Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins.
By Manfred J. Sippl. 1990
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- Yang Zhang
- Ben M. Webb
- David Baker
- Jinbo Xu
- Hahnbeom Park
- Andrej Sali
- Tanja Kortemme
- Jeffrey J. Gray
Citations in the corpus
- Scientific Benchmarks for Guiding Macromolecular Energy Function Improvement (2013, methodology): “…energy—has been used to justify creating knowledge-based potentials from distribution of features from crystal structures (Miyazawa & Jernigan, 1985; Sippl, 1990); for example, rotamer libraries are often based on feature distributions (Dunbrack & Karplus, 1993; Ponder & Richards, 1987).”
- The Rosetta all-atom energy function for macromolecular modeling and design (2017, methodology): “We further investigated this result on the atomic level with the function print_atom_pair_energy_table by generating atom-pair energy tables (Supporting Information) for residues 5, 27, 45, 46, and 80 against both threonine and valine at residue 193 (Example for residue 80 in Table 3 ).”
- A position-specific distance-dependent statistical potential for protein structure and functional study (2012, neutral): “…2006) indicate that knowledge-based statistical potentials (Lu et al., 2008; Miyazawa and Jernigan, 1985; Shen and Sali, 2006; Simons et al., 1997; Sippl, 1990; Tanaka and Scheraga, 1976; Zhang and Zhang, 2010; Zhou and Zhou, 2002) compare favorably to physics-based potentials (Brooks et al.,…”
- Energy-based models for atomic-resolution protein conformations (2020, methodology): “Our work is a logical extension of statistical potential methods (Tanaka & Scheraga, 1976; Sippl, 1990; Lazaridis & Karplus, 2000) that fit energetic terms from data, which, in combination with physically motivated force Published as a conference paper at ICLR 2020 fields, have contributed to the…”
- New statistical potential for quality assessment of protein models and a survey of energy functions (2010, methodology): “For sparse data treatment the scheme introduced by Sippl [19] was used.”
- Bilingual language model for protein sequence and structure (2024, unknown): “The term inverse folding [84], [85] has been applied to the challenge of finding all the protein sequences that adopt a particular 3D structure (in the past loosely”
- Integrating statistical pair potentials into protein complex prediction (2007, background): “Further subdividing the atom space into larger alphabets leads to quickly diminishing returns, with effective MI declining below the level of the first two atom types past the alphabet of size 12.”
- An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction. (1998, background): “As with the conditional probability analysis, the reaction co-ordinate may be any convenient measure of property of the molecule (Beveridge & DiCapua, 1989), such as the separation of speci®c types of atoms (Bahar & Jernigan, 1997) or residues (Sippl, 1990; Jones et al., 1992), the distance between ”
- CUPSAT: prediction of protein stability upon point mutations (2006, methodology): “Boltzmann’s energy values were then calculated from the radial pair distribution of amino acid atoms (10).”
- Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized (2010, methodology): “Many different approaches for developing KBPs exist, but the most successful methods to date build upon a seminal paper by Sippl – published two decades ago – which introduced KBPs based on probability distributions of pairwise distances in proteins and reference states [7].”
- Comparative Protein Structure Modeling Using Modeller (2006, methodology): “…type, and hydrogen-bonding properties (Shi et al., 2001; Karchin et al., 2003; McGuffin and Jones, 2003; Zhou and Zhou, 2005) or on statistical potentials for residue interactions implied by the alignment (Sippl, 1990; Bowie et al., 1991; Sippl, 1995; Skolnick and Kihara, 2001; Xu et al., 2003).”
- The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins. (2005, background): “For globular proteins, the contribution of interresidue interactions to total energy is often approximated by low-resolution force fields, or statistical potentials, energy-like quantities derived from globular proteins based on the observed amino acid pairing frequencies.(18,19) In deriving the act”