Making Drug Discovery More Efficient Applying Statistical Entropy to Biology

• 作者: Philip D. Houck
• 来源期刊: 现代物理(英文)
• 学科: 数学
• 关键词: Negative Entropy Quantification of Biology Carrier Proteins Drug Development
• 年，卷（期）: xdwlyw_2020,（12）
• 页码范围: 1969-1976
• 页数: 8页
• 分类号: O17

摘要

Biology without governing principle makes predications impossible. Observations lead to some successful therapies, and to unexpected failures. Erwin Schr<span style="white-space:nowrap;">&ouml;</span>dinger attempted to quantify biology with the concept of negative entropy. These insights lead to fundamental principles of biologic entropy. The quantification of negative entropy is difficult to calculate since the number of parts of the body and the way these parts are arranged is very large (atomistic disorder). There can be approximations that answer questions such as why females live longer, and why a lower body temperature predicts longevity. This concept can reveal the culprit of diabetes II;understanding the microbiome can reduce its entropy by increasing the entropy of its host. The real advantage of statistical entropy is finding new drugs and predicting viral mutations based on energetics and negative entropy. The misfolding of a protein will increase the entropy of an individual with the result of early death. The calculations of biologic entropy require the knowledge of each developmental step, and the statistical possibilities of the next step. If the step is crucial to maintain low entropy, a carrier protein will assure the energetics of the step is favorable. This protein is the target of new therapies.