An iterative method for extracting energy-like quantities from protein structures.

By Paul D. Thomas, Ken A. Dill. 1996

We present a method (ENERGI) for extracting energy-like quantities from a data base of protein structures. In this paper, we use the method to generate pairwise additive amino acid "energy" scores. These scores are obtained by iteration until they correctly discriminate a set of known protein folds from decoy conformations. The method succeeds in lattice model tests and in the gapless threading problem as defined by Maiorov and Crippen [Maiorov, V. N. & Crippen, G. M. (1992) J. Mol. Biol. 227, 876-888]. A more challenging test of threading a larger set of test proteins derived from the representative set of Hobohm and Sander [Hobohm, U. & Sander, C. (1994) Protein Sci. 3, 522-524] is used as a "workbench" for exploring how the ENERGI scores depend on their parameter sets.

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Citations in the corpus

IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding (2018, methodology): “This approach utilizes a low-resolution statistical potential to characterize the tendencies of amino acid pairs to form contacts, observed in a collection of globular protein structures (40).”
Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized (2010, methodology): “Although iterative application of the inverse Boltzmann formula has been described before [24,35,58,59], its theoretical justification, optimal definition of the reference state and scope remained unclear.”
The scoring of poses in protein-protein docking: current capabilities and future directions (2013, unknown): “CP_TD [163] r”
Contact Potential for Structure Prediction of Proteins and Protein Complexes from Potts Model. (2018, background): “A different strategy for deriving statistical potentials is based on optimization of the energy parameters to maximize recognition of the native structure from a set of decoys (30–32).”
Statistical potential for assessment and prediction of protein structures (2006, unknown): “1995; Thomas and Dill 1996b).”
Advances and Challenges in Protein-Ligand Docking (2010, background): “The principle behind knowledge-based scoring functions is the potential of mean force [129], which is defined by the inverse Boltzmann relation [130–133]”
New statistical potential for quality assessment of protein models and a survey of energy functions (2010, background): “…use C a , C b atoms or side chain centroids and are usually based on the 20 naturally occurring amino acids [2,15,24,25], although both reduced [7,26,27] and extended [28,29] amino acid alphabets were explored, where the extended alphabet further classifies each residue according to the possible…”
Determination of domain structure of proteins from X-ray solution scattering. (2001, background): “A C ␣ chain was folded accounting for the primary and secondary structure, backbone angles distribution (Kleywegt, 1997), hydrophobicity (Huang et al., 1995), and interaction potentials between residues (Miyazawa and Jernigan, 1999; Thomas and Dill, 1996).”