Why Computational Methods of Drug Discovery is the Solution we need today?

Computer-aided drug design CADD is the development of novel drugs using Computational Tools. Computational drug discovery companies use computational drug discovery as a way of increasing the effectiveness and decreasing drug development costs. 

Bioinformatics enables the availability of biological molecules on Computers. This has enabled the applicability of computer-aided methods of discovery at every stage of drug development. 

The traditional methods of Drug discovery are time-consuming and risky. Also actually testing out different drugs can increase the costs. Because of this, the popularity of CADD quickly increased once different computational tools have provided the environment for the rapid drug discovery process.

This is achieved by screening and synthesizing huge libraries of compounds in a short time. The use of computational tools for drug discovery can reduce the costs up to 50% by reducing the risk of failures and shortening the research cycle.

The efficiency and accuracy of these tools depend on the following.

Different Methods of Drug Discovery

Technical aspects of Drug Discover Tools

  1. Conformation generation and sampling
  2. Scoring functions
  3. Optimization Algorithms
  4. Molecular similarity  calculations
  5. Virtual Library design
  6. Sequence-based drug design

Computational Methods of Drug Discovery

Computational methods of Drug discovery can be categorized into;

  1. Structure-Based Drug Design (SDBB)
  2. Ligand Based Drug Design (LBDD)

SDBB methods analyze macromolecular targets to identify key sites that are important for their respective biological function.

LBDD method focuses on known antibiotic Ligands for a target to establish the relationship between their properties and antibiotic activities.

These methods can produce an atomic-level structure-activity relationship (SAR). SAR facilitates the drug design process to minimize time and costs.

SAR or Structure-Activity Relationship is the relation between the structure of the molecule and its biological effect on the body. Scientists and Chemists use this technique for drug discovery by testing different chemical groups for a particular biomedical compound by inserting the chemicals into the compound to test its effects. SAR determines the relationship of a chemical molecule with its effects on human or animal species. 

Understanding this relationship helps to reveal the limitations in the current antibiotics and thus helps in the design of new drugs. Medicinal chemists also look for new antibiotics using SAR for existing targets.

There are commercially available software packages to manipulate and quantify the properties of potential drugs. Some of them are stated below;

Software algorithm used for Drug Discovery

  1. CHARRM, AMBER, NAMD, GROMACS  and OpenMM are commonly used simulation codes that run on a variety of Computer Architectures
  2. PDB or protein data bank provides the structures of different RNA. 
  3. MODELLER helps with the construction of a 3D structure using homology methods.
  4. FINDSITE and ConCavity are used for binding site identification
  5. DOCK and AutoDock are well-known freeware programs for Virtual screening techniques
  6. ChemBridge and ChemDiv are used for the construction of virtual screening databases
  7. Some commercially available CADD software packages include Discovery Studios, Open Eye, Schrodinger and MOE. These packages cover most of the tools used in CADD.

Now, CADD can be classified into ligand identification or hit optimization. Various screening methods are used for the same are given below.

Screening Methods for Drug Discovery

1. MD Simulations

MD simulations are used to study ligand interactions with the target. These studies are conducted at atomic levels to estimate relative free energies of binding. 

2. Site Identification by Ligand Competitive Saturation (SILCS)

Site identification by Ligand Competitive saturation is CADD protocol is used to facilitate ligand design. It uses small organic solutes such as propane to identify 3D functional group binding patterns.

It is then subjected to MD simulations to reveal what types of functionalities bind with the protein surface.

3. Database preparation

Virtual screening is a viable method to find lower molecular weight binders to give proteins. VS is often carried out against databases that contain commercially available compounds. There are various databases available. Some scientists also use their own databases for virtual screening.

4. Docking Based VS

Docking based VS is used for binding energy calculation. There are numerous amounts of proteins present in the human body. It is impossible to scan those using physical methods. In Docking based VS a panel of proteins is scanned by potential targets for the given ligands.

5. SILCS Pharm

It is an alternative docking based VS. It can filter a database for potential binders to a specific target. This model is defined as distributed chemical features that are essential for specific ligand-target binding.

4. Similarity Search

LBDD methods can be utilized to develop a SAR to find more hit compounds. The similarity search method is the most straightforward and rapid approach. It is able to search for compounds that are chemically similar to the input compound.


There are more methods than the ones stated below that use SAR and other approaches for novel drug discovery.

The use of CADD by computational Drug discovery companies has increased in the past few years because of the opportunity it offers. 

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