In silico site-directed mutagenesis of neutralizing mAb 4C4 and analysis of its interaction with G-H loop of VP1 to explore its therapeutic applications against FMD

Abstract

Investigating the behaviour of bio-molecules through computational mutagenesis is gaining interest to facilitate the development of new therapeutic solutions for infectious diseases. The antigenetically variant genotypes of foot and mouth disease virus (FMDV) and their subsequent infections are challenging to tackle with traditional vaccination. In such scenario, neutralizing antibodies might provide an alternate solution to manage the FMDV infection. Thus, we have analysed the interaction of the mAb 4C4 with a synthetic G-H loop of FMDV-VP1 through in silico mutagenesis and molecular modelling. Initially, a set of 25,434 mutants were designed and the mutants having better energetic stability than 4C4 were clustered based on sequence identity. The best mutant representing each cluster was selected and evaluated for its binding affinity with the antigen in terms of docking scores, interaction energy and binding energy. Six mutants have confirmed better binding affinities towards the antigen than 4C4. Further, interaction of these mutants with the natural G-H loop that is bound to mAb SD6 was also evaluated. One 4C4 variant having mutations at the positions 2034(N→L), 2096(N→C), 2098(D→Y), 2532(T→K) and 2599(A→G) has revealed better binding affinities towards both the synthetic and natural G-H loops than 4C4 and SD6, respectively. A molecular dynamic simulation for 50 ns was conducted for mutant and wild-type antibody structures which supported the pre-simulation results. Therefore, these mutations on mAb 4C4 are believed to provide a better antibody-based therapeutic option for FMD.

Communicated by Ramaswamy H. Sarma

Keywords:

• Foot and mouth disease
• G-H loop
• in silico mutagenesis
• computer-added antibody design
• antigenetically variant genotype

Availability of data:

All necessary data used in the study concerning the results are provided in the Supplemental material 4.

Acknowledgements

TKS acknowledges the receipt of fellowship from PG School, IARI, New Delhi, during his PhD study. All authors wish to acknowledge the grant for CABin Scheme Network project on Agricultural Bioinformatics and Computational Biology (F.No. Agril.Edn.14/2/2017-A&P dated 02.08.2017), received from Indian Council of Agricultural Research (ICAR), New Delhi. Authors are also thankful to Mr. Vikas Punia for providing technical support during the study.

Disclosure statement

No potential conflict of interest was reported by the author(s).