Goran Krilov

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The mechanism (or mechanisms) of enthalpy-entropy (H/S) compensation in protein-ligand binding remains controversial, and there are still no predictive models (theoretical or experimental) in which hypotheses of ligand binding can be readily tested. Here we describe a particularly well-defined system of protein and ligands--human carbonic anhydrase (HCA)(More)
We present a new computational strategy for the design and evaluation of novel enzymatic pathways for the biosynthesis of fuels and chemicals. The approach combines the use of the Biochemical Network Integrated Computational Explorer (BNICE) framework and a structure-based screening method for rapid generation and evaluation of novel enzymatic reactions and(More)
Detailed understanding of protein-ligand interactions is crucial to the design of more effective drugs. This is particularly true when targets are protein interfaces which have flexible, shallow binding sites that exhibit substantial structural rearrangement upon ligand binding. In this study, we use molecular dynamics simulations and free energy(More)
G protein-coupled receptors (GPCRs) represent a large family of signaling proteins that includes many therapeutic targets. GPCR ligands include odorants, tastants, and neurotransmitters and vary in size and properties. Dramatic chemical diversity may occur even among ligands of the same receptor. Our goal is to unravel the structural and chemical features(More)
The fluctuating elastic boundary (FEB) model for molecular dynamics has recently been developed and validated through simulations of liquid argon. In the FEB model, a flexible boundary which consists of particles connected by springs is used to confine the solvated system, thereby eliminating the need for periodic boundary conditions. In this study, we(More)
Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods(More)
We present the reactive flux analytic continuation ͑RFAC͒ method, based on the quantum reactive flux formalism combined with a numerical analytic continuation approach to calculate quantum canonical rates in condensed phase systems. We express the imaginary time reactive-flux correlation function in terms of a frequency dependent rate constant, and use path(More)
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