Review
Medicine, Research & Experimental
Rahul Khetan, Robin Curtis, Charlotte M. Deane, Johannes Thorling Hadsund, Uddipan Kar, Konrad Krawczyk, Daisuke Kuroda, Sarah A. Robinson, Pietro Sormanni, Kouhei Tsumoto, Jim Warwicker, Andrew C. R. Martin
Summary: This article provides an overview of antibody informatics tools for the prediction of developability issues and evaluates the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Furthermore, it discusses the potential of developability guidelines based on in silico metrics.
Article
Immunology
Ran Salomon, Rony Dahan
Summary: The clinical use of anti-CD40 agonist monoclonal antibodies faces challenges due to dose-limiting toxicity. Novel approaches are being explored to overcome the systemic toxicity associated with CD40 agonism.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Medicine, Research & Experimental
Andre Azevedo Reis Teixeira, Michael Frank Erasmus, Sara D'Angelo, Leslie Naranjo, Fortunato Ferrara, Camila Leal-Lopes, Oliver Durrant, Cecile Galmiche, Aleardo Morelli, Anthony Scott-Tucker, Andrew Raymon Morton Bradbury
Summary: This paper introduces a new antibody library format that generates high-affinity binders with drug-like developability properties directly from initial selections, reducing the need for further engineering or affinity maturation. This innovative design is expected to accelerate drug development processes by reducing the failure rate of leads due to poor antibody affinities and developability.
Article
Immunology
Brian M. Petersen, Sophia A. Ulmer, Emily R. Rhodes, Matias F. Gutierrez-Gonzalez, Brandon J. Dekosky, Kayla G. Sprenger, Timothy A. Whitehead
Summary: Monoclonal antibodies are key therapeutics for cancer, inflammation, and infectious diseases. Natural human antibody repertoire-based scoring matrices can accurately predict mutations in therapeutic antibodies. High frequency mutations in natural human antibody repertoires have the potential to improve existing therapeutic antibodies and reduce immunogenicity.
FRONTIERS IN IMMUNOLOGY
(2021)
Article
Biochemical Research Methods
Panagiotis Moulos
Summary: This article introduces a software package called recoup, which can visualize genomic coverage profiles generated from Next Generation Sequencing data quickly, flexibly, comprehensively, while also considering ease of use and reusability.
BMC BIOINFORMATICS
(2021)
Article
Biochemistry & Molecular Biology
Hye Lim Choi, Ha Rim Yang, Ha Gyeong Shin, Kyusang Hwang, Ji Woong Kim, Ji Hyun Lee, Taehoon Ryu, Yushin Jung, Sukmook Lee
Summary: Antibody phage display is a crucial technology for discovering and developing target-specific monoclonal antibodies. This study constructed a large human combinatorial single-chain variable fragment library with high diversity, which can be used for the rapid development of recombinant human monoclonal antibodies for therapeutic and diagnostic applications.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Medicine, Research & Experimental
Sharon M. Campbell, Joseph DeBartolo, James R. Apgar, Lydia Mosyak, Virginie McManus, Sonia Beyer, Eric M. Bennett, Matthew Lambert, Orla Cunningham
Summary: Despite advances in antibody library technologies, ensuring selected antibodies do not acquire additional specificities or biophysical liabilities during optimization remains a challenge. Through structure-guided library design, next-generation sequencing and linear regression models, a high-affinity anti-IL-21 R antibody with desirable stability and biophysical profile was identified.
Article
Biotechnology & Applied Microbiology
David Roush, Michael Iammarino, Rebecca Chmielowski, Francis Insaidoo, Mark A. McCoy, Allison Ortigosa, Michael Rauscher
Summary: Advancement in all disciplines requires a balance of disruption and advancement of classical techniques. Recovery of biological products is experiencing a renaissance, and purification technologies need breakthroughs, including nonchromatographic approaches. Molecular modeling can support the crystallization and purification processes of biologics.
BIOTECHNOLOGY AND BIOENGINEERING
(2023)
Article
Biochemical Research Methods
Raphael R. Eguchi, Christian A. Choe, Po-Ssu Huang
Summary: The article introduces a new approach for generating the 3D coordinates of immunoglobulins using a variational auto-encoder. The model is demonstrated to be effective in creating computational models for protein design and shows potential in guiding protein design through a generative prior.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Immunology
Lauren M. Walker, Andrea R. Shiakolas, Rohit Venkat, Zhaojing Ariel Liu, Steven Wall, Nagarajan Raju, Kelsey A. Pilewski, Ian Setliff, Amyn A. Murji, Rebecca Gillespie, Nigel A. Makoah, Masaru Kanekiyo, Mark Connors, Lynn Morris, Ivelin S. Georgiev
Summary: The development of novel technologies for discovering human monoclonal antibodies has been extremely valuable in combating infectious diseases. LIBRA-seq with epitope mapping is a next-generation sequencing technology that can determine residue-level epitopes for thousands of single B cells simultaneously, making it an efficient tool for high-throughput identification of antibodies against specific antigen epitopes.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Valentin Dietlin-Auril, Maxime Lecerf, Stephanie Depinay, Remi Noe, Jordan D. Dimitrov
Summary: The study found that a significant percentage of therapeutic antibodies in clinical stages show pronounced binding to a specific substance, which may indicate unfavorable functional and physicochemical features of the antibodies. Therefore, a simple approach was proposed for early identification of developability liabilities of these therapeutic antibodies.
MOLECULAR IMMUNOLOGY
(2021)
Article
Biochemical Research Methods
Muhammad Tahir, Muhammad Sardaraz, Zahid Mehmood, Muhammad Saud Khan
Summary: This paper proposed an efficient error estimation computational model ESREEM to assess error rates in NGS data. The model is based on a probabilistic error model integrated with Hidden Markov Model, and experimental results show that it efficiently estimates errors compared to state-of-the-art algorithms.
CURRENT BIOINFORMATICS
(2021)
Article
Medicine, Research & Experimental
Norbert Furtmann, Marion Schneider, Nadja Spindler, Bjoern Steinmann, Ziyu Li, Ingo Focken, Joachim Meyer, Dilyana Dimova, Katja Kroll, Wulf Dirk Leuschner, Audrey Debeaumont, Magali Mathieu, Christian Lange, Werner Dittrich, Jochen Kruip, Thorsten Schmidt, Joerg Birkenfeld
Summary: Next-generation multi-specific antibody therapeutics (MSATs) combine multiple functional activities into one molecule for higher efficacy, but often face challenges in yield and drug-like properties. A novel format-agnostic platform process has been established for rapid generation and multiparametric screening of tens of thousands of MSAT variants, utilizing full automation and advanced DNA workflows to optimize production and potency. This platform demonstrated significant improvements in potency and production titers for a next-generation bispecific CODV-Ig through screening of over 25,000 protein variants, showcasing its power and versatility.
Article
Biochemistry & Molecular Biology
Franz Waibl, Monica L. Fernandez-Quintero, Florian S. Wedl, Hubert Kettenberger, Guy Georges, Klaus R. Liedl
Summary: This study investigates the hydrophobicity of monoclonal antibodies and compares different scoring schemes and hydrophobicity scales. The understanding of hydrophobicity in antibody development is improved, and it is found that the diversity of the dataset affects the performance of hydrophobicity scores.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Article
Biochemistry & Molecular Biology
Nicola Zilio, Helle D. Ulrich
Summary: Mapping the genome-wide distribution of single-strand breaks is crucial for understanding damage signaling and DNA repair. This article reviews classical and newly developed high-resolution methods for mapping single-strand breaks, highlighting the valuable insights they provide into the impact of this type of damage on the genome.
Editorial Material
Pediatrics
Veronika Baghin, Seraina Prader, Selma Sirin, Jana Pachlopnik Schmid, Johannes Trueck
ARCHIVES OF DISEASE IN CHILDHOOD-EDUCATION AND PRACTICE EDITION
(2023)
Letter
Immunology
Maarja Soomann, Seraina Prader, Jana Pachlopnik Schmid, Tayfun Gungor, Johannes Truck
JOURNAL OF CLINICAL IMMUNOLOGY
(2023)
Article
Chemistry, Medicinal
Stephanie Wills, Ruben Sanchez-Garcia, Tim Dudgeon, Stephen D. Roughley, Andy Merritt, Roderick E. Hubbard, James Davidson, Frank von Delft, Charlotte M. Deane
Summary: Fragment merging is a promising approach to advancing fragments directly to on-scale potency. Searching commercial catalogues allows for quick and cost-effective identification of these merges, circumventing the challenge of synthetic accessibility.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Immunology
Sophie Strasser, Christa Relly, Christoph Berger, Johannes Truck
Summary: A retrospective analysis found that a substantial proportion of children with severe bacterial infections (SBIs) had immune function impairments. Routine immunological testing can help identify these abnormalities and optimize preventive measures to avoid future SBI episodes.
JOURNAL OF INFECTIOUS DISEASES
(2023)
Article
Biology
Brennan Abanades, Wing Ki Wong, Fergus Boyles, Guy Georges, Alexander Bujotzek, Charlotte M. Deane
Summary: Immune receptor proteins are important in the immune system and have potential as biotherapeutics. A deep learning model called ImmuneBuilder is presented, which accurately predicts the structure of antibodies, nanobodies, and T-cell receptors. ImmuneBuilder outperforms AlphaFold2 in terms of accuracy and speed.
COMMUNICATIONS BIOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Maranga Mokaya, Fergus Imrie, Willem P. van Hoorn, Aleksandra Kalisz, Anthony R. Bradley, Charlotte M. Deane
Summary: Deep reinforcement learning methods are potentially powerful tools for de novo design in the field of drug discovery. However, when there are few or no examples of desired molecules in the training data, recurrent neural network-based methods may have limitations in generating diverse and controllable molecular sets. To address these issues, a new curriculum-learning-inspired recurrent iterative optimization procedure is proposed, which allows the optimization of generated molecules for both known and unknown molecular profiles and provides control over exploration and exploitation. This method has been shown to generate specific and diverse sets of molecules with significantly more scaffolds compared to standard methods, although the choice of simplified molecular-input line-entry system (SMILES) representation has been found to affect the success of molecular optimization.
NATURE MACHINE INTELLIGENCE
(2023)
Article
Biochemical Research Methods
Oliver M. Crook, Nathan Gittens, Chun-wa Chung, Charlotte M. Deane
Summary: Proteins undergo structural perturbations when binding to others or subjected to environmental changes. HDX-MS can explore conformational changes in proteins by examining differences in deuterium incorporation rate. We propose a flexible Bayesian framework that improves stability, allows uncertainty quantification, and calculates statistical quantities that are inaccessible to other methods. Our findings demonstrate that a Bayesian approach can identify important binding epitopes from HDX data with consistent results.
JOURNAL OF PROTEOME RESEARCH
(2023)
Editorial Material
Biotechnology & Applied Microbiology
Carlos Outeiral, Charlotte M. Deane
Summary: This study presents a general-purpose protein language model that can rapidly improve antibody properties.
NATURE BIOTECHNOLOGY
(2023)
Article
Medicine, Research & Experimental
Henderson Zhu, Irina Chelysheva, Deborah L. Cross, Luke Blackwell, Celina Jin, Malick M. Gibani, Elizabeth Jones, Jennifer Hill, Johannes Truck, Dominic F. Kelly, Christoph J. Blohmke, Andrew J. Pollard, Daniel O'Connor
Summary: This study compares the immune responses and protection effects of two typhoid vaccines, ViPS and ViTT, through the analysis of genomic data. The study reveals distinct molecular features between the two vaccines, mainly related to humoral immune responses. Furthermore, the study identifies molecular correlates of protection against S. Typhi infection. These findings have important implications for future vaccine design and assessment.
JOURNAL OF CLINICAL INVESTIGATION
(2023)
Article
Multidisciplinary Sciences
Tobias H. Olsen, Brennan Abanades, Iain H. Moal, Charlotte M. Deane
Summary: KA-Search is a tool for rapid searching of antibody variable domains by amino acid sequence identity. It can predict antibody properties and find the most similar sequences from billions of antibody sequences within minutes. Examples of insights obtained using KA-Search are provided.
SCIENTIFIC REPORTS
(2023)
Article
Chemistry, Multidisciplinary
Ruben Sanchez-Garcia, David Havasi, Gergely Takacs, Matthew C. Robinson, Alpha Lee, Frank von Delft, Charlotte M. Deane
Summary: Compound availability is crucial in the drug discovery process. Synthetic accessibility scores have been used as proxies for compound availability, but they are not effective in representing compound prices. In this paper, we propose a deep learning model called CoPriNet, which can accurately predict compound prices and has fast execution times, making it suitable for high-throughput experiments.
Article
Biochemistry & Molecular Biology
Brennan Abanades, Tobias H. Olsen, Matthew I. J. Raybould, Broncio Aguilar-Sanjuan, Wing Ki Wong, Guy Georges, Alexander Bujotzek, Charlotte M. Deane
Summary: The study introduces PLAbDab, a self-updating database of antibodies that contains over 150,000 paired antibody sequences and 3D structural models. It allows users to search by sequence, structure, or keyword, and provides functions such as annotating query antibodies, analyzing structural models, and facilitating the compilation of customized datasets.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemical Research Methods
Lewis Chinery, Newton Wahome, Iain Moal, Charlotte M. Deane
Summary: The development of new vaccines and antibody therapeutics is a time-consuming and costly process. In this study, a structure-based paratope prediction tool called Paragraph is introduced, which outperforms existing tools by using simpler feature vectors and no antigen information.
Article
Pediatrics
Chantal D. Tan, Eline E. P. L. van der Walle, Clementien L. Vermont, Ulrich von Both, Enitan D. Carrol, Irini Eleftheriou, Marieke Emonts, Michiel van der Flier, Ronald de Groot, Jethro Herberg, Benno Kohlmaier, Michael Levin, Emma Lim, Ian K. Maconochie, Federico Martinon-Torres, Ruud G. Nijman, Marko Pokorn, Irene Rivero-Calle, Maria Tsolia, Shunmay Yeung, Werner Zenz, Dace Zavadska, Henriette A. Moll
Summary: Febrile children below 3 months are at higher risk for serious bacterial infections, leading to extensive diagnostics and treatment. This study found large practice variation in management, with limited guideline adherence but highest adherence for admission, indicating a cautious approach. Future studies should focus on guideline revision and new biomarkers to optimize management in young febrile children.
EUROPEAN JOURNAL OF PEDIATRICS
(2022)