What Is Structure-based Drug Design?
Structure-based drug screening and ligand binding mode analysis have become key elements in the calculation process of modern drug development. It can not only discover potential compounds targeting specific targets, but also help explain the structure-activity relationship observed experimentally. Therefore, structure-based computer technology plays an essential role in all stages of drug development. At Alfa Chemistry, we provide a series of structure-based drug design (SBDD) services and our capabilities include virtual screening, flexible target sampling, skeleton transitions, de novo design, and estimation of the affinity between ligands and target proteins.
Figure 1. Structure-based drug design (SBDD) process. (Ben, L.; et al. 2016)
Application of Structure-based Drug Design
- Predicting the binding of small molecules to protein targets
- Calculating binding affinity
Our Structure-based Drug Design Services
Alfa Chemistry has an experienced computational science team that applies SBDD techniques to carry out drug discovery projects. Our rapid and high-quality services are as follow:
The successful evaluation of binding energy depends on the accurate prediction of the binding mode. We use molecular docking method to determine the best position and orientation of small molecules in protein targets. A simple and accurate scoring function has been established and applied to evaluate the binding affinity, and it has proven to be available for the prediction of computational screening in high-throughput molecular docking. Moreover, our calculation simulation provides sufficient accuracy to calculate the relative binding energy either. The flexibility of the target cannot be ignored in molecular docking process. Our scientists use induced-fit docking and molecular dynamics (MD) simulation methods to obtain diversified protein conformations and handle the flexibility issues of crystal structures.
Crystal structure prediction
Most research on molecular docking prediction is based on molecules that bind to protein targets with detectable affinity and available crystal structures. We perform crystal structure prediction to optimize the binding mode of small molecules in protein structures, and estimate the affinity of ligand to target protein.
At Alfa Chemistry, our groups carry out homology modeling and model optimization based on the sequence information of the target and the structure of the same histone protein when the crystal data is absent or unavailable.
Structure-based virtual screening
The aim of virtual screening is to evaluate whether the compounds in the molecular library are likely to bind to proteins, and to list the molecules most likely to bind with the highest affinity. We can perform rapid searching of large libraries of chemical structures to identify potential drug candidate which are most likely to bind to a drug target followed by molecular docking process. Our structure-based virtual screening can significantly improve the hit rate by considerably decreasing the number of compounds for experimental estimation of their activity and thereby increases the success rate of in vitro experiments.
We use MD simulation to analyze the binding site and binding mode of the mapped ligand. The simulation of ligand unbinding provides an in-depth understanding of the affinity of the complex and quantifies the energy change throughout the process. MD simulations can provide protein conformations beyond those available in protein crystallography, discover new hidden binding sites, and expand the druggability of the target. We use MD approach to increase or decrease the size of the active site pocket using all-atom simulations. The initial posture of the ligand that induces binding can be obtained by docking a known inhibitor to the pocket of the target protein. At Alfa Chemistry, MD simulations can be performed in the presence of lower concentrations of ligands, which have proven to be able to effectively detect conformational spaces and discover new concealed pockets.
Quantum mechanics (QM) calculation
The optimization of lead compounds can be achieved by screening small molecules of the same series. Sampling and optimization of the conformation of the R group can improve the accuracy of predicting the binding mode. We use QM calculation to predict the stable state and flexibility of the compound conformation, and study the binding mode of the compound and the target.
Fragment-based drug design (FBDD)
At Alfa Chemistry, FBDD is supplied as a complementary approach of SBDD. We use this tool to find key ligand-receptor interactions, providing a good starting point for compound design. In this procedure, the leads are identified, optimized, and linked together to produce high-affinity ligands based on the structure-activity relationships (SAR).
- We can apply a variety of skeleton transition methods to generate new patented compound sets to improve the properties of compounds.
- Our experts are capable of utilizing the solute and solvation energy to optimize the binding affinity, and more accurately predict the 'natural' binding mode of the compound.
Our structure-based drug design services remarkably reduce the cost, promote further experiments, and accelerate the process of drug design for customers worldwide. Our personalized and all-around services will satisfy your innovative study demands. If you are interested in our services, please don't hesitate to contact us. We are glad to cooperate with you and witness your success!
- Ben, L.; et al. Quantitative Methods in System-Based Drug Discovery. INTECH. 2016, 6: 86-98.