in silico Assessment of Antibody Drug Resistance to Bamlanivimab of SARS-CoV-2 Variant B.1.617

Zhang, Leili; Huynh, Tien; Luan, Binquan

The highly infectious SARS-CoV-2 variant B.1.617 with double mutations E484Q and L452R in the receptor binding domain (RBD) of SARS-CoV-2’s spike protein is worrisome. Demonstrated in crystal structures, the residues 452 and 484 in RBD are not in direct contact with interfacial residues in the angiotensin converting enzyme 2 (ACE2). This suggests that albeit there are some possibly nonlocal effects, the E484Q and L452R mutations might not significantly affect RBD’s binding with ACE2, which is an important step for viral entry into host cells. Thus, without the known molecular mechanism, these two successful mutations (from the point of view of SARS-CoV-2) can be hypothesized to evade human antibodies. Using in silico all-atom molecular dynamics (MD) simulation as well as deep learning (DL) approaches, here we show that these two mutations significantly reduce the binding affinity between RBD and the antibody LY-CoV555 (also named as Bamlanivimab) that was proven to be efficacious for neutralizing the wide-type SARS-CoV-2. With the revealed molecular mechanism on how L452R and E484K evade LY-CoV555, we expect that more specific therapeutic antibodies can be accordingly designed and/or a precision mixing of antibodies can be achieved in a cocktail treatment for patients infected with the variant B.1.617.