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Reverse Virtual Screening

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Virtual screening method has become an indispensable and important technology in the development of new drugs. In the traditional virtual screening method, a computer algorithm program based on physical chemistry is used to rank the small molecule compounds in the database for a given target protein, and the potential ligand molecules of the target protein are selected from them. Reverse virtual screening is another virtual screening method, which is the opposite of the traditional virtual screening method. In a reverse virtual screening, the target protein that can bind to a given ligand molecule is able to be selected from the database. Nowadays, the reverse virtual screening method based on molecular docking has important application prospects in the field of drug target determination, new use of old drugs, and drug side effects/toxicology research.

Depiction of high-throughput virtual screening: multiple ligands are docked to a receptor and ranked by energy estimate.Figure 1. Depiction of high-throughput virtual screening: multiple ligands are docked to a receptor and ranked by energy estimate. (Jacob, R. B.; et al. 2012)

Application of Reverse Virtual Screening

  • Target identification

Reverse virtual screening can be used in the determination of drug targets, which can help to understand the mechanism of drug action, and effectively improve the drug to enhance its efficacy.

  • Drug repositioning

We use this strategy to find new target proteins for existing drugs to achieve the purpose of treating new diseases.

  • Side effects/toxicity studies

Our teams apply reverse virtual screening to predict drug's side effects in the early stage of new drug development by determining other proteins that can bind to the drug in addition to the target protein.

Methodologies

  • Ligand-based methods
  • Binding site comparisons
  • Protein-ligand interaction fingerprints
  • Docking-based methods

Reverse Virtual Screening Process

The reverse virtual screening method based on molecular docking generally consists of two parts: the molecular docking method used as a search engine and the protein target database. Alfa Chemistry has established a reverse virtual screening workflow:

  • Database preparation
  • Ligand search

The molecular docking program is used to dock the small molecule with the protein receptor in the database one by one.

  • Score and rank complex structures.

Output the corresponding score value, and the protein receptors in the database are ranked according to the score.

  • Manual selection

The protein with the highest score is selected as the potential target of the ligand molecule.

Components of Reverse Virtual Screening

At Alfa Chemistry, we apply a docking-based method to perform reverse virtual screening, and major components are explained as follows:

  • Target databases

Our database is composed of protein receptors with known structures and capable of binding small molecule ligands. We can also construct a more refined protein receptor database to meet your demands.

  • Docking engines

At Alfa Chemistry, a molecular docking program is designed to predict a complex structure. We implement stochastic Monte Carlo (MC) methods to design algorithms. For deterministic search, energy minimization methods and molecular dynamics (MD) simulations are applied. Our experts also support the application of soft docking that allows an overlap between the ligand and the receptor by softening the interatomic van der Waals (vdW) interactions. In terms of docking with multiple receptor structures, we use pre-generated receptor conformers. In addition, induced fit docking (IFD) is available in which we can change both protein and ligand conformations to fit each other during the docking process.

  • Scoring functions

We mainly apply three major scoring functions: force field-based, empirical, and knowledge-based. Parameters in force field-based scoring functions are derived from molecular mechanical force fields used in MD simulations, including contributions from vdW interactions, electrostatic interactions, and bond stretching/bending/torsional potentials. We fully consider the desolvation effects by using implicit solvent models like the Poisson-Boltzmann/surface area (PB/SA) model and the generalized-Born/surface area (GB/SA) model. Different energy terms such as vdW, electrostatics, hydrogen bond, desolvation, entropy, hydrophobicity, and so on are used in the empirical scoring functions. Our scientists develop the knowledge-based scoring functions through the statistical analysis of the atom pair occurrence frequencies in a training set of experimentally determined protein-ligand complex structures.

  • Web servers

Our several web servers have been developed to handle hundreds of dockings and to conduct post analysis. The server automatically runs the reverse virtual screening and outputs a list of potential targets.

Alfa Chemistry's Advantages

  • A variety of international recognized and industrial leading drug design software are available to provide reverse virtual screening services.
  • We offer additional ADMET drug-ready and molecular structure diversity filter to support the screening process.
  • Alfa Chemistry supports multiple databases for pharmacophore screening and molecular docking according to your specific needs.

Our reverse virtual screening 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!

Reference

  • Jacob, R. B.; et al. Accessible High-Throughput Virtual Screening Molecular Docking Software for Students and Educators. PLOS Computational Biology. 2012, 8(5): e1002499.

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