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Free download Biopharmics Surflex platform for Windows PC. It is a comprehensive software set for advanced molecular modeling and discovery of medicines. This includes a variety of modules for managing different aspects of calculating chemistry, from the treatment of small molecules to virtual selection and binding of affinity.
Overview of the Biofarmika Platform
It consists of five modules: tools, resemblance, dock and xgen and relatives. Each module is designed to simplify specific drug discovery and molecular modeling tasks, providing researchers reliable and effective workflow.
Tool module
Tool module is focused on the preparation and processing of small molecules. This offers a set of features that provides quick and accurate processing of molecular data.
Features and Advantages:
- 2D to 3D Conversion: transforms smiles or
- Protonation: adjusts molecules protons.
- Conformors generation: create various molecules conformations.
This module uses the MMFF94SF force field to withdraw the structure to ensure a high impact. This is particularly proficient in treating macrocyclic ligands and can include NMR restrictions, which are very important for large pepticts of macrocys.
Similarity module
Similarity module is designed to perform 3D molecular similarities.
Features and Benefits:
- Virtual Verification:
Effectively screening large molecular databases with speeds above 20 million compounds per day. The alignment of comparative analysis is several ligands.
The virtual selection capabilities of the module are practically and statistically superior, making it a powerful tool for high throughput.
Docking and XGen modules
These modules are a detailed solution for virtual selection, decide, and X-Rabem Modulia and X Rabelia Modules and X-Rabem Models. Liganda.
Docking Module Properties:
- PDB Reatver: Automates for large -scale and PDB structures automatically select appropriate protein conformations for virtual selection.
XGen Module Properties:
- Ligando Density Modeling: Uses Conformation Ensembles for real space development. X-ray density.
These modules are high validated and can Handle Both non-Macryclic and Macroclic Ligats with High Accuracy. Quansa Method for Predicting Binding Affinity and Ligand Pose, Integraming Machine Learning to Enhance Predictive Accuracy.
properties and advantages:
- bind the Afinitian forecast: using physical models.
- model anticipation: accuracy over time.
This module creates detailed models that approximate the causal basis of the interaction of the protein-lighter interaction, making it a unique and powerful tool for drug discovery.
