Variants of SARS-CoV-2 keep emerging and causing new waves of COVID-19 around the world. Effective new approaches in drug development are based on the binding of agents, such as neutralizing monoclonal antibodies to a receptor-binding domain (RBD) of SARS-CoV-2 spike protein. However, mutations in RBD may lower the affinity of previously developed antibodies. Therefore, rapid analysis of new variants and selection of a binding partner with high affinity is of great therapeutic importance. Here, we explore a computational approach based on molecular dynamics simulations and conformational clusterization techniques for the wild-type and omicron variants of RBD. Biochemical experiments support the hypothesis of the presence of several conformational states within the RBD assembly. The development of such an approach will facilitate the selection of neutralization drugs with higher affinity based on the primary structure of the target antigen.