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Do Not Hesitate to Use Tversky—and Other Hints for Successful Active Analogue Searches with Feature Count Descriptors

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What this work says

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

inferredcites →https://doi.org/10.1002/cbic.200700195openalex-snapshot

Scaffold Hopping by “Fuzzy” Pharmacophores and its Application to RNA Targets

inferredcites →https://doi.org/10.1002/cmdc.200600161openalex-snapshot

Asymmetry of Chemical Similarity

inferredcites →https://doi.org/10.1002/cmdc.200700050openalex-snapshot

Apparent Asymmetry in Fingerprint Similarity Searching is a Direct Consequence of Differences in Bit Densities and Molecular Size

inferredcites →https://doi.org/10.1002/cmdc.200800408openalex-snapshot

Improving the Search Performance of Extended Connectivity Fingerprints through Activity‐Oriented Feature Filtering and Application of a Bit‐Density‐Dependent Similarity Function

inferredcites →https://doi.org/10.1002/minf.201000099openalex-snapshot

ISIDA Property‐Labelled Fragment Descriptors

inferredcites →https://doi.org/10.1002/qsar.200610091openalex-snapshot

Scaffold‐Hopping: How Far Can You Jump?

inferredcites →https://doi.org/10.1007/s10822-005-9008-0openalex-snapshot

Substructural fragments: an universal language to encode reactions, molecular and supramolecular structures

inferredcites →https://doi.org/10.1007/s10822-011-9416-2openalex-snapshot

Local neighborhood behavior in a combinatorial library context

inferredcites →https://doi.org/10.1016/j.bmc.2012.04.024openalex-snapshot

Using self-organizing maps to accelerate similarity search

inferredcites →https://doi.org/10.1016/j.cbpa.2004.04.003openalex-snapshot

Pursuing the leadlikeness concept in pharmaceutical research

inferredcites →https://doi.org/10.1016/s0960-894x(02)00244-5openalex-snapshot

Drugs, leads, and drug-likeness: an analysis of some recently launched drugs

inferredcites →https://doi.org/10.1021/ci025634zopenalex-snapshot

Neighborhood Behavior of in Silico Structural Spaces with Respect to in Vitro Activity Spaces−A Novel Understanding of the Molecular Similarity Principle in the Context of Multiple Receptor Binding Profiles

inferredcites →https://doi.org/10.1021/ci025635ropenalex-snapshot

Neighborhood Behavior of in Silico Structural Spaces with Respect to In Vitro Activity Spaces−A Benchmark for Neighborhood Behavior Assessment of Different in Silico Similarity Metrics

inferredcites →https://doi.org/10.1021/ci060117sopenalex-snapshot

On Outliers and Activity CliffsWhy QSAR Often Disappoints

inferredcites →https://doi.org/10.1021/ci300149nopenalex-snapshot

Mining Chemical Reactions Using Neighborhood Behavior and Condensed Graphs of Reactions Approaches

inferredcites →https://doi.org/10.1021/ci6002416openalex-snapshot

Fuzzy Tricentric Pharmacophore Fingerprints. 1. Topological Fuzzy Pharmacophore Triplets and Adapted Molecular Similarity Scoring Schemes

inferredcites →https://doi.org/10.1021/ci700314xopenalex-snapshot

Balancing the Influence of Molecular Complexity on Fingerprint Similarity Searching

inferredcites →https://doi.org/10.1021/ci7003237openalex-snapshot

Fuzzy Tricentric Pharmacophore Fingerprints. 2. Application of Topological Fuzzy Pharmacophore Triplets in Quantitative Structure−Activity Relationships

inferredcites →https://doi.org/10.1021/ci7004093openalex-snapshot

Structure−Activity Landscape Index: Identifying and Quantifying Activity Cliffs

inferredcites →https://doi.org/10.1021/ci7004498openalex-snapshot

Application of Belief Theory to Similarity Data Fusion for Use in Analog Searching and Lead Hopping

inferredcites →https://doi.org/10.1021/ci800157jopenalex-snapshot

Fingerprint Directed Scaffold Hopping for Identification of CCR2 Antagonists

inferredcites →https://doi.org/10.1021/ci800302gopenalex-snapshot

Analysis of Neighborhood Behavior in Lead Optimization and Array Design

inferredcites →https://doi.org/10.1021/ci900092yopenalex-snapshot

Using Tversky Similarity Searches for Core Hopping: Finding the Needles in the Haystack

inferredcites →https://doi.org/10.1021/ci900108dopenalex-snapshot

Development of a Compound Class-Directed Similarity Coefficient That Accounts for Molecular Complexity Effects in Fingerprint Searching

inferredcites →https://doi.org/10.1021/ci900243aopenalex-snapshot

Structural Interpretation of Activity Cliffs Revealed by Systematic Analysis of Structure−Activity Relationships in Analog Series

inferredcites →https://doi.org/10.1021/ci960039gopenalex-snapshot

Diversity Profiling and Design Using 3D Pharmacophores: Pharmacophore-Derived Queries (PDQ)

inferredcites →https://doi.org/10.1021/ci980185hopenalex-snapshot

Comparing 3D Pharmacophore Triplets and 2D Fingerprints for Selecting Diverse Compound Subsets

inferredcites →https://doi.org/10.1021/jm020155copenalex-snapshot

Do Structurally Similar Molecules Have Similar Biological Activity?

inferredcites →https://doi.org/10.1021/jm061259gopenalex-snapshot

SHOP: Scaffold HOPping by GRID-Based Similarity Searches

inferredcites →https://doi.org/10.1021/jm960290nopenalex-snapshot

Neighborhood Behavior: A Useful Concept for Validation of “Molecular Diversity” Descriptors

inferredcites →https://doi.org/10.1021/jm9806998openalex-snapshot

New 4-Point Pharmacophore Method for Molecular Similarity and Diversity Applications: Overview of the Method and Applications, Including a Novel Approach to the Design of Combinatorial Libraries Containing Privileged Substructures

inferredcites →https://doi.org/10.1037/0033-295x.84.4.327openalex-snapshot

Features of similarity.

inferredcites →https://doi.org/10.1080/07366290701415820openalex-snapshot

Successful “In Silico” Design of New Efficient Uranyl Binders

inferredcites →https://doi.org/10.1093/biomet/34.1-2.28openalex-snapshot

THE GENERALIZATION OF ‘STUDENT'S’ PROBLEM WHEN SEVERAL DIFFERENT POPULATION VARLANCES ARE INVOLVED

inferredcites →https://doi.org/10.1517/17460441.2.4.423openalex-snapshot

Chemical similarity searches: when is complexity justified?

inferredcites →https://doi.org/10.2174/1568026043451186openalex-snapshot

Molecular Similarity and Property Similarity

inferredcites →https://doi.org/10.2174/157340908785747465openalex-snapshot

ISIDA - Platform for Virtual Screening Based on Fragment and Pharmacophoric Descriptors

What points at this work

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

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Generative Topographic Mapping Approach to Chemical Space Analysis

inferred← citeshttps://doi.org/10.1007/s10822-014-9743-1openalex-snapshot

Computational chemogenomics: Is it more than inductive transfer?

inferred← citeshttps://doi.org/10.1007/s10822-015-9882-zopenalex-snapshot

Mappability of drug-like space: towards a polypharmacologically competent map of drug-relevant compounds

inferred← citeshttps://doi.org/10.1007/s10822-016-9935-yopenalex-snapshot

Maximum common substructure-based Tversky index: an asymmetric hybrid similarity measure

inferred← citeshttps://doi.org/10.1007/s10822-016-9959-3openalex-snapshot

ROCS-derived features for virtual screening

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QSAR modeling and chemical space analysis of antimalarial compounds

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Assessment of tautomer distribution using the condensed reaction graph approach

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Shape similarity guided pose prediction: lessons from D3R Grand Challenge 3

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Electrostatic-field and surface-shape similarity for virtual screening and pose prediction

inferred← citeshttps://doi.org/10.1007/s12272-015-0607-6openalex-snapshot

Finding new scaffolds of JAK3 inhibitors in public database: 3D-QSAR models & shape-based screening

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Shape-Restrained Modeling of Protein–Small-Molecule Complexes with High Ambiguity Driven DOCKing

inferred← citeshttps://doi.org/10.1021/acs.jcim.4c00516openalex-snapshot

PheSA: An Open-Source Tool for Pharmacophore-Enhanced Shape Alignment

inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00572openalex-snapshot

Ultra-High-Throughput Structure-Based Virtual Screening for Small-Molecule Inhibitors of Protein–Protein Interactions

inferred← citeshttps://doi.org/10.1021/acs.jcim.5c00175openalex-snapshot

Evaluating Molecular Similarity Measures: Do Similarity Measures Reflect Electronic Structure Properties?

inferred← citeshttps://doi.org/10.1021/acsomega.9b02470openalex-snapshot

Large-Scale Comparison of Alternative Similarity Search Strategies with Varying Chemical Information Contents

inferred← citeshttps://doi.org/10.1021/ci500480bopenalex-snapshot

Investigation of the Use of Spectral Clustering for the Analysis of Molecular Data

inferred← citeshttps://doi.org/10.1021/ci5005702openalex-snapshot

Maximum Common Substructure-Based Data Fusion in Similarity Searching

inferred← citeshttps://doi.org/10.1039/c8ce00855hopenalex-snapshot

A chiral spiroborate anion from diphenyl- l -tartramide [B{ l -Tar(NHPh) 2 } 2 ] − applied to some challenging resolutions

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Hepatocyte Growth Factor-Modified Dental Pulp Stem Cells Potentially Regulate Novel Renal Fibrosis-Associated Gene via PI3K/AKT/GSK3β Pathway to Alleviate Renal Fibrosis

inferred← citeshttps://doi.org/10.1101/2021.06.10.447890openalex-snapshot

Shape-restrained modelling of protein-small molecule complexes with HADDOCK

inferred← citeshttps://doi.org/10.1101/2025.09.24.678312openalex-snapshot

Small Molecule Approach to RNA Targeting Binder Discovery (SMARTBind) Using Deep Learning Without Structural Input

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New hit compounds against Trypanosoma cruzi derived from mining yeast chemogenomic profiling data

inferred← citeshttps://doi.org/10.1186/s13321-017-0198-yopenalex-snapshot

Analysis of drug–endogenous human metabolite similarities in terms of their maximum common substructures

inferred← citeshttps://doi.org/10.1517/17460441.2016.1117070openalex-snapshot

An overview of molecular fingerprint similarity search in virtual screening

inferred← citeshttps://doi.org/10.48550/arxiv.1904.08915openalex-snapshot

Decoding Molecular Graph Embeddings with Reinforcement Learning

inferred← citeshttps://doi.org/10.70675/50158fa9z2b5fz48cfzb16cz4f95b63cb87fopenalex-snapshot

Property-enriched fragment descriptors for adaptive QSAR

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Analysis of the chemical space of antimalarial compounds by generative topographie mapping

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