Abstract
Protein stability, the most important aspect of molecular dynamics and simulations, requires sophisticated instrumentations of molecular biology to analyze its kinetic and thermodynamic background. Sequence- and structure-based programs on protein stability exist which relies only on single point mutations and sequence optimality. The energy distribution conferred by each hydrophobic amino acid in the protein essentially paves way for understanding its stability. To the best of our knowledge, Protein Stability is a first program of its kind, developed to explore the energy requirement of each amino acid in the protein sequence derived from various applied kinetic and thermodynamic quantities. The algorithm is strongly dependent both on kinetic quantities such as atomic solvation energies and solvent accessible surface area and thermodynamic quantities viz. enthalpy, entropy, heat capacity, etc. The hydrophobicity pattern of protein was considered as the important component of protein stabilization.
Highlights
In recent years, a certain success has been achieved in understanding the molecular basis of protein stability, mainly due to the considerable increase in the number of available amino acid sequences and 3-D structures
The term „protein stability‟ used by these servers/programs is based on the intention of protein engineering and makes use of evolutionary protein sequence dynamics, statistical potentials extracted from datasets of protein structures, empirical potentials built from optimized combinations of various physical energy terms, etc (Capriotti et al, 2001; Schymkowitz et al, 2005; Parthiban et al, 2006; Dehouck et al, 2011)
The main objective of this program is that one might get a clear understanding of the protein stability from the sequence itself without the need of its 3D structure which can help us to study the protein dynamics and folding pattern which act as a prerequisite for protein characterization experiments
Summary
A certain success has been achieved in understanding the molecular basis of protein stability, mainly due to the considerable increase in the number of available amino acid sequences and 3-D structures. A new functionality called „sequence optimality‟ developed in PoPMuSiC 2.1, estimates the optimality of each amino acid in the sequence with respect to the stability of the structure that can be used to detect structural weaknesses (a cluster of non-optimal residues) which may represent interesting sites for introducing targeted mutations This optimality predictor is derived from large-scale protein catalytic site data (Dehouck et al, 2011). Partitioning model helped to explore its kinetics and thermal denaturation gives major contribution to understand its transition from native to folded structure through thermodynamics. Both require the estimation of Gibbs free energy to study each amino acid contribution for the maintenance of native structure (kinetically and thermodynamically)
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