Premium
Conformational analysis by scaled energy embedding
Author(s) -
Crippen Gordon M.
Publication year - 1984
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.540050607
Subject(s) - embedding , extension (predicate logic) , energy (signal processing) , energy minimization , value (mathematics) , geometric analysis , computer science , mathematics , statistical physics , algorithm , physics , mathematical analysis , quantum mechanics , artificial intelligence , differential algebraic equation , ordinary differential equation , programming language , differential equation , machine learning
Abstract Distance geometry has been used for some years to find conformations of molecules consistent with given bounds on the interatomic distances. A recent extension of the method, called energy embedding, enforces the geometric constraints as before, but also biases the results toward low‐energy structures. Now a significant improvement on energy embedding is presented, which is less dependent on local optimization for satisfying the geometric constraints. Tests on very small systems with well understood energy functions show that the global minimum energy value is often attained, and geometric constraints are always satisfied.