Docking screens for drug discovery / edited by Walter Filgueira de Azevedo Jr.

Format:

Book

Contributor:

Azevedo, Walter Filgueira de, Jr., editor.

Series:

Methods in molecular biology (Clifton, N.J.) ; v. 2984.

Methods in molecular biology, 1940-6029 ; 2984

Language:

English

Subjects (All):

Drug development--Laboratory manuals.

Drug development.

Physical Description:

1 online resource (xiv, 314 pages) : illustrations (some color).

Edition:

Second edition.

Place of Publication:

New York, NY : Humana Press, [2026]

Summary:

This second edition volume expands on the previous edition with discussions on the latest advancements in artificial intelligence (AI) applications in protein-drug interaction studies, and describes applications of different computational methodologies for drug discovery and creating efficient docking workflows using Jupyter Notebooks. The chapters in this book cover topics such as AlphaFold; AI models to address protein-ligand interactions; machine-learning models to predict binding affinity based on the atomic coordinates of protein-ligand complexes; AutoDock Vina; Molegro Virtual Docker (MVD); and workflows integrating docking engines and machine-learning techniques to build regression models and apply them to drug discovery. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Docking Screens for Drug Discovery, Second Edition is a valuable reference for all researchers interested in learning more about the development of computational tools for drug discovery.

Contents:

A primer on SAnDReS 2.0 for scoring function design / Amauri Duarte da Silva, Martina Veit-Acosta, Olga Tarasova & Walter Filgueira de Azevedo Jr.

Exploring the scoring function space with lasso regression / Amauri Duarte da Silva, Stéphanie Baud & Walter Filgueira de Azevedo Jr.

Combining MVD and ridge method to predict CDK2 inhibition / Sema Nur Pehlivan, Amauri Duarte da Silva & Walter Filgueira de Azevedo Jr.

Elastic net regression to predict CDK2 inhibition / Amauri Duarte da Silva & Walter Filgueira de Azevedo Jr.

Gradient descent to predict enzyme inhibition / Amauri Duarte da Silva & Walter Filgueira de Azevedo Jr.

Decision tree for prediction of binding affinity / Amauri Duarte da Silva & Walter Filgueira de Azevedo Jr.

Calculating enzyme inhibition with random forests / Amauri Duarte da Silva & Walter Filgueira de Azevedo Jr.

Extremely randomized trees to determine binding affinity / Amauri Duarte da Silva & Walter Filgueira de Azevedo Jr.

Hands-on docking with Molegro Virtual Docker / Damla Dere, Sema Nur Pehlivan, Amauri Duarte da Silva & Walter Filgueira de Azevedo Jr.

Molegro Virtual Docker for docking screens / Josimary Morais Vasconcelos Oliveira, Amauri Duarte da Silva, Alexandra Martins dos Santos Soares & Walter Filgueira de Azevedo Jr.

Molegro Data Modeller for machine learning / Amauri Duarte da Silva, Nelson José Freitas da Silveira, Patrícia Rufino Oliveira & Walter Filgueira de Azevedo Jr.

Neural networks with Molegro Data Modeller / Amauri Duarte da Silva & Walter Filgueira de Azevedo Jr.

AlphaFold for docking screens / Amauri Duarte da Silva & Walter Filgueira de Azevedo Jr.

Differential evolution for docking simulations / Amauri Duarte da Silva, Silvana Russo, Enrique González-Vergara & Walter Filgueira de Azevedo Jr.

Machine learning to predict CDK4 inhibition / Walter Filgueira de Azevedo Jr.

Targeting CDK9 with Molegro Virtual Docker / Walter Filgueira de Azevedo Jr.

CDK7 as a target for docking screens / Walter Filgueira de Azevedo Jr.

Molegro Data Modeller to estimate CDK6 inhibition / Walter Filgueira de Azevedo Jr.

Neural networks to calculate CDK2 inhibition / Walter Filgueira de Azevedo Jr.

Tree-based methods to predict enzyme inhibition / Walter Filgueira de Azevedo Jr.

Notes:

Includes bibliographical references and index.

Online resource; title from PDF title page (SpringerLink, viewed October 28, 2025).

Other Format:

Print version: Docking screens for drug discovery. Docking screens for drug discovery

ISBN:

9781071649497

1071649493

OCLC:

1547386628

Access Restriction:

Restricted for use by site license