Current Computer-Aided Drug Design

Scope & Guideline

Fostering Collaboration for Breakthroughs in Drug Discovery

Introduction

Immerse yourself in the scholarly insights of Current Computer-Aided Drug Design with our comprehensive guidelines detailing its aims and scope. This page is your resource for understanding the journal's thematic priorities. Stay abreast of trending topics currently drawing significant attention and explore declining topics for a full picture of evolving interests. Our selection of highly cited topics and recent high-impact papers is curated within these guidelines to enhance your research impact.
LanguageEnglish
ISSN1573-4099
PublisherBENTHAM SCIENCE PUBL LTD
Support Open AccessNo
CountryUnited Arab Emirates
TypeJournal
Convergefrom 2006 to 2024
AbbreviationCURR COMPUT-AID DRUG / Curr. Comput.-Aided Drug Des.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES

Aims and Scopes

The journal 'Current Computer-Aided Drug Design' focuses on the advancement of computational methods and technologies in drug design and discovery. It encompasses a wide range of methodologies aimed at predicting, modeling, and validating potential drug candidates, thus contributing significantly to the field of pharmacology and medicinal chemistry.
  1. Computational Drug Design and Discovery:
    The journal emphasizes methodologies for computational drug design, including molecular docking, QSAR modeling, and molecular dynamics simulations, to identify and optimize potential drug candidates.
  2. Network Pharmacology:
    A significant focus is placed on network pharmacology, which integrates systems biology with pharmacological data to understand drug mechanisms and interactions within biological networks.
  3. In Silico Evaluation:
    The use of in silico approaches for evaluating the pharmacokinetic and toxicological profiles of drug candidates is a core area, ensuring that new compounds are not only effective but also safe for use.
  4. Integration of Traditional and Modern Approaches:
    The journal publishes studies that explore the integration of traditional medicine practices with modern computational techniques, particularly in the context of natural product drug discovery.
  5. AI and Machine Learning in Drug Design:
    There is a growing emphasis on the application of artificial intelligence and machine learning methods to predict drug-target interactions, optimize drug design processes, and analyze large datasets.
The journal 'Current Computer-Aided Drug Design' is witnessing several emerging trends that reflect the current landscape of drug discovery and design. These trends highlight the innovative applications of computational techniques in addressing contemporary challenges in pharmacology.
  1. Artificial Intelligence and Machine Learning:
    The application of AI and machine learning techniques for predicting drug interactions and optimizing drug design is rapidly gaining traction, reflecting a broader trend in the pharmaceutical industry towards data-driven decision making.
  2. Multi-target Drug Design:
    Emerging research is increasingly focusing on multi-target drug design strategies, which consider the complex interactions within biological systems, thus enhancing the effectiveness of therapeutic agents.
  3. Integration of Big Data and Bioinformatics:
    There is a growing trend towards leveraging big data and bioinformatics tools to analyze vast datasets for drug discovery, enabling more informed predictions and insights into drug efficacy and safety.
  4. Virtual Screening Techniques:
    Advanced virtual screening methodologies, including hybrid approaches that combine multiple computational techniques, are becoming prevalent as researchers seek to streamline the drug discovery process.
  5. Mechanistic Studies Using Network Pharmacology:
    The use of network pharmacology to elucidate the mechanisms of action of drugs and their interactions within biological systems is on the rise, emphasizing a systems biology approach to drug discovery.

Declining or Waning

As the field of computer-aided drug design evolves, certain themes appear to be waning in prominence. The following areas have been observed to decline in recent publications, indicating a shift in focus toward more contemporary methodologies and applications.
  1. Traditional Medicinal Approaches:
    While traditional medicinal approaches have been significant in the past, there has been a noticeable decline in studies solely focused on herbal or traditional remedies without the integration of computational methods.
  2. Basic Pharmacological Studies:
    Basic pharmacological studies, which do not employ advanced computational techniques, are becoming less frequent as the journal shifts towards more technologically-driven research.
  3. Single-target Drug Design:
    Research that focuses on single-target drug design is decreasing as there is a growing recognition of the importance of polypharmacology and multi-target approaches in drug development.
  4. In vitro Studies without Computational Validation:
    There is a decline in the publication of in vitro studies that do not include computational validation or modeling, reflecting a preference for studies that integrate both experimental and computational methods.

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