Ligand-based virtual screening (LBVS) is one of the two main computational techniques for virtual screening.The LBVS approach attempts to prioritize candidate molecules rather than determine whether a candidate molecule is active or not. Typically, a simple LBVS process consists of only a few steps. First, a molecular representation of each input molecule is created. Second, similarities between candidate molecules and known active molecules will be evaluated and ranked according to their respective scores. Finally, a small number of active compounds will be identified from a library containing a large number of inactive compounds. Creative Enzymes provides you with a variety of ligand-based restriction enzyme inhibitors design service to meet your scientific research needs.
Ligand-based restriction enzyme inhibitors design can be effectively applied to accelerate drug discovery. Our ligand-based virtual screens can be divided into three categories.
Molecular or physicochemical global parameters such as molecular volume, number of hydrogen bond donors/acceptors are applied for substructure screening. We search the database for molecules containing the query molecule as substructure.
Computational chemical similarity is described using the properties of two-dimensional chemical structures, such as molecular fingerprinting (FP).FP is a typical pathway-based approach that analyzes linear pathways of all fragments of a molecular structure with a given number of bonds, and it uses simple vectors to characterize many chemical features. And the quantification of similarity between FP is usually obtained by Tanimoto coefficients.
This method mainly considers the three-dimensional geometric conformation of molecules, including pharmacophore identification and shape similarity. The most commonly used methods for three-dimensional similarity quantification are Tanimoto correlation coefficient and Manhattan distance. We mainly apply this method to study skeleton migration, and use the WEGA algorithm to calculate the 3D structural similarity between the query molecule and the molecules in the database.
Creative Enzymes has designed a multi-feature integration algorithm based on algorithm-based matching and machine learning development containing various descriptors.
Our ligand-based approach is based on molecular similarity evaluation between the submitted molecules and those in the active compound database. This database consists of multiple reported bioactive molecules with target or mechanism information.
Creative Enzymes is a company that provides professional and comprehensive ligand-based restriction enzyme inhibitors design service. We have years of experience to meet your specific project needs in using enzyme research to add value to your research projects. Creative Enzymes can provide you with personalized solutions to help you thrive every step of the way around your interest in your workflow. If you would like to know more about this service, please feel free to contact us.
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