Original Research

Published on 29 Oct 2024

Drug–drug interaction extraction based on multimodal feature fusion by Transformer and BiGRU

in In silico Methods and Artificial Intelligence for Drug Discovery

Changqing Yu
Shanwen Zhang
Xuqi Wang
Tailong Shi
Chen Jiang
Sizhe Liang
Guanghao Ma

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1460672

192 views

Mini Review

Published on 03 Sep 2024

AI-accelerated therapeutic antibody development: practical insights

in In silico Methods and Artificial Intelligence for Drug Discovery

Luca Santuari
Marianne Bachmann Salvy
Ioannis Xenarios
Bulak Arpat

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1447867

1,826 views

Mini Review

Published on 20 Aug 2024

How drug repurposing can advance drug discovery: challenges and opportunities

in In silico Methods and Artificial Intelligence for Drug Discovery

Luca Pinzi
Nicolò Bisi
Giulio Rastelli

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1460100

1,966 views
2 citations

Mini Review

Published on 09 Jul 2024

The role of physicochemical and topological parameters in drug design

in In silico Methods and Artificial Intelligence for Drug Discovery

Janki Darlami
Shweta Sharma

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1424402

1,307 views

Editorial

Published on 15 May 2024

Editorial: Recent trends in anti-cancer drug discovery by in silico methods

in In silico Methods and Artificial Intelligence for Drug Discovery

Carmen Cerchia
Jose Correa Basurto
Angelo Lupo
Antonio Lavecchia

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1420267

779 views

Review

Published on 05 Apr 2024

Integrative computational approaches for discovery and evaluation of lead compound for drug design

in In silico Methods and Artificial Intelligence for Drug Discovery

Utkarsha Naithani
Vandana Guleria

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1362456

2,927 views
2 citations

Original Research

Published on 04 Apr 2024

Application of machine learning to predict unbound drug bioavailability in the brain

in In silico Methods and Artificial Intelligence for Drug Discovery

J. Francisco Morales
M. Esperanza Ruiz
Robert E. Stratford
Alan Talevi

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1360732

1,419 views
2 citations

Mini Review

Published on 05 Mar 2024

Applying artificial intelligence to accelerate and de-risk antibody discovery

in In silico Methods and Artificial Intelligence for Drug Discovery

Astrid Musnier
Christophe Dumet
Saheli Mitra
Adrien Verdier
Raouf Keskes
Augustin Chassine
Yann Jullian
Mélanie Cortes
Yannick Corde
Zakaria Omahdi

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1339697

2,808 views
2 citations

Editorial

Published on 21 Feb 2024

Editorial: Use of computational tools for designing epigenetic drugs

in In silico Methods and Artificial Intelligence for Drug Discovery

Yudibeth Sixto-López
Abdullahi Ibrahim Uba
Kuldeep K. Roy

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1381450

839 views

Review

Published on 08 Feb 2024

Machine learning in toxicological sciences: opportunities for assessing drug toxicity

in In silico Methods and Artificial Intelligence for Drug Discovery

Lusine Tonoyan
Arno G. Siraki

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1336025

3,573 views
1 citation

Original Research

Published on 05 Feb 2024

Rapid screening of chemicals for their potential to cause specific toxidromes

in In silico Methods and Artificial Intelligence for Drug Discovery

Ruifeng Liu
Mohamed Diwan M. AbdulHameed
Zhen Xu
Benjamin Clancy
Valmik Desai
Anders Wallqvist

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1324564

975 views

Mini Review

Published on 02 Feb 2024

Deep generative models in the quest for anticancer drugs: ways forward

in In silico Methods and Artificial Intelligence for Drug Discovery

Virgilio Romanelli
Carmen Cerchia
Antonio Lavecchia

Frontiers in Drug Discovery

doi 10.3389/fddsv.2024.1362956

1,183 views
1 citation

Original Research

Published on 11 Dec 2023

Consensus docking aid to model the activity of an inhibitor of DNA methyltransferase 1 inspired by de novo design

in In silico Methods and Artificial Intelligence for Drug Discovery

Diana L. Prado-Romero
Alejandro Gómez-García
Raziel Cedillo-González
Hassan Villegas-Quintero
Juan F. Avellaneda-Tamayo
Edgar López-López
Fernanda I. Saldívar-González
Ana L. Chávez-Hernández
José L. Medina-Franco

Frontiers in Drug Discovery

doi 10.3389/fddsv.2023.1261094

2,802 views
4 citations

Review

Published on 18 Sep 2023

State-of-the-art strategies to prioritize Mycobacterium tuberculosis drug targets for drug discovery using a subtractive genomics approach

in In silico Methods and Artificial Intelligence for Drug Discovery

Adetutu Akinnuwesi
Samuel Egieyeh
Ruben Cloete

Frontiers in Drug Discovery

doi 10.3389/fddsv.2023.1254656

1,614 views
1 citation

Review

Published on 25 Jul 2023

The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study

in In silico Methods and Artificial Intelligence for Drug Discovery

Mateus Sá Magalhães Serafim
Simone Queiroz Pantaleão
Elany Barbosa da Silva
James H. McKerrow
Anthony J. O’Donoghue
Bruno Eduardo Fernandes Mota
Kathia Maria Honorio
Vinícius Gonçalves Maltarollo

Frontiers in Drug Discovery

doi 10.3389/fddsv.2023.1237655

1,743 views
3 citations

Review

Published on 21 Jun 2023

Yin-yang in drug discovery: rethinking de novo design and development of predictive models

in In silico Methods and Artificial Intelligence for Drug Discovery

Ana L. Chávez-Hernández
Edgar López-López
José L. Medina-Franco

Frontiers in Drug Discovery

doi 10.3389/fddsv.2023.1222655

3,952 views
3 citations

Navigation group

Articles

Drug–drug interaction extraction based on multimodal feature fusion by Transformer and BiGRU

AI-accelerated therapeutic antibody development: practical insights

How drug repurposing can advance drug discovery: challenges and opportunities

The role of physicochemical and topological parameters in drug design

Editorial: Recent trends in anti-cancer drug discovery by in silico methods

Integrative computational approaches for discovery and evaluation of lead compound for drug design

Application of machine learning to predict unbound drug bioavailability in the brain

Applying artificial intelligence to accelerate and de-risk antibody discovery

Editorial: Use of computational tools for designing epigenetic drugs

Machine learning in toxicological sciences: opportunities for assessing drug toxicity

Rapid screening of chemicals for their potential to cause specific toxidromes

Deep generative models in the quest for anticancer drugs: ways forward

Consensus docking aid to model the activity of an inhibitor of DNA methyltransferase 1 inspired by de novo design

State-of-the-art strategies to prioritize Mycobacterium tuberculosis drug targets for drug discovery using a subtractive genomics approach

The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study

Yin-yang in drug discovery: rethinking de novo design and development of predictive models