Showing papers by "Michael Feig published in 2007"
TL;DR: Kinetic properties of alanine dipeptide, the B1 domain of streptococcal protein G, and ubiquitin are compared between explicit solvent and implicit solvent simulations with the GBMV method and it is found that local conformational exploration without the crossing of significant barriers can be accelerated.
Abstract: Kinetic properties of alanine dipeptide, the B1 domain of streptococcal protein G, and ubiquitin are compared between explicit solvent and implicit solvent simulations with the generalized Born molecular volume (GBMV) method. The results indicate that kinetics from explicit solvent simulations and experiments can be matched closely when the implicit solvent simulations are combined with Langevin dynamics and a friction coefficient near 10 ps-1. Smaller and larger friction coefficients accelerate and slow down conformational sampling. It is found that local conformational exploration without the crossing of significant barriers can be accelerated by a factor of 4−5; however, the acceleration of barrier crossings is limited to about a factor of 2. The use of a Nose−Hoover thermostat instead of Langevin dynamics greatly enhances local conformational sampling but slows down the crossing of barriers by at least an order of magnitude because of the lack of solute−solvent stochastic collisions.
70 citations
TL;DR: Conformational sampling based on the coarse‐grained SICHO model, atomic level of detail molecular dynamics simulations, and normal‐mode analysis is compared and all of the sampling methods can achieve significant refinement close to experimental structures, although the distribution of structures and the ability to reach native‐like structures differs greatly.
Abstract: Protein structure refinement from comparative models with the goal of predicting structures at near-experimental accuracy remains an unsolved problem. Structure refinement might be achieved with an iterative protocol where the most native-like structure from a set of decoys generated from an initial model in one cycle is used as the starting structure for the next cycle. Conformational sampling based on the coarse-grained SICHO model, atomic level of detail molecular dynamics simulations, and normal-mode analysis is compared in the context of such a protocol. All of the sampling methods can achieve significant refinement close to experimental structures, although the distribution of structures and the ability to reach native-like structures differs greatly. Implications for the practical application of such sampling methods and the requirements for scoring functions in an iterative refinement protocol are analyzed in the context of theoretical predictions for the distribution of protein-like conformations with a random sampling protocol. Proteins 2008. © 2007 Wiley-Liss, Inc.
40 citations
TL;DR: Materials and methods MD simulations of 6 FDA-approved drugs, which are Lopinavir (LPV), Ritonavir (RTV), Saquinavir(SQV), Indinavir(IDV), Amprenavir, and Nelfinavir, were performed using AMBER 8 to predict mutation prediction.
Abstract: Materials and methods MD simulations of 6 FDA-approved drugs, which are Lopinavir (LPV), Ritonavir (RTV), Saquinavir (SQV), Indinavir (IDV), Amprenavir (APV), and Nelfinavir (NFV), were performed using AMBER 8. The total inhibitorenzyme binding free energy (ΔGtotal) including entropic contributions of 6 complexes was estimated based on MM-PB(GB)SA approach. The decomposition free energy (ΔGDC), representing interaction between inhibitor and each residue, was calculated and used as the criteria for the mutation prediction.
1 citations