A computational approach for studying antibody-antigen interactions without prior structural information: the anti-testosterone binding antibody as a case study

Abstract

Given the increasing exploitation of antibodies in different contexts such as molecular diagnostics and therapeutics, it would be beneficial to unravel the atomistic level properties of antibody-antigen complexes with the help of computational modeling. Thus, here we have studied the feasibility of computational tools to gather atomic scale information regarding the antibody-antigen complexes solely starting from an amino acid sequence. First, we constructed a homology model for the anti-testosterone binding antibody based on the knowledge based classification of complementary determining regions (CDRs) and implicit solvent molecular dynamics simulations. To further examine whether the generated homology model is suitable for studying antibody-antigen interactions, docking calculations were carried out followed by binding free-energy simulations. Our results indicate that with the antibody modeling approach presented here it is possible to construct accurate homology models for antibodies which correctly describes the antibody-antigen interactions, and produces absolute binding free-energies that are comparable with experimental values. In addition, our simulations suggest that the conformations of complementary determining regions (CDRs) may considerably change from the X-ray configuration upon solvation. In conclusion, here we have introduced an antibody modeling workflow that can be used in studying the interactions between antibody and antigen solely based on an amino acid sequence, which in turn provides novel opportunities to tune the properties of antibodies in different applications. Proteins 2017; 85:322-331. © 2016 Wiley Periodicals, Inc.

Variable Regions of Antibodies and T-Cell Receptors May Not Be Sufficient in Molecular Simulations Investigating Binding

“…An alternative approach to reduce computational costs is to reduce the size of the system that will be simulated. This is often seen practice for both antibodies and TCRs where only the variable regions are simulated ,,− as only these domains are in direct contact with the antigen and frequently a structure of the constant regions is not available (605 of the 2668 antibody X-ray structures listed in the SabDab do not contain constant regions). Not including the constant regions saves a considerable amount of computation time.…”

Stereospecific interactions between histidine and monoclonal antibodies

“…Homology models of mAb‐1 and mAb‐2, generated using Accelrys Discovery Studio (Discovery Studio Modeling Environment, Release 2017; Dassault Systèmes BIOVIA, San Diego: Dassault Systèmes, 2016) were used for the starting structures. The suitability of this approach has previously been demonstrated by Koivuniemi et al () in the context of antibody‐antigen interactions. The MD simulations were set up using MOE 2018.01 (Molecular Operating Environment, 2018.01; Chemical Computing Group Inc., Montreal, Canada, 2017).…”

“…MD simulations have been used to predict protein structure (Cheung & Yu, ), protein‐ligand binding (Araki et al, ), antibody‐antigen interactions (Koivuniemi, Takkinen, & Nevanen, ), and protein‐protein interactions (Rodrigues & Bonvin, ). In this work, MD simulations were used to probe the local interactions between the histidine enantiomers and the antibodies.…”

The Impact of Bioinformatics on Vaccine Design and Development

“…One way to avoid this drawback is the strategy presented by Koivuniemi et al, which involved homology modeling to deduce the structure of the antigen and the antibody, docking, and molecular dynamics simulations [41] (Figure 1). Figure 1.…”