AMBER

Amber, an acronym for Assisted Model Building with Energy Refinement, is a family of force fields for molecular dynamics of biomolecules originally developed by the late Peter Kollman's group at the University of California, San Francisco. AMBER is also the name for the molecular dynamics software package that simulates these force fields. It is maintained by an active collaboration between David Case at Rutgers University, Tom Cheatham at the University of Utah, Tom Darden at NIEHS, Ken Merz at Florida, Carlos Simmerling at Stony Brook University, Ray Luo at UC Irvine, and Junmei Wang at Encysive Pharmaceuticals. (Read more on Wikipedia).

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Projects

Electrostatic embedded energy calculations of proteins, using the ONETEP DFT code

Chris-Kriton Skylaris (Investigator), Stephen Fox, Chris Pittock

Calculating the energy of a biomolecule in solvent, using quantum mechanics (QM) is possible, but extremely challenging, even with linear-scaling QM methods like ONETEP. Using electrostatic embedding, a novel twist on the existing QM/MM method is used to calculate the binding energy of a small ligand to a solvated protein, increasing the accuracy and realism of our general project work.

Hybrid quantum and classical free energy methods in computational drug optimisation

Jonathan Essex, Chris-Kriton Skylaris (Investigators), Christopher Cave-Ayland

This work is based around the application of thermodynamics and quantum mechanics to the field of computational drug design and optimisation. Through the application of these theories the calculation of the physical properties of drug-like molecules is possible and hence some predictive power for their pharmaceutical activity in vivo can be obtained.

Molecular Fragments in Inhibitor Design

Jonathan Essex (Investigator), Michael Bodnarchuk

Fragment-Based Drug Discovery (FBDD) has emerged as an important tool in the drug discovery process. Instead of screening entire drug molecules, FBDD screens molecular fragments; constituents which make up drug molecules. A computational approach to identifying fragment binding is currently being sought which also yield binding free energy estimation.

Sustainable domain-specific software generation tools for extremely parallel particle-based simulations

Chris-Kriton Skylaris (Investigator)

A range of particle based methods (PBM) are currently used to simulate materials in chemistry, engineering, physics and biophysics. The 4 types of PBM considered directly in the proposed are molecular dynamics (MD), the ONETEP quantum mechanics-based program, discrete element modelling (DEM), and smoothed particle hydrodynamics (SPH).
The overall research objective is to develop a sustainable tool that will deliver, in the future, cutting edge research applicable to applications ranging from dam engineering to atomistic drug design.

Water Molecules in Protein Binding Sites

Jonathan Essex (Investigator), Michael Bodnarchuk

Water molecules are commonplace in protein binding sites, although the true location of them can often be hard to predict from crystallographic methods. We are developing tools which enable the location and affinity of water molecules to be found.

People

Jonathan Essex
Professor, Chemistry (FNES)

Nicolas Green
Reader, Electronics and Computer Science (FPAS)

Chris-Kriton Skylaris
Lecturer, Chemistry (FNES)

Michael Bodnarchuk
Postgraduate Research Student, Chemistry (FNES)

Christopher Cave-Ayland
Postgraduate Research Student, Electronics and Computer Science (FPAS)

Stephen Fox
Postgraduate Research Student, Chemistry (FNES)

Chris Pittock
Postgraduate Research Student, Chemistry (FNES)

Barbara Sander
Postgraduate Research Student, Chemistry (FNES)

Petrina Butler
Administrative Staff, Research and Innovation Services