Partner Certification & Solutions Catalog


CombiGlide 4.1

The Advantages of Computational Lead Optimization
The virtual chemical space that chemists are interested in is too large to be synthesized and screened, even using modern methods of combinatorial chemistry and robotic synthesis. Therefore, there is a real need for efficient and reliable methods to rationally select the optimal library members for synthesis. Additionally, once a promising lead compound is discovered, different core scaffolds as well as side-chain substitutions must be enumerated and examined to evaluate relative binding affinities towards a particular target. Accurate ligand-receptor scoring coupled with intelligent and efficient combinatorial docking and core-hopping methods can accelerate lead optimization and aid in designing the optimal, focused compound library for further synthesis.
Schroedinger's CombiGlide can flexibly vary the core or side-chain substitutions, creating virtual combinatorial libraries that may be screened for leads, identify novel scaffolds, or generate focused libraries in support of lead optimization efforts.

							
							
							
							
						
  • Category Engineering
  • Highlights
  • Platform SLED 12
  • Hardware Architecture x86-64
  • Certification SUSE Ready
  • Platform SLES 12
  • Hardware Architecture x86-64
  • Certification SUSE Ready
  • Platform SLED 11
  • Hardware Architecture x86-64
  • Certification SUSE Ready
  • Platform SLES 11
  • Hardware Architecture x86-64
  • Certification SUSE Ready

Other Versions

CombiGlide 3.9

  • Platform SLED 12, SLES 12, SLED 11, SLES 11
  • Hardware Architecture x86-64
  • Certification SUSE Ready
  • Highlights

CombiGlide 2.8

  • Platform SLED 11, SLES 11
  • Hardware Architecture x86-64, x86
  • Certification SUSE Ready
  • Highlights

CombiGlide 2.7.111

  • Platform SLED 11, SLES 11
  • Hardware Architecture x86-64, x86
  • Certification SUSE Ready
  • Highlights