A feel for the powerful computational tools used in the fight against SARS-Cov-2 (Covid).
As I approach the end of my life, I stand in awe of the power of humanity to see, even as we stand on the precipice of disaster, as clearly we do. I have no metaphysical views of any kind to be sure, but perhaps with an admittedly somewhat jaundiced genuflection in the direction of the Anthropic Principle, this seems to be something of a purpose for living at all, merely that, to see.
As an example, I personally feel that the science behind addressing the Covid-19 was remarkable in the speed of its success, the vast tragic realities notwithstanding. Many of us see it as a triumph of molecular biology, and indeed it is, but the tools of molecular biology are deeper than most of us realize, and much of this is represented by vast in silico capabilities.
I'm catching up on some reading, and I came across this review article by scientists at the University of Michigan in Chemical Reviews: Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2
Kaifu Gao, Rui Wang, Jiahui Chen, Limei Cheng, Jaclyn Frishcosy, Yuta Huzumi, Yuchi Qiu, Tom Schluckbier, Xiaoqi Wei, and Guo-Wei Wei Chemical Reviews 2022 122 (13), 11287-11368.
It's a long technical article, but I thought I'd just mention the depth of these tools merely by producing the Table of Contents for the paper:
1. Introduction 11288
2. Methods and Approaches 11289
2.1. Biophysics 11289
2.1.1. Thermodynamics 11289
2.1.2. Electrostatic Modeling 11293
2.1.3. Molecular Dynamics (MD) Simulation 11294
2.1.4. Normal-Mode Analysis 11296
2.1.5. Monte Carlo Methods 11297
2.1.6. Molecular Docking 11298
2.1.7. Binding Free Energy Calculations 11300
2.1.8. Density-Functional Theory (DFT) and
Quantum Mechanism (QM) Methods 11303
2.1.9. Quantum Mechanics/Molecular Mechanics
(QM/MM) 11304
2.2. Mathematical Approaches 11304
2.2.1. Graph Network Analysis 11304
2.2.2. Flexibility−Rigidity Index (FRI) 11306
2.2.3. Topological Data Analysis (TDA) 11307
2.3. Machine Learning 11308
2.3.1. Dimensionality Reduction 11308
2.3.2. Linear Regression 11309
2.3.3. Logistic Regression 11310
2.3.4. k-Nearest Neighbors 11310
2.3.5. K-Means Clustering 11311
2.3.6. Support Vector Machine 11311
2.3.7. Decision Trees, Random Forest, and
Gradient Boosting Decision Trees 11312
2.3.8. Artificial Neural Network (ANN) 11312
2.3.9. Convolutional Neural Network (CNN) 11314
2.3.10. Natural Language Processing (NLP)
Methods 11315
2.3.11. Autoencoder and Transformer 11316
2.4. Topics in Bioinformatics and Cheminformatics
11316
2.4.1. Sequence Alignment 11316
2.4.2. Homology Modeling 11317
2.4.3. Network-Based Bioinformatics 11317
2.4.4. Quantitative Structure−Activity Relationship
(QSAR) Models 11320
2.4.5. Pharmacophore Models 11321
2.5. Miscellaneous 11321
2.5.1. Molecular Modeling of Peptides, Proteins,
or Graphene Binding to SARSCoV-
2 Targets 11321
2.5.2. Molecular Modeling Studies on Vaccines
11321
2.5.3. Molecular Modeling of Blocking Host
Targets with Controversy 11321
2.5.4. Combination of Docking and MD
Simulation 11322
2.5.5. Accuracy Tests of Molecular Modeling
Methods on SARS-CoV-2 Targets 11323
2.5.6. Combined MD Simulation and Deep
Learning 11323
2.5.7. Combined MD Simulation and Experiment
11323
2.5.8. Combined MD Simulation and Data
Analysis 11323
2.5.9. Combinations of Multiple Molecular
Modeling Methods 11324
2.5.10. Molecular Modeling of Mutational
Impacts 11324
2.5.11. Protein Pocket Detection 11324
2.5.12. AlphaFold 11324
3. Discussion 11325
3.1. Drug Repurposing 11325
3.2. Mutational Impacts on SARS-CoV-2 Infectivity
11326
3.3. Mechanisms of SARS-CoV-2 Evolution 11327
3.4. Mutational Impacts on SARS-CoV-2 Antibodies
and Vaccines 11327
4. Concluding Remarks 11328
Author Information 11328
Corresponding Author 11328
Authors 11328
Author Contributions 11329
Notes 11329
Biographies 11329
Acknowledgments 11329
Glossary 11329
Mathematical Symbols in Section 2.1 11329
Mathematical Symbols in Sections 2.2, 2.3, and
2.4 11330
Abbreviations 11331
References 11332
So many lives, so much work when into what this review recalls, that I am filled with deep respect and perhaps, should I allow myself as much, a mote of hope.
Have a nice weekend.
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