|
1
|
Meng F, Zhou N, Hu G, Liu R, Zhang Y, Jing M, Hou Q. A comprehensive overview of recent advances in generative models for antibodies. Comput Struct Biotechnol J 2024; 23:2648-2660. [PMID: 39027650 PMCID: PMC11254834 DOI: 10.1016/j.csbj.2024.06.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 06/15/2024] [Accepted: 06/18/2024] [Indexed: 07/20/2024] Open
Abstract
Therapeutic antibodies are an important class of biopharmaceuticals. With the rapid development of deep learning methods and the increasing amount of antibody data, antibody generative models have made great progress recently. They aim to solve the antibody space searching problems and are widely incorporated into the antibody development process. Therefore, a comprehensive introduction to the development methods in this field is imperative. Here, we collected 34 representative antibody generative models published recently and all generative models can be divided into three categories: sequence-generating models, structure-generating models, and hybrid models, based on their principles and algorithms. We further studied their performance and contributions to antibody sequence prediction, structure optimization, and affinity enhancement. Our manuscript will provide a comprehensive overview of the status of antibody generative models and also offer guidance for selecting different approaches.
Collapse
Affiliation(s)
- Fanxu Meng
- College of Chemical Engineering, Qingdao University of Science and Technology, Qingdao 266042, China
| | - Na Zhou
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250100, China
- National Institute of Health Data Science of China, Shandong University, Jinan 250100, China
| | - Guangchun Hu
- School of Information Science and Engineering, University of Jinan, Jinan 250022, China
| | - Ruotong Liu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250100, China
- National Institute of Health Data Science of China, Shandong University, Jinan 250100, China
| | - Yuanyuan Zhang
- College of Chemical Engineering, Qingdao University of Science and Technology, Qingdao 266042, China
| | - Ming Jing
- Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
- Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan 250000, China
| | - Qingzhen Hou
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250100, China
- National Institute of Health Data Science of China, Shandong University, Jinan 250100, China
| |
Collapse
|
|
2
|
Martarelli N, Capurro M, Mansour G, Jahromi RV, Stella A, Rossi R, Longetti E, Bigerna B, Gentili M, Rosseto A, Rossi R, Cencini C, Emiliani C, Martino S, Beeg M, Gobbi M, Tiacci E, Falini B, Morena F, Perriello VM. Artificial Intelligence-Powered Molecular Docking and Steered Molecular Dynamics for Accurate scFv Selection of Anti-CD30 Chimeric Antigen Receptors. Int J Mol Sci 2024; 25:7231. [PMID: 39000338 PMCID: PMC11242627 DOI: 10.3390/ijms25137231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 06/25/2024] [Accepted: 06/27/2024] [Indexed: 07/16/2024] Open
Abstract
Chimeric antigen receptor (CAR) T cells represent a revolutionary immunotherapy that allows specific tumor recognition by a unique single-chain fragment variable (scFv) derived from monoclonal antibodies (mAbs). scFv selection is consequently a fundamental step for CAR construction, to ensure accurate and effective CAR signaling toward tumor antigen binding. However, conventional in vitro and in vivo biological approaches to compare different scFv-derived CARs are expensive and labor-intensive. With the aim to predict the finest scFv binding before CAR-T cell engineering, we performed artificial intelligence (AI)-guided molecular docking and steered molecular dynamics analysis of different anti-CD30 mAb clones. Virtual computational scFv screening showed comparable results to surface plasmon resonance (SPR) and functional CAR-T cell in vitro and in vivo assays, respectively, in terms of binding capacity and anti-tumor efficacy. The proposed fast and low-cost in silico analysis has the potential to advance the development of novel CAR constructs, with a substantial impact on reducing time, costs, and the need for laboratory animal use.
Collapse
Affiliation(s)
- Nico Martarelli
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Michela Capurro
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Gizem Mansour
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milano, Italy; (G.M.); (M.B.); (M.G.)
| | - Ramina Vossoughi Jahromi
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Arianna Stella
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Roberta Rossi
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Emanuele Longetti
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Barbara Bigerna
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Marco Gentili
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Ariele Rosseto
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Riccardo Rossi
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Chiara Cencini
- Department of Chemistry, Biology, and Biotechnologies, Via del Giochetto, University of Perugia, 06122 Perugia, Italy; (C.C.); (C.E.); (S.M.)
| | - Carla Emiliani
- Department of Chemistry, Biology, and Biotechnologies, Via del Giochetto, University of Perugia, 06122 Perugia, Italy; (C.C.); (C.E.); (S.M.)
| | - Sabata Martino
- Department of Chemistry, Biology, and Biotechnologies, Via del Giochetto, University of Perugia, 06122 Perugia, Italy; (C.C.); (C.E.); (S.M.)
| | - Marten Beeg
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milano, Italy; (G.M.); (M.B.); (M.G.)
| | - Marco Gobbi
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milano, Italy; (G.M.); (M.B.); (M.G.)
| | - Enrico Tiacci
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Brunangelo Falini
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| | - Francesco Morena
- Department of Chemistry, Biology, and Biotechnologies, Via del Giochetto, University of Perugia, 06122 Perugia, Italy; (C.C.); (C.E.); (S.M.)
| | - Vincenzo Maria Perriello
- Institute of Hematology and Center for Hemato-Oncology Research, University of Perugia and Santa Maria della Misericordia Hospital, 06132 Perugia, Italy; (N.M.); (M.C.); (R.V.J.); (A.S.); (R.R.); (E.L.); (B.B.); (M.G.); (A.R.); (R.R.); (E.T.); (B.F.)
| |
Collapse
|
|
3
|
Chaves EJF, Coêlho DF, Cruz CHB, Moreira EG, Simões JCM, Nascimento-Filho MJ, Lins RD. Structure-based computational design of antibody mimetics: challenges and perspectives. FEBS Open Bio 2024. [PMID: 38925955 DOI: 10.1002/2211-5463.13855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Revised: 05/17/2024] [Accepted: 06/19/2024] [Indexed: 06/28/2024] Open
Abstract
The design of antibody mimetics holds great promise for revolutionizing therapeutic interventions by offering alternatives to conventional antibody therapies. Structure-based computational approaches have emerged as indispensable tools in the rational design of those molecules, enabling the precise manipulation of their structural and functional properties. This review covers the main classes of designed antigen-binding motifs, as well as alternative strategies to develop tailored ones. We discuss the intricacies of different computational protein-protein interaction design strategies, showcased by selected successful cases in the literature. Subsequently, we explore the latest advancements in the computational techniques including the integration of machine and deep learning methodologies into the design framework, which has led to an augmented design pipeline. Finally, we verse onto the current challenges that stand in the way between high-throughput computer design of antibody mimetics and experimental realization, offering a forward-looking perspective into the field and the promises it holds to biotechnology.
Collapse
Affiliation(s)
- Elton J F Chaves
- Aggeu Magalhães Institute, Oswaldo Cruz Foundation, Recife, Brazil
| | - Danilo F Coêlho
- Department of Fundamental Chemistry, Federal University of Pernambuco, Recife, Brazil
| | - Carlos H B Cruz
- Institute of Structural and Molecular Biology, University College London, UK
| | | | - Júlio C M Simões
- Aggeu Magalhães Institute, Oswaldo Cruz Foundation, Recife, Brazil
- Department of Fundamental Chemistry, Federal University of Pernambuco, Recife, Brazil
| | - Manassés J Nascimento-Filho
- Aggeu Magalhães Institute, Oswaldo Cruz Foundation, Recife, Brazil
- Department of Fundamental Chemistry, Federal University of Pernambuco, Recife, Brazil
| | - Roberto D Lins
- Aggeu Magalhães Institute, Oswaldo Cruz Foundation, Recife, Brazil
- Department of Fundamental Chemistry, Federal University of Pernambuco, Recife, Brazil
- Fiocruz Genomics Network, Brazil
| |
Collapse
|
|
4
|
El Salamouni NS, Cater JH, Spenkelink LM, Yu H. Nanobody engineering: computational modelling and design for biomedical and therapeutic applications. FEBS Open Bio 2024. [PMID: 38898362 DOI: 10.1002/2211-5463.13850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 05/25/2024] [Accepted: 06/10/2024] [Indexed: 06/21/2024] Open
Abstract
Nanobodies, the smallest functional antibody fragment derived from camelid heavy-chain-only antibodies, have emerged as powerful tools for diverse biomedical applications. In this comprehensive review, we discuss the structural characteristics, functional properties, and computational approaches driving the design and optimisation of synthetic nanobodies. We explore their unique antigen-binding domains, highlighting the critical role of complementarity-determining regions in target recognition and specificity. This review further underscores the advantages of nanobodies over conventional antibodies from a biosynthesis perspective, including their small size, stability, and solubility, which make them ideal candidates for economical antigen capture in diagnostics, therapeutics, and biosensing. We discuss the recent advancements in computational methods for nanobody modelling, epitope prediction, and affinity maturation, shedding light on their intricate antigen-binding mechanisms and conformational dynamics. Finally, we examine a direct example of how computational design strategies were implemented for improving a nanobody-based immunosensor, known as a Quenchbody. Through combining experimental findings and computational insights, this review elucidates the transformative impact of nanobodies in biotechnology and biomedical research, offering a roadmap for future advancements and applications in healthcare and diagnostics.
Collapse
Affiliation(s)
- Nehad S El Salamouni
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Australia
| | - Jordan H Cater
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Australia
| | - Lisanne M Spenkelink
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Australia
| | - Haibo Yu
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Australia
- ARC Centre of Excellence in Quantum Biotechnology, University of Wollongong, Australia
| |
Collapse
|
|
5
|
Guo X, Wu Y, Xue Y, Xie N, Shen G. Revolutionizing cancer immunotherapy: unleashing the potential of bispecific antibodies for targeted treatment. Front Immunol 2023; 14:1291836. [PMID: 38106416 PMCID: PMC10722299 DOI: 10.3389/fimmu.2023.1291836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Accepted: 11/08/2023] [Indexed: 12/19/2023] Open
Abstract
Recent progressions in immunotherapy have transformed cancer treatment, providing a promising strategy that activates the immune system of the patient to find and eliminate cancerous cells. Bispecific antibodies, which engage two separate antigens or one antigen with two distinct epitopes, are of tremendous concern in immunotherapy. The bi-targeting idea enabled by bispecific antibodies (BsAbs) is especially attractive from a medical standpoint since most diseases are complex, involving several receptors, ligands, and signaling pathways. Several research look into the processes in which BsAbs identify different cancer targets such angiogenesis, reproduction, metastasis, and immune regulation. By rerouting cells or altering other pathways, the bispecific proteins perform effector activities in addition to those of natural antibodies. This opens up a wide range of clinical applications and helps patients with resistant tumors respond better to medication. Yet, further study is necessary to identify the best conditions where to use these medications for treating tumor, their appropriate combination partners, and methods to reduce toxicity. In this review, we provide insights into the BsAb format classification based on their composition and symmetry, as well as the delivery mode, focus on the action mechanism of the molecule, and discuss the challenges and future perspectives in BsAb development.
Collapse
Affiliation(s)
- Xiaohan Guo
- West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, China
| | - Yi Wu
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, China
| | - Ying Xue
- West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, China
| | - Na Xie
- West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, China
| | - Guobo Shen
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, China
| |
Collapse
|
|
6
|
Liu ML, Chen ZJ, Huang XQ, Wang H, Zhao JL, Shen YD, Luo L, Wen XW, Hammock B, Xu ZL. A bispecific nanobody with high sensitivity/efficiency for simultaneous determination of carbaryl and its metabolite 1-naphthol in the soil and rice samples. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 335:122265. [PMID: 37517641 PMCID: PMC10529271 DOI: 10.1016/j.envpol.2023.122265] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/01/2023]
Abstract
The simultaneous determination of carbaryl and its metabolite 1-naphthol is essential for risk assessment of pesticide exposure in agricultural and environmental samples. Herein, several bispecific nanobodies (BsNbs) with different lengths of hydrophilic linkers and junction sites were prepared and characterized for the simultaneous recognition of carbaryl and its metabolite 1-naphthol. It was found that the affinity of BsNbs to the analytes could be regulated by controlling linker length and linking terminal. Additionally, molecular simulation revealed that linker lengths affected the conformation of BsNbs, leading to alteration in sensitivity. The BsNb with G4S linker, named G4S-C-N-VHH, showing good thermal stability and sensitivity was used to develop a bispecific indirect competitive enzyme-linked immunosorbent assay (Bic-ELISA). The assay demonstrated a limit of detection of 0.8 ng/mL for carbaryl and 0.4 ng/mL for 1-naphthol in buffer system. Good recoveries from soil and rice samples were obtained, ranging from 80.0% to 112.7% (carbaryl) and 76.5%-110.8% (1-naphthol), respectively. Taken together, this study firstly provided a BsNb with high sensitivity and efficiency against environmental pesticide and its metabolite, and firstly used molecular dynamics simulation to explore the influence of linker on recognition. The results are valuable for the application of immunoassay with high efficiency in the fields of environment and agriculture.
Collapse
Affiliation(s)
- Min-Ling Liu
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Research Center for Green Development of Agriculture, South China Agricultural University, Guangzhou, 510642, China
| | - Zi-Jian Chen
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Research Center for Green Development of Agriculture, South China Agricultural University, Guangzhou, 510642, China; Laboratory of Quality & Safety Risk Assessment for Agro-products (Zhaoqing), Ministry of Agriculture and Rural Affairs, School of Food and Pharmaceutical Engineering, Zhaoqing University, Zhaoqing, 526061, China
| | - Xiao-Qing Huang
- Guangzhou Institute of Food Inspection, Guangzhou, 510410, China
| | - Hong Wang
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Research Center for Green Development of Agriculture, South China Agricultural University, Guangzhou, 510642, China
| | - Jin-Li Zhao
- Guangzhou Institute of Food Inspection, Guangzhou, 510410, China
| | - Yu-Dong Shen
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Research Center for Green Development of Agriculture, South China Agricultural University, Guangzhou, 510642, China
| | - Lin Luo
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Research Center for Green Development of Agriculture, South China Agricultural University, Guangzhou, 510642, China
| | - Xiao-Wei Wen
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Research Center for Green Development of Agriculture, South China Agricultural University, Guangzhou, 510642, China
| | - Bruce Hammock
- Department of Entomology and UCD Comprehensive Cancer Center, University of California, Davis, CA, 95616, United States
| | - Zhen-Lin Xu
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Research Center for Green Development of Agriculture, South China Agricultural University, Guangzhou, 510642, China.
| |
Collapse
|