Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques.

By Ephraim KATCHALSKI-KATZIRtt, I. Shariv, M. Eisenstein, A. Friesem, C. Aflalo, Ilya A. VAKSERt. 1992

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Citations in the corpus

Correlated mutations contain information about protein-protein interaction. (1997, unknown): “…geometrically complementary regions between the two proteins (Cher®ls et al., 1991; Fischer et al., 1995; Helmer-Citterich & Tramontano, 1994; Jackson & Sternberg, 1995; Jiang & Kim, 1991; Shoichet & Kuntz, 1991; Stoddard & Koshland, 1992; Walls & Sternberg, 1992; Katchalski-Katzir et al., 1992).”
The scoring of poses in protein-protein docking: current capabilities and future directions (2013, methodology): “These range from composite scoring functions using a linear combination of terms, usually models of the underlying physical phenomena at play [52-65], to methods derived from the statistics of structural databases [63,66-70], docking decoys [71-75], experimental binding energies [76], methods based ”
CPORT: A Consensus Interface Predictor and Its Performance in Prediction-Driven Docking with HADDOCK (2011, unknown): “Unlike HADDOCK, ZDOCK is optimized for such cases, containing features such as shape complementarity [30,31] and statistical contact potentials [32] that are absent in HADDOCK.”
ZRANK: Reranking protein docking predictions with an optimized energy function (2007, methodology): “…FTDOCK, 5 GRAMM, 6 and ZDOCK 7 all use grid-based spatial searches that are sped up with a Fast Fourier Transform (FFT), a method first applied by Katchal-ski-Katzir et al. 8 The program HEX 9 also utilizes the FFT, but in this case it is to speed up a rotational search, using spherical harmonics.”
Entropia: architecture and performance of an enterprise desktop grid system (2003, unknown): “1 R 2=0.96 0 20 40 60 80 100 120 140 0 100 200 300 400 500 600 700 NumberofNodes 609”
Protein Docking Model Evaluation by Graph Neural Networks (2020, methodology): “These include docking conformational searches, such as fast Fourier transform (Katchalski-Katzir et al., 1992; Padhorny et al., 2016), geometric hashing (Fischer et al.”
Protein docking using spherical polar Fourier correlations (2000, methodology): “…CPU, central processor unit; FFT, fast Fourier transform; PDB, protein data bank; RMS, root mean squared; Mb, megabyte; VH, antibody variable heavy chain; VL, antibody variable light chain; 3D, three-dimensional; 6D, six-dimensional. tions can still take many CPU-hours, 22 or even CPU-days.”
Protein–protein docking by fast generalized Fourier transforms on 5D rotational manifolds (2016, unknown): “It is clear that this scoring function, which is essentially the one used by Katchalski-Katzir and coworkers [5], reaches its minimum on a conformation in which the ligand maximally overlaps with the surface layer of the receptor, thus providing optimal shape complementarity.”
Predicting interactions of winged‐helix transcription factors with DNA (2004, methodology): “16–20 These global search techniques were tested on a series of DNA–repressor complexes.”