Molecular Modeling and Virtual Screening in Modern Drug Discovery Paper Example

Introduction

In the modern world of drug discovery, computational chemistry has dramatically helped the drug-making sector develop new medicines. The drug discovery process involves practices like binding protein agents o the target and increase chances of it helping in drug development process (Ganesan, 2008). Computational chemistry involves the use of algorithms that use physics knowledge together with computers. The computers and algorithms help scientists to discover the molecular chemical properties and at the same time. Knowing the molecular configuration of a biochemical agent helps the scientists to develop something to help in dealing with diseases. A variety of computational chemistry procedures helps in predicting and calculation of the expected outcome. For example, the algorithm improves the possibility of knowing the characteristics that we expect.

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Although computational chemistry is very expensive, it is impossible to avoid using it, for it is beneficial in medicine development. The use of the molecular analysis and modeling processes usually helps to improve and speed up the process of developing and testing drugs. The procedure of computational chemistry involves three essential steps, namely, lead identification, lead optimization, and clinical trial. The process helps identify the target of the drug, describes the newly formed drug, and optimizes the drug (Duffy et al., 2012)

Lead Identification

For the process of modern drug discovery, identifying screen hit is very important. The method of lead identification helps the medical researchers determine the enzyme or receptor on which the drug will act. In this case, the receptor is a chemical compound that the pharmaceutical developers can use for testing the drug once they develop it. The target is usually produced in the pharmaceutical industry and is a natural molecular structure on which the drug in construction will act (Katsila, et al, 2016). In conducting lead identification, a high level of technology is essential.

The technicians need to have resources like bio-informatics and computational genomics to determine the target. The first important step in assessing the effectiveness of the drug on the receptors is searching to look for inhibitors of molecules. The searching process is called hit identification. Lead hit identification also helps in identifying the activity and usability of the drug targets through screening. Once the hit identification is over, the scientist proceeds to the next steps where the lead generation process takes place before moving to the optimization stage (Jacoby, 2011). The diagram below shows an example of a receptor.

Lead Optimization

Once the drug developers have identified the hit targets, the next step is usually to optimize the target to make them have a higher affinity, selectivity, and reduce the side effects of the drug on the target. The aim of optimizing the objective is to make them more stable by increasing the half-life of the hit target. Structure-Based Drug Design (SBDG) is applied when structural information of the hit target is readily available. The use of structure-based procedures results in developing very effective drugs with fewer side effects (Ghose et al., 2012).

The processes of SBDD applies principles of molecular recognition to identify the structure of the protein targets (Bohacek et al.,1996). On the other hand, when the information on the target's molecular structure is absent, Ligand-Based Drug Design (LBDG) is vital for the optimization process. Ligand-based design results in the development of an agent that will bind very effectively with the target and make a compelling drug target. The ligand design also helps identify other biological agents' features, such as availability half-life and the side effect, which are essential in drug development (Krusemark, 2012).

The two drug design procedures are essential in identifying the agents' arrangement to serve as the targets. Determining the structure of the goal helps in assessing the suitability of the hit target. If the target passes all the qualifications to be used as the target, testing it becomes practical. The pharmaceutical procedure relies on information from practices that initially, the drug makers contacted earlier (Verbist et al., 2015). Therefore, it easy to predict and improve the effectiveness of the method.

Clinical Trial

Once the pharmacists have identified the hit target and have optimized it, they take the next action of testing the effectiveness of the drug under construction. The trials are experimental procedures that medical developers do in medical research. The testing process involves the use of human beings. The people in the clinical testing step are essential, for they help to provide feedback on the effect of the drug (Bill and Gates Foundation, 2014 ). The clinical testers use people to test the impact of the new vaccines, medicines, dietary supplements, or medical equipment.

Out of the clinical drug testing, the researchers have to prepare a report on the impact of the new drug on human beings. The next step in drug development is vetting the drug and assessing the drug's risk on human beings. The task of testing the drug is usually in the hands of health committees. Once health authorities or committees are satisfied that the drug is healthy for human use, they approve the dug and declare it ready for use.

The process of drug development is becoming better every day because pharmaceutical firms are now using a more robust algorithm for the means of developing drugs. The advancement in technology has made computational chemistry to be more productive. The improvements have made the drug development processes to be cheaper, faster, and more productive. Lead target identification and optimization have become more effective because of the use of more reliable algorithms in drug discovery processes (Lipinski et al., 1997). The method of drug discovery usually appears as you can see in the diagram below.

The Role of Computational Chemistry in Modern Drug Discovery

Improved use of technology in drug discovery has dramatically increased the drug developing process. For instance, the recent eruption of the technique called the Free Energy Perturbation (FEP) estimations show that there is a significant improvement for chemical analogy (Bohacek, & McMartin, 1997). Th increased energy helps improve the process of target identification and optimization making drug discovery a great success.

The use of the high-class Molecular Dynamics (MD) is a significant advancement in computational chemistry technology. MD is a simulation method that uses computers to analyze the movement of atoms and molecules physically. Newton's equations of motion help to quantify the properties of the atoms and molecules in motion. The analytical tool is handy in the protein target optimization process as it helps in the study of the energetics and therefore results in developing a more stiff target. The technology is the one that has made the ligand biding process to become more productive. MD helps scientists evaluate the strength of a compound by determining its ability to bind to the target stiffly.

Additionally, the use of MD has made it possible for a compound to remain bind to the target for a long time. The increased ability of a compound to stay bound to the target long makes scientists enjoy increased efficacy, especially when doing the work within an organism (Clerk et al., 2010).

Advancement in computational chemistry technology has also led to the development of Quantum Mechanics (QM). QM is a technique that we can use in different fields to determine how different elements of matter move and interact with each other. This technology is highly instrumental in predicting events' outcomes due to motion and interactions (Tsekov et al., 2018). Quantum mechanics is the last decade's most significant technological advancement in drug discovery (Liu et al., 2015). QM is a technology used to develop and optimize lead targets using structure-based techniques and is now highly accessible to scientists (Vivo, 2011). for instance, the use of QM techniques to study how covalent inhibitors react with the drug testing target.

The knowledge of the structure of the protein target is instrumental in drug discovery as it makes it possible to develop and test the drugs that the scientists develop. Knowing the formation of a compound has become very easy because of high-resolution X-Ray crystallography or Nuclear Magnetic Resonance (NMR) (Klages & Kessler, 2007). Both XRay crystallography and NMR help to identify the 3-dimensional anatomical structure of a biological molecule like protein. In the field of computational chemistry, both techniques are instrumental in determining the target's structure and, therefore, help make the right choice of destination (Crespo et al., 2017).

Computational chemistry mostly helps drug developers in the lead identification and optimization phase of drug development. Structure-Based Drug Discovery uses the most advanced techniques in the computation of the anatomy of elements in the process of coming up with a target. The methods of computing in SBDD also include the means of Force Field-based approach and the QM process (Vivo, 2011; Brown & Jacoby, 2006). Regardless of the technique that scientists will use, it is essential first to analyze the compounds to determine the potency of the target they choose.

Virtual screening and Quantity Structure-Activity Relationship (QSAR) are now very instrumental in the process of drug discovery. QSAR helps identify and predict the biological property of the novel compounds (Vilar et al., 2008). QSAR technology allows scientists to establish the relationship between molecule receptors and their ability to serve as drug target candidates (Geromichalos, 2012).

The virtual screening methods can discover small molecules that can serve as hit targets for the drug under construction. Virtual screening makes the scientist identify the physio-biological properties of the biochemical agents. Hence, they get able to determine whether the agents are suitable for use as the hit target. Once the scientists identify the molecules, it becomes easy for them to test and optimize the particles using the other techniques.

Although there are various computational chemistry techniques, each method is usually suitable for a given step or type of drug discovery. The recent technological advancements in the field of computational chemistry have made drug testing techniques to be more productive. The improvement has resulted in designing, detecting, and optimizing the lead targets to become very easy and effective (Hung & cheng, 2014). The effect of improved detection and optimizing is developing of extreme drug candidates. Some processes which people initially considered to be unfit for use in drug development are now the most effective means of the process of developing drugs.

Procedures of computational chemistry are fundamental as they help identify and analyze the effect that the drug could have on living organisms. The assessment ensures that by the time the scientists test the drug on human beings, they can predict the drug's outcome.

Virtual High-Throughput Screening

Virtual High-Throughput Screening (vHTS) is one of the modern ways of screening that drug developers use to make drug discovery faster and more effective (Zoete et al., 2006). This screening technique uses automated equipment to test a significant number of samples rapidly. HTS help to screen a high number of small molecules of known structures as well as chemical compounds and tracts of na...