In Silico Therapeutic Study: The Next Frontier in the Fight against SARS-CoV-2 and Its Variants DOI Creative Commons
Calvin R. Wei, Zarrin Basharat, Godwin C. Lang’at

et al.

Drugs and Drug Candidates, Journal Year: 2024, Volume and Issue: 3(1), P. 54 - 69

Published: Jan. 5, 2024

COVID-19 has claimed around 7 million lives (from December 2019–November 2023) worldwide and continues to impact global health. SARS-CoV-2, the virus causing disease, is characterized by a high rate of mutations, which contributes its rapid spread, virulence, vaccine escape. While several vaccines have been produced minimize severity coronavirus, diverse treatment regimens approved US FDA under Emergency Use Authorization (EUA), SARS-CoV-2 viral mutations continue derail efforts scientists as emerging variants evade recommended therapies. Nonetheless, computational models exist that offer an opportunity for swift development new drugs or repurposing old drugs. In this review, we focus on use various virtual screening techniques like homology modeling, molecular docking, dynamics simulations, QSAR, pharmacophore etc., in therapeutics against major (Alpha, Beta, Gamma, Delta, Omicron). The results promising from computer-aided drug design (CADD) studies suggesting potential compounds variants. Hence, silico therapeutic represent transformative approach holds great promise advancing our fight ever-evolving landscape

Language: Английский

Simulation-based approaches for drug delivery systems: Navigating advancements, opportunities, and challenges DOI Creative Commons

Iman Salahshoori,

Mahdi Golriz,

Marcos A.L. Nobre

et al.

Journal of Molecular Liquids, Journal Year: 2023, Volume and Issue: 395, P. 123888 - 123888

Published: Dec. 27, 2023

Efficient drug delivery systems (DDSs) play a pivotal role in ensuring pharmaceuticals' targeted and effective administration. However, the intricate interplay between formulations poses challenges their design optimization. Simulations have emerged as indispensable tools for comprehending these interactions enhancing DDS performance to address this complexity. This comprehensive review explores latest advancements simulation techniques provides detailed analysis. The encompasses various methodologies, including molecular dynamics (MD), Monte Carlo (MC), finite element analysis (FEA), computational fluid (CFD), density functional theory (DFT), machine learning (ML), dissipative particle (DPD). These are critically examined context of research. article presents illustrative case studies involving liposomal, polymer-based, nano-particulate, implantable DDSs, demonstrating influential simulations optimizing systems. Furthermore, addresses advantages limitations It also identifies future directions research development, such integrating multiple techniques, refining validating models greater accuracy, overcoming limitations, exploring applications personalized medicine innovative DDSs. employing like MD, MC, FEA, CFD, DFT, ML, DPD offer crucial insights into behaviour, aiding Despite advantages, rapid cost-effective screening, require validation addressing limitations. Future should focus on models, enhance outcomes. paper underscores contribution emphasizing providing valuable facilitating development optimization ultimately patient As we continue explore impact advancing discovery improving DDSs is expected be profound.

Language: Английский

Citations

56
Enabling the immune escaped etesevimab fully-armed against SARS-CoV-2 Omicron subvariants including KP.2 DOI Creative Commons
Chao Su,

Juanhua He,

Yufeng Xie

et al.

hLife, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

2
Vaccine Target Discovery DOI
Li Chuin Chong, Asif Manzoor Khan

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

Citations

12
Advancing vaccine development in genomic era: A paradigm shift in vaccine discovery DOI

Miraj Ud din,

Xiaohui Liu, Hui Jiang

et al.

Progress in Biomedical Engineering, Journal Year: 2025, Volume and Issue: 7(2), P. 022004 - 022004

Published: Feb. 5, 2025

Abstract The issue of antibiotic resistance is increasing with time because the quick rise microbial strains. Overuse antibiotics has led to multidrug-resistant, pan-drug-resistant, and extensively drug-resistant bacterial strains, which have worsened situation. Different techniques been considered applied combat this issue, such as developing new antibiotics, practicing stewardship, improving hygiene levels, controlling overuse. Vaccine development made a substantial contribution overcoming although it underestimated. In recent era, reverse vaccinology contributed different kinds vaccines against pathogens, revolutionizing vaccine process. Reverse helps prioritize better candidates by using various tools filter pathogen’s complete genome. review, we will shed light on computational designing, immunoinformatic tools, genomic proteomic data, challenges success stories designing.

Language: Английский

Citations

1
Biophysics of SARS-CoV-2 spike protein’s receptor-binding domain interaction with ACE2 and neutralizing antibodies: from computation to functional insights DOI
Fernando Luís Barroso da Silva,

Karen Paco,

Aatto Laaksonen

et al.

Biophysical Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: March 8, 2025

Language: Английский

Citations

1
A new era of antibody discovery: an in-depth review of AI-driven approaches DOI
Jin Cheng,

Tianjian Liang,

Xiang‐Qun Xie

et al.

Drug Discovery Today, Journal Year: 2024, Volume and Issue: 29(6), P. 103984 - 103984

Published: April 18, 2024

Language: Английский

Citations

7
Revisiting the dimensions of universal vaccine with special focus on COVID-19: Efficacy versus methods of designing DOI

Puja Jaishwal,

Kisalay Jha,

Satarudra Prakash Singh

et al.

International Journal of Biological Macromolecules, Journal Year: 2024, Volume and Issue: 277, P. 134012 - 134012

Published: July 22, 2024

Language: Английский

Citations

4
AMEP: The Active Matter Evaluation Package for Python DOI Creative Commons
Lukas Hecht,

Kay-Robert Dormann,

Kai Luca Spanheimer

et al.

Computer Physics Communications, Journal Year: 2025, Volume and Issue: unknown, P. 109483 - 109483

Published: Jan. 1, 2025

Language: Английский

Citations

0
Type-2 fuzzy support vector machine model for conformational epitope prediction DOI
Chhaya Singh, Neeraj Jain, Neeru Adlakha

et al.

Network Modeling Analysis in Health Informatics and Bioinformatics, Journal Year: 2025, Volume and Issue: 14(1)

Published: Jan. 6, 2025

Language: Английский

Citations

0
Predicting Antibody Affinity Changes upon Mutation Based on Unbound Protein Structures DOI Open Access
Zhengshan Chen, Song He, Xiangyang Chi

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(3), P. 1343 - 1343

Published: Feb. 5, 2025

Antibodies are key proteins in the immune system that can reversibly and non-covalently bind specifically to their corresponding antigens, forming antigen–antibody complexes. They play a crucial role recognizing foreign or self-antigens during adaptive response. Monoclonal antibodies have emerged as promising class of biological macromolecule therapeutics with broad market prospects. In process antibody drug development, engineering challenge is improve affinity candidate antibodies, without experimentally resolved structures complexes input for computer-aided predictive methods. this work, we present an approach predicting effect residue mutations on The method involves graph representation utilizes pre-trained encoder. encoder captures residue-level microenvironment target along antigen context pre- post-mutation. inherently possesses potential identify paratope residues. addition, curated benchmark dataset antibody. Compared baseline methods based complex sequences, our achieves superior comparable average accuracy datasets. Additionally, validate its advantage not requiring effects against SARS-CoV-2, influenza, human cytomegalovirus. Our shows identifying practical applications.

Language: Английский

Citations

0