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Compass: A shape-based machine learning tool for drug design

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What this work says

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

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New aromatic musk odorants: Design and synthesis
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An all atom force field for simulations of proteins and nucleic acids
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Macromodel—an integrated software system for modeling organic and bioorganic molecules using molecular mechanics
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Structure-odor relationships using neural networks
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Structure-activity relationships in human chemoreception
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Computer-Assisted Drug Design
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An internal-coordinate Monte Carlo method for searching conformational space
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Directional hydrogen bonding to sp2- and sp3-hybridized oxygen atoms and its relevance to ligand-macromolecule interactions
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A QSAR investigation of dihydrofolate reductase inhibition by Baker triazines based upon molecular shape analysis
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Olfaction, musk odor, and molecular properties
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Extraction of important molecular features of musk compounds using pattern recognition techniques
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Compass: Predicting Biological Activities from Molecular Surface Properties. Performance Comparisons on a Steroid Benchmark
inferredcites →https://doi.org/10.1021/jm00056a002openalex-snapshot
Structure-activity relationships from molecular similarity matrices
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Design of enzyme inhibitors using iterative protein crystallographic analysis
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The ensemble approach to distance geometry: application to the nicotinic pharmacophore
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Use of physicochemical parameters in distance geometry and related three-dimensional quantitative structure-activity relationships: A demonstration using Escherichia coli dihydrofolate reductase inhibitors
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Structure-activity studies of musk odorants using pattern recognition: monocyclic nitrobenzenes
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Structure-activity studies of musk odorants using pattern recognition: bicyclo- and tricyclo-benzenoids
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Analysis of a system of description of odors by means of four different multivariate statistical methods
inferredcites →https://doi.org/10.1093/chemse/16.4.319openalex-snapshot
Quantitative structure-activity relationships of structurally similar odorless and odoriferous benzenoid musks
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Analytical molecular surface calculation
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Structure-Based Discovery of Inhibitors of Thymidylate Synthase
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Parallel Distributed Processing

What points at this work

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

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THE CHALLENGE OF CREATIVITY IN DRUG DESIGN
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Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose
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