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

Original Research

Published on 07 Aug 2026

Spectral analysis and AI/ML-based data-driven approaches for enhanced protein conformation selection and prediction in drug discovery

in In silico Methods and Artificial Intelligence for Drug Discovery

Shivangi Gupta
Vineetha Menon
Jerome Baudry

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1805731

399 views

Perspective

Accepted on 03 Aug 2026

Do property cliffs exist? A conceptual analysis of structural changes and molecular properties

in In silico Methods and Artificial Intelligence for Drug Discovery

Elier Enrique Abreu-Martinez
David Ignacio Ramirez-Pama
Gabriel Merino
Karina Martinez-Mayorga

Frontiers in Drug Discovery

Review

Published on 17 Jul 2026

Toward explainable and adaptive artificial intelligence systems for antimicrobial peptide discovery under resistance pressure

in In silico Methods and Artificial Intelligence for Drug Discovery

Ana Luisa Islas-Ávila
Julián García-Vinuesa
Nicole Soto-García
Michelle Soto-García
Bárbara Gutiérrez-Cárdenas
Alejandro Inostroza-Munoz
Mehdi D. Davari
Leandro Murgas
Roberto Uribe-Paredes
Alicia Martínez-Rebollar

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1820604

758 views

Perspective

Published on 14 Jul 2026

Modulating the human gut microbiome-host system: a new drug discovery paradigm

in In silico Methods and Artificial Intelligence for Drug Discovery

Gonzalo Colmenarejo

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1898583

852 views

Mini Review

Published on 09 Jul 2026

Computational screening of plant-derived compounds against SARS-CoV-2: methodological trends, limitations, and opportunities

in In silico Methods and Artificial Intelligence for Drug Discovery

Alejandra Ojeda-Pérez
Rocío Borges-Argáez
Norberto Sánchez-Cruz

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1882806

611 views

Original Research

Published on 07 Jul 2026

Mapping the otoactive landscape: an LLM-aided extraction of compounds and their targets

in In silico Methods and Artificial Intelligence for Drug Discovery

Aylin del Moral-Morales
Jean Arguello‐Camarillo
Jesús Yael Castañón Bello
Angélica Chavez-Romero
José L. Medina-Franco
Hugo Nájera
Gerardo Pérez-Hernández

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1834905

953 views

Review

Published on 06 Jul 2026

Physical feasibility gating in early drug discovery: a decision framework for identifying predictable physical failures, with retrospective illustration

in In silico Methods and Artificial Intelligence for Drug Discovery

Sarfaraz K. Niazi

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1799663

747 views

Review

Accepted on 30 Jun 2026

A Survey of LLMs in Drug Discovery and Precision Medicine

in In silico Methods and Artificial Intelligence for Drug Discovery

Hasi Hays
William J. Richardson

Frontiers in Drug Discovery

373 views

Mini Review

Published on 17 Jun 2026

Pairwise learning for molecular property prediction and optimization

in In silico Methods and Artificial Intelligence for Drug Discovery

Zachary Fralish
Daniel Reker

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1859068

1,348 views

Original Research

Published on 29 May 2026

High-throughput repurposing screen identifies a DHODH inhibitor as a potent antiviral candidate against chikungunya virus

in In silico Methods and Artificial Intelligence for Drug Discovery

Eliana Castro
Diego Ezequiel Alvarez

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1846068

1,286 views

Original Research

Published on 15 May 2026

Virtual screening and molecular dynamics simulations of cannabinoid receptor 2 agonists as drug candidates for osteoarthritis therapy

in In silico Methods and Artificial Intelligence for Drug Discovery

Fernanda F. De Souza
Juliana F. Vilachã
Heberth De Paula
Kathia Maria Honorio

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1809420

1,511 views

Perspective

Published on 04 May 2026

Artificial intelligence for small-molecule chemical probe design: why drug-centric models may not transfer cleanly

in In silico Methods and Artificial Intelligence for Drug Discovery

Renzo Carlucci
Exequiel O. J. Porta

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1836983

1,729 views

Specialty Grand Challenge

Published on 16 Feb 2026

Revisiting the grand challenges: the road travelled and ahead at the frontiers of computer-aided drug design

in In silico Methods and Artificial Intelligence for Drug Discovery

José L. Medina-Franco

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1780834

1,823 views
1 citation

Brief Research Report

Published on 28 Jan 2026

Structure-based virtual screening for TRPM8 modulators

in In silico Methods and Artificial Intelligence for Drug Discovery

Nivya James
Pedro J. Ballester

Frontiers in Drug Discovery

doi 10.3389/fddsv.2026.1770904

2,152 views

Original Research

Published on 16 Jan 2026

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

doi 10.3389/fddsv.2025.1731262

4,375 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

4,432 views

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

2,329 views
1 citation

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

2,186 views
1 citation

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

3,537 views
2 citations

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

5,485 views
7 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

18,013 views
23 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

3,330 views
2 citations

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

3,308 views
2 citations

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

5,635 views
17 citations

60 articles

articles

Spectral analysis and AI/ML-based data-driven approaches for enhanced protein conformation selection and prediction in drug discovery

Do property cliffs exist? A conceptual analysis of structural changes and molecular properties

Toward explainable and adaptive artificial intelligence systems for antimicrobial peptide discovery under resistance pressure

Modulating the human gut microbiome-host system: a new drug discovery paradigm

Computational screening of plant-derived compounds against SARS-CoV-2: methodological trends, limitations, and opportunities

Mapping the otoactive landscape: an LLM-aided extraction of compounds and their targets

Physical feasibility gating in early drug discovery: a decision framework for identifying predictable physical failures, with retrospective illustration

A Survey of LLMs in Drug Discovery and Precision Medicine

Pairwise learning for molecular property prediction and optimization

High-throughput repurposing screen identifies a DHODH inhibitor as a potent antiviral candidate against chikungunya virus

Virtual screening and molecular dynamics simulations of cannabinoid receptor 2 agonists as drug candidates for osteoarthritis therapy

Artificial intelligence for small-molecule chemical probe design: why drug-centric models may not transfer cleanly

Revisiting the grand challenges: the road travelled and ahead at the frontiers of computer-aided drug design

Structure-based virtual screening for TRPM8 modulators

Enhancing structure-based virtual screening of MDM2–p53 inhibitors: a benchmark of machine learning vs. traditional docking scoring functions

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

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

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