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25th Anniversary of IJMS: Updates and Advances in Molecular Informatics

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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: 20 August 2026 | Viewed by 7398

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Dr. M. Natália D.S. Cordeiro

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LAQV-REQUIMTE, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
Interests: molecular modelling and simulations; first principle calculations; machine learning tools; material sciences; catalysis; drug design; environmental chemistry
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Prof. Dr. Giulio Vistoli

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Department of Pharmaceutical Sciences, Università degli Studi di Milano, via Mangiagalli 25, 20133 Milano, Italy
Interests: computational chemistry; drug design; cheminformatics; molecular docking; ADME predictions; lipophilicity
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Special Issue Information

Dear Colleagues,

This Special Issue commemorates the 25th anniversary of the International Journal of Molecular Sciences (IJMS), celebrating a quarter-century of pioneering research in the molecular sciences. We invite submissions that reflect on major advances in molecular informatics over this period and highlight emerging directions for the field. As molecular data continues to grow exponentially, molecular informatics plays a critical role in decoding complex biological and chemical systems, accelerating discovery, and fostering innovation.

This Special Issue aims to provide a comprehensive overview of current methodologies, applications, and theoretical developments. We encourage contributions that demonstrate the impact of molecular informatics across a wide range of areas, including drug discovery, materials science, systems biology, and the integration of artificial intelligence in molecular research. Join us in celebrating this milestone by sharing your innovative work and shaping the future of molecular informatics.

Dr. M. Natália D.S. Cordeiro
Prof. Dr. Giulio Vistoli
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

AI-guided drug repurposing
virtual screening in personalized medicine
machine learning for toxicity prediction
network-based biomarkers in complex diseases
in silico pharmacokinetics and ADMET profiling
data-driven materials design
deep learning for molecular property prediction
AI-assisted nanomaterial synthesis
systems biology models for metabolic engineering

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Published Papers (7 papers)

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Research

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12 pages, 1977 KB

Open AccessArticle

Population-Scale Plasma Proteomic Profiles Associated with Chronic Periodontitis in the UK Biobank

by Su Kang Kim, Min Kyoung Kim, Sang Wook Kang and Ju Yeon Ban

Int. J. Mol. Sci. 2026, 27(5), 2514; https://doi.org/10.3390/ijms27052514 - 9 Mar 2026

Viewed by 627

Abstract

Periodontitis is a chronic infectious disease characterized by the destruction of the tooth-supporting tissues, including the gingiva, periodontal ligament, and alveolar bone, which may ultimately lead to tooth loss. However, blood-based biomarkers reflecting systemic inflammation in periodontitis remain poorly defined. We analyzed plasma proteomic data from the UK Biobank using Olink Explore proteomics to identify systemic protein signatures distinguishing chronic periodontitis patients (n = 90) from healthy controls (n = 2234). Among 2151 proteins passing quality control, 29 proteins showed significant differential expression (FDR < 1.0 × 10⁻⁵). Growth differentiation factor 15 (GDF15) exhibited the strongest upregulation (mean NPX: −0.183 to 0.157, effect size = 0.337, FDR = 2.82 × 10⁻¹²), followed by N-terminal pro-B-type natriuretic peptide (NT-proBNP) (effect size = 0.594), Interleukin-6 (IL-6) (effect size = 0.450), and Insulin-like growth factor binding protein-(4IGFBP4) (effect size = 0.269). Multiple TNF receptor superfamily members (TNFRSF1A/1B, TNFRSF10A/10B) and proteins involved in extracellular matrix remodeling (COL6A3, ADAM12) and vascular stress (ADM) were significantly elevated. In contrast, EGFR and DNER showed decreased expression. Protein–protein interaction network analysis revealed IL-6 as a central hub protein forming a tightly interconnected cluster with TNF receptor family members. These findings indicate systemic plasma protein profiles associated with chronic periodontitis within this population-based cohort. The identified proteins may provide a basis for future evaluation of blood-based biomarkers for chronic periodontitis, pending further validation. Full article

(This article belongs to the Special Issue 25th Anniversary of IJMS: Updates and Advances in Molecular Informatics)

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23 pages, 4932 KB

Open AccessArticle

Library Preparation Biases Plant Virome Detection: Poly(A) mRNA Enrichment vs. rRNA Depletion in Pepper and Garlic

by Hoseong Choi, Dong Woo Kang, Yeonhwa Jo, Jisoo Park, Dongjoo Min, Gyeong Geun Min, Jisu Kim, Chaemin Shin, Jin-Sung Hong and Won Kyong Cho

Int. J. Mol. Sci. 2026, 27(5), 2300; https://doi.org/10.3390/ijms27052300 - 28 Feb 2026

Viewed by 575

Abstract

High-throughput RNA sequencing reveals plant viromes, but library preparation methods may bias viral detection. Here, we compared rRNA-depleted total RNA-seq and poly(A)-selected mRNA-seq using field-collected pepper leaves (Anseong and Jincheon) and garlic cloves (Hoengseong) from Korean commercial fields. rRNA-depleted total RNA-seq consistently recovered more viruses, longer contigs, and complete multipartite DNA virus genomes (e.g., milk vetch dwarf virus components, tomato spotted wilt virus segments), while mRNA-seq was dominated by highly expressed polyadenylated viruses like broad bean wilt virus 2. In Jincheon pepper, mRNA-seq missed hot pepper endornavirus, pepper cryptic virus 2, and multiple milk vetch dwarf virus segments revealed by total RNA-seq. Garlic libraries showed similar patterns, with total RNA-seq additionally detecting low-titer RNA viruses likely representing contamination. rRNA-depleted total RNA-seq provides a more complete, less biased view of plant viromes and is recommended for comprehensive virus discovery and genome reconstruction, while mRNA-seq remains useful for polyadenylated virus quantification and host gene expression analysis alongside virome profiling. Full article

(This article belongs to the Special Issue 25th Anniversary of IJMS: Updates and Advances in Molecular Informatics)

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24 pages, 1821 KB

Open AccessArticle

PepScorer::RMSD: An Improved Machine Learning Scoring Function for Protein–Peptide Docking

by Andrea Giuseppe Cavalli, Giulio Vistoli, Alessandro Pedretti, Laura Fumagalli and Angelica Mazzolari

Int. J. Mol. Sci. 2026, 27(2), 870; https://doi.org/10.3390/ijms27020870 - 15 Jan 2026

Viewed by 1035

Abstract

Over the past two decades, pharmaceutical peptides have emerged as a powerful alternative to traditional small molecules, offering high potency, specificity, and low toxicity. However, most computational drug discovery tools remain optimized for small molecules and need to be entirely adapted to peptide-based compounds. Molecular docking algorithms, commonly employed to rank drug candidates in early-stage drug discovery, often fail to accurately predict peptide binding poses due to their high conformational flexibility and scoring functions not being tailored to peptides. To address these limitations, we present PepScorer::RMSD, a novel machine learning-based scoring function specifically designed for pose selection and enhancement of docking power (DP) in virtual screening campaigns targeting peptide libraries. The model predicts the root-mean-squared deviation (RMSD) of a peptide pose relative to its native conformation using a curated dataset of protein–peptide complexes (3–10 amino acids). PepScorer::RMSD outperformed conventional, ML-based, and peptide-specific scoring functions, achieving a Pearson correlation of 0.70, a mean absolute error of 1.77 Å, and top-1 DP values of 92% on the evaluation set and 81% on an external test set. Our PLANTS-based workflow was benchmarked against AlphaFold-Multimer predictions, confirming its robustness for virtual screening. PepScorer::RMSD and the curated dataset are freely available in Zenodo Full article

(This article belongs to the Special Issue 25th Anniversary of IJMS: Updates and Advances in Molecular Informatics)

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19 pages, 2897 KB

Open AccessArticle

Functional Analysis of Hyaluronidase-like Genes in Ovarian Development of Macrobrachium nipponense and Comparative Evaluation with Other Key Regulatory Genes

by Zhiming Wang, Hao Dong, Hui Qiao, Wenyi Zhang, Shubo Jin, Yiwei Xiong, Zhenghao Ye, Yan Gong, Sufei Jiang and Hongtuo Fu

Int. J. Mol. Sci. 2025, 26(21), 10748; https://doi.org/10.3390/ijms262110748 - 5 Nov 2025

Viewed by 813

Abstract

This study conducted a bioinformatic analysis of two Hyaluronidase-like isoforms (Mn-HyaL1 and Mn-HyaL2) in Macrobrachium nipponense and investigated their phylogenetic relationships. The open reading frames of Mn-HyaL1 and Mn-HyaL2 were 1101 bp (encoding 366 amino acids) and 1164 bp (encoding 387 amino acids), respectively. Both isoforms exhibited similar conserved domains, with an amino acid sequence similarity of 60.21%. Quantitative PCR analysis revealed that the expression levels of Mn-HyaL1 and Mn-HyaL2 increased during the mid-to-late phase of each developmental stage, were higher during the reproductive season than in the non-reproductive season, and were more abundant in the hepatopancreas than in other tissues. RNA interference experiments targeting both genes simultaneously demonstrated that knockdown of Mn-HyaL2 significantly accelerated ovarian development in M. nipponense, indicating that Mn-HyaL genes function as negative regulators of ovarian maturation. A comparative analysis of multiple genes revealed the following descending order of potency in promoting ovarian development in M. nipponense: Mn-Cholesterol 7-desaturase > Mn-Cathepsin L1. The order of potency in inhibiting ovarian development in M. nipponense, from strongest to weakest, was determined to be Mn-Gonad-inhibiting hormone > Mn-HyaL2. Full article

(This article belongs to the Special Issue 25th Anniversary of IJMS: Updates and Advances in Molecular Informatics)

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13 pages, 1868 KB

Open AccessArticle

Deep Sequencing Analysis of Hepatitis C Virus Subtypes and Resistance-Associated Substitutions in Genotype 4 Patients Resistant to Direct-Acting Antiviral (DAA) Treatment in Egypt

by Damir Garcia-Cehic, Asmaa Mosbeh, Heba A. Gad, Asmaa Ibrahim Gomaa, Marta Ibañez Lligoña, Josep Gregori, Sergi Colomer-Castell, Carolina Campos, Francisco Rodriguez-Frias, Juan Ignacio Esteban, Mohamed S. Kohla, Mohamed Helmy Abdel-Rahman and Josep Quer

Int. J. Mol. Sci. 2025, 26(21), 10649; https://doi.org/10.3390/ijms262110649 - 31 Oct 2025

Viewed by 1011

Abstract

Egypt has the highest global prevalence of hepatitis C virus (HCV), with genotype 4 (G4) in over 94% of cases. Direct-acting antivirals (DAAs) yield sustained virologic response (SVR) rates above 95%. Second-generation DAAs are recommended for patients with virological failure, achieving over 90% eradication. This study aimed to classify and evaluate the pattern of HCV resistance-associated substitutions (RASs) in patients who failed DAA treatment in Egypt. A total of 1778 chronically infected HCV patients from Egypt’s Nile Delta were enrolled (2016–2018). Among them, 37 relapsed, and high-quality serum samples from 22 patients were available, including 6 cases with pre- and post-treatment samples. Next-generation sequencing (NGS) was performed for HCV subtyping and RAS identification. Among the 22 analyzed cases, 21 (95.4%) were G4: 11 were classified as subtype G4a, seven G4o, and three G4m. One patient (4.5%) was identified as G1g. One case shifted from G4a pre- to G4o post-treatment, suggesting reinfection. The RAS pattern in rare G4 subtypes (G4m/G4o) differs from the G4a subtype. The combination of L28M/L30S mutations was detected in 8/11 G4a samples; in contrast, RASs in G4o were characterized by T30S or Y93C/H/N/S substitutions. Notably, some substitutions identified as RASs may represent fixed polymorphisms in regional viral populations, such as those in Egypt’s Nile Delta. HCV subtypes significantly influence the RAS pattern, particularly within the NS5A region, after DAA-treatment failure. The RAS pattern differs among G4 subtypes, particularly in rare ones, predisposing patients to resistance and underscoring the importance of NGS in regional populations to optimize treatment strategies. Full article

(This article belongs to the Special Issue 25th Anniversary of IJMS: Updates and Advances in Molecular Informatics)

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23 pages, 4383 KB

Open AccessArticle

Gaussian Accelerated Molecular Dynamics Simulations Combined with NRIMD to Explore the Mechanism of Substrate Selectivity of Cid1 Polymerase for Different Nucleoside Triphosphates

by Hanwen Liu, Xue Zhou, Haohao Wang, Fuyan Cao and Weiwei Han

Int. J. Mol. Sci. 2025, 26(19), 9325; https://doi.org/10.3390/ijms26199325 - 24 Sep 2025

Cited by 1 | Viewed by 1167

Abstract

Cid1 protein is a crucial component in the RNA interference pathway and abnormal nuclear RNA turnover processes, primarily responsible for adding uridine to the 3′ end of RNA. Cid1 exhibits selective polymerization of UTP over other nucleoside triphosphates. To explore the mechanism of this selectivity, five systems: free-Cid1, Cid1-ATP, Cid1-UTP, Cid1-CTP, and Cid1-GTP with 500 ns Gaussian accelerated molecular dynamics (GaMD) simulations were performed to investigate conformational changes and binding affinities between substrates and Cid1. The results showed that UTP formed stronger and more numerous non-covalent interactions with Cid1 compared to the other three substrates. The Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) binding energy analysis revealed a substrate preference for Cid1 polymerase in the order of UTP, followed by ATP, CTP, and GTP. These findings provide theoretical insights into the substrate selectivity mechanism of Cid1 and provide theoretical clues for the design and modification of Cid1 polymerase. Full article

(This article belongs to the Special Issue 25th Anniversary of IJMS: Updates and Advances in Molecular Informatics)

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Review

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32 pages, 1215 KB

Open AccessReview

Integration of Bulk and Single-Cell RNA Sequencing Analyses in Biomedicine

by Nikita Golushko and Anton Buzdin

Int. J. Mol. Sci. 2026, 27(7), 3334; https://doi.org/10.3390/ijms27073334 - 7 Apr 2026

Viewed by 947

Abstract

Transcriptome profiling is a cornerstone of functional genomics, enabling the detailed characterization of gene expression in health and disease. Bulk RNA sequencing (bulk RNAseq) remains the most widely used approach in clinical and large-cohort studies due to its cost-effectiveness, robustness, and comprehensive transcriptome coverage. However, bulk RNAseq inherently averages gene expression signals across heterogeneous cell populations, thereby masking cellular diversity and obscuring rare cell types. In contrast, single-cell RNA sequencing (scRNAseq) enables a high-resolution analysis of cellular heterogeneity, allowing the identification of distinct cell types, transitional states, and developmental trajectories. Nevertheless, scRNAseq is associated with higher cost, limited scalability, increased technical noise, sparse expression matrices, and protocol-dependent biases introduced during tissue dissociation or nuclear isolation. In this review, we summarize the conceptual and methodological foundations of integrating bulk RNAseq and scRNAseq data, emphasizing their complementary strengths and limitations. We discuss how scRNAseq-derived cell-type atlases can serve as reference matrices for computational reconstruction (deconvolution) of bulk RNAseq profiles and examine key sources of technical and biological variability. Furthermore, we outline major integration strategies, including reference-based deconvolution, pseudobulk aggregation, and Bayesian joint modeling to provide an overview of widely used analytical tools and essential components of scRNAseq data processing workflows. Full article

(This article belongs to the Special Issue 25th Anniversary of IJMS: Updates and Advances in Molecular Informatics)

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