Frontiers in Drug Discovery | In silico Methods and Artificial Intelligence for Drug Discovery

Original Research

Accepted on 16 Dec 2025

Enhancing Structure-Based Virtual Screening of MDM2–p53 Inhibitors: A Benchmark of Machine Learning vs. Traditional Docking Scoring Functions

in In silico Methods and Artificial Intelligence for Drug Discovery

Marcia Yineth Castillo Tarazona
Gian Pietro Miscione

Frontiers in Drug Discovery

Original Research

Published on 10 Dec 2025

A network-based protocol to prioritize compounds for biological testing: discovery of Anti-Staphylococcus aureus cacalol derivatives

in In silico Methods and Artificial Intelligence for Drug Discovery

Edgar López-López
Julio C. Pardo-Novoa
Carolina Barrientos-Salcedo
Micheel M. Vichi-Ramírez
Carlos M. Cerda-García-Rojas

Frontiers in Drug Discovery

doi 10.3389/fddsv.2025.1724392

539 views

Review

Published on 10 Dec 2025

Exploring deep learning approaches in anticancer drug design: a review of recent advances

in In silico Methods and Artificial Intelligence for Drug Discovery

Kaoutar M’rhar
Mohamed-Amine Chadi
Hajar Mousannif

Frontiers in Drug Discovery

doi 10.3389/fddsv.2025.1713308

520 views

Study Protocol

Published on 09 Dec 2025

Integrated in vivo and in silico evaluation of antimalarial compounds from Vernonia ambigua leaves identified by GC-MS profiling

in In silico Methods and Artificial Intelligence for Drug Discovery

Amina Jega Yusuf
Abdul-Rahman Abdullahi Alpha
Mustapha Salihu
Jamila Aminu
Naz Mina Mert Sahin
Kemal Yelekçi
Abdullahi Ibrahim Uba
Mustapha Umar Imam

Frontiers in Drug Discovery

doi 10.3389/fddsv.2025.1635697

410 views

Original Research

Published on 10 Sep 2025

Bioinformatics-driven identification and prioritization of PTSD targets based on published multi-omic data

in In silico Methods and Artificial Intelligence for Drug Discovery

Mark Zervas
Allyson Gage
Magali Haas

Frontiers in Drug Discovery

doi 10.3389/fddsv.2025.1613261

1,628 views

Opinion

Published on 25 Aug 2025

On the biologically relevant chemical space: BioReCS

in In silico Methods and Artificial Intelligence for Drug Discovery

José L. Medina-Franco
Edgar López-López
Juan F. Avellaneda-Tamayo
William J. Zamora

Frontiers in Drug Discovery

doi 10.3389/fddsv.2025.1674289

3,160 views
3 citations

Mini Review

Published on 26 Jun 2025

AI-driven innovation in antibody-drug conjugate design

in In silico Methods and Artificial Intelligence for Drug Discovery

Heather A. Noriega
Xiang Simon Wang

Frontiers in Drug Discovery

doi 10.3389/fddsv.2025.1628789

8,699 views
8 citations

Editorial

Published on 10 Jun 2025

Editorial: Pharmacokinetics modeling in the Artificial Intelligence Era

in In silico Methods and Artificial Intelligence for Drug Discovery

Simone Brogi
Patric Schyman
Vishal B. Siramshetty

Frontiers in Drug Discovery

doi 10.3389/fddsv.2025.1636070

1,885 views

Editorial

Published on 04 Jun 2025

Editorial: Enhancing drug discovery through structure-based design and computational techniques

in In silico Methods and Artificial Intelligence for Drug Discovery

Rajesh Kumar Pathak
Dev Bukhsh Singh
Binh P. Nguyen

Frontiers in Drug Discovery

doi 10.3389/fddsv.2025.1632015

2,006 views

Original Research

Published on 15 Apr 2025

Identification of natural compounds as potential inhibitors of Interleukin-23: virtual screening, ADMET, drug-likeness, and dynamic simulation

in In silico Methods and Artificial Intelligence for Drug Discovery

Davood Gheidari
Morteza Mehrdad
Mahan Etedali

Frontiers in Drug Discovery

doi 10.3389/fddsv.2025.1525533

2,860 views
9 citations

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

2,123 views
1 citation

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

8,401 views
9 citations

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

16,285 views
41 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

6,023 views
8 citations

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

2,020 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

15,957 views
55 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

3,593 views
6 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

8,144 views
9 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

1,537 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

9,856 views
21 citations

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

2,113 views
1 citation

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

2,706 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

5,101 views
6 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

3,615 views
7 citations

46 articles

articles

Enhancing Structure-Based Virtual Screening of MDM2–p53 Inhibitors: A Benchmark of Machine Learning vs. Traditional Docking Scoring Functions

A network-based protocol to prioritize compounds for biological testing: discovery of Anti-Staphylococcus aureus cacalol derivatives

Exploring deep learning approaches in anticancer drug design: a review of recent advances

Integrated in vivo and in silico evaluation of antimalarial compounds from Vernonia ambigua leaves identified by GC-MS profiling

Bioinformatics-driven identification and prioritization of PTSD targets based on published multi-omic data

On the biologically relevant chemical space: BioReCS

AI-driven innovation in antibody-drug conjugate design

Editorial: Pharmacokinetics modeling in the Artificial Intelligence Era

Editorial: Enhancing drug discovery through structure-based design and computational techniques

Identification of natural compounds as potential inhibitors of Interleukin-23: virtual screening, ADMET, drug-likeness, and dynamic simulation

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