Recep Adiyaman
Vision About Experience Education Skills Publications Tools Newsletter Updates Podcasts Blog Contact CV Subscribe
All Issues
Older Newer
Daily Signal February 17, 2026 · 9 min read

Issue #49: AlphaFold2-Guided Cyclic Peptide Stabilizer Design to Target Protein-Protein Interactions.

Protein Design Digest - 2026-02-17 - A New Insight into the Study of Neural Cell Adhesion Molecule (NCAM) Polysialylation Inhibition Incorporated the Molecular Docking Models into the NMR Spectroscopy of a Crucial Peptide-Ligand Interaction.

Share X LinkedIn
Protein Design Daily

Building something in Protein Design?

I love collaborating on new challenges. Let's build together.

LinkedIn Email

Subscribe to Protein Design Digest

Daily curated signals from arXiv, PubMed, and BioRxiv.

Signal of the Day

AlphaFold2-Guided Cyclic Peptide Stabilizer Design to Target Protein-Protein Interactions.

The control and modulation of protein-protein interactions (PPIs) is of central importance for the majority of biological processes and most biomedical applications. Stabilization of PPIs, besides inhibition, is of growing pharmaceutical interest. Due to their small size, drug-like organic molecules may not provide sufficient interaction surfaces to allow for high-affinity dual binding to both partners of a protein-protein complex. Cyclic peptides offer larger interaction surfaces, making them a promising class of stabilizers of PPIs. We have developed a computational protocol to rapidly and systematically design cyclic peptides that optimize not only the interaction with one target protein but simultaneously optimize the dual binding to two protein partners. The cyclic peptide generation is based on a modified AlphaFold2-based peptide design approach and combines confidence scoring with force field-based scoring using Molecular Dynamics simulations. The performance of the method is tested on protein-protein complexes with known cyclic peptide binders and stabilizers. In addition, the approach is used to design cyclic peptides that can act as bifunctional molecules, recruiting the cellular protein degradation system to a target protein. The designed cyclic peptides achieve similar or better calculated interaction scores than known binders and exhibit well-balanced interactions with both protein partners. The design protocol is generally applicable to cyclic peptide design for modulating or inducing protein-protein association and could be useful for many biomedical design efforts.

Why this matters:

Also Worth Reading

Investigation of the potential mechanism by which methylparaben induces psoriasis: an integrated study using network toxicology, molecular docking, molecular dynamics simulation, and eight machine learning algorithms.

Psoriasis is a chronic inflammatory skin disease with limited safe and effective treatments. Methylparaben, a widely used preservative in cosmetics, pharmaceuticals, and food, is an emerging environmental pollutant linked to immune-related skin disorders, but its role and mechanism in psoriasis remain unclear. This study explored its potential mechanism using network toxicology, molecular docking, molecular dynamics simulation, and eight machine learning algorithms. Methylparaben targets were retrieved from GeneCards and TCMSP, and psoriasis-related targets from CTD and GeneCards. Overlapping targets were screened with Venny 2.1.0. A PPI network was constructed via STRING, and core targets identified using Cytoscape 3.10.2. GO and KEGG enrichment analyses were performed on DAVID. Molecular docking evaluated the binding affinity of methylparaben with key targets. A total of 138 compound-related and 5,592 psoriasis-related targets were identified. Core targets such as INS, HIF1A, and PPARG are involved in regulating immune-inflammatory responses, keratinocyte proliferation and differentiation, and oxidative stress. GO analysis revealed enrichment in xenobiotic metabolism, lipopolysaccharide response, and metal ion binding. KEGG analysis highlighted pathways related to cancer, chemical carcinogenesis from reactive oxygen species, and drug metabolism via cytochrome P450 enzymes. Molecular docking showed stable binding of methylparaben to INS (-4.5 kcal/mol), HIF1A (-5.9 kcal/mol), and PPARG (-5.5 kcal/mol), primarily through hydrogen bonds and hydrophobic interactions. Methylparaben may exert its effects on psoriasis via multi-target and multi-pathway mechanisms, influencing inflammation, oxidative stress, and cellular regulation. These findings provide valuable insight into its toxicological mechanism and potential therapeutic application.

Innovative Approaches in Molecular Docking for the Discovery of Novel Inhibitors Against Alzheimer’s Disease.

Introduction Alzheimer’s disease (AD) is a debilitating neurodegenerative condition marked by progressive cognitive decline and memory impairment, affecting millions worldwide. Despite extensive research, no definitive cure exists, underscoring the need for innovative approaches to drug discovery and development. Methods This review focuses on the application of molecular docking techniques in the context of AD drug discovery. The methodology involves the use of computational modeling tools to predict and analyze the interactions between small drug-like molecules and key protein targets implicated in AD pathogenesis, particularly amyloid-beta (Aβ) and tau proteins. Results Molecular docking has enabled the virtual screening of large chemical libraries to identify potential inhibitors of Aβ aggregation and tau hyperphosphorylation. Numerous studies have validated docking-predicted interactions with in vitro and in vivo experiments, resulting in the discovery of novel compounds with promising pharmacological profiles. Docking has also aided in the optimization of ligand binding affinity and selectivity toward AD-relevant targets. Discussion The integration of molecular docking with experimental techniques enhances the reliability and efficiency of the drug discovery process. Docking allows for the early identification of bioactive molecules, reducing time and cost compared to traditional methods. However, limitations such as rigid receptor assumptions and scoring function inaccuracies require further refinement. Conclusion Molecular docking stands out as a powerful computational tool in the quest for effective AD therapies. Simulating protein-ligand interactions accelerates the identification of potential drug candidates and supports the rational design of targeted interventions, paving the way for future clinical applications in combating Alzheimer’s disease.

A Network Pharmacology Prediction and Molecular Docking-Based Strategy to Explore the Potential Pharmacological Mechanism of Vitexin for Cerebral Ischemia-reperfusion Injury.

Cerebral ischemia-reperfusion injury (CIRI) is a key problem to be solved urgently in the treatment of ischemic stroke, which seriously affects the prognosis of patients. As a natural flavonoid, Vitexin has been confirmed to alleviate CIRI, but the molecular network mechanism of its action has not been systematically analyzed. The HMC3 cells were subjected to OGD/R treatment to establish a CIRI cell model. Effect of Vitexin on cell viability, apoptosis, and levels of inflammatory factors were determined by CCK-8, TUNEL, and ELISA methods. The intersection of Vitexin target genes obtained from the SwissTargetPrediction website and I/R-related genes predicted from the GeneCards website was displayed by Venn diagram, and the PPI network between them was constructed through the STRING website to screen key genes. Meanwhile, GO and KEGG analyses of these genes were performed on the DAVID 6.8 database. PPI network of Vitexin-key genes-signaling pathway was then constructed via STRING website. Molecular docking of Vitexin with key targets was achieved by AutuDock Vina software. Additionally, the expression of MAPK8 and MAPK signaling pathway-related proteins was monitored by Western blot. Besides, the in vivo effect of Vitexin on CIRI was evaluated via a MCAO model. Vitexin could restore the cell viability of HMC3 cells impaired by OGD/R, and inhibited cell apoptosis and the levels of inflammatory factors. The Venn diagram identified 32 common genes betweenVitexin targets and I/R-related genes. Meanwhile, the top 5 genes (PIK3CA, MAPK8, ABL1, JAK2, and HDAC6) with the strongest interactions were screened via the PPI network. The GO and KEGG analyses of the 32 common genes revealed that they were mainly enriched in protein phosphorylation, ErbB signaling pathway, and MAPK signaling pathway. The Vitexin-Genes-Pathways PPI network indicated that the MAPK signaling pathway was sensitive to Vitexin. Molecular docking confirmed that vitexin had a close binding with five key genes. Moreover, Vitexin downregulated the expression of MAPK8 protein and curbed the MAPK signaling pathway. Vitexin could effectively alleviate CIRI, including cerebral infarction and inflammatory response in rats. Through the application of network pharmacology and molecular docking techniques, this study confirmed that Vitexin could strongly bind to the MAPK8 protein, thereby inhibiting its expression and blocking the MAPK signaling pathway to effectively alleviate CIRI.

Research & AI Updates

From the Industry

Quick Reads

Computational Insights into the Selectivity of Lipases in the (-)-Epigallocatechin Gallate (EGCG) Esterification Reaction Based on Molecular Docking.

The lipase-catalyzed esterification reaction of (-)-epigallocatechin gallate (EGCG) is an effective method to improve its lipophilicity. Read more →

AlphaFold2-Guided Cyclic Peptide Stabilizer Design to Target Protein-Protein Interactions.

The control and modulation of protein-protein interactions (PPIs) is of central importance for the majority of biological processes and most biomedical applications. Read more →

Glycosylation Matters: Network Pharmacology-Based and Molecular Docking Analysis of Resveratrol Glycosylated Derivatives on Parkinson’s Disease.

Resveratrol (RV), a natural polyphenol, has been extensively studied for its neuroprotective potential in Parkinson’s Disease (PD), but its clinical translation is limited by poor bioavailability and rapid metabolism. Read more →

A Synthesis of Novel Tetracyclic Azocino[4,3-b]Indole Framework: Combined Spectroscopic, DFT, Molecular Docking, and ADMET Analysis.

The paper describes a new synthetic method for the 1,5-methanoazocino [4,3-b]indole. Read more →

Screening of Natural Inhibitors from Pleurotus ostreatus against PHGDH for Enhancing Antiviral Innate Immunity through Mendelian Randomization, Machine Learning, Molecular Docking, Molecular Dynamics Simulation, and Binding Free Energy Calculation

Antidepressant Mechanisms of L-Theanine in Tea Based on Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulations

Mechanistic insights into PFAS derivatives-induced coronary heart disease and atherosclerotic renal artery stenosis via integrated network toxicology and molecular modeling.

Per- and polyfluoroalkyl substances (PFAS), such as PFHpA, PFOA, PFNA, and PFDA, are persistent environmental pollutants associated with multiple diseases. Read more →

Exploring the Therapeutic Mechanism of Xiehuo Pingtu San in Treating Thyroid Eye Disease Based on Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

Pipeline Tip

Use GPU-accelerated MD refinement to lift model quality in under 2 hours.

Resources & Tools

The protein structure is the language of life; design is its poetry. — Recep Adiyaman

BS HF DK