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Protein and ligand structure |
Overview
The height of structural knowledge is possession of a ligand-protein complex. Even though (due to our poor understanding of large-molecule physics) we can not predict affinities, or even likely trends, from such information such structures do help rationalize medicinal chemistry. And allows graduate students to get Ph.D.s by creating more useless scoring functions.
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ZAP: Ultimately, one of the hopes for Poisson-Boltzmann technology is to make a contribution to the evaluation of binding energies. To date it has typically been applied naively, i.e. often with poor charge sets, incorrect placements of protons, side chains, incomplete convergence, questionable dielectrics and poor choices of atomic radii. Even so, it often improves trends compared to traditional scoring functions. PB may be limited for binding energies, but the experimental determination has not yet been made.
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SZYBKI: (It means fast in Polish). We consider the Merck Force Field developed by Halgren et al to still be one of the best force fields available. SZYBKI is our implementation of MMFF, complete with solvent terms for use in ligand, protein-ligand and protein minimizations.
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AFITT: Our
crystallographic project AFITT has, at its heart, the
same concepts as the rest of OpenEye tools: that shape,
electrostatics and chemistry matter. For instance,
many ligand structures deposited in the PDB are manifestly
incorrect (over strained, clashing with the protein,
in incorrect chemical forms). The goal of AFITT was
to give crystallographers and modelers the tools to
over come such problems by including a modern forcefield
(MMFF), strong cheminformatics (OEChem) and shape fitting
for real space refinement.
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VIDA: Many of our tools either generate or sift through vast quantities of 3D ligand information, and as such VIDA is the best program available for large scale visualization. VIDA can handle small lists of molecules or corporate collections and can view them as multi-pane 3D, 2D depictions, SMILES strings, spreadsheet entries, html forms, graphs and drill-down lists. It can view them in the context of proteins or other small molecules, as simple line models or photo-realistic balls and sticks. With a python core VIDA is easily scriptable and can be tailored to many end-uses. Works, naturally, on many platforms.
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