Interactions between macromolecules, such as proteins and nucleic acids, are essential for
cellular functions. Experimental methods can fail to provide all the information required to …

Computer-aided discovery of vaccine targets has become a cornerstone of rational vaccine
design. In this article, I discuss how Machine Learning (ML) can inform and guide key …

Immune receptor proteins play a key role in the immune system and have shown great
promise as biotherapeutics. The structure of these proteins is critical for understanding their …

Antibodies are currently the most important class of biotherapeutics and are used to treat
numerous diseases. Recent advances in computational methods are ushering in a new era …

Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs)
are tremendous, the design and discovery of new candidates remain a time and cost …

Antibodies are versatile molecular binders with an established and growing role as
therapeutics. Computational approaches to develo** and designing these molecules are …

Antibodies are proteins that recognize the molecular surfaces of potentially noxious
molecules to mount an adaptive immune response or, in the case of autoimmune diseases …

Accurate predictive modeling of antibody-antigen complex structures and structure-based
antibody design remain major challenges in computational biology, with implications for …

The design of new biomolecules able to harness immune mechanisms for the treatment of
diseases is a prime challenge for computational and simulative approaches. For instance, in …

Routinely screened antibody fragments usually require further in vitro maturation to achieve
the desired biophysical properties. Blind in vitro strategies can produce improved ligands by …