Antonio Lavecchia

8.2k total citations · 4 hit papers
170 papers, 6.3k citations indexed

About

Antonio Lavecchia is a scholar working on Molecular Biology, Organic Chemistry and Pharmacology. According to data from OpenAlex, Antonio Lavecchia has authored 170 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 122 papers in Molecular Biology, 46 papers in Organic Chemistry and 22 papers in Pharmacology. Recurrent topics in Antonio Lavecchia's work include Peroxisome Proliferator-Activated Receptors (37 papers), Synthesis and biological activity (16 papers) and Metabolism, Diabetes, and Cancer (15 papers). Antonio Lavecchia is often cited by papers focused on Peroxisome Proliferator-Activated Receptors (37 papers), Synthesis and biological activity (16 papers) and Metabolism, Diabetes, and Cancer (15 papers). Antonio Lavecchia collaborates with scholars based in Italy, Germany and India. Antonio Lavecchia's co-authors include Ettore Novellino, Carmen Di Giovanni, Carmen Cerchia, Fulvio Loiodice, Luciana Marinelli, Antonio Laghezza, Marino Artico, Paolo Tortorella, Romano Silvestri and Giuseppe La Regina and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

Antonio Lavecchia

166 papers receiving 6.2k citations

Hit Papers

Machine-learning approaches in drug discovery: methods an... 2013 2026 2017 2021 2014 2013 2024 2025 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Machine-learning approaches in drug discovery: methods and applications
    2014 521 citations Antonio Lavecchia Drug Discovery Today profile →
  2. Virtual Screening Strategies in Drug Discovery: A Critical Review
    2013 461 citations Antonio Lavecchia et al. profile →
  3. Unleashing the power of generative AI in drug discovery
    2024 64 citations Amit Gangwal, Antonio Lavecchia Drug Discovery Today profile →
  4. Artificial intelligence in preclinical research: enhancing digital twins and organ-on-chip to reduce animal testing
    2025 23 citations Amit Gangwal, Antonio Lavecchia Drug Discovery Today profile →

Peers

Antonio Lavecchia
György M. Keserű Hungary
Antti Poso Finland
Shengyong Yang China
Giulio Rastelli Italy
Paul C. Sanschagrin United States
Michael Gütschow Germany
Liangren Zhang China
Richard D. Taylor United Kingdom
Miles Congreve United Kingdom
Ajit Jadhav United States
György M. Keserű Hungary
Antonio Lavecchia
Citations per year, relative to Antonio Lavecchia Antonio Lavecchia (= 1×) peers György M. Keserű

Countries citing papers authored by Antonio Lavecchia

Since Specialization
Citations

This map shows the geographic impact of Antonio Lavecchia's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Antonio Lavecchia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Antonio Lavecchia more than expected).

Fields of papers citing papers by Antonio Lavecchia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Antonio Lavecchia. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Antonio Lavecchia. The network helps show where Antonio Lavecchia may publish in the future.

Co-authorship network of co-authors of Antonio Lavecchia

This figure shows the co-authorship network connecting the top 25 collaborators of Antonio Lavecchia. A scholar is included among the top collaborators of Antonio Lavecchia based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Antonio Lavecchia. Antonio Lavecchia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gangwal, Amit & Antonio Lavecchia. (2025). Artificial intelligence in anti-obesity drug discovery: unlocking next-generation therapeutics. Drug Discovery Today. 30(4). 104333–104333. 3 indexed citations
2.
Napolitano, Filomena, Giuseppina Minopoli, Silvia Bagnoli, et al.. (2025). Targeting RPSA to modulate endosomal trafficking and amyloidogenesis in genetic Alzheimer's disease. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1871(5). 167753–167753. 1 indexed citations
3.
Lavecchia, Antonio. (2025). Explainable Artificial Intelligence in Drug Discovery: Bridging Predictive Power and Mechanistic Insight. Wiley Interdisciplinary Reviews Computational Molecular Science. 15(5). 1 indexed citations
4.
Delre, Pietro, Carmen Cerchia, & Antonio Lavecchia. (2025). Artificial intelligence in the development of small nucleic acid therapeutics: toward smarter and safer medicines. Drug Discovery Today. 30(11). 104488–104488.
5.
Laghezza, Antonio, Federica Gilardi, Aurélien Thomas, et al.. (2025). A new potent and selective peroxisome proliferator-activated receptor alpha partial agonist displays anti-steatotic effects In vitro and behaves as a safe hypolipidemic and hypoglycemic agent in a diabetic mouse model. European Journal of Medicinal Chemistry. 289. 117494–117494. 1 indexed citations
6.
7.
Laghezza, Antonio, Carmen Cerchia, Inmaculada Fernández, et al.. (2024). Synthesis and in vitro cytotoxicity of benzoxazole‐based PPARα/γ antagonists in colorectal cancer cell lines. Archiv der Pharmazie. 357(9). e2400086–e2400086. 4 indexed citations
8.
Napolitano, Filomena, Francesca Wanda Rossi, Amato de Paulis, Antonio Lavecchia, & Nunzia Montuori. (2024). The Crosstalk between N-Formyl Peptide Receptors and uPAR in Systemic Sclerosis: Molecular Mechanisms, Pathogenetic Role and Therapeutic Opportunities. International Journal of Molecular Sciences. 25(6). 3156–3156. 1 indexed citations
9.
Mercuri, Antonella, et al.. (2024). Cladosporols and PPARγ: Same Gun, Same Bullet, More Targets. Biomolecules. 14(8). 998–998. 1 indexed citations
10.
Laghezza, Antonio, Carmen Cerchia, Erica Pranzini, et al.. (2023). A New Antidiabetic Agent Showing Short- and Long-Term Effects Due to Peroxisome Proliferator-Activated Receptor Alpha/Gamma Dual Agonism and Mitochondrial Pyruvate Carrier Inhibition. Journal of Medicinal Chemistry. 66(5). 3566–3587. 5 indexed citations
11.
Cerchia, Carmen, Emanuela Roscetto, Rosarita Nasso, et al.. (2022). In Silico Identification of Novel Inhibitors Targeting the Homodimeric Interface of Superoxide Dismutase from the Dental Pathogen Streptococcus mutans. Antioxidants. 11(4). 785–785. 6 indexed citations
12.
Cerchia, Carmen, Antonio Laghezza, Luca Piemontese, et al.. (2022). A chemoinformatics search for peroxisome proliferator-activated receptors ligands revealed a new pan-agonist able to reduce lipid accumulation and improve insulin sensitivity. European Journal of Medicinal Chemistry. 235. 114240–114240. 7 indexed citations
13.
Veneruso, Iolanda, Antonella Izzo, Maurizio Renna, et al.. (2022). Activation of Non-Canonical Autophagic Pathway through Inhibition of Non-Integrin Laminin Receptor in Neuronal Cells. Cells. 11(3). 466–466. 6 indexed citations
14.
Corvino, Angela, Ida Cerqua, Giuseppe Caliendo, et al.. (2021). Antagonizing S1P3 Receptor with Cell-Penetrating Pepducins in Skeletal Muscle Fibrosis. International Journal of Molecular Sciences. 22(16). 8861–8861. 2 indexed citations
15.
Tilekar, Kalpana, Neha Upadhyay, Antonio Laghezza, et al.. (2021). Thiazolidinedione “Magic Bullets” Simultaneously Targeting PPARγ and HDACs: Design, Synthesis, and Investigations of their In Vitro and In Vivo Antitumor Effects. Journal of Medicinal Chemistry. 64(10). 6949–6971. 29 indexed citations
16.
Izzo, Antonella, Nunzia Mollo, Filomena Napolitano, et al.. (2020). Inhibition of 37/67kDa Laminin-1 Receptor Restores APP Maturation and Reduces Amyloid-β in Human Skin Fibroblasts from Familial Alzheimer’s Disease. Journal of Personalized Medicine. 10(4). 232–232. 11 indexed citations
17.
Ammazzalorso, Alessandra, Isabella Bruno, Rosalba Florio, et al.. (2020). Sulfonimide and Amide Derivatives as Novel PPARα Antagonists: Synthesis, Antiproliferative Activity, and Docking Studies. ACS Medicinal Chemistry Letters. 11(5). 624–632. 16 indexed citations
18.
Ettari, Roberta, Carmen Cerchia, Ettore Novellino, et al.. (2019). Development of Novel Amides as Noncovalent Inhibitors of Immunoproteasomes. ChemMedChem. 14(8). 842–852. 19 indexed citations
19.
Laghezza, Antonio, Luca Piemontese, Carmen Cerchia, et al.. (2018). Identification of the First PPARα/γ Dual Agonist Able To Bind to Canonical and Alternative Sites of PPARγ and To Inhibit Its Cdk5-Mediated Phosphorylation. Journal of Medicinal Chemistry. 61(18). 8282–8298. 33 indexed citations
20.
Cosconati, Sandro, Luciana Marinelli, Antonio Lavecchia, & Ettore Novellino. (2007). Characterizing the 1,4-Dihydropyridines Binding Interactions in the L-Type Ca 2+ Channel:  Model Construction and Docking Calculations. Journal of Medicinal Chemistry. 50(7). 1504–1513. 85 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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