Molecular Modeling and SimulationsMOE has core technology for simulations of small organics and macromolecules. Simulations are an important tool to validate ligand pose geometries, stability and the generation of macromolecule conformations for docking, protein engineering, etc.
Automatically correct many problems encountered in crystallographic data such as missing loops, empty residues, chain termini or breaks, missing disulfide bonds or atom names, picking alternate conformations, etc using the Structure Preparation application. Optimize the hydrogen bonding network by navigating through different tautomer/protomer states or automatically by using Protonate3D [Labute 2008]. Protonate3D calculates optimal protonation states, including titration, rotamer and “flips” using a large-scale combinatorial search.
Use industry standard molecular mechanics forcefields such as AMBER 94/99, CHARMM 27, MMFF94(s), OPLS-AA and Engh-Huber that run on multiple CPU threads. Amber12:EHT uses Amber12 parameters for macromolecules and Extended Hückel Theory parameterization for small molecules that takes electronic effects into account. Calculate partial charges including AM1-BCC charges [Jakalian 2002]. Choose from gas phase, distance dependent dielectric, reaction field and GB/VI Generalized Born [Labute 2008] implicit solvent electrostatics. Use Rigid-Body energy minimization for fusion protein construction.
Generate dynamics trajectories with advanced integration algorithms for constant pressure and/or temperature ensembles: Nosé-Poincaré-Anderson [Sturgeon 2000][Bond 1999] and Nosé-Hoover-Anderson [Hoover 1985]. Create explicit solvent droplets or periodic systems. Automatically generate scripts for MOE/batch or the NAMD engine from a specialized protocol language to run locally, on GPUs or clusters. Calculate MM/PBSA energies using the Poisson-Boltzmann equation solver.
Perform a conformational search using LowModeMD, molecular dynamics, stochastic or systematic search methodologies. LowModeMD [Labute 2010] generates conformations of small molecules, protein loops, macrocycles and multi-component systems by performing a fast implicit vibrational analysis and short molecular dynamics simulation. Use implicit or explicit water and counter-ions.
Quantum Mechanical calculations are supported through interfaces to popular quantum codes: Gaussian, GAMESS, MOPAC and ADF. Optimize small molecule conformation databases (in parallel) using the quantum engines. Use a graphical interface to configure a calculation and view results such as electron density contours, molecular orbital plots, energy level diagrams and other properties.
Perform 3D alignment (or superposition) of known and putative ligands to determine structural requirements for biological activity – particularly useful in ligand based drug design protocols. Use the all-atom flexible alignment procedure [Chan 2010, Labute 2001] that combines a forcefield and a 3D similarity function based on Gaussian descriptions of shape and pharmacophore features to produce an ensemble of possible alignments of a collection of small molecules.
[Chan 2010] Chan, S.L., Labute, P.; Training a Scoring Function for the Alignment of Small Molecules; J. Chem. Inf. Model. 50 (2010) 1724 – 1735.
[Hoover 1985] Hoover, W.G.; Canonical Dynamics: Equilibrium Phase-Space Distributions;Physica 188A (1985) 111–122.
[Jakalian 2002] Jakalian, A.; Jack, D.B.; Bayly, C.I.; Fast, Efficient Generation of High-Quality Atomic Charges. AM1-BCC Model: II. Parameterization and Validation. J. Comput. Chem. 23(2002) 1623–1641.
[Labute 2001] Labute, P., Williams, C., Feher, M., Sourial, E., Schmidt, J. M.; Flexible Alignment of Small Molecules; J. Med. Chem. 44 (2001) 1483–1490.
[Labute 2008] Labute, P.; The Generalized Born / Volume Integral (GB/VI) Implicit Solvent Model: Estimation of the Free Energy of Hydration Using London Dispersion Instead of Atomic Surface Area; J. Comput. Chem. 29 (2008) 1963–1968.
[Labute 2008] Labute, P.; Protonate3D: Assignment of Ionization States and Hydrogen Coordinates to Macromolecular Structures; Proteins 75 (2008) 187–205.
[Labute 2010] Labute, P.; LowModeMD – Implicit Low Mode Velocity Filtering Applied to Conformational Search of Macrocycles and Protein Loops; J. Chem. Inf. Model. 50 (2010) 792–800.
[NAMD] NAMD User's Guide Version 2.7b1 (2009) University of Illinois;www.ks.uiuc.edu/Research/namd.
[Sturgeon 2000] Sturgeon, J.B., Laird, B.B.; Symplectic algorithm for constant-pressure molecular-dynamics using a Nose-Poincare thermostat; J. Chem. Phys. 112 (2000) 3474-3482.
[Bond 1999] Bond, S.D., Leimkuhler, B.J., Laird, B.B.; The Nose-Poincare method for constant temperature molecular dynamics; J. Comp. Phys. 151 (1999) 114-134.