The Impact of Structural Bioinformatics Tools and Resources on SARS-CoV-2 Research and Therapeutic Strategies
Overview
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SARS-CoV-2 is the causative agent of COVID-19, the ongoing global pandemic. It has posed a worldwide challenge to human health as no effective treatment is currently available to combat the disease. Its severity has led to unprecedented collaborative initiatives for therapeutic solutions against COVID-19. Studies resorting to structure-based drug design for COVID-19 are plethoric and show good promise. Structural biology provides key insights into 3D structures, critical residues/mutations in SARS-CoV-2 proteins, implicated in infectivity, molecular recognition and susceptibility to a broad range of host species. The detailed understanding of viral proteins and their complexes with host receptors and candidate epitope/lead compounds is the key to developing a structure-guided therapeutic design. Since the discovery of SARS-CoV-2, several structures of its proteins have been determined experimentally at an unprecedented speed and deposited in the Protein Data Bank. Further, specialized structural bioinformatics tools and resources have been developed for theoretical models, data on protein dynamics from computer simulations, impact of variants/mutations and molecular therapeutics. Here, we provide an overview of ongoing efforts on developing structural bioinformatics tools and resources for COVID-19 research. We also discuss the impact of these resources and structure-based studies, to understand various aspects of SARS-CoV-2 infection and therapeutic development. These include (i) understanding differences between SARS-CoV-2 and SARS-CoV, leading to increased infectivity of SARS-CoV-2, (ii) deciphering key residues in the SARS-CoV-2 involved in receptor-antibody recognition, (iii) analysis of variants in host proteins that affect host susceptibility to infection and (iv) analyses facilitating structure-based drug and vaccine design against SARS-CoV-2.
Meira D, Zetum A, Casotti M, Campos da Silva D, de Araujo B, Vicente C Heliyon. 2025; 10(14):e34393.
PMID: 39816364 PMC: 11734128. DOI: 10.1016/j.heliyon.2024.e34393.
Mia M, Allaie I, Zhang X, Li K, Khan S, Kadotani S PLoS Negl Trop Dis. 2024; 18(8):e0012473.
PMID: 39213433 PMC: 11392244. DOI: 10.1371/journal.pntd.0012473.
Ko S, Kim J, Lim J, Lee S, Park J, Woo J mSystems. 2023; 9(1):e0094323.
PMID: 38085058 PMC: 10871167. DOI: 10.1128/msystems.00943-23.
Liang B, Zhu Y, Shi W, Ni C, Tan B, Tang S Research (Wash D C). 2023; 6:0078.
PMID: 36930770 PMC: 10013967. DOI: 10.34133/research.0078.
The Advantage of Using Immunoinformatic Tools on Vaccine Design and Development for Coronavirus.
Garcia-Machorro J, Ramirez-Salinas G, Martinez-Archundia M, Correa-Basurto J Vaccines (Basel). 2022; 10(11).
PMID: 36366353 PMC: 9693616. DOI: 10.3390/vaccines10111844.