Maestro Elements
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Maestro Elements: A streamlined version of the Maestro interface with integrated computational analyses designed for medicinal chemists

Modelers throughout biopharmaceutical industry use Maestro, the feature-rich modeling environment of Schrödinger’s drug design software, while chemists usually view computed results in their own favorite graphical interfaces. This process creates unnecessary inefficiencies, and important information could be lost. Furthermore, it hinders the chemists from exploring additional computational analyses on their own.

Maestro Elements was developed to facilitate communication and collaboration between modelers and chemists. Maestro Elements is fully compatible with Maestro, but is designed for medicinal chemists who need something that just “works.” Task-oriented interfaces in Maestro Elements flatten the learning curve, allowing chemists and biologists to visualize data provided by modelers, and perform simple “what if” calculational experiments on their own with minimal setup work required. Maestro Elements runs on desktop Windows machines and comes with all of its capabilities fully integrated.

Features

There are three different versions of Maestro Elements available:

Basic level

  • Full featured 3D graphical interface
  • Molecular spreadsheet with 2D structures
  • Project sharing
  • Image saving and movie making capabilities
  • Molecule builder with 2D fragments
  • Molecular adjustment (dihedral, chirality, rotamer)
  • Display contacts, distances, and H-bonds
  • Protein binding site characterization

Intermediate level

in addition to the above,

  • Ligand preparation (1D/2D to 3D conversion)
  • Flexible ligand alignment
  • Protein-protein alignment
  • Calculation of molecular properties
  • Property filtering
  • pKa prediction (rule-based)
  • Torsional energy scan
  • Minimization
  • Align binding sites
  • Protein structure reports
  • Ramachandran plot
  • Conformational search
  • R-group analysis
  • Electrostatic potential surface

Advanced level

in addition to the above,

  • Binding site identification and characterization
  • Binding site druggability assessment
  • Automated protein preparation
  • pKa prediction (ab initio)
  • Shape-based screening
  • Core hopping
  • Sequence alignment and editing
  • Interactive ligand design with energy-based scoring
  • Pharmacophore searching