Why do we need so many chemical similarity search methods?

The Protein Data Bank

Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196

Chemical Similarity Searching

Willett, P., Barnard, J. M., & Downs, G. M. (1998) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci9800211 · Cited by 1,775

Concepts and applications of molecular similarity

Johnson, M. A., & Maggiora, G. M. (1990) · Wiley eBooks · Cited by 1,301

Atom pairs as molecular features in structure-activity studies: definition and applications

Carhart, R. E., Smith, D. H., & Venkataraghavan, R. (1985) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci00046a002 · Cited by 1,101

Virtual screening—an overview

Walters, W. P., Stahl, M. T., & Murcko, M. A. (1998) · Drug Discovery Today · doi:10.1016/s1359-6446(97)01163-x · Cited by 996

Consensus scoring: a method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins.

Charifson, P. S., Corkery, J. J., Murcko, M. A., & Walters, W. P. (1999) · Journal of Medicinal Chemistry · doi:10.1021/jm990352k · Cited by 698

Use of Structure−Activity Data To Compare Structure-Based Clustering Methods and Descriptors for Use in Compound Selection

Brown, R. D., & Martin, Y. C. (1996) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci9501047 · Cited by 631

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

Patterson, D. E., CRAMER, R. D. I., Ferguson, A. M., Clark, R. D., & Weinberger, L. E. (1996) · Journal of Medicinal Chemistry · doi:10.1021/jm960290n · Cited by 509

The Information Content of 2D and 3D Structural Descriptors Relevant to Ligand-Receptor Binding

Brown, R. D., & Martin, Y. C. (1997) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci960373c · Cited by 378

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

Mason, J. S., Morize, I., Menard, P. R., Cheney, D. L., Hulme, C., & Labaudinière, R. F. (1999) · Journal of Medicinal Chemistry · doi:10.1021/jm9806998 · Cited by 375

Pharmacophore modeling coupled with molecular dynamic simulation approach to identify new leads for meprin-β metalloprotease

Chaudhuri, A., Hudait, N., & Chakraborty, S. S. (2019) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2019.04.014 · Cited by 5

An Enhancement of Bayesian Inference Network for Ligand-Based Virtual Screening using Features Selection

Ahmed, A. (2011) · American Journal of Applied Sciences · doi:10.3844/ajassp.2011.368.373 · Cited by 5

Flexible Alignment of Small Molecules Using the Penalty Method

Shin, W., Hyun, S. A., Chae, C. H., & Chon, J. K. (2009) · Journal of Chemical Information and Modeling · doi:10.1021/ci8004463 · Cited by 5

Compound Selection Using Measures of Similarity and Dissimilarity

Gillet, V. J., & Willett, P. (2007) · Elsevier eBooks · doi:10.1016/b0-08-045044-x/00249-2 · Cited by 5

Uncovering molecular determinants of potency and binding affinity in hit compounds targeting FGF14/Nav1.6 complex

Teimouri, H., Haghighijoo, Z., Baumgartner, T. J., Singh, A. K., Wadsworth, P. A., Zhang, C., Chen, H., Zhou, J., & Laezza, F. (2025) · Journal of Cheminformatics · doi:10.1186/s13321-025-01122-0 · Cited by 5

New similarity-based algorithm and its application to classification of anticonvulsant compounds

Talevi, A., Prieto, J., Bruno‐Blanch, L. E., & Castro, E. A. (2007) · Journal of Enzyme Inhibition and Medicinal Chemistry · doi:10.1080/14756360701190170 · Cited by 4

Molecular Similarity Approaches in Chemoinformatics: Early History and Literature Status

Willett, P. (2016) · ACS symposium series · doi:10.1021/bk-2016-1222.ch006 · Cited by 4

Docking and Virtual Screening

Morris, G. M. (2012) · Royal Society of Chemistry eBooks · doi:10.1039/9781849735377-00171 · Cited by 4

Cheminformatic Analysis of High-Throughput Compound Screens

Backman, T. W. H., & Girke, T. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-592-7_15 · Cited by 4

Cheminformatics techniques in antimalarial drug discovery and development from natural products 1: basic concepts

Egieyeh, S. A., Malan, S. F., & Christoffels, A. G. (2019) · Physical Sciences Reviews · doi:10.1515/psr-2018-0130 · Cited by 4

Ligand Based Pharmacophore Modeling Followed by Biological Screening Lead to Discovery of Novel PDK1 Inhibitors as Anticancer Agents

Mansi, I. A., Al-Sha’er, M. A., Mhaidat, N. M., & Taha, M. O. (2019) · Anti-Cancer Agents in Medicinal Chemistry · doi:10.2174/1871520620666191224110600 · Cited by 4

Turbo Similarity Searching: Effect of Partial Ranking and Fusion Rules on ChEMBL Database

Alhasbary, A. A. M., & Malim, N. H. A. H. (2021) · Molecular Informatics · doi:10.1002/minf.202100106 · Cited by 4

AN ACTIVITY PREDICTION MODEL USING SHAPE-BASED DESCRIPTOR METHOD

Hamza, H., Salim, N. B., & Saeed, F. (2016) · Jurnal Teknologi · doi:10.11113/jt.v78.9245 · Cited by 4

Cross‐Classified Multilevel Modelling of the Effectiveness of Similarity‐Based Virtual Screening

Mazalan, L., Bell, A., Sbaffi, L., & Willett, P. (2017) · ChemMedChem · doi:10.1002/cmdc.201700487 · Cited by 4

Data Mining Approaches for Compound Selection and Iterative Screening

Vogt, M., & Bajorath, J. (2009) · doi:10.1002/9780470567623.ch4 · Cited by 4

Computational discovery and repurposing of chloramphenicol succinate as a potent P2Y14 receptor antagonist for inflammatory bowel disease therapy

Tian, S., Wang, K., Liu, C., Chen, X., Kong, X., Zhang, Z., Shao, G., Ren, S., Hu, Q., & Li, H. (2025) · Journal of Advanced Research · doi:10.1016/j.jare.2025.08.035 · Cited by 3

Marine bioactive molecules as potential antiviral agents against HMPV key proteins: An integrated machine learning based in-silico approach

Arulsamy, S., Ramar, M., Natarajan, K., Natarajan, K., Krishnan, S. K., & Pavadai, P. (2025) · Journal of the Indian Chemical Society · doi:10.1016/j.jics.2025.102133 · Cited by 3

A Hybrid Approach Based on Self-Organizing Neural Networks and the K-Nearest Neighbors Method to Study Molecular Similarity

Amine, A., Elberrichi, Z. E., Simonet, M., & Rahmouni, A. (2011) · International Journal of Chemoinformatics and Chemical Engineering · doi:10.4018/ijcce.2011010106 · Cited by 3

VIRTUAL SCREENING IN DRUG DESIGN - OVERVIEW OF MOST FREQUENT TECHNIQUES

Kučera, T. (2016) · Military Medical Science Letters · doi:10.31482/mmsl.2016.014 · Cited by 3

Integration of fingerprint-based similarity searching and kernel-based partial least squares analysis to predict inhibitory activity against CSK, HER2, JAK1, JAK2, and JAK3

Deokar, H. S., Deokar, M., & Buolamwini, J. K. (2023) · Molecular Diversity · doi:10.1007/s11030-022-10596-1 · Cited by 3

Exploring the Role of Chemoinformatics in Accelerating Drug Discovery: A Computational Approach

Aarthy, M., Panwar, U., & Singh, S. K. (2023) · Methods in molecular biology · doi:10.1007/978-1-0716-3441-7_12 · Cited by 3

Quimioinformática, Inteligencia Artificial y la Química de Alimentos

Avellaneda-Tamayo, J. F., Sánchez-Ruiz, A., Savic, B., Medina‐Franco, J. L., & Colmenarejo, G. (2024) · TIP Revista Especializada en Ciencias Químico-Biológicas · doi:10.22201/fesz.23958723e.2024.652 · Cited by 2

An enhancement of Bayesian inference network for ligand-based virtual screening using minifingerprints

Ahmed, A., Abdo, A., & Salim, N. B. (2011) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.920338 · Cited by 3

1 Finding Protein Kinase Hits using Structural Information

Cherry, M., Reader, J., & Williams, D. (2006) · Progress in medicinal chemistry · doi:10.1016/s0079-6468(05)44401-x · Cited by 3

Application of Shannon-like diversity measures to cell-based chemistry spaces

Shanmugasundaram, V., & Maggiora, G. M. (2010) · Journal of Mathematical Chemistry · doi:10.1007/s10910-010-9745-8 · Cited by 4

In Silico Design and Selection of Anti-fungal AmB-polyene-analog Lead Molecules by Virtual Screening Method.

Ferdosiyan, M., & Sardari, S. (2010) · Europe PMC (PubMed Central) · Cited by 3

Discovery of Check Point Kinase 1 (Chk1) Inhibitors as Potential Anticancer Agents Using Ligand-Based Modelling and Virtual Screening

Al-Sha’er, M. A., Khanfar, M. A., & Taha, M. O. (2015) · Journal of In Silico & In Vitro Pharmacology · doi:10.21767/2469-6692.10006 · Cited by 3

Compound Library Design – Principles and Applications

Zheng, W., & Johnson, S. R. (2008) · Royal Society of Chemistry eBooks · doi:10.1039/9781847558879-00268 · Cited by 3

A Fast Algorithm for Large Common Connected Induced Subgraphs

Conte, A., Grossi, R., Marino, A., Tattini, L., & Versari, L. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-58163-7_4 · Cited by 3

Chemoinformatics Theory

(2006) · Springer eBooks · doi:10.1007/1-4020-5001-1_1 · Cited by 3

Molecular Design Method based on New Molecular Representation and Variational Auto-encoder

Li, K., Zhang, W., & Gao, M. (2023) · doi:10.5121/csit.2023.130303 · Cited by 3

Functional Feature Extraction and Chemical Retrieval

Tang, P., Hui, S. C., & Cong, G. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-31235-9_34 · Cited by 3

The Drug Discovery and Development Process

Bodor, N. S., & Buchwald, P. (2012) · Wiley eBooks · doi:10.1002/9781118407738.ch3 · Cited by 2

Chemoinformatics techniques for data mining in files of two-dimensional and three-dimensional chemical molecules.

Willett, P. (2005) · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · Cited by 3

Molecular Similarity: Theory, Applications, and PerspectivesPreprint

Pérez, K. L., Avellaneda-Tamayo, J. F., Chen, L., López, E. L., Juárez‐Mercado, K. E., Medina‐Franco, J. L., & Miranda‐Quintana, R. A. (2023) · ChemRxiv · doi:10.26434/chemrxiv-2023-cs3wb · Cited by 3

Computer‐aided (in silico) approaches in the mode‐of‐action analysis and safety assessment of Ostarine and 4‐methylamphetamine

Fauzi, F. M., Koutsoukas, A., Cunningham, A., Gallegos, A., Sedefov, R., & Bender, A. (2013) · Human Psychopharmacology Clinical and Experimental · doi:10.1002/hup.2322 · Cited by 2

Drug Design Methods to Regulate Protein–Protein Interactions

Poluri, K. M., Gulati, K., Tripathi, D. K., & Nagar, N. (2023) · Springer eBooks · doi:10.1007/978-981-99-2423-3_6 · Cited by 2

Cheminformatics Exploration of Structural Physicochemical Properties, Molecular Fingerprinting, and Diversity of the Chemical Space of Compounds from Betel Nut ( Areca catechu L.)

Li, Y., Wang, X., Sun, H., Wang, H., & Ma, C. (2024) · ACS Omega · doi:10.1021/acsomega.4c09386 · Cited by 2

Hypershape Recognition: A General Framework for Moment-Based Molecular Similarity

Costamagna, M., Foscato, M., Grellscheid, D., & Jensen, V. R. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5c00555 · Cited by 2

Drug target prediction using chem- and bioinformatics

Guedes, R. C., & Rodrigues, T. (2018) · Physical Sciences Reviews · doi:10.1515/psr-2018-0112 · Cited by 2

LINGO-DL: a text-based approach for molecular similarity searching

Abdo, A., & Pupin, M. (2021) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-021-00383-9 · Cited by 2

Biology Oriented Synthesis and Diversity Oriented Synthesis in Compound Collection Development

Kumar, K., Wetzel, S., & Waldmann, H. (2008) · Elsevier eBooks · doi:10.1016/b978-0-12-374194-3.00009-3 · Cited by 2

Similarity study of serine proteases inhibitors

Perekhodtsev, G. D. (2006) · Molecular Diversity · doi:10.1007/s11030-006-2153-0 · Cited by 2

Quantitative Structure Activity Analysis of Leishmanicidal Compounds

(2012) · BENTHAM SCIENCE PUBLISHERS eBooks · doi:10.2174/978160805183011201010033 · Cited by 2

Ligand-Based Virtual Screening Using Bayesian Inference Network

Abdo, A., & Salim, N. B. (2011) · ACS symposium series · doi:10.1021/bk-2011-1076.ch004 · Cited by 2

Hit and Lead Generation Strategies

Ettmayer, P., Schnitzer, R., Bergner, A., & Nar, H. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-409547-2.12313-3 · Cited by 2

Prediction of New Bioactive Molecules of Chemical Compound Using Boosting Ensemble Methods

Hashim, H., & Saeed, F. (2017) · Communications in computer and information science · doi:10.1007/978-981-10-7242-0_22 · Cited by 2

LWDOSM: Language for Writing Descriptors of Outline Shape of Molecules

Hamza, H., Salim, N. B., Abdo, A., & Saeed, F. (2012) · Communications in computer and information science · doi:10.1007/978-3-642-35326-0_25 · Cited by 2

A Toolbox for the Identification of Modes of Action of Natural Products

Rodrigues, T. (2019) · Fortschritte der Chemie Organischer Naturstoffe/Fortschritte der Chemie organischer Naturstoffe/Progress in the chemistry of organic natural products · doi:10.1007/978-3-030-14632-0_3 · Cited by 2

In SilicoScreening

Stumpfe, D., Geppert, H., & Bajorath, J. (2010) · Wiley eBooks · doi:10.1002/9780470584170.ch3 · Cited by 3

Lead Identification by Virtual Screening

Kämper, A., Rognan, D., & Lengauer, T. (2007) · Wiley eBooks · doi:10.1002/9783527619368.ch18 · Cited by 2

The GPCR — 7TM Receptor Target Family

Jacoby, E., Bouhelal, R., Gerspacher, M., & Seuwen, K. (2007) · Chemical biology · doi:10.1002/9783527619375.ch15d · Cited by 2

CRITICAL ASSESSMENT OF VIRTUAL SCREENING FOR HIT IDENTIFICATION

Stumpfe, D., & Bajorath, J. (2013) · doi:10.1002/9781118742785.ch6 · Cited by 2

Molecular Similarity Methods and QSAR Models As Tools for Virtual Screening

Bajorath, J. (2010) · Wiley eBooks · doi:10.1002/9780470571224.pse004 · Cited by 2

Monomer structure fingerprints: an extension of the monomer composition version for peptide databases

Abdo, A., Ghaleb, E., Alajmi, N. K. A., & Pupin, M. (2020) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-020-00336-8 · Cited by 1

Inhibition Potential of Quercetin Similar Compounds to SARS‐CoV‐2 Main Protease by High‐Throughput Virtual Screening, Molecular Simulations, ADMET Analysis, and DFT Studies

Gyawali, K., Chhetri, S. P., Khanal, K., Kshetri, M. B., Maharjan, R., Acharya, A., Khanal, M., Ghimire, M. P., & Lamichhane, T. R. (2025) · Chemistry & Biodiversity · doi:10.1002/cbdv.202501485 · Cited by 2

The Evaluation of Retrieval Effectiveness in Chemical Database Searching

Willett, P. (2005) · Springer eBooks · doi:10.1007/1-4020-3467-9_13 · Cited by 1

Inference networks for molecular database similarity searching

Abdo, A., & Salim, N. B. (2008) · Cited by 1

In silico Discovery of Chemotherapeutic Agents

Birkholtz, L., Burger, P., Aci‐Sèche, S., Valadié, H., da Costa, A. L., Brillet, L., de Beer, T., Joubert, F., Wells, G. A., Breton, V., et al. (2009) · Springer eBooks · doi:10.1007/978-1-4419-1327-2_14 · Cited by 1

Nanocrystal energetics via quantum similarity measures

Balta, M. İ. T., & Kılıç, Ç. (2014) · Modelling and Simulation in Materials Science and Engineering · doi:10.1088/0965-0393/22/2/025009 · Cited by 1

An alphabetic code based atomic level molecular similarity search in databases

Nallusamy, S., & Selvaraj, S. (2012) · Bioinformation · doi:10.6026/97320630008498 · Cited by 1

Structure-Based Virtual Screening Using Index Technology

Schlosser, J. (2011) · Cited by 1

Optimization and visualization of the edge weights in optimal assignment methods for virtual screening

Rosenbaum, L., Jahn, A., Dörr, A., & Zell, A. (2013) · BioData Mining · doi:10.1186/1756-0381-6-7 · Cited by 1

On Application of Carhart Atom Pairs to Predict Anticonvulsant Activity

Talevi, A., Prieto, J., Bruno‐Blanch, L. E., & Castro, E. A. (2006) · American journal of biochemistry & biotechnology/American journal of biochemistry and biotechnology · doi:10.3844/ajbbsp.2006.119.128 · Cited by 1

In Silico-Screening Approaches for Lead Generation: Identification of Novel Allosteric Modulators of Human-Erythrocyte Pyruvate Kinase

Tripathi, A., & Safo, M. K. (2011) · Methods in molecular biology · doi:10.1007/978-1-61779-334-9_19 · Cited by 1

A novel QSAR approach in modeling antifungal activity of some 5- or 6-methyl-2-substituded benzoxazoles/ benzimidazoles against C. albicans using molecular descriptors

Moldovan, C. D., Costescu, A., Katona, G., & Diudea, M. V. (2008) · Cited by 1

Molecular Docking Based on Ligand by Complexity LMC

Medina, M. M., González-Mendoza, M., & Hernández-Gress, N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-62428-0_34 · Cited by 1

Virtual Screening Methods Based on Bayesian Statistics

Vogt, M., & Bajorath, J. (2010) · IGI Global eBooks · doi:10.4018/978-1-61520-911-8.ch010 · Cited by 1

From chemical documentation to chemoinformatics: 50 years of chemical information science

Willett, P. (2018) · Facet eBooks · doi:10.29085/9781856049986.010 · Cited by 1

Visualizing and Analyzing the Chemical Space of Natural Product Databases for Drug Discovery

Barazorda-Ccahuana, H. L., Juárez‐Mercado, K. E., Medina‐Franco, J. L., & Chávez‐Fumagalli, M. Á. (2024) · Journal of Visualized Experiments · doi:10.3791/66349 · Cited by 1

Screening of oxidative stress components of cigarette smoke based on machine learning model integration

Hong, Y., Lv, J., Hong, Y., Wang, J., Huang, X., & Chen, C. (2025) · Toxicology and Applied Pharmacology · doi:10.1016/j.taap.2025.117387 · Cited by 1

A fast discovery algorithm for large common connected induced subgraphs

Conte, A., Grossi, R., Marino, A., Tattini, L., & Versari, L. (2019) · Discrete Applied Mathematics · doi:10.1016/j.dam.2019.02.023 · Cited by 1

Scenarios and Case Studies: Examples for Ligand‐Based Virtual Screening

Howe, T. J., Bemporad, D., & Tresadern, G. (2011) · Methods and principles in medicinal chemistry · doi:10.1002/9783527633326.ch13 · Cited by 1

Syst ematic Computational Analysis of Structure-Activity Relationships

Peltason, L. (2009) · bonndoc (University of Bonn) · Cited by 1

Cognitive Chemistry: The Marriage of Machine Learning and Chemistry to Accelerate Materials Discovery

Pyzer‐Knapp, E. O. (2019) · Wiley eBooks · doi:10.1002/9783527802265.ch8 · Cited by 1

Virtual Screening

Muegge, I., & Oloff, S. (2010) · Wiley eBooks · doi:10.1002/0471266949.bmc006.pub2 · Cited by 1

Screening virtual basado en topología molecular: una nueva metodología en el descubrimiento de agentes anticonvulsivos

Talevi, A. (2007) · doi:10.35537/10915/2353

Statistical Methods for Predicting Compound Recovery Rates for Ligand‐Based Virtual Screening and Assessing the Probability of Activity

Vogt, M., & Bajorath, J. (2012) · doi:10.1002/9783527645121.ch8

Structure‐Based Design of BACE Inhibitors: Technical and Practical Aspects of Preparation, 3‐Dimensional Structure, and Computational Analysis

Vajdos, F. F., Shanmugasundaram, V., & Tomasselli, A. G. (2010) · doi:10.1002/9780470594087.ch6

A new Ligand-Based approach to virtual screening, and prolifing or large chemical libraries

Gregori‐Puigjané, E. (2008) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)

In silico und in vitro Screening von Proteinliganden zur Apoptoseinduktion

Füllbeck, M. (2007) · doi:10.18452/15702

Sobre os estudos metabólicos de fármacos empregando-se atividade enzimática de CYP450 visando-se estabelecer correlações entre estrutura e atividade

Bauab, R. D. L. (2012) · doi:10.11606/d.75.2012.tde-17042012-103806

Ligand-based Methods for Data Management and Modelling

Alvarsson, J. (2015) · KTH Publication Database DiVA (KTH Royal Institute of Technology)

Novel algorithms and tools for ligand-based drug design: A machine learning approach for ligand profiling

Ma, C. (2012)

Novel Method for Improving the Exact Matching of the Molecular Graphs

Chowdary, C. S., & Mitra, P. (2013)

Software for supporting large scale data processing for High Throughput Screening

Tai, D. W. (2011) · KU ScholarWorks (The University of Kansas)

Rational design of small-molecule inhibitors of protein-protein interactions: Application to the oncogenic c-Myc/Max interaction

Meireles, L. (2011) · D-Scholarship@Pitt (University of Pittsburgh)

Machine learning techniques applied to chemotaxonomy and ligand-based virtual screening

Hristozov, D. (2007)

Compression of Topological Fragment Spectra (TFS) for Accelerating Chemical Data Mining

Shiga, M., & TAKAHASHI, Y. (2012) · Journal of Computer Chemistry Japan · doi:10.2477/jccj.2012-0002

A Simulation Study of the Use of Similarity Fusion for Virtual Screening

Whittle, M., Gillet, V. J., & Willett, P. (2010) · IGI Global eBooks · doi:10.4018/978-1-61520-911-8.ch004

Molecular Similarity

Amine, A., Elberrichi, Z. E., Simonet, M., & Rahmouni, A. (2011) · IGI Global eBooks · doi:10.4018/978-1-60960-860-6.ch005

Acoplamiento molecular basado en ligando por Complejidad LMC

Medina, M. M., & González-Mendoza, M. (2016) · Research in Computing Science · doi:10.13053/rcs-116-1-15

Exploiting receptor flexibility to improve the accuracy of structure-based virtual screening

Awuni, Y. (2017) · doi:10.32657/10356/69603

Jeffrey Divergence Applied to Docking Virtual

Medina, M. M., González-Mendoza, M., & Herrera-Alcántara, O. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-02837-4_26

In Silico Based Approach to Investigate Plant Lignans as Inhibitor Candidates for Estrogen Receptor in Breast Cancer

Mohamadyar‐Toupkanlou, F., Esfandiari, M., Kashef-Saberi, M. S., Kabiri, M., & Bazi, Z. (2021) · Clinical Cancer Drugs · doi:10.2174/2212697x08666210923123117

A Hybrid Approach Based on Self-Organizing Neural Networks and the K-Nearest Neighbors Method to Study Molecular Similarity

Amine, A., Elberrichi, Z. E., Simonet, M., & Rahmouni, A. (2013) · IGI Global eBooks · doi:10.4018/978-1-4666-4010-8.ch006

A Hybrid Approach Based on Self-Organizing Neural Networks and the K-Nearest Neighbors Method to Study Molecular Similarity

Amine, A., Elberrichi, Z. E., Simonet, M., & Rahmouni, A. (2012) · IGI Global eBooks · doi:10.4018/978-1-4666-2455-9.ch113

Directional cooperative networks

Ito, Y., & Nguyen, L.-M. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.127788

Directional Generative Networks; Comparison to Evolutionary Algorithms, Using Measurements for Molecules

Ito, Y., & Nguyen, L.-M. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-60511-6_10

Sobre os estudos metabólicos de fármacos empregando-se atividade enzimática de CYP450 visando-se estabelecer correlações entre estrutura e atividade

Bauab, R. D. L. (2011) · doi:10.11606/d.75.2011.tde-17042012-103806

Similarity searching

Stumpfe, D., & Bajorath, J. (2011) · Wiley Interdisciplinary Reviews Computational Molecular Science · doi:10.1002/wcms.23 · Cited by 126

Applications of Information Retrieval Methods in Computer-Aided Drug Discovery

Willett, P. (2001) · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · Cited by 1

Comparison of Similarity Method to Improve Retrieval Performance for Chemical Data

Nurjana, N. R., & Zainudin, S. (2018) · Asia-Pacific Journal of Information Technology and Multimedia · doi:10.17576/apjitm-2018-0701-08 · Cited by 2

Chemical similarity searches: when is complexity justified?

Sheridan, R. P. (2007) · Expert Opinion on Drug Discovery · doi:10.1517/17460441.2.4.423 · Cited by 49

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

Laufkötter, O., Miyao, T., & Bajorath, J. (2019) · ACS Omega · doi:10.1021/acsomega.9b02470 · Cited by 10