Evidence map›Paper›PMID 39630336›Full record

ReviewApplied biochemistry and biotechnology2025

Decoding Drug Discovery: Exploring A-to-Z In Silico Methods for Beginners.

Hezha O Rasul, Dlzar D Ghafour, Bakhtyar K Aziz, Bryar A Hassan, Tarik A Rashid, Arif Kivrak

Abstract readReview
PubMed Publisher
In one paragraph

Review in Applied biochemistry and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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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

6 authors.

Hezha O RasulDepartment of Pharmaceutical Chemistry, College of Science, Charmo University, Peshawa Street, Chamchamal, 46023, Sulaimani, Iraq. hezha.rasul@chu.edu.iq.ORCID http://orcid.org/0000-0001-5250-003X
Dlzar D GhafourDepartment of Medical Laboratory Science, College of Science, Komar University of Science and Technology, 46001, Sulaimani, Iraq.
Bakhtyar K AzizDepartment of Nanoscience and Applied Chemistry, College of Science, Charmo University, Peshawa Street, Chamchamal, 46023, Sulaimani, Iraq.
Bryar A HassanComputer Science and Engineering Department, School of Science and Engineering, University of Kurdistan Hewler, KRI, Iraq.
Tarik A RashidComputer Science and Engineering Department, School of Science and Engineering, University of Kurdistan Hewler, KRI, Iraq.
Arif KivrakDepartment of Chemistry, Faculty of Sciences and Arts, Eskisehir Osmangazi University, Eskişehir, 26040, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The drug development process is a critical challenge in the pharmaceutical industry due to its time-consuming nature and the need to discover new drug potentials to address various ailments. The initial step in drug development, drug target identification, often consumes considerable time. While valid, traditional methods such as in vivo and in vitro approaches are limited in their ability to analyze vast amounts of data efficiently, leading to wasteful outcomes. To expedite and streamline drug development, an increasing reliance on computer-aided drug design (CADD) approaches has merged. These sophisticated in silico methods offer a promising avenue for efficiently identifying viable drug candidates, thus providing pharmaceutical firms with significant opportunities to uncover new prospective drug targets. The main goal of this work is to review in silico methods used in the drug development process with a focus on identifying therapeutic targets linked to specific diseases at the genetic or protein level. This article thoroughly discusses A-to-Z in silico techniques, which are essential for identifying the targets of bioactive compounds and their potential therapeutic effects. This review intends to improve drug discovery processes by illuminating the state of these cutting-edge approaches, thereby maximizing the effectiveness and duration of clinical trials for novel drug target investigation.

Indexed as

Computer-Aided DesignComputer SimulationDrug DesignDrug DiscoveryHumansArtificial intelligenceCADDMM-GBSAMolecular dockingMolecular dynamics

Identifiers

PMID39630336

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.