The phrase “in silico” is pseudo-Latin referring to silicon in computer chips and it has become a frequently used term describing biological or other experiments performed by computers. This is an evolution of traditional in vivo and in vitro models that were used to develop new drugs and verify pharmacological hypotheses for over a hundred years. Facing an increasing number of chronic illnesses and growing unmet medical needs, researchers recognize the necessity of discovering time-saving methods to deal with a large amount of complex information in drug discovery. In silico techniques are emerging to help simulate virtually all aspects of drug discovery and make decisions in picking strategies and targets.
More and more end-users, including contract research organizations, academic and research institutes, as well as biotechnology and pharmaceutical companies, are dedicated to developing drugs for complex and rare diseases leveraging computer-aided technologies. Ranging from small molecule drugs preclinical research to clinical candidates development stages, in silico technology is extensively explored and deployed in different stages of drug discovery.
Computational approaches are increasingly playing an important part in generating hypotheses, interpreting complex data, and guiding experimental works. Specifically, fields boosted by in silico techniques include but are not limited to:
- Antibody design and engineering
- Computer-aided drug design
Computer-aided Antibody Design
The in silico molecular techniques are gradually gaining traction for the engineering of antibodies, which help design molecules with optimized affinity, efficacy, safety, and therapeutic function.
The ability to bind certain molecules with high affinity and specificity makes antibodies potent diagnostic and therapeutic tools in life sciences research. In the field of computer-aided antibody design, in silico technology has been widely used in different parts of antibody design, including structure modeling, stability evaluation of antibodies, antigen-antibody complex prediction, and allosteric effects in antibodies. For instance, researchers can develop unique epitope-specific antibodies with high specificity and affinity using computer-aided epitope-specific antibody design platforms.
Computer-aided Drug Development
In silico approaches along with the application of A.I. platforms have driven pharmaceutical research and improved the efficiency of the drug discovery and development pipeline. Computer-aided techniques are making difference from various aspects in developing novel drugs and candidates, involving computational chemistry, molecular modeling, molecular design, and rational drug design. For example, a computer-aided modeling tool developed by scientists from Queen’s University Belfast can more selectively predict and identify novel sites of binding for potential drugs, leading to more effective drug targeting, increasing therapeutic efficacy, and reducing side effects in treating a range of illnesses.
Moreover, the time-saving and cost-effective method also contributes to limiting the usage of animal models in biopharmaceutical research and providing extensive support to pharmacologists and medical chemists.
In silico Drug Discovery in COVID-19
It’s anticipated that the global market of in silico drug discovery will reach a valuation of USD 6.34 billion by 2027. The current epidemic of COVID-19 is extremely propelling the demand and development of in silico drug discovery. In silico techniques are increasingly adopted to detect and diagnose coronavirus among patients, as well as to develop new therapeutics. Computer-aided solutions can help find new molecules from the molecular library, identify drug targets, and develop personalized drug candidates.