Discipline: Chemistry & Chemical Sciences
Subcategory: STEM Research
- Clark Atlanta University
Studies on interactions between graphene and amino acids are important to obtain knowledge that will be useful in producing graphene-based biochemical sensors, and biomedical implants. Graphene provides high sensitivity and selectivity when different molecules are adsorbed. In this study, two finite size graphene sheets of small graphene (GS) consists of 62 carbon atoms and large graphene sheet (GL) consists of 186 carbon atoms were considered to understand the binding of five naturally occurring amino acids (tyrosine (Tyr), phenylalanine (Phe), tryptophan (Trp), histidine (His), and proline (Pro)) with them. Conformational analysis was done for each of the above-mentioned amino acids using HF/3-21G level as implemented in Spartan ’16. Two lowest energy conformers and one highest energy conformer for each amino acid were chosen to examine the binding with graphene sheets. We considered different orientations for each conformer of amino acid to study the interactions with small and large graphene at M06-2X/6-31G(d) level. All geometry optimizations were performed within the symmetry constraints. Binding energies with and without basis set superposition error (BSSE) were calculated in the gas phase. We also examined the influence of solvent (water) on the binding affinity of each of the amino acids with graphene. HOMO-LUMO energy gaps were calculated at the TPSSh/6-31G(d)//M06-2X/6-31G(d) level for all the complexes and pristine graphene. Our aim is to address the following questions: (i) Which conformer of amino acid provides the most stable complex? (ii) What types of interactions (pi…pi, C-H/N-H…pi, or combinations of these interactions) are responsible for stabilization of the complexes? (iii) How does the size of graphene sheet affect the binding strength? (iv) How does the binding affinity vary from gas phase to aqueous medium? (v) Does the band gap of graphene alter by the binding of amino acids with it?
Funder Acknowledgement(s): National Science Foundation (NSF) is acknowledged for funding through HBCU-UP Research Initiation Award (Grant number 1601071); Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the NSF grant number ACI-1053575, is acknowledged for computational resources
Faculty Advisor: None Listed,