Evidence map›Paper›PMID 29542412›Full record

ReviewCurrent neuropharmacology2018

Current Therapeutic Molecules and Targets in Neurodegenerative Diseases Based on in silico Drug Design.

Sheikh Arslan Sehgal, Mirza A Hammad, Rana Adnan Tahir, Hafiza Nisha Akram, Faheem Ahmad

Abstract readReview
In one paragraph

Review in Current neuropharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. In Silico Identification of Novel Compounds as Anthelmintics AgainstAnimals : an open access journal from MDPI · 2025
    Article
  3. Medicinal chemistry (Shariqah (United Arab Emirates)) · 2025
    Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Review
  15. Review
  16. Review
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

5 authors.

Sheikh Arslan SehgalState Key Laboratory of Biomembrane and Membrane Biotechnology, Institute of Zoology, Chinese Academy of Sciences; Beijing, China.
Mirza A HammadUniversity of Chinese Academy of Sciences, Beijing, China.
Rana Adnan TahirDepartment of Biosciences, COMSATS Institute of Information Technology, Sahiwal, Pakistan.
Hafiza Nisha AkramDepartment of Environmental Sciences, Quaid-e-Azam University Islamabad, Pakistan.
Faheem AhmadDepartment of Biosciences, COMSATS Institute of Information Technology, Islamabad, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs the number of elderly persons increases, neurodegenerative diseases are becoming ubiquitous. There is currently a great need for knowledge concerning management of oldage neurodegenerative diseases; the most important of which are: Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis, and Huntington's disease.

objectiveTo summarize the potential of computationally predicted molecules and targets against neurodegenerative diseases.

methodReview of literature published since 1997 against neurodegenerative diseases, utilizing as keywords: in silico, Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis ALS, and Huntington's disease was conducted. RESULTS AND

conclusionDue to the costs associated with experimentation and current ethical law, performing experiments directly on living organisms has become much more difficult. In this scenario, in silico techniques have been successful and have become powerful tools in the search to cure disease. Researchers use the Computer Aided Drug Design pipeline which: 1) generates 3- dimensional structures of target proteins through homology modeling 2) achieves stabilization through molecular dynamics simulation, and 3) exploits molecular docking through large compound libraries. Next generation sequencing is continually producing enormous amounts of raw sequence data while neuroimaging is producing a multitude of raw image data. To solve such pressing problems, these new tools and algorithms are required. This review elaborates precise in silico tools and techniques for drug targets, active molecules, and molecular docking studies, together with future prospects and challenges concerning possible breakthroughs in Alzheimer's, Parkinson's, Amyotrophic Lateral Sclerosis, and Huntington's disease.

Indexed as

Computer SimulationDrug DesignAnimalsDatabases, FactualHumansMolecular Docking SimulationNeurodegenerative DiseasesNeuroprotective AgentsNeuroprotective Agentsalzheimer's diseaseamyotrophic lateral sclerosisand huntington's diseasecomputer aided drug designIn silico analysisparkinson's disease.

Identifiers

PMID29542412
PMCPMC6080102

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.