原题
Computational Chemistry in Drug Discovery
Computational chemistry has transformed drug discovery by providing tools to model and predict molecular behavior. Traditionally, drug discovery involved labor-intensive trial and error. Now, with advanced algorithms and powerful computers, researchers can test interactions between drug candidates and biological targets via computer simulations before moving to the lab.
One major advantage of computational methods is their ability to analyze vast chemical spaces. For example, machine learning algorithms can predict the binding affinity of millions of compounds to a target protein, narrowing down candidates for testing. This speeds up the discovery process and reduces costs. In one case, researchers identified a promising compound for treating a rare disease in weeks, a task that would have taken years using traditional methods.
Moreover, computational chemistry optimizes drug properties. By simulating different modifications to a molecular structure, researchers can predict changes in a drug's efficacy and safety. Repeating and refining this process fine-tunes drug candidates to achieve optimal therapeutic profiles. For example, modifying a molecule to enhance stability in the bloodstream can prevent it from breaking down too quickly, ensuring it reaches its target.
Computational predictions must be validated experimentally, as computer models can sometimes produce false positives. Accurately simulating the human body's complex environment remains a formidable task.
The word "formidable" in the passage is closest in meaning to
Avery challenging
Bvery exciting
Curgent
Dmanageable
正确答案：A
解题思路
老师暂未填写解题思路。