Biofunctionalization and immobilization of a membrane via peptide binding (CR3-1, S2) by a Monte Carlo simulation

Abstract

A coarse-grained computer simulation model is used to study the immobilization of a dynamic tethered membrane (representation of a clay platelet) in a matrix of mobile peptide chains CR3-1: 1Trp-2Pro-3Ser-4Ser-5Tyr-6Leu-7Ser-8Pro-9Ile-10Pro-11Tyr-12Ser and S2: 1His-2Gly-3Ile-4Asn-5Thr-6Thr-7Lys-8Pro-9Phe-10Lys-11Ser-12Val on a cubic lattice. Each residue interacts with the membrane nodes with appropriate interaction and executes their stochastic motion with the Metropolis algorithm. Density profiles, binding energy of each residue, mobility, and targeted structural profile are analyzed as a function of peptide concentration. We find that the binding of peptides S2 is anchored by lysine residues (7Lys, 10Lys) while peptides CR3-1 do not bind to membrane. The membrane slows down as peptides S2 continues to bind leading to its eventual pinning. How fast the immobilization of the membrane occurs depends on peptide concentration. Binding of peptide S2 modulates the morphology of the membrane. The immobilization of membrane occurs faster if peptides S2 are replaced by the homopolymer of lysine ([Lys]12 of the same molecular weight), the strongest binding residue. The surface of membrane can be patterned with somewhat reduced roughness with the homopolymer of lysine than that with peptide S2

Stability of peptide (P1 and P2) binding to a graphene sheet via an all-atom to all-residue coarse-grained approach

“…33,34 We have already adopted such methods in studying the global properties of proteins 17,18 and peptide binding to specific substrates. [7][8][9]37,38 In this article, we would like to develop it further with input from an all-atom MD simulation. A peptide can be represented by a chain of coarsegrained nodes where each node represents an amino acid.…”

Variation in Structure of a Protein (H2AX) with Knowledge-Based Interactions

“…Despite the simple matrix grid, the degrees of freedom for each residue and peptide bond are ample, much more than that with the fixed bond length frequently used in lattice simulations [15]. Such a bond-fluctuating mechanism has become a common tool in computer simulation modeling of complex systems as is the case for homopolymers [15], proteins [12], [13], membranes [16], and bio-functionalized nano assemblies [17]. It should be pointed out that our coarse-grained protein with fluctuating (i.e., expanding and contracting) covalent bonds between consecutive residues captures much more details (with many more degrees of freedom) than that of the minimalist HP model used for the sensitivity test by Betancourt and Thirumalai [7].…”

Control over Self-Assembly of Diblock Copolymers on Hexagonal and Square Templates for High Area Density Circuit Boards

“…Displacements of the vacancies led to faster equilibration of the dense polymer melt than displacements of the polymer beads. ,, Displacements of vacancies and adjustments of the polymer structure were limited by excluded volume, allowed bond lengths of 1 and (2) 1/2 , and exclusion of bond-crossing moves. The Metropolis criterion was invoked to evaluate the acceptability of each attempted move. − …”