With a strong background in bio, organic, and physical chemistry, I am an established computational chemist with over 25 years of experience and broad expertise in molecular modeling applied to (bio)pharmaceutical research; ranging from cheminformatics-based small-molecule lead discovery and optimization to structural bioinformatics-based computational biology, and from molecular simulations of protein-ligand complexes to engineering of therapeutic proteins and antibody humanization.

Name: Prof. Dr. Traian Sulea
Affiliation: National Research Council Canada, Montreal, Canada
Research interests: health, biotechnology, biotherapeutics, chemistry, information technology, modelling software

The following is a short interview with Prof. Dr. Traian Sulea:

1. Could you please briefly introduce yourself?

I am the Principal Research Officer and Team Leader of Molecular Modeling at the National Research Council Canada, which I joined as a post-doctoral fellow in 1995. I have also been an Adjunct Professor at the Institute of Parasitology of McGill University since 2012, where I teach structural bioinformatics and therapeutic antibody design. My expertise in applying computational approaches to the discovery and optimization of bioactive small-molecules and biologics includes the development of computational methods for biomolecular applications with a focus on continuum solvation and binding affinity predictions, structure-based engineering of protein fusions, selective targeting of solid tumor microenvironment, and antibody optimization via humanization, affinity maturation, selective conjugation, and developability assessment. I have authored over 150 publications, including 110 peer-reviewed articles, 38 international patents, and 5 book chapters.

2. What do you think of the development status and trends of open access publishing?

Huge strides have been made in making scientific research widely accessible to everyone. More and more scientific studies and associated data are freely available, and I believe this trend will continue. Peer-reviewing is also an important process of scientific publishing, and much debate has been shared lately on the quality of this process, which can certainly benefit from fine-tuning and improvement, perhaps also via adding a component involving a wider community-based evaluation of submitted papers.

3. What is your impression of the Antibodies journal?

Antibodies is a journal addressing a niche area of research that lacks sufficient publishing venues. With a relatively well-reputed history and track record, it definitely has huge potential to become one of the leading journals in this field of antibody research, where both fundamental and applied science can find their homes.

4. What do you think will be the research hotspots in the field of antibodies in the next few years, and can you describe them to us?

I think that even higher-throughput methods for screening even larger antibody libraries will always be in vogue in the field of antibody discovery, characterization, and optimization towards drug candidates with unparalleled medical benefits. As a molecular modeler and computational structural biologist, I am in awe of the latest advances in antibody structure prediction methods, and so I am certain computational methods based on artificial intelligence and deep learning from large datasets will be the next hotspot of this field for the next while.

5. Can you give any advice on academic research for young scholars in related fields?

Emerging young scientists should get involved in the field of therapeutic antibody engineering and pay particular attention to the fast-paced developments in artificial intelligence, which are on the verge of reshaping the discovery and optimization of antibody drugs in the near future.

6. Could you kindly share with us your thoughts and outlook on this E-conference?

I believe this is a timely conference in the field of therapeutic antibody discovery and development. I hope the research presented throughout the conference will be positioned at the forefront of the field and, therefore, able to spur much interest and further advances. It also has the potential to boost the visibility of the Antibodies journal to the relevant audience. The organizing committee has assembled an excellent team of high-profile scientists serving in various roles, like conference and session chairs, as well as selection committee members, and has been able to invite renowned scientists to deliver keynote lectures and oral presentations. It is my belief that this first edition will serve as a stepping stone towards defining this conference as a must-attend event in the future.

7. Could you please provide a brief introduction to the session you are chairing, titled “Computational Antibody Engineering”?

In silico design and optimization of antibodies for therapeutic applications has gained significant traction in the past decade. It builds on the solid foundation established for classical methods in protein structure-based modeling, combined with the recent breakthrough of artificial intelligence in protein structure prediction. Recognition of these achievements in 2024 by the Nobel Prize in Chemistry demonstrated the value carried by these computational protein engineering methods, with far-reaching potential practical applications in therapeutic antibody discovery and development. This timely session thus welcomes contributions describing the latest refinements of established classical physics-based computational methods as well as the recent developments of rapidly evolving artificial intelligence-based approaches. Presentations will cover computational predictions of antibody–antigen binding affinity, specificity, docking and epitope mapping, predictions of antibody biophysical properties such as stability, aggregation, and immunogenicity, design and triage of antibody libraries for hit enrichment and downstream manufacturability, molecular engineering of novel antibody modalities, and entirely in silico antibody discovery efforts.