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Current Computer-Aided Drug Design

ISSN: 1573-4099 (Print)
eISSN: 1875-6697 (Online)

Journal
Impact Factor :

1.5

Scopus
CiteScore:

3.7

Aims and Scope:Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design.

Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews/mini-reviews, original research articles and letter articles written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, theoretical chemistry; computational chemistry; computer and molecular graphics; molecular modeling; protein engineering; drug design; expert systems; general structure-property relationships; molecular dynamics; chemical database development and usage etc., providing excellent rationales for drug development.

Editor-in-Chief:


Dong-Qing WeiState Key Laboratory of Microbial Metabolism and College of Life Sciences and Biotechnology
Shanghai Jiaotong University
Shanghai
China

Indexed in:


EI Compendex, Scopus, SCI Expanded... View all

Special Issues With Active Call for Papers

Submission closes on: Dec 31, 2025
Computer-Aided Drug Discoveries for Emerging Diseases

Computer-aided drug design is a rapidly growing research field that continues to gain momentum, attracting increasing interest from the scientific community. This trend is largely driven by the growing utilization of machine learning and artificial intelligence in drug design and discovery. Artificial Intelligence has proven efficacy across various applications, including the prediction of physical-chemical properties and biological activities of small molecules, in silico assessment of absorption, distribution, metabolism, and excretion and toxicological (ADMET) profiles of... see more

Submission closes on: Dec 31, 2025
Artificial Intelligence in Biomedical Research: Enhancing Data Analysis for Drug Discovery and Development

This thematic issue highlights the transformative impact of Artificial Intelligence (AI), with a particular focus on Machine Learning (ML) and Deep Learning (DL) techniques, in advancing biomedical research. As a result of these cutting-edge AI methodologies, drug discovery and development are revolutionizing data analysis. Rapid advances in artificial intelligence technologies present unprecedented opportunities for accelerating drug discovery, optimizing therapeutic strategies, and enhancing treatment effectiveness. Researchers and clinicians can improve the precision and speed of identifying... see more

Submission closes on: Dec 31, 2025
Deep Learning Approaches in Bioinformatics for Computer-Aided Drug Development Targeting Brain Tumors

The integration of deep learning and bioinformatics is revolutionizing the field of computer-aided drug development, particularly in the fight against brain tumors one of the most aggressive and lethal types of cancer. Brain tumors present significant challenges due to their heterogeneity and complexity, which require novel approaches for early diagnosis and personalized treatment. By leveraging deep learning algorithms, researchers can extract valuable insights from vast and complex bioinformatics data, identifying novel therapeutic targets and accelerating... see more

Submission closes on: Dec 31, 2025
Emerging Trends in Computer-Aided Drug and Healthcare Solutions

This special issue aims to further the advancement of knowledge in drug design, healthcare innovations, and medical solutions by leveraging modern computational techniques. In recent years, computer-aided drug design has transformed the approach to medicinal chemistry, accelerating the drug discovery process and fostering innovation. The goal of this issue is to showcase pioneering research that highlights the application of computational methods, including molecular modeling, machine learning, deep learning, and bioinformatics, in the design and development... see more