HOW PROTEINS COMMUNICATE: THE MOLECULAR LANGUAGE BEHIND CELL SIGNALING
Background: Proteins are crucial communicators in cells, converging signaling pathways through smooth interactions and modification that regulate cellular activity and responsiveness.Objective: The current research was conducted to examine how proteins engage with each other through protein-protein interactions (PPIs) and post-translational modifications (PTMs) and how their disruption results in human diseases. Methodology: Qualitative and integrative review of the literature was conducted utilizing peer-reviewed articles from the years 2015–2024, focusing on structural biology, proteomics, and disease models to investigate protein signaling mechanisms. Results: The study identified that PTMs and PPIs like phosphorylation, ubiquitination, acetylation, and methylation play critical roles in ensuring signal fidelity; their deregulation is implicated in cancers, neurodegenerative, and autoimmune diseases. Conclusion: Understanding protein communication language at the molecular level offers valuable insights into mechanisms of disease and a new door toward targeted therapeutic investigation.
Authors
- Muhammad Usama (ORCID: https://orcid.org/0000-0003-0153-1201)
- Muhammad Siddique Afridi (ORCID: https://orcid.org/0000-0002-5505-2612)
- Shalini Shah
- Maria Aslam (ORCID: https://orcid.org/0000-0002-5376-013X)
- Samiyah Tasleem (ORCID: https://orcid.org/0000-0001-6815-5306)
- Noor Ul Ain (ORCID: https://orcid.org/0009-0001-1248-4933)
- Sundas Fayyaz (ORCID: https://orcid.org/0000-0001-8107-165X)
- Faiza Akhtar
- Esha
Institutions
- University of Lahore (PK)
- University of the Punjab (PK)
- Hamdard University (PK)
- Government College University, Faisalabad (PK)
- The University of Agriculture, Peshawar (PK)
- Academy of Nutrition and Dietetics (US)
- University of Agriculture Faisalabad (PK)
- Zhejiang University (CN)
- University of Veterinary and Animal Sciences (PK)
Publication Details
- Journal
- Journal of medical & health sciences review.
- Published
- 2025-05-17
- DOI
- https://doi.org/10.62019/b2y07688
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 0.00