
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Veröffentlicht in: | Journal of computational chemistry 1987-10, Vol.8 (7), p.972-981 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | It is quite easy to propose an empirical potential for conformational analysis such that given crystal structures lie near local minima. What is much more difficult, is to devise a function such that the native structure lies near a relatively deep local minimum, at least in some neighborhood of the native in conformation space. An algorithm is presented for finding such a potential acting on proteins where each amino acid residue is represented by a single point. When the given structure is either an α‐helical, β‐strand, or hairpin bend segment of pancreatic trypsin inhibitor, the resulting potential function in each case possesses a deep minimum within 0.10 Å of the native conformation. The improved energy embedding algorithm locates a marginally better minimum in each case only 0.1–1.3 Å away from the respective native state. In other words, this potential function guides a conformational search toward structures very close to the native over a wide range of conformation space. |
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ISSN: | 0192-8651 1096-987X |
DOI: | 10.1002/jcc.540080707 |