Department of Chemistry, Integral University, Lucknow, 226026, U.P., India.
Department of Chemistry, Isabella Thoburn College, Lucknow, 226007, U.P., India.
Curr Top Med Chem. 2023;23(17):1640-1663. doi: 10.2174/1568026623666230201144522.
Microbial diseases, specifically originating from viruses are the major cause of human mortality all over the world. The current COVID-19 pandemic is a case in point, where the dynamics of the viral-human interactions are still not completely understood, making its treatment a case of trial and error. Scientists are struggling to devise a strategy to contain the pandemic for over a year and this brings to light the lack of understanding of how the virus grows and multiplies in the human body.
This paper presents the perspective of the authors on the applicability of computational tools for deep learning and understanding of host-microbe interaction, disease progression and management, drug resistance and immune modulation through in silico methodologies which can aid in effective and selective drug development. The paper has summarized advances in the last five years. The studies published and indexed in leading databases have been included in the review.
Computational systems biology works on an interface of biology and mathematics and intends to unravel the complex mechanisms between the biological systems and the inter and intra species dynamics using computational tools, and high-throughput technologies developed on algorithms, networks and complex connections to simulate cellular biological processes.
Computational strategies and modelling integrate and prioritize microbial-host interactions and may predict the conditions in which the fine-tuning attenuates. These microbial-host interactions and working mechanisms are important from the aspect of effective drug designing and fine- tuning the therapeutic interventions.
微生物疾病，特别是源自病毒的疾病是全世界人类死亡的主要原因。目前的 COVID-19 大流行就是一个例子，病毒与人类的相互作用的动态仍然没有完全被理解，这使得它的治疗成为一种试错的情况。科学家们一直在努力制定策略来控制大流行超过一年，这凸显了人们对病毒在人体中生长和繁殖的方式缺乏了解。
本文介绍了作者对计算工具在深度学习和理解宿主-微生物相互作用、疾病进展和管理、耐药性和免疫调节方面的适用性的看法，这些工具可以通过计算机模拟方法来辅助有效的和选择性的药物开发。本文总结了过去五年的进展。综述中包括了在主要数据库中发表和索引的研究。
计算系统生物学是生物学和数学的交叉学科，旨在使用计算工具和基于算法、网络和复杂连接的高通量技术，揭示生物系统之间以及物种内部和物种之间的复杂机制，以模拟细胞生物学过程。
计算策略和建模整合并优先考虑微生物-宿主相互作用，并可能预测精细调节减弱的条件。这些微生物-宿主相互作用和工作机制从有效药物设计和精细调节治疗干预的角度来看非常重要。
