ReviewInterdisciplinary sciences, computational life sciences2022
In silico Methods for Identification of Potential Therapeutic Targets.
Review in Interdisciplinary sciences, computational life sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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.
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.
Who cites it
33 citing papers in PubMed.
- From probe to prodrug: immunoproteasome activity as a trigger for disease-selective therapeutics.Signal transduction and targeted therapy · 2026Article
- Review
- Minimal Computational Framework for Systematic Identification of Antimicrobial Targets.bioRxiv : the preprint server for biology · 2026Article
- Time-Resolved Transcriptomic Profiling of Chandipura Virus Infection Reveals Dynamic Host Responses and Host-Directed Therapeutic Targets.International journal of molecular sciences · 2026Article
- Targeting SARS-CoV-2 Main Protease: A Bacteria-Based Colorimetric Assay for Screening Natural Antiviral Inhibitors.Viruses · 2026Article
- Genome-Wide Protein Interaction Analysis in Parasitic Gyrodactylus Flatworms-Fish Hosts System and Drug Target Identification.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- NeXus: An Automated Platform for Network Pharmacology and Multi-Method Enrichment Analysis.International journal of molecular sciences · 2025Article
- From AI-AssistedPharmaceuticals (Basel, Switzerland) · 2025Review
- Sequence-Based Protein-Protein Interaction Prediction and Its Applications in Drug Discovery.Cells · 2025Review
- Network Pharmacology, Molecular Docking and Molecular Dynamics Studies to Predict the Molecular Targets and Mechanisms of Action ofPlants (Basel, Switzerland) · 2025Article
- Alternative therapeutic approaches for combating multi-drug-resistant bacteria: Reverse vaccinology against Enterobacter cloacae.Journal, genetic engineering & biotechnology · 2025Article
- Tetrahydrocurcumin targets TRIP13 inhibiting the interaction of TRIP13/USP7/c-FLIP to mediate c-FLIP ubiquitination in triple-negative breast cancer.Journal of advanced research · 2025Article
- Minneola tangelo essential oil exhibits antibacterial activity against multidrug-resistant pathogens while maintaining cell safety.BMC complementary medicine and therapies · 2025Article
- Unveiling the synergistic power of 3-hydrazinoquinoxaline-2-thiol and vancomycin against MRSA: AnBiomolecules & biomedicine · 2025Article
- Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research.Bioengineering (Basel, Switzerland) · 2025Review
- Computable properties of selected monomeric acylphloroglucinols with anticancer and/or antimalarial activities and first-approximation docking study.Journal of molecular modeling · 2025Article
- CANDI: a web server for predicting molecular targets and pathways of cannabis-based therapeutics.Journal of cannabis research · 2025Article
- In Silico Identification of Potential Clovibactin-like Antibiotics Binding to Unique Cell Wall Precursors in Diverse Gram-Positive Bacterial Strains.International journal of molecular sciences · 2025Article
- Neuroprotective Potential of Aminonaphthoquinone Derivatives Against Amyloid Beta-Induced Neuronal Cell Death Through Modulation of SIRT1 and BACE1.Neurochemical research · 2024Article
- The Comparative Characterization of a HypervirulentInternational journal of molecular sciences · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
At the initial stage of drug discovery, identifying novel targets with maximal efficacy and minimal side effects can improve the success rate and portfolio value of drug discovery projects while simultaneously reducing cycle time and cost. However, harnessing the full potential of big data to narrow the range of plausible targets through existing computational methods remains a key issue in this field. This paper reviews two categories of in silico methods-comparative genomics and network-based methods-for finding potential therapeutic targets among cellular functions based on understanding their related biological processes. In addition to describing the principles, databases, software, and applications, we discuss some recent studies and prospects of the methods. While comparative genomics is mostly applied to infectious diseases, network-based methods can be applied to infectious and non-infectious diseases. Nonetheless, the methods often complement each other in their advantages and disadvantages. The information reported here guides toward improving the application of big data-driven computational methods for therapeutic target discovery.
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Registered trials
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.