Molegro Virtual Docker for Docking Screens.

Josimary Morais Vasconcelos Oliveira, Amauri Duarte da Silva, Alexandra Martins Dos Santos Soares, Walter Filgueira de Azevedo

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Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 authors.

Josimary Morais Vasconcelos OliveiraGraduate Program in Physiological Sciences. Federal University of Alfenas (UNIFAL-MG), Alfenas, Minas Gerais, Brazil.

Amauri Duarte da SilvaGraduate Program in Information Technologies and Health Management, Federal University of Health Sciences of Porto Alegre, Porto Alegre, RS, Brazil.

Alexandra Martins Dos Santos SoaresPrograma de Pós-Graduação em Biodiversidade e Biotecnologia da Amazônia - Bionorte, Universidade Federal do Maranhão, São Luís, MA, Brazil.

Walter Filgueira de AzevedoDepartment of Physics, Institute of Exact Sciences, Federal University of Alfenas, Alfenas, MG, Brazil.

Funding

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6 · The paper itself

Abstract

Docking screens aim at scanning large datasets of small molecules to find potential binders to protein targets related to pathologies. The main computational workhorse of this approach is protein-ligand docking. This chapter focuses on an integrated workflow to perform docking screens using Molegro Virtual Docker (MVD). We describe how to proceed with a target structure and integrate all necessary binding affinity data available at BindingDB to build a regression model to predict inhibition of cyclin-dependent kinase 2 (CDK2) using Molegro Data Modeller (MDM), a machine learning tool integrated into MVD. CDK2 is a protein target for anticancer drug development. Our regression model built with MDM shows superior predictive performance compared with classical scoring functions employed in docking programs. This MDM-built model is ready to use for virtual screening purposes. The integration relies on Jupyter Notebooks at Google Colab. All CDK2 datasets and Jupyter Notebooks discussed in this work are available at GitHub: https://github.com/azevedolab/docking#readme .

Indexed as

Cyclin-Dependent Kinase 2Molecular Docking SimulationSoftwareBinding SitesHumansLigandsMachine LearningProtein BindingProtein Kinase InhibitorsUser-Computer InterfaceCDK2 protein, humanCyclin-Dependent Kinase 2LigandsProtein Kinase InhibitorsCyclin-dependent kinase 2Docking screenDrug discoveryMachine learningMolegro virtual dockerScoring function space

Identifiers

PMID41075090

DOI10.1007/978-1-0716-4949-7_10

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.