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Article ; Online: Uncovering the secrets of resistance: An introduction to computational methods in infectious disease research.

Padhi, Aditya K / Maurya, Shweata

Advances in protein chemistry and structural biology

2024 Volume 139, Page(s) 173–220

Abstract: Antimicrobial resistance (AMR) is a growing global concern with significant implications for infectious disease control and therapeutics development. This chapter presents a comprehensive overview of computational methods in the study of AMR. We explore ... ...

Abstract	Antimicrobial resistance (AMR) is a growing global concern with significant implications for infectious disease control and therapeutics development. This chapter presents a comprehensive overview of computational methods in the study of AMR. We explore the prevalence and statistics of AMR, underscoring its alarming impact on public health. The role of AMR in infectious disease outbreaks and its impact on therapeutics development are discussed, emphasizing the need for novel strategies. Resistance mutations are pivotal in AMR, enabling pathogens to evade antimicrobial treatments. We delve into their importance and contribution to the spread of AMR. Experimental methods for quantitatively evaluating resistance mutations are described, along with their limitations. To address these challenges, computational methods provide promising solutions. We highlight the advantages of computational approaches, including rapid analysis of large datasets and prediction of resistance profiles. A comprehensive overview of computational methods for studying AMR is presented, encompassing genomics, proteomics, structural bioinformatics, network analysis, and machine learning algorithms. The strengths and limitations of each method are briefly outlined. Additionally, we introduce ResScan-design, our own computational method, which employs a protein (re)design protocol to identify potential resistance mutations and adaptation signatures in pathogens. Case studies are discussed to showcase the application of ResScan in elucidating hotspot residues, understanding underlying mechanisms, and guiding the design of effective therapies. In conclusion, we emphasize the value of computational methods in understanding and combating AMR. Integration of experimental and computational approaches can expedite the discovery of innovative antimicrobial treatments and mitigate the threat posed by AMR.
MeSH term(s)	Humans ; Algorithms ; Computational Biology ; Genomics ; Anti-Infective Agents ; Communicable Diseases/drug therapy ; Communicable Diseases/genetics
Chemical Substances	Anti-Infective Agents
Language	English
Publishing date	2024-02-15
Publishing country	Netherlands
Document type	Review ; Journal Article
ZDB-ID	2473077-4
ISSN	1876-1631 ; 1876-1623
ISSN (online)	1876-1631
ISSN	1876-1623
DOI	10.1016/bs.apcsb.2023.11.004
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Article ; Online: Long-timescale atomistic simulations uncover loss-of-function mechanisms of uncharacterized Angiogenin mutants associated with ALS.

Dewangan, Deeksha / Joshi, Aryaman / Padhi, Aditya K

Archives of biochemistry and biophysics

2024 Volume 756, Page(s) 110000

Abstract: Amyotrophic Lateral Sclerosis (ALS) is a devastating neurodegenerative disease characterized by progressive degeneration of motor neurons, resulting in respiratory failure and mortality within 3-5 years. Mutations in the Angiogenin (ANG) cause loss of ... ...

Abstract	Amyotrophic Lateral Sclerosis (ALS) is a devastating neurodegenerative disease characterized by progressive degeneration of motor neurons, resulting in respiratory failure and mortality within 3-5 years. Mutations in the Angiogenin (ANG) cause loss of ribonucleolytic and nuclear translocation activities, contributing to ALS pathogenesis. This study focused on investigating two uncharacterized ANG mutations, T11S and R122H, newly identified in the Project Mine consortium. Using extensive computational analysis, including structural modeling and microsecond-timescale molecular dynamics (MD) simulations, we observed conformational changes in the catalytic residue His114 of ANG induced by T11S and R122H mutations. These alterations impaired ribonucleolytic activity, as inferred through molecular docking and binding free energy calculations. Gibbs free energy landscape and residue-residue interaction network analysis further supported our findings, revealing the energetic states and allosteric pathway from the mutated site to His114. Additionally, we assessed the binding of NCI-65828, an inhibitor of ribonucleolytic activity of ANG, and found reduced effectiveness in binding to T11S and R122H mutants when His114 assumed a non-native conformation. This highlights the crucial role of His114 and its association with ALS. Elucidating the relationship between physical structure and functional dynamics of frequently mutated ANG mutants is essential for understanding ALS pathogenesis and developing more effective therapeutic interventions.
Language	English
Publishing date	2024-04-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	523-x
ISSN	1096-0384 ; 0003-9861
ISSN (online)	1096-0384
ISSN	0003-9861
DOI	10.1016/j.abb.2024.110000
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Article ; Online: High-throughput design of symmetrical dimeric SARS-CoV-2 main protease: structural and physical insights into hotspots for adaptation and therapeutics.

Padhi, Aditya K / Tripathi, Timir

Physical chemistry chemical physics : PCCP

2022 Volume 24, Issue 16, Page(s) 9141–9145

Abstract: Dimerization of SARS-CoV-2 main protease ( ... ...

Abstract	Dimerization of SARS-CoV-2 main protease (M
MeSH term(s)	COVID-19 ; Coronavirus 3C Proteases/genetics ; Dimerization ; Humans ; Protein Engineering ; SARS-CoV-2/enzymology ; SARS-CoV-2/genetics
Chemical Substances	3C-like proteinase, SARS-CoV-2 (EC 3.4.22.-) ; Coronavirus 3C Proteases (EC 3.4.22.28)
Language	English
Publishing date	2022-04-20
Publishing country	England
Document type	Journal Article
ZDB-ID	1476244-4
ISSN	1463-9084 ; 1463-9076
ISSN (online)	1463-9084
ISSN	1463-9076
DOI	10.1039/d2cp00171c
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Article ; Online: Hotspot residues and resistance mutations in the nirmatrelvir-binding site of SARS-CoV-2 main protease: Design, identification, and correlation with globally circulating viral genomes.

Padhi, Aditya K / Tripathi, Timir

Biochemical and biophysical research communications

2022 Volume 629, Page(s) 54–60

Abstract: Shortly after the onset of the COVID-19 pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has acquired numerous variations in its intracellular proteins to adapt quickly, become more infectious, and ultimately develop drug resistance ...

Abstract	Shortly after the onset of the COVID-19 pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has acquired numerous variations in its intracellular proteins to adapt quickly, become more infectious, and ultimately develop drug resistance by mutating certain hotspot residues. To keep the emerging variants at bay, including Omicron and subvariants, FDA has approved the antiviral nirmatrelvir for mild-to-moderate and high-risk COVID-19 cases. Like other viruses, SARS-CoV-2 could acquire mutations in its main protease (M
MeSH term(s)	Antiviral Agents/chemistry ; Binding Sites ; COVID-19/genetics ; Coronavirus 3C Proteases ; Cysteine Endopeptidases/metabolism ; Genome, Viral ; Humans ; Mutation ; Pandemics ; Protease Inhibitors/chemistry ; SARS-CoV-2/genetics ; Viral Nonstructural Proteins/chemistry
Chemical Substances	Antiviral Agents ; Protease Inhibitors ; Viral Nonstructural Proteins ; 3C-like proteinase, SARS-CoV-2 (EC 3.4.22.-) ; Cysteine Endopeptidases (EC 3.4.22.-) ; Coronavirus 3C Proteases (EC 3.4.22.28)
Language	English
Publishing date	2022-09-07
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	205723-2
ISSN	1090-2104 ; 0006-291X ; 0006-291X
ISSN (online)	1090-2104 ; 0006-291X
ISSN	0006-291X
DOI	10.1016/j.bbrc.2022.09.010
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Article ; Online: A comprehensive protein design protocol to identify resistance mutations and signatures of adaptation in pathogens.

Padhi, Aditya K / Tripathi, Timir

Briefings in functional genomics

2022 Volume 22, Issue 2, Page(s) 195–203

Abstract: Most pathogens mutate and evolve over time to escape immune and drug pressure. To achieve this, they alter specific hotspot residues in their intracellular proteins to render the targeted drug(s) ineffective and develop resistance. Such hotspot residues ... ...

Abstract	Most pathogens mutate and evolve over time to escape immune and drug pressure. To achieve this, they alter specific hotspot residues in their intracellular proteins to render the targeted drug(s) ineffective and develop resistance. Such hotspot residues may be located as a cluster or uniformly as a signature of adaptation in a protein. Identifying the hotspots and signatures is extremely important to comprehensively understand the disease pathogenesis and rapidly develop next-generation therapeutics. As experimental methods are time-consuming and often cumbersome, there is a need to develop efficient computational protocols and adequately utilize them. To address this issue, we present a unique computational protein design protocol that identifies hotspot residues, resistance mutations and signatures of adaptation in a pathogen's protein against a bound drug. Using the protocol, the binding affinity between the designed mutants and drug is computed quickly, which offers predictions for comparison with biophysical experiments. The applicability and accuracy of the protocol are shown using case studies of a few protein-drug complexes. As a validation, resistance mutations in severe acute respiratory syndrome coronavirus 2 main protease (Mpro) against narlaprevir (an inhibitor of hepatitis C NS3/4A serine protease) are identified. Notably, a detailed methodology and description of the working principles of the protocol are presented. In conclusion, our protocol will assist in providing a first-hand explanation of adaptation, hotspot-residue variations and surveillance of evolving resistance mutations in a pathogenic protein.
MeSH term(s)	Humans ; Antiviral Agents/chemistry ; Antiviral Agents/metabolism ; Antiviral Agents/pharmacology ; COVID-19 ; Mutation/genetics ; Hepacivirus
Chemical Substances	Antiviral Agents
Language	English
Publishing date	2022-07-18
Publishing country	England
Document type	Journal Article
ZDB-ID	2540916-5
ISSN	2041-2657 ; 2041-2649 ; 2041-2647
ISSN (online)	2041-2657
ISSN	2041-2649 ; 2041-2647
DOI	10.1093/bfgp/elac020
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Article: Computational Protein Design for COVID-19 Research and Emerging Therapeutics.

Kalita, Parismita / Tripathi, Timir / Padhi, Aditya K

ACS central science

2023 Volume 9, Issue 4, Page(s) 602–613

Abstract: As the world struggles with the ongoing COVID-19 pandemic, unprecedented obstacles have continuously been traversed as new SARS-CoV-2 variants continually emerge. Infectious disease outbreaks are unavoidable, but the knowledge gained from the successes ... ...

Abstract	As the world struggles with the ongoing COVID-19 pandemic, unprecedented obstacles have continuously been traversed as new SARS-CoV-2 variants continually emerge. Infectious disease outbreaks are unavoidable, but the knowledge gained from the successes and failures will help create a robust health management system to deal with such pandemics. Previously, scientists required years to develop diagnostics, therapeutics, or vaccines; however, we have seen that, with the rapid deployment of high-throughput technologies and unprecedented scientific collaboration worldwide, breakthrough discoveries can be accelerated and insights broadened. Computational protein design (CPD) is a game-changing new technology that has provided alternative therapeutic strategies for pandemic management. In addition to the development of peptide-based inhibitors, miniprotein binders, decoys, biosensors, nanobodies, and monoclonal antibodies, CPD has also been used to redesign native SARS-CoV-2 proteins and human ACE2 receptors. We discuss how novel CPD strategies have been exploited to develop rationally designed and robust COVID-19 treatment strategies.
Language	English
Publishing date	2023-03-20
Publishing country	United States
Document type	Journal Article ; Review
ISSN	2374-7943
ISSN	2374-7943
DOI	10.1021/acscentsci.2c01513
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Article ; Online: Immunoinformatics Protocol to Design Multi-Epitope Subunit Vaccines.

Kalita, Parismita / Padhi, Aditya K / Tripathi, Timir

Methods in molecular biology (Clifton, N.J.)

2023 Volume 2673, Page(s) 357–369

Abstract: With the development of scientific technologies, the accessibility of genomic data, computational tools, software, databases, and machine learning, the field of immunoinformatics has emerged as an effective technique for immunologists to design potential ...

Abstract	With the development of scientific technologies, the accessibility of genomic data, computational tools, software, databases, and machine learning, the field of immunoinformatics has emerged as an effective technique for immunologists to design potential vaccines in a short time. A large number of tools and databases are available to screen the genome sequences of parasites/pathogens and identify the highly immunogenic peptides or epitopes that can be used to design effective vaccines. In this chapter, we provide an easy-to-use protocol for the design of multi-epitope-based subunit vaccines. Though the computational immunoinformatics-based approaches have demonstrated their competency in designing potentially effective vaccine candidates quickly, their immunogenicity and safety must be evaluated in laboratory settings before they are tested in clinical trials.
MeSH term(s)	Epitopes, B-Lymphocyte ; Epitopes, T-Lymphocyte ; Vaccines, Subunit ; Peptides ; Computational Biology/methods ; Molecular Docking Simulation
Chemical Substances	Epitopes, B-Lymphocyte ; Epitopes, T-Lymphocyte ; Vaccines, Subunit ; Peptides
Language	English
Publishing date	2023-05-31
Publishing country	United States
Document type	Journal Article
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-0716-3239-0_25
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Article ; Online: Comment on: Vitamin D receptor gene polymorphisms and osteoarthritis: a meta-analysis.

Panda, Aditya K / Padhi, Sunali

Rheumatology (Oxford, England)

2021 Volume 60, Issue 6, Page(s) e215

MeSH term(s)	Humans ; Osteoarthritis/genetics ; Polymorphism, Genetic ; Receptors, Calcitriol/genetics
Chemical Substances	Receptors, Calcitriol
Language	English
Publishing date	2021-01-20
Publishing country	England
Document type	Journal Article ; Comment
ZDB-ID	1464822-2
ISSN	1462-0332 ; 1462-0324
ISSN (online)	1462-0332
ISSN	1462-0324
DOI	10.1093/rheumatology/keab063
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Article ; Online: Interface design of SARS-CoV-2 symmetrical nsp7 dimer and machine learning-guided nsp7 sequence prediction reveals physicochemical properties and hotspots for nsp7 stability, adaptation, and therapeutic design.

Yadav, Amar Jeet / Kumar, Shivank / Maurya, Shweata / Bhagat, Khushboo / Padhi, Aditya K

Physical chemistry chemical physics : PCCP

2024

Abstract: The COVID-19 pandemic, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), necessitates a profound understanding of the virus and its lifecycle. As an RNA virus with high mutation rates, SARS-CoV-2 exhibits genetic variability leading ...

Abstract	The COVID-19 pandemic, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), necessitates a profound understanding of the virus and its lifecycle. As an RNA virus with high mutation rates, SARS-CoV-2 exhibits genetic variability leading to the emergence of variants with potential implications. Among its key proteins, the RNA-dependent RNA polymerase (RdRp) is pivotal for viral replication. Notably, RdRp forms dimers
Language	English
Publishing date	2024-04-30
Publishing country	England
Document type	Journal Article
ZDB-ID	1476244-4
ISSN	1463-9084 ; 1463-9076
ISSN (online)	1463-9084
ISSN	1463-9076
DOI	10.1039/d4cp01014k
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Article: Hotspot residues and resistance mutations in the nirmatrelvir-binding site of SARS-CoV-2 main protease: Design, identification, and correlation with globally circulating viral genomes

Padhi, Aditya K. / Tripathi, Timir

Biochemical and biophysical research communications. 2022 Nov. 12, v. 629

2022

Abstract	Shortly after the onset of the COVID-19 pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has acquired numerous variations in its intracellular proteins to adapt quickly, become more infectious, and ultimately develop drug resistance by mutating certain hotspot residues. To keep the emerging variants at bay, including Omicron and subvariants, FDA has approved the antiviral nirmatrelvir for mild-to-moderate and high-risk COVID-19 cases. Like other viruses, SARS-CoV-2 could acquire mutations in its main protease (Mᵖʳᵒ) to adapt and develop resistance against nirmatrelvir. Employing a unique high-throughput protein design technique, the hotspot residues, and signatures of adaptation of Mᵖʳᵒ having the highest probability of mutating and rendering nirmatrelvir ineffective were identified. Our results show that ∼40% of the designed mutations in Mᵖʳᵒ already exist in the globally circulating SARS-CoV-2 lineages and several predicted mutations. Moreover, several high-frequency, designed mutations were found to be in corroboration with the experimentally reported nirmatrelvir-resistant mutants and are naturally occurring. Our work on the targeted design of the nirmatrelvir-binding site offers a comprehensive picture of potential hotspot sites and resistance mutations in Mᵖʳᵒ and is thus crucial in comprehending viral adaptation, robust antiviral design, and surveillance of evolving Mᵖʳᵒ variations.
Keywords	COVID-19 infection ; Severe acute respiratory syndrome coronavirus 2 ; drug resistance ; monitoring ; probability ; proteinases ; research ; viral genome
Language	English
Dates of publication	2022-1112
Size	p. 54-60.
Publishing place	Elsevier Inc.
Document type	Article
ZDB-ID	205723-2
ISSN	0006-291X ; 0006-291X
ISSN (online)	0006-291X
ISSN	0006-291X
DOI	10.1016/j.bbrc.2022.09.010
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