Evaluating conformational free energies: The colony energy and its application to the problem of loop prediction

By Zhexin Xiang, C. Soto, Barry Honig. 2002

370 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology

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Citations in the corpus

High resolution comparative modeling with RosettaCM (2013, background): “These structures are then clustered, and the center of the largest cluster (where each model is weighted such that low-energy models have highest weight(Xiang et al., 2002)) is selected as the top model.”
Fast Protein Loop Sampling and Structure Prediction Using Distance-Guided Sequential Chain-Growth Monte Carlo Method (2014, positive): “Compared to the Direct Tweak sampling method, DISGRO has improved Rmin for 12-residue loops (1:28 Å vs 1:48 Å), slightly improved Rmin for 11-residue loops (1:19 Å vs 1:20 Å) and inferior Rmin for 8-residue loops (0:80 Å vs 0:69 Å).”
ModLoop: automated modeling of loops in protein structures (2003, background): “Consequently, the accuracy of loop modeling (Oliva et al., 1997; Fine et al., 1986; Xiang et al., 2002; van Vlijmen and Karplus, 1997; Rapp and Friesner, 1999; Martin and Thornton, 1996) is a major factor determining the usefulness of comparative protein structure models”
Principles of Flexible Protein-Protein Docking (2008, background): “Some docking methods93 simply ignore flexible loops during the docking and rebuild them afterwards in a loop modeling5,95 step.”
ASTRO-FOLD: a combinatorial and global optimization framework for Ab initio prediction of three-dimensional structures of proteins from the amino acid sequence. (2003, background): “refinement, such as loop closure and side-chain refinement, remain a challenge (Fiser et al., 2000; Tosatto et al., 2002; Xiang et al., 2002).”
Comparative Protein Structure Modeling Using MODELLER (2016, background): “The accuracy of loop predictions can be further improved by clustering the sampled loop conformations and partially accounting for the entropic contribution to the free energy (Xiang et al., 2002).”
Modeling structurally variable regions in homologous proteins with rosetta (2004, background): “nents of molecular mechanics force fields, with a variety of treatments of electrostatics and solvation.(18,25,28) Knowl-”
Design of Nanoparticulate Group 2 Influenza Virus Hemagglutinin Stem Antigens That Activate Unmutated Ancestor B Cell Receptors of Broadly Neutralizing Antibody Lineages (2018, positive): “Loops were modeled with LOOPY (62), superpositions were performed using UCSF Chimera (63) or LSQMAN (64), and energy minimization of ﬁnal models was performed using RELAX (65) from the ROSETTA suite.”
Cyclic coordinate descent: A robotics algorithm for protein loop closure (2003, methodology): “It has been used in a number of loop-modeling programs, including Drawbridge (Ring et al. 1992), the Biopolymer program (Tripos, Inc.), and Loopy (Xiang et al. 2002).”
Exploring the extremes of sequence/structure space with ensemble fold recognition in the program Phyre (2008, neutral): “29”
Accurate and efficient loop selections by the DFIRE‐based all‐atom statistical potential (2004, methodology): “The Jacobson decoy set (2003) is substantially larger than the RAPPER decoy set because it includes not only the loop targets collected by Fiser et al. (2000) but also those by Xiang et al. (2002).”
A hierarchical approach to all‐atom protein loop prediction (2004, methodology): “Fiser et al. 9 used a mixture of molecular mechanics force-ﬁeld terms and statistically derived terms for scoring, whereas Xiang et al. 8 used a scoring function that included steric interactions, hydrophobicity, torsional energy, and hydrogen bonding, but ignored many electrostatic effects.”