Evidence map›Paper›PMID 39810447›Full record

ReviewCurrent drug discovery technologies2025

Importance of Computer-aided Drug Design in Modern Pharmaceutical Research.

Uma Agarwal, Rajiv Kumar Tonk, Swati Paliwal

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current drug discovery technologies, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Uma AgarwalDepartment of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Delhi Pharmaceutical Sciences and Research University, Pushp Vihar Sector-3, M-B Road, New Delhi, 110017, India.ORCID 0000-0003-4821-4430
Rajiv Kumar TonkDepartment of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Delhi Pharmaceutical Sciences and Research University, Pushp Vihar Sector-3, M-B Road, New Delhi, 110017, India.ORCID 0000-0002-0842-5121
Swati PaliwalDepartment of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Delhi Pharmaceutical Sciences and Research University, Pushp Vihar Sector-3, M-B Road, New Delhi, 110017, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputer-aided Drug Design (CADD) approaches are essential in the drug discovery and development process. Pharmaceutical and biotechnology organizations, as well as academic institutions, utilize CADDs to identify and enhance the efficacy of bioactive compounds.

objectiveThis study aims to entice researchers by investigating the significance or value of Computer- aided Drug and Design (CADD) and its fundamental principles. The main focus is to speed up the drug discovery process, improve accuracy, and reduce the time and financial resources needed, ultimately making a positive impact on public health.

methodsA comprehensive literature search was conducted using databases such as PubMed and Scopus, focusing on studies published till 2024. The selection of studies was based on their analysis of the connection between contemporary pharmaceutical research and computer-aided drug design, with a focus on both structure-based and ligand-based drug design strategies can include molecular docking, fragment-based drug discovery, de novo drug design, pharmacophore modelling, Quantitative structure-activity relationship, 3D-QSAR, homology modelling,

resultsComputer-aided Drug Design (CADD) approaches are mathematical tools used to modify and measure certain characteristics of possible drug candidates. These methods are implemented in various applications. These encompass a variety of software products that are accessible to the public and can be purchased for corporate use. The CADD method is used at several stages of the drug development process, including as a foundation for chemical synthesis and biological testing. It provides information for the development of future SAR (Structure-Activity Relationship), resulting in enhanced molecules in terms of their activity and ADME (Absorption, Distribution, Metabolism, and Excretion). CADD techniques are predominantly employed to analyze and assess the affinity of large molecules for specific biomolecules, such as DNA, RNA, proteins, and enzymes, which serve exclusively as receptors. CADD improves the selection of lead compounds by predicting various parameters, including drug-likeness, physicochemical properties, pharmacokinetics, and toxicity. The application of CADD in drug modelling is to tackle challenges such as cost and time constraints. Modern computer-assisted drug discovery necessitates conducting virtual screening and high-throughput screening (HTS).

conclusionComputer-aided drug design plays a crucial role for academic institutions and leading pharmaceutical companies in the development of drugs that enhance potency with the significance of reducing both time and costs.

Indexed as

Computer-Aided DesignDrug DesignDrug DiscoveryPharmaceutical ResearchHumansMolecular Docking SimulationQuantitative Structure-Activity Relationshipbioactive compounds.biomoleculesComputer-aided drug designhigh-throughput screeningligand-based drug designstructure-based drug design

Identifiers

What Socratic holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.