Article
Immunology
Ana Clara Gazzinelli-Guimaraes, Denise Silva Nogueira, Chiara Cassia Oliveira Amorim, Fabricio Marcus Silva Oliveira, Anderson Coqueiro-Dos-Santos, Samuel Alexandre Pimenta Carvalho, Lucas Kraemer, Fernando Sergio Barbosa, Vanessa Gomes Fraga, Flaviane Vieira Santos, Joseane Camilla de Castro, Remo Castro Russo, Milena Apetito Akamatsu, Paulo Lee Ho, Maria Elena Bottazzi, Peter J. Hotez, Bin Zhan, Daniella Castanheira Bartholomeu, Lilian Lacerda Bueno, Ricardo Toshio Fujiwara
Summary: Control of human ascariasis relies on mass drug administration, but a vaccine should be the primary target for infection control. A multipeptide chimera vaccine, ASCVac-1, demonstrated significant efficacy in reducing parasite count in a mouse model through strong IgG-based Th2 immune responses.
FRONTIERS IN IMMUNOLOGY
(2021)
Article
Immunology
Muhammad Naveed, Allah Rakha Yaseen, Hira Khalid, Urooj Ali, Ali A. Rabaan, Mohamed Garout, Muhammad A. Halwani, Abbas Al Mutair, Saad Alhumaid, Zainab Al Alawi, Yousef N. Alhashem, Naveed Ahmed, Chan Yean Yean
Summary: In this study, a multiple epitope-based vaccine was designed against HPIV-1, and the computational analysis showed that the constructed vaccine model has the potential to combat laryngotracheobronchitis infections caused by HPIV-1.
Article
Immunology
Maritsa Margaroni, Maria Agallou, Evgenia Tsanaktsidou, Olga Kammona, Costas Kiparissides, Evdokia Karagouni
Summary: In this study, a multi-epitope chimeric protein called LeishChim was designed using a reverse vaccinology approach. It was found to be stable, non-allergenic, and immunogenic, with the ability to bind strongly to MHCI and MHCII molecules. Preclinical evaluation in mice demonstrated its potential as a vaccine candidate.
Article
Immunology
Mahreen Nawaz, Asad Ullah, Alhanouf Al-Harbi, Mahboob Ul Haq, Alaa R. Hameed, Sajjad Ahmad, Aamir Aziz, Khadija Raziq, Saifullah Khan, Muhammad Irfan, Riaz Muhammad
Summary: This study aimed to develop a broad-spectrum, multi-epitope vaccine to control bacterial infections and reduce the burden on healthcare systems. A computational framework was used to filter immunogenic vaccine candidates, and the selected candidates were further optimized and analyzed through molecular dynamics simulations. The results showed that the vaccine candidates had strong binding potential with immune receptors and were exposed to the host's immune system.
Article
Infectious Diseases
Dawood Ghafoor, Ayesha Kousar, Waqar Ahmed, Soma Khan, Zia Ullah, Nasir Ullah, Shahzeb Khan, Sadia Ahmed, Zafran Khan, Rida Riaz
Summary: A vaccine candidate was designed against the Hantaan virus using immunoinformatics and reverse vaccinology tools to predict B and T cell epitopes, resulting in a multi-epitope subunit vaccine model. The model was evaluated for physiochemical parameters and docking with TLR-4, showing enhanced immunogenicity by adding Human beta-defensin at the N-terminus. Immune simulations suggested a natural immune response and in-silico cloning in E. coli was successful for maximal vaccine expression. Further experimental verification is needed for immunogenicity and efficacy confirmation against Hantaan virus infections.
INFECTION GENETICS AND EVOLUTION
(2021)
Article
Immunology
Alhumaidi B. Alabbas
Summary: This study developed a multi-epitope-based vaccine against Sin Nombre orthohantavirus using computational methods. The selected epitopes showed potential as antigenic, nonallergenic, nontoxic, and water-soluble components of the vaccine. Molecular docking and simulation analysis demonstrated that the vaccine had good binding affinity with TLR-4 and TLR-8, which are important for inducing an immune response. However, experimental validation is needed to confirm these findings.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Immunology
Ali Forouharmehr
Summary: This study selected 10 antigenic proteins and isolated B cell, MHCI, and MHCII epitopes from them to engineer a poly-epitope vaccine with a molecular adjuvant. The designed vaccine, with 730 amino acids in length and a molecular weight of 77.67 kDa, showed promising features and binding energy for future application.
MICROBIAL PATHOGENESIS
(2021)
Review
Chemistry, Medicinal
Yuan Tan, Faqin Tang
Summary: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may lead to severe and potentially fatal respiratory diseases, and a specific vaccine is crucial for controlling the spread of the disease and reducing mortality rates. The infection activates various immune cells, triggering immune responses, but it may also result in excessive inflammation and pulmonary immunopathology.
MEDICINAL RESEARCH REVIEWS
(2021)
Article
Environmental Sciences
Asad Ullah, Sajjad Ahmad, Saba Ismail, Zobia Afsheen, Muhammad Khurram, Muhammad Tahir ul Qamar, Naif AlSuhaymi, Mahdi H. Alsugoor, Khaled S. Allemailem
Summary: A multi-epitope-based vaccine against Morganella morganii was designed by predicting and selecting five virulent proteins from the pathogen, linking the epitopes and boosting immune responses with the cholera toxin B subunit. Molecular dynamic simulations confirmed the stable conformation and strong binding affinity of the vaccine with receptors, suggesting the potential development of a novel vaccine against M. morganii.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Article
Biochemical Research Methods
Giulia Russo, Elena Crispino, Avisa Maleki, Valentina Di Salvatore, Filippo Stanco, Francesco Pappalardo
Summary: When reverse vaccinology was introduced, it was a computational approach starting from the pathogen's genomic sequence to identify potential proteins and peptides for vaccine production. Over the years, it has evolved into a suite of bioinformatics tools and processes. However, the ability to predict vaccine efficacy is still lacking. This article proposes an advanced immune system simulator to address this gap and applies it to design and predict the efficacy of a potential vaccine against H5N1 influenza.
BMC BIOINFORMATICS
(2023)
Article
Multidisciplinary Sciences
Lu Liu, Wanli Yu, Kuojun Cai, Siyuan Ma, Yanfeng Wang, Yuhui Ma, Hongqiong Zhao
Summary: Through pangenome analysis and reverse vaccinology, 16 potential vaccine candidates for R. equi were identified, and antigenic epitopes with strong immunogenicity were predicted, providing a foundation for the development of a multivalent or universal vaccine.
Article
Environmental Sciences
Hassan N. Althurwi, Khalid M. Alharthy, Faisal F. Albaqami, Ali Altharawi, Muhammad Rizwan Javed, Ziyad Tariq Muhseen, Muhammad Tahir ul Qamar
Summary: This study proposes a bioinformatics approach to design an mRNA-based multi-epitope (MEV) vaccine for preventing EBV infections. By selecting and evaluating specific epitopes, the researchers identified the most potent ones capable of inducing an immune response. Immune simulation results confirmed the potential of the designed vaccine.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Biology
Muhammad Tahir ul Qamar, Sajjad Ahmad, Israr Fatima, Faisal Ahmad, Farah Shahid, Anam Naz, Sumra Wajid Abbasi, Abbas Khan, Muhammad Usman Mirza, Usman Ali Ashfaq, Ling-Ling Chen
Summary: This study used subtractive proteomics assisted reverse vaccinology-based immunoinformatics pipeline to target antigenic proteins for developing a multi-epitope vaccine (MEV) against Staphylococcus aureus infections. Immunoinformatics tools were used to predict T-cell and B-cell epitopes, and a MEV construct with CTL, HTL, and LBL epitopes was designed. Molecular docking and dynamics simulations were performed to validate the interaction of MEV with TLR4 and MHC molecules, showing high antigenicity and stability. Further experimental validations are needed to confirm the effectiveness of the proposed MEV vaccine candidate.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Editorial Material
Virology
Stephanie Ishack, Shari R. Lipner
Summary: The rapid spread of SARS-CoV-2 has resulted in a high number of infections and deaths, highlighting the urgent need for more rapid and precise vaccine design using computational methods.
JOURNAL OF MEDICAL VIROLOGY
(2021)
Editorial Material
Immunology
Jose de la Fuente, Marinela Contreras
Summary: This article introduces the immunological quantum from a historical perspective, supported by bibliometric analysis of quantum vaccine algorithms and describes different vaccinomics and quantum vaccinomics algorithms. Finally, novel platforms and algorithms are proposed for further advancement in quantum vaccinomics. The concept of immune protective epitopes or immunological quantum is mentioned for the design of candidate vaccine antigens, which can elicit a protective immune response. Vaccines play a crucial role in preventing and controlling infectious diseases worldwide.
FRONTIERS IN IMMUNOLOGY
(2023)
Article
Biochemical Research Methods
Avisa Maleki, Giulia Russo, Giuseppe Alessandro Parasiliti Palumbo, Francesco Pappalardo
Summary: This study designed a recombinant multi-epitope vaccine based on a highly conserved epitope of hemagglutinin, neuraminidase, and membrane matrix proteins using an immunoinformatic approach. The vaccine showed good immunological properties and immune response prediction.
BMC BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Giulia Russo, Valentina Di Salvatore, Giuseppe Sgroi, Giuseppe Alessandro Parasiliti Palumbo, Pedro A. Reche, Francesco Pappalardo
Summary: The COVID-19 pandemic has emphasized the importance of using bioinformatics software to quickly develop intervention solutions. Advances in computer modeling and simulation have improved the discovery, development, assessment, and monitoring of therapeutic strategies. The combined use of molecular prediction tools and computer simulation plays a crucial role in predicting the efficacy and safety of new vaccines.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Oncology
G. Catanuto, N. Rocco, A. Maglia, P. Barry, A. Karakatsanis, G. Sgroi, G. Russo, F. Pappalardo, M. B. Nava
Summary: This study used Delphi survey to investigate key factors in the decision making process of surgical oncology on the breast. The results, validated by text mining and natural language processing techniques, indicated that there are specific decision drivers and outcomes recognized by experts in breast cancer surgery decision making.
Article
Engineering, Biomedical
Cristina Curreli, Valentina Di Salvatore, Giulia Russo, Francesco Pappalardo, Marco Viceconti
Summary: This study develops a computer simulation environment that can predict the dose-response of new therapeutic vaccines against tuberculosis, supporting the optimal design of clinical trials. Before using this in silico methodology, it is important to assess the credibility of the predictive model and a risk-informed credibility assessment plan is presented.
ANNALS OF BIOMEDICAL ENGINEERING
(2023)
Article
Biochemical Research Methods
Giuseppe Sgroi, Giulia Russo, Anna Maglia, Giuseppe Catanuto, Peter Barry, Andreas Karakatsanis, Nicola Rocco, Francesco Pappalardo
Summary: This study applies natural language processing and machine learning to predict the context related to Delphi surveys in surgical decision-making, enhancing the usefulness of Delphi surveys and suggesting keywords for evaluation.
BMC BIOINFORMATICS
(2022)
Article
Pharmacology & Pharmacy
Flora T. Musuamba, S. Y. Amy Cheung, Pieter Colin, Elin H. Davies, Jeffrey S. Barret, Francesco Pappalardo, Michael Chappell, Jean-Michel Dogne, Adriana Ceci, Oscar Della Pasqua, Ine S. Rusten
Summary: The benefit/risk balance is the most important question when considering market access for medicinal products. This assessment involves evaluating efficacy, safety, dose selection, pharmacology, and drug quality. However, there is currently no systematic approach to assess and establish the acceptability of alternative methods and data sources, leading to regulatory skepticism toward new data types and methods. To mitigate uncertainties in efficacy and safety characterization, a data-knowledge backbone is needed. This white paper proposes an ecosystem based on a repository, high-quality standards, and credibility assessment for better regulatory decision making.
CLINICAL PHARMACOLOGY & THERAPEUTICS
(2023)
Article
Computer Science, Information Systems
Francesco Pappalardo, John Wilkinson, Francois Busquet, Antoine Bril, Mark Palmer, Barry Walker, Cristina Curreli, Giulia Russo, Thierry Marchal, Elena Toschi, Rossana Alessandrello, Vincenzo Costignola, Ingrid Klingmann, Martina Contin, Bernard Staumont, Matthias Woiczinski, Christian Kaddick, Valentina Di Salvatore, Alessandra Aldieri, Liesbet Geris, Marco Viceconti
Summary: In Silico Trials methodologies will have a significant impact on the development and risk reduction of medical devices in the future. The regulatory pathway for Digital Patient and Personal Health Forecasting solutions is clear, but more complex for In Silico Trials solutions. It is suggested that the European regulatory system should start an innovation process to avoid companies focusing on other markets like the USA.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Article
Biology
Alessia Rondinella, Elena Crispino, Francesco Guarnera, Oliver Giudice, Alessandro Ortis, Giulia Russo, Clara Di Lorenzo, Davide Maimone, Francesco Pappalardo, Sebastiano Battiato
Summary: This paper proposes a framework that exploits an augmented U-Net architecture with a convolutional long short-term memory layer and attention mechanism to segment and quantify multiple sclerosis lesions detected in magnetic resonance images. Quantitative and qualitative evaluation demonstrate that the method outperforms previous state-of-the-art approaches, reporting an overall Dice score of 89% and showing robustness and generalization ability on never seen new test samples of a new dedicated dataset under construction.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Review
Computer Science, Information Systems
Alessio Bottrighi, Marzio Pennisi
Summary: Artificial intelligence, particularly machine learning and deep learning, has become increasingly important in the medical field, with the Italian scientific community playing a key role. Italian researchers have extensively utilized ML and DL techniques in medicine over the past five years, addressing a wide range of medical problems and contributing to advancements in the field.
Article
Biochemistry & Molecular Biology
Avisa Maleki, Elena Crispino, Serena Anna Italia, Valentina Di Salvatore, Maria Assunta Chiacchio, Fianne Sips, Roberta Bursi, Giulia Russo, Davide Maimone, Francesco Pappalardo
Summary: Multiple sclerosis is an autoimmune inflammatory disease that affects the central nervous system. Universal Immune System Simulator can be potentially used to predict the effects of treatments against multiple sclerosis. The retrospective validation of UISS-MS with clinical data confirms its ability to simulate the mechanisms and outcomes of treatments.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Biochemical Research Methods
Giulia Russo, Giuseppe Alessandro Parasiliti Palumbo, Marzio Pennisi, Francesco Pappalardo
Summary: This article introduces an automatic tool for the verification assessment of mechanistic Agent-Based Models and demonstrates its application through a case study of an Agent-Based Model in silico trial. The described workflow allows researchers and practitioners to easily perform verification steps and provide strong evidence for further regulatory requirements.
BMC BIOINFORMATICS
(2022)
Article
Biochemistry & Molecular Biology
Francesco Pappalardo, Giulia Russo, Emanuela Corsini, Alicia Paini, Andrew Worth
Summary: The identification of immunotoxicity hazard aims to assess the unintended effects of chemical exposure on the immune system. Perfluorinated alkylate substances (PFAS) have been found to be immunotoxic and associated with lower antibody responses and increased susceptibility to diseases. Mathematical modeling and simulation platforms can be utilized to evaluate the adverse effects of immunotoxicants. The Universal Immune System Simulator demonstrates the potential for assessing immunotoxicity through computational models.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
