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Determination of clefts in receptor structures

https://doi.org/10.1007/bf01557724
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Using shape complementarity as an initial screen in designing ligands for a receptor binding site of known three-dimensional structure
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Theoretical investigation on the role of solvent in solvolytic reactions. Part 7. The enhancement of solvolysis of fluoromethane viewed by Voronoi polyhedra
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Macromolecular shape and surface maps by solvent exclusion.
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Computing Dirichlet Tessellations in the Plane
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Computing Dirichlet tessellations
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Computing the n-dimensional Delaunay tessellation with application to Voronoi polytopes
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Automated site-directed drug design: the concept of spacer skeletons for primary structure generation
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Automated site-directed drug design : the formation of molecular templates in primary structure generation
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Analytical molecular surface calculation
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Molecular surface Triangulation
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The geometry of the reactive site and of the peptide groups in trypsin, trypsinogen and its complexes with inhibitors
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DRUG‐RECEPTOR RECOGNITION: MOLECULAR ORIENTATION AND DIELECTRIC EFFECTS
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Computer Simulations of the Diffusion of a Substrate to an Active Site of an Enzyme
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Solvent-Accessible Surfaces of Proteins and Nucleic Acids
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AREAS, VOLUMES, PACKING, AND PROTEIN STRUCTURE
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Nouvelles applications des paramètres continus à la théorie des formes quadratiques. Deuxième mémoire. Recherches sur les parallélloèdres primitifs.
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Packing and Covering.

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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New Computational Approaches to Predict Protein‐Ligand Interactions
inferred← citeshttps://doi.org/10.1002/ange.19961082205openalex-snapshot
Was läßt sich aus der molekularen Erkennung in Protein‐Ligand‐Komplexen für das Design neuer Wirkstoffe lernen?
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What Can We Learn from Molecular Recognition in Protein–Ligand Complexes for the Design of New Drugs?
inferred← citeshttps://doi.org/10.1002/prot.20897openalex-snapshot
On the nature of cavities on protein surfaces: Application to the identification of drug‐binding sites
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Similarity in chemistry: Past, present and future
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The Castlemaine Project: Development of an AI-based Drug Design Support System
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CAVIAR: a method for automatic cavity detection, description and decomposition into subcavities
inferred← citeshttps://doi.org/10.1016/0076-6879(91)02010-7openalex-snapshot
[8] Clefts and binding sites in protein receptors
inferred← citeshttps://doi.org/10.1016/b978-0-7506-1188-6.50034-xopenalex-snapshot
The Castlemaine Project: development of an AI-based design support system
inferred← citeshttps://doi.org/10.1016/b978-012159640-8/50003-6openalex-snapshot
Computer Methods in Protein Modeling: An Overview
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Drug receptor interactions
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Computational tools for structure-based ligand design
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Chapter 11 Site-Directed Computer-Aided Drug Design: Progress Towards the Design of Novel Lead Compounds Using ‘Molecular’ Lattices
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Improving VEGFR-2 Docking-Based Screening by Pharmacophore Postfiltering and Similarity Search Postprocessing
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Ionic association in electrolyte solutions: A Voronoi polyhedra analysis
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Homogeneous bubble nucleation in water at negative pressure: A Voronoi polyhedra analysis
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Computing cavities, channels, pores and pockets in proteins from non-spherical ligands models
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Automatic Cavity Identification and Decomposition into Subpockets with CAVIAR
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Automatic Cavity Identification and Decomposition into Subpockets with CAVIAR
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