GPU-I-TASSER: a GPU accelerated I-TASSER protein structure prediction tool

MacCarthy, Elijah; Zhang, Chengxin; Zhang, Yang; Dukka, K C

doi:10.1093/bioinformatics/btab871

Cited by 8 publications

(5 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A known peptide–MHC complex structure is utilised to predict the binding structures of other peptides to the same MHC molecule by maximising the alignment of the amino acid sequence and their 3D structural patterns. I-TASSER ( MacCarthy et al, 2022 ), Phyre2 ( Kelley et al, 2015 ), and RaptorX ( Wang et al, 2016 ) servers are used for threading modelling. Ab initio protein modelling predicts 3D structures based on novel folds and can be utilised if the structure of interest is unavailable or if the sequence identity between the template and the protein of interest is less than 30%.…”

Section: Survey Methodologymentioning

confidence: 99%

See 1 more Smart Citation

Riding the wave of innovation: immunoinformatics in fish disease control

Razali,

Shamsir,

Ishak

et al. 2023

PeerJ

View full text Add to dashboard Cite

The spread of infectious illnesses has been a significant factor restricting aquaculture production. To maximise aquatic animal health, vaccination tactics are very successful and cost-efficient for protecting fish and aquaculture animals against many disease pathogens. However, due to the increasing number of immunological cases and their complexity, it is impossible to manage, analyse, visualise, and interpret such data without the assistance of advanced computational techniques. Hence, the use of immunoinformatics tools is crucial, as they not only facilitate the management of massive amounts of data but also greatly contribute to the creation of fresh hypotheses regarding immune responses. In recent years, advances in biotechnology and immunoinformatics have opened up new research avenues for generating novel vaccines and enhancing existing vaccinations against outbreaks of infectious illnesses, thereby reducing aquaculture losses. This review focuses on understanding in silico epitope-based vaccine design, the creation of multi-epitope vaccines, the molecular interaction of immunogenic vaccines, and the application of immunoinformatics in fish disease based on the frequency of their application and reliable results. It is believed that it can bridge the gap between experimental and computational approaches and reduce the need for experimental research, so that only wet laboratory testing integrated with in silico techniques may yield highly promising results and be useful for the development of vaccines for fish.

show abstract

Section: Survey Methodologymentioning

confidence: 99%

“…Based on physical principles, this method involves computing all energy parameters of protein folding and determining the state with the lowest free energy. ROBETTA ( Park et al, 2018 ), TrRosetta ( Du et al, 2021 ) and I-TASSER ( MacCarthy et al, 2022 ) are servers that can be used to predict the ab initio protein structure.…”

Section: Survey Methodologymentioning

confidence: 99%

Riding the wave of innovation: immunoinformatics in fish disease control

Razali,

Shamsir,

Ishak

et al. 2023

PeerJ

View full text Add to dashboard Cite

show abstract

“…In addition, for comparison purposes, an ACE2-derived peptide (i.e., "IEEQAKTFLDKFNHEAEDLFYQSS") was included in the screening dataset. The structures of the preselected peptides that could not be retrieved from the PDB were predicted by different sequence-based in silico tools (I-TASSER (Iterative Threading ASSEmbly Refinement) [207,208] and PEP-FOLD 3.5 [140]) and then used as input for a docking-based virtual screening against the spike RBD [190]. The docking analysis predicted for the twelve antimicrobial peptides and the three lysozyme-derived peptides better binding affinities for the spike RBD than that predicted for the ACE2 reference peptide.…”

Section: Case Studies: Targeting Sars-cov-2mentioning

confidence: 99%

Virtual Screening of Peptide Libraries: The Search for Peptide-Based Therapeutics Using Computational Tools

Vincenzi,

Mercurio,

Leone

2024

IJMS

View full text Add to dashboard Cite

Over the last few decades, we have witnessed growing interest from both academic and industrial laboratories in peptides as possible therapeutics. Bioactive peptides have a high potential to treat various diseases with specificity and biological safety. Compared to small molecules, peptides represent better candidates as inhibitors (or general modulators) of key protein–protein interactions. In fact, undruggable proteins containing large and smooth surfaces can be more easily targeted with the conformational plasticity of peptides. The discovery of bioactive peptides, working against disease-relevant protein targets, generally requires the high-throughput screening of large libraries, and in silico approaches are highly exploited for their low-cost incidence and efficiency. The present review reports on the potential challenges linked to the employment of peptides as therapeutics and describes computational approaches, mainly structure-based virtual screening (SBVS), to support the identification of novel peptides for therapeutic implementations. Cutting-edge SBVS strategies are reviewed along with examples of applications focused on diverse classes of bioactive peptides (i.e., anticancer, antimicrobial/antiviral peptides, peptides blocking amyloid fiber formation).

show abstract

“…rcsb.org [16]. All the crystal structures were prepared by removing existing ligands and water molecules using I-TASSER (Iterative Threading Assembly Refinement) [17], https://zhanggroup.org/I-TASSER/.…”

Section: Preparation Of Target Proteinmentioning

confidence: 99%

Computational Prediction of Bioactive Compounds as Potential Inhibitors of Covid-19 Main Protease, Spike Glycoprotein Receptor-Binding Domain, and Rna-Dependent Rna Polymerase

SHARMA¹,

BUWA²

2022

Innovare J Med Sci

View full text Add to dashboard Cite

Objectives: It has been known for ages that natural products have potent antiviral activity and hence show inhibitory effects on SARS-CoV-2 infections. In this study, some promising bioactive compounds from natural sources for drug development against SARS-CoV-2 were studied. Methods: The study was based on a computational approach using different phytochemicals for evaluating their potential against non-structural (main protease [MPro], RNA-dependent RNA polymerase [RdRp], and structural [spike [S] glycoprotein receptor-binding domain]) viral proteins. Molecular docking was conducted systematically using PyRx and AutoDock 4.2 to determine the binding affinities between bioactive compounds and Mpro, spike RBD, and RdRp. Twenty-two ligands were selected in this study from different sources including three known inhibitors of the virus remdesivir, favipiravir, and nelfinavir. The pharmacological assessment of the ligands was achieved using ADMET filters. Results: The docking results revealed that β-carotene, piperine, and cianidanol were the best antagonists for Mpro, isovitexin, quercitin, β-carotene, piperine, and cianidanol were the best antagonists for RdRp, and in case of the spike RBD, capsaicin, cianidanol, curcumin, gingerol, isovitexin, piperine, quercitin, rhapontin, and riboflavin were found to be best. Conclusion: All of these bioactive compounds could be considered potential drug candidates for COVID-19 inhibition due to their promising binding affinities with the viral structural and non-structural proteins.

show abstract

GPU-I-TASSER: a GPU accelerated I-TASSER protein structure prediction tool

Cited by 8 publications

References 12 publications

Riding the wave of innovation: immunoinformatics in fish disease control

Riding the wave of innovation: immunoinformatics in fish disease control

Virtual Screening of Peptide Libraries: The Search for Peptide-Based Therapeutics Using Computational Tools

Computational Prediction of Bioactive Compounds as Potential Inhibitors of Covid-19 Main Protease, Spike Glycoprotein Receptor-Binding Domain, and Rna-Dependent Rna Polymerase

Contact Info

Product

Resources

About