Recep Adiyaman
Vision About Experience Education Skills Publications Tools Newsletter Updates Podcasts Blog Contact CV Subscribe
All Issues
Older Newer
Daily Signal March 10, 2026 · 9 min read

Issue #64: scDock: Streamlining drug discovery targeting cell-cell communication via scRNA-seq analysis and molecular docking.

Protein Design Digest - 2026-03-10 - scDock: Streamlining drug discovery targeting cell-cell communication via scRNA-seq analysis and molecular docking.

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

scDock: Streamlining drug discovery targeting cell-cell communication via scRNA-seq analysis and molecular docking.

Summary Identifying drugs that target intercellular communication networks represents a promising therapeutic strategy, yet linking single-cell RNA sequencing (scRNA-seq) analysis to structure-based drug screening remains technically challenging and requires substantial bioinformatics expertise. We present scDock, an integrated and user-friendly pipeline that seamlessly connects scRNA-seq data processing, cell-cell communication inference, and molecular docking-based drug discovery. Through a single configuration file, users can execute the complete workflow, from raw scRNA-seq data to ranked drug candidates, without programming skills. scDock automates the identification of disease-relevant ligand-receptor interactions from scRNA-seq data and performs structure-based virtual screening against these communication targets using Protein Data Bank (PDB) or AlphaFold-predicted protein structures. The pipeline generates comprehensive outputs at each stage, enabling users to explore intercellular signaling alterations and discover therapeutic compounds targeting specific cell-cell communications. scDock addresses a critical gap by providing an accessible end-to-end solution for communication-targeted drug discovery from single-cell data. Availability and implementation scDock is freely available at https://doi.org/10.6084/m9.figshare.31370368 and https://github.com/Andrewneteye4343/scDock. It is implemented in R, Python, shell scripts, and supports Linux systems, including Ubuntu and Debian. Supplementary information Supplementary data are available at Bioinformatics online.

Why this matters: Enhances small-molecule or peptide docking accuracy for targeted drug discovery.

Also Worth Reading

Exploring the Mechanism of Action of Chicoric Acid Against Influenza Virus Infection Based on Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation.

This study theoretically explores the mechanism of action of Chicoric acid against influenza virus based on network pharmacology, molecular docking, and molecular dynamics simulation techniques, aiming to provide insights for the development of new veterinary drugs for influenza. Potential targets for influenza virus action were identified using the PharmMapper (i.e. Version 2017) server and disease databases including GeneCards and OMIM. The STRING online analysis platform and Cytoscape 3.9.1 software were employed to construct a protein-protein interaction (PPI) network of the target proteins, followed by topological analysis to screen for key targets. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the intersecting targets using the DAVID database. A “drug-target-pathway” network diagram was constructed using Cytoscape 3.9.1 software. Molecular docking was carried out with AutoDock 1.5.6 and PyMOL 2.5 software to identify dominant binding targets, followed by molecular dynamics simulation analysis. The results of network analysis showed that there were 31 potential targets of Chicoric acid; the protein interaction network suggested that UBC, UBA52, RPS27A, HCK, and CDKN1B may be the core targets of Chicoric acid; 55 cell biological processes were obtained by GO enrichment analysis, and 15 related signaling pathways were obtained by KEGG pathway enrichment analysis; molecular docking showed that UBC and UBA52 had a good affinity to Chicoric acid and may be the dominant target of Chicoric acid exerting its effect. Chicoric acid may play a role in antiviral activity by acting on the dominant protein of UBC and UBA52, thus achieving an anti-influenza virus effect.

A multimodal approach integrating spectroscopy, deep learning guided molecular docking, and molecular dynamics simulation for predictive assessment of pioglitazone to albumin binding for formulation development.

Binding affinity is a critical parameter that can influence the state of the drug in vivo and help to define the formulation strategy. The current study implements a multimodal approach to analyse the binding affinity between human serum albumin (HSA) and pioglitazone. Ultraviolet (UV) absorbance and fluorescence spectrometry analyses were performed on different combinations of HSA and pioglitazone complexes, and the absorbance and fluorescence intensities were mapped to calculate the binding constant. DynamicBind, a distinct deep-learning artificial intelligence tool, was implemented to perform in silico docking studies using a non-conventional approach. Furthermore, molecular dynamics simulation was also performed to generate root mean square deviation, radius of gyration, and root mean square fluctuation values, followed by principal component analysis, probability distribution function, and free energy landscape analysis. The simulation output was analysed to interpret the binding affinity and associated conformation of the protein-active pharmaceutical ingredient (API) complex. The binding constant calculated through UV analysis was 1.1 × 10 4 M -1 . Fluorescence spectroscopic analysis derived a value of 1.7 × 10 5 M -1 . At the same time, DynamicBind predicted the cLDDT score for the top predicted model to be 0.634, and a binding affinity value of greater than 5, indicating a relatively moderate binding between pioglitazone and HSA. The results from molecular dynamics simulations further complemented our earlier observations, indicating non-covalent binding interactions and a stable protein-API complex, which is desirable for developing a formulation using HSA as a carrier polymer. This orthogonal approach also provided critical information on the fate of the API and possible considerations that needed to be made during the design of the formulation process, highlighting the need for similar approaches that could provide multifaceted advantages and help in optimising R&D costs and timelines.

Binding interactions of Trametes villosa and Trametes lactinea laccases with 4-nonylphenol and its intermediates: molecular docking and molecular dynamics approaches.

Emerging pollutants such as 4-nonylphenol (4-NP) act as endocrine disruptors and have been associated with reproductive toxicity in humans and wildlife, as well as with physiological disturbances in aquatic, terrestrial, and plant organisms. Laccases are oxidoreductases with notable biotechnological relevance and the ability to oxidize phenolic pollutants, making them attractive candidates for biodegradation strategies. This study investigated the interactions between laccases from Trametes villosa and Trametes lactinea and 4-NP and its degradation intermediates via molecular docking and molecular dynamics simulations (MDS). Ligands were geometrically optimized using the PM7 semiempirical method, and their global reactivity descriptors were computed to explore correlations between electronic properties and laccase binding affinity. Docking revealed favorable binding energies (ΔG bind ≈ -6 kcal·mol -1 ) and recurrent interactions with key amino acid residues, including Ala, Glu, Leu, Phe, Pro, Ser, Val, and His, mainly through hydrogen bonding and hydrophobic contacts. The MDS confirmed the stability of the enzyme-ligand complexes, as indicated by low root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values, along with consistent radius of gyration and solvent-accessible surface areas throughout the trajectories. Binding free energy calculations using the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method indicated stronger binding affinity under solvation, with ΔG bind values of -26.45 and -17.73 kcal·mol -1 for T. villosa and T. lactinea, respectively, highlighting hydrophobic and van der Waals contributions as the primary stabilizing forces. Overall, these results provide computational evidence that laccases from T. villosa and T. lactinea have potential for application in the oxidative biodegradation of 4-NP. These findings advance the molecular understanding of fungal laccase‒pollutant interactions and support future in vitro validation and protein engineering strategies aimed at enhancing biodegradation efficiency.

Research & AI Updates

From the Industry

Quick Reads

Phytochemical Profiling, Antioxidant, and Broad-Spectrum Antimicrobial Activities of Origanum vulgare Essential Oil with Molecular Docking and ADME Insights.

This study evaluated the chemical composition, antimicrobial, antioxidant, and pharmacological properties of Origanum vulgare essential oil (OVEO). Read more →

Inhibitory effects of three genuine resin glycosides from Calystegia hederacea on in vitro porcine lipase assay and in silico docking simulation analysis.

Resin glycosides are characteristically present in Convolvulaceae plants. Read more →

MML-DTI: Multimanifold Learning with Hyperbolic Graph Neural Networks for Enhanced Drug-Target Interaction Prediction.

Accurately predicting drug-target interactions (DTIs) is crucial for drug discovery, repositioning. Read more →

mSphere of Influence: The power of in situ-structural biology without leaving “home”.

Nicholas A. Read more →

Benzo[d]imidazole anchored oxadiazole derivatives: synthesis, characterization, biological evaluation, in silico docking and ADME-T analysis.

A novel series of 1,2,4-oxadiazoles based on benzo[d]imidazole-1,3,4-oxadiazole fused 1,2,4-oxadiazoles, were synthesised. Read more →

Novel phenylamino pyrimidine derivatives as potent and selective inhibitors of ABL1 tyrosine kinase for targeted anticancer therapy.

Phenyl amino pyrimidine (PAP) derivatives represent a promising scaffold in anticancer drug discovery due to their potential to selectively inhibit tyrosine kinase (TK) enzymes implicated in tumor progression. Read more →

In vitro bioactivities and molecular docking analysis of methanolic extract from Phoenix dactylifera L. (cv. Ghars) seeds.

Integrated network toxicology and transcriptomics analysis reveals the pathogenic mechanisms in DBP/MBP-induced MASLD/MASH.

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) and Metabolic Dysfunction-Associated Steatohepatitis (MASH) are challenging public health worldwide, with multifactorial pathogenic mechanisms. Read more →

Pipeline Tip

Verify FASTA headers for special characters that break Rosetta pipelines.

Resources & Tools

Deep learning is not a magic wand, but a powerful lens for structural biology. — Recep Adiyaman

BS HF DK