LIVIVO - Search results -

Search results

Result 1 - 10 of total 58

Search options

Article ; Online: Construing recombinant ZFP160 from Aspergillus terreus as pterin deaminase enzyme.

Bijukumar, Sajitha / Murugesan, Thandeeswaran / Dhanapal, Anand Raj / Mubarak, Shoufia Jabeen / Vedagiri, Hemamalini / Jayaraman, Angayarkanni

Biotechnology and applied biochemistry

2023 Volume 70, Issue 6, Page(s) 2150–2162

Abstract: Pterin deaminase stands as a metalloenzyme and exhibits both antitumor and anticancer activities. Therefore, this study aimed to explore the molecular function of zinc finger protein-160 (zfp160) from Aspergillus terreus with its enzyme mechanism in ... ...

Abstract	Pterin deaminase stands as a metalloenzyme and exhibits both antitumor and anticancer activities. Therefore, this study aimed to explore the molecular function of zinc finger protein-160 (zfp160) from Aspergillus terreus with its enzyme mechanism in detail. Subsequently, preliminary molecular docking studies on zfp160 from A. terreus were done. Next, the cloning and expression of zfp160 protein were carried out. Following, protein expression was induced and purified through nickel NTA column with imidazole gradient elution. Through the Mascot search engine tool, the expressed protein of MALDI-TOF was confirmed by 32 kDa bands of SDS-PAGE. Furthermore, its enzymatic characterization and biochemical categorization were also explored. The optimum conditions for enzyme were determined to be pH 8, temperature 35°C, km 50 μm with folic acid as substrate, and V
MeSH term(s)	Molecular Docking Simulation ; Aspergillus ; Aminohydrolases/chemistry ; Aminohydrolases/metabolism ; Hydrogen-Ion Concentration ; Temperature
Chemical Substances	pterin deaminase (EC 3.5.4.11) ; Aminohydrolases (EC 3.5.4.-)
Language	English
Publishing date	2023-09-27
Publishing country	United States
Document type	Journal Article
ZDB-ID	883433-7
ISSN	1470-8744 ; 0885-4513
ISSN (online)	1470-8744
ISSN	0885-4513
DOI	10.1002/bab.2515
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 1865: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Identification and structural prediction of the unrevealed amidohydrolase enzyme: Pterin deaminase from Agrobacterium tumefaciens LBA4404.

Dhanapal, Anand Raj / Thandeeswaran, Murugesan / Muthusamy, Palaniswamy / Jayaraman, Angayarkanni

Biotechnology and applied biochemistry

2022 Volume 70, Issue 1, Page(s) 193–200

Abstract: Microbes make a remarkable contribution to the health and well-being of living beings all over the world. Interestingly, pterin deaminase is an amidohydrolase enzyme that exhibits antitumor, anticancer activities and antioxidant properties. With the ... ...

Abstract	Microbes make a remarkable contribution to the health and well-being of living beings all over the world. Interestingly, pterin deaminase is an amidohydrolase enzyme that exhibits antitumor, anticancer activities and antioxidant properties. With the existing evidence of the presence of pterin deaminase from microbial sources, an attempt was made to reveal the existence of this enzyme in the unexplored bacterium Agrobacterium tumefaciens LBA4404. After, the cells were harvested and characterized as intracellular enzymes and then partially purified through acetone precipitation. Subsequently, further purification step was carried out with an ion-exchange chromatogram (HiTrap Q FF) using the Fast-Protein Liquid Chromatography technique (FPLC). Henceforward, the approximate molecular weight of the purified pterin deaminase was determined through SDS-PAGE. Furthermore, the purified protein was identified accurately by MALDI-TOF, and the sequence was explored through a Mascot search engine. Additionally, the three-dimensional structure was predicted and then validated, as well as ligand-binding sites, and the stability of this enzyme was confirmed for the first time. Thus, the present study revealed the selected parameters showing a considerable impact on the identification and purification of pterin deaminase from A. tumefaciens LBA4404 for the first time. The enzyme specificity makes it a favorable choice as a potent anticancer agent.
MeSH term(s)	Agrobacterium tumefaciens ; Amidohydrolases ; Aminohydrolases/chemistry ; Aminohydrolases/metabolism
Chemical Substances	pterin deaminase (EC 3.5.4.11) ; Amidohydrolases (EC 3.5.-) ; Aminohydrolases (EC 3.5.4.-)
Language	English
Publishing date	2022-05-09
Publishing country	United States
Document type	Journal Article
ZDB-ID	883433-7
ISSN	1470-8744 ; 0885-4513
ISSN (online)	1470-8744
ISSN	0885-4513
DOI	10.1002/bab.2342
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.A 1865: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: Pneumococcal vaccines.

Manoharan, Anand / Jayaraman, Ranjith

Indian journal of medical microbiology

2019 Volume 36, Issue 4, Page(s) 465–474

Abstract: Streptococcus pneumoniae continues to take a heavy toll on childhood mortality and morbidity across the developing world. An estimated 10.6 million invasive pneumococcal diseases (IPDs) occur every year, with nearly 1 million deaths in children under 5 ... ...

Abstract	Streptococcus pneumoniae continues to take a heavy toll on childhood mortality and morbidity across the developing world. An estimated 10.6 million invasive pneumococcal diseases (IPDs) occur every year, with nearly 1 million deaths in children under 5 years of age. Introduction of vaccines in the childhood immunisation programme in developed world has brought down the incidence of the disease considerably. However, childhood immunocompromising illnesses including HIV have increased the risk of IPD several folds. There is also a growing concern on the increasing antibiotic resistance among these invasive strains to penicillin, other beta-lactams and macrolides, making treatment difficult and expensive. It is estimated that about 62% of IPD worldwide is caused by the 10 most common serotypes. Although the ranking of individual pneumococcal serotypes causing serious disease varies among nations, the 7-13 serotypes included in pneumococcal conjugate vaccines (PCVs) may prevent 50%-80% of all paediatric pneumococcal diseases globally. The World Health Organization has recommended the use of PCV-10/13 in the national immunisation programmes (NIPs) of developing countries. Four doses of PCV-13 have been recommended by the US Association of Pediatrics and Centers for Disease Control and Prevention, at intervals of each 2 months for the first 6 months and by the 12
MeSH term(s)	Bacteremia/epidemiology ; Bacteremia/microbiology ; Bacteremia/mortality ; Bacteremia/prevention & control ; Global Health ; Health Policy ; Humans ; Incidence ; Meningitis, Bacterial/epidemiology ; Meningitis, Bacterial/microbiology ; Meningitis, Bacterial/mortality ; Meningitis, Bacterial/prevention & control ; Pneumococcal Infections/epidemiology ; Pneumococcal Infections/microbiology ; Pneumococcal Infections/mortality ; Pneumococcal Infections/prevention & control ; Pneumococcal Vaccines/administration & dosage ; Pneumococcal Vaccines/immunology ; Serogroup ; Streptococcus pneumoniae/classification ; Streptococcus pneumoniae/immunology ; World Health Organization
Chemical Substances	10-valent pneumococcal conjugate vaccine ; 13-valent pneumococcal vaccine ; Pneumococcal Vaccines
Language	English
Publishing date	2019-03-17
Publishing country	India
Document type	Journal Article ; Review
ZDB-ID	1038798-5
ISSN	1998-3646 ; 0255-0857
ISSN (online)	1998-3646
ISSN	0255-0857
DOI	10.4103/ijmm.IJMM_18_442
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.A 2639: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: Bioconversion of lovastatin to simvastatin by Streptomyces carpaticus toward the inhibition of HMG-CoA activity.

Balraj, Janani / Murugesan, Thandeeswaran / Dhanapal, Anand Raj / Kalieswaran, Vidhya / Jairaman, Karunyadevi / Archunan, Govindaraju / Jayaraman, Angayarkanni

Biotechnology and applied biochemistry

2023 Volume 70, Issue 3, Page(s) 1162–1175

Abstract: The aim of this study was the modification of lovastatin by microbes to improve its potential. Actinobacteria exhibit staggering diversity in terms of their biosynthetic capability for specialized metabolites which has been traced back to the presence of ...

Abstract	The aim of this study was the modification of lovastatin by microbes to improve its potential. Actinobacteria exhibit staggering diversity in terms of their biosynthetic capability for specialized metabolites which has been traced back to the presence of specialized gene clusters. The objective of the study is to exploit the potential of Actinobacteria strain(s), which can biotransform lovastatin to simvastatin, which might be a more potent therapeutic agent than lovastatin. We have screened 40 Actinobacteria strains and assessed their biotransformation potential primarily through thin layer chromatography (TLC) analysis, followed by high performance thin layer chromatography and high performance liquid chromatography analysis. One strain C7 (CTL S12) has been identified as a potential Actinobacteria that favored the simvastatin biotransformation. The morphological and biochemical analysis together with 16S rRNA sequencing coupled with phylogenetic analysis confirmed the ideal strain (C7) as Streptomyces carpaticus. Successively, the purified simvastatin from S. carpaticus was characterized by liquid chromatography-mass spectrometry (LC-MS), infrared spectrometry, nuclear magnetic resonance, and HMG-CoA assay. In the LC-MS analysis, a peak at 419.24 m/z confirmed the elemental composition of simvastatin (C
MeSH term(s)	Lovastatin/pharmacology ; Lovastatin/therapeutic use ; Simvastatin/pharmacology ; Hydroxymethylglutaryl-CoA Reductase Inhibitors ; RNA, Ribosomal, 16S/genetics ; Phylogeny
Chemical Substances	Lovastatin (9LHU78OQFD) ; Simvastatin (AGG2FN16EV) ; Hydroxymethylglutaryl-CoA Reductase Inhibitors ; 3-hydroxy-3-methylglutaryl-coenzyme A (1553-55-5) ; RNA, Ribosomal, 16S
Language	English
Publishing date	2023-01-03
Publishing country	United States
Document type	Journal Article
ZDB-ID	883433-7
ISSN	1470-8744 ; 0885-4513
ISSN (online)	1470-8744
ISSN	0885-4513
DOI	10.1002/bab.2429
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 1865: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Customised enriched coconut oil as panacea for oral biofilm mediated diseases - A prospective study.

Sai, Shamini / Nivedha, Raga T / Narasimhan, Srinivasan / Veronica, Aruna K / Selvakumar, Jayaraman / Susila, Anand V

Indian journal of dental research : official publication of Indian Society for Dental Research

2023 Volume 34, Issue 2, Page(s) 159–163

Abstract: Aims: To evaluate a customised enriched formulation of coconut (CEC) oil with Arimedadi Tailam (AT) and 0.2% chlorhexidine mouth rinse (CHX) for their plaque control and potential anticaries effects using the oratest in healthy volunteers.: Settings ... ...

Abstract	Aims: To evaluate a customised enriched formulation of coconut (CEC) oil with Arimedadi Tailam (AT) and 0.2% chlorhexidine mouth rinse (CHX) for their plaque control and potential anticaries effects using the oratest in healthy volunteers. Settings and design: Parallel, double-blinded (outcome assessor and statistician), randomised controlled institution-based pilot study. Methods and materials: 60 adults (18-22 years) having DMFT score of 2-11, gingival and plaque index as zero, no history of antibiotics for one month or fluoride application in 2 weeks were randomly divided (computer-generated list) and allocated into 3 groups (A-CHX, B-CEC, C-AT) of 20 subjects each based on the intervention. Oratest at baseline, days 15 and 30 were recorded. Statistical analysis used: Due to 5 dropouts on day 30, data were analysed based on the intention-to-treat (ITT) approach. The difference in oratest scores (baseline vs. day 15 and 30) were found to be normally distributed (Shapiro-Wilk test and Levene's test). One way ANOVA followed by Tukey's post hoc test was used to determine the statistically significant difference (P < 0.05) between groups. Results: Plaque and gingival index was zero throughout the study period. Difference in oratest scores was highest with CEC oil, followed by CHX and AT though there was no statistically significant differences between groups at baseline vs day 15 (P = 0.203) and baseline vs day 30 (P = 0.085) and between oils from baseline vs day 30 (P = 0.068). Conclusions: Within the limitations of the pilot study, both oils are comparable to CHX for their antiplaque and anticaries potential. Clinically, CEC was better than AT though statistical difference was not there.
MeSH term(s)	Humans ; Anti-Infective Agents, Local/therapeutic use ; Chlorhexidine ; Coconut Oil ; Dental Plaque/drug therapy ; Dental Plaque/prevention & control ; Mouthwashes/therapeutic use ; Pilot Projects ; Prospective Studies ; Young Adult
Chemical Substances	Anti-Infective Agents, Local ; Chlorhexidine (R4KO0DY52L) ; Coconut Oil (Q9L0O73W7L) ; Mouthwashes
Language	English
Publishing date	2023-10-03
Publishing country	India
Document type	Randomized Controlled Trial ; Journal Article
ZDB-ID	1354886-4
ISSN	1998-3603 ; 0970-9290
ISSN (online)	1998-3603
ISSN	0970-9290
DOI	10.4103/ijdr.ijdr_955_22
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 4581: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Enhancing antibody affinity through experimental sampling of non-deleterious CDR mutations predicted by machine learning.

Clark, Thomas / Subramanian, Vidya / Jayaraman, Akila / Fitzpatrick, Emmett / Gopal, Ranjani / Pentakota, Niharika / Rurak, Troy / Anand, Shweta / Viglione, Alexander / Raman, Rahul / Tharakaraman, Kannan / Sasisekharan, Ram

Communications chemistry

2023 Volume 6, Issue 1, Page(s) 244

Abstract: The application of machine learning (ML) models to optimize antibody affinity to an antigen is gaining prominence. Unfortunately, the small and biased nature of the publicly available antibody-antigen interaction datasets makes it challenging to build an ...

Abstract	The application of machine learning (ML) models to optimize antibody affinity to an antigen is gaining prominence. Unfortunately, the small and biased nature of the publicly available antibody-antigen interaction datasets makes it challenging to build an ML model that can accurately predict binding affinity changes due to mutations (ΔΔG). Recognizing these inherent limitations, we reformulated the problem to ask whether an ML model capable of classifying deleterious vs non-deleterious mutations can guide antibody affinity maturation in a practical setting. To test this hypothesis, we developed a Random Forest classifier (Antibody Random Forest Classifier or AbRFC) with expert-guided features and integrated it into a computational-experimental workflow. AbRFC effectively predicted non-deleterious mutations on an in-house validation dataset that is free of biases seen in the publicly available training datasets. Furthermore, experimental screening of a limited number of predictions from the model (<10^2 designs) identified affinity-enhancing mutations in two unrelated SARS-CoV-2 antibodies, resulting in constructs with up to 1000-fold increased binding to the SARS-COV-2 RBD. Our findings indicate that accurate prediction and screening of non-deleterious mutations using machine learning offers a powerful approach to improving antibody affinity.
Language	English
Publishing date	2023-11-09
Publishing country	England
Document type	Journal Article
ZDB-ID	2929562-2
ISSN	2399-3669 ; 2399-3669
ISSN (online)	2399-3669
ISSN	2399-3669
DOI	10.1038/s42004-023-01037-7
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Book ; Online: SICKLE

Sani, Depanshu / Mahato, Sandeep / Saini, Sourabh / Agarwal, Harsh Kumar / Devshali, Charu Chandra / Anand, Saket / Arora, Gaurav / Jayaraman, Thiagarajan

A Multi-Sensor Satellite Imagery Dataset Annotated with Multiple Key Cropping Parameters

2023

Abstract: The availability of well-curated datasets has driven the success of Machine Learning (ML) models. Despite greater access to earth observation data in agriculture, there is a scarcity of curated and labelled datasets, which limits the potential of its use ...

Abstract	The availability of well-curated datasets has driven the success of Machine Learning (ML) models. Despite greater access to earth observation data in agriculture, there is a scarcity of curated and labelled datasets, which limits the potential of its use in training ML models for remote sensing (RS) in agriculture. To this end, we introduce a first-of-its-kind dataset called SICKLE, which constitutes a time-series of multi-resolution imagery from 3 distinct satellites: Landsat-8, Sentinel-1 and Sentinel-2. Our dataset constitutes multi-spectral, thermal and microwave sensors during January 2018 - March 2021 period. We construct each temporal sequence by considering the cropping practices followed by farmers primarily engaged in paddy cultivation in the Cauvery Delta region of Tamil Nadu, India; and annotate the corresponding imagery with key cropping parameters at multiple resolutions (i.e. 3m, 10m and 30m). Our dataset comprises 2,370 season-wise samples from 388 unique plots, having an average size of 0.38 acres, for classifying 21 crop types across 4 districts in the Delta, which amounts to approximately 209,000 satellite images. Out of the 2,370 samples, 351 paddy samples from 145 plots are annotated with multiple crop parameters; such as the variety of paddy, its growing season and productivity in terms of per-acre yields. Ours is also one among the first studies that consider the growing season activities pertinent to crop phenology (spans sowing, transplanting and harvesting dates) as parameters of interest. We benchmark SICKLE on three tasks: crop type, crop phenology (sowing, transplanting, harvesting), and yield prediction Comment: Accepted as an oral presentation at WACV 2024
Keywords	Computer Science - Computer Vision and Pattern Recognition
Publishing date	2023-11-29
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Book ; Online: Crop Type Identification for Smallholding Farms

Sani, Depanshu / Mahato, Sandeep / Sirohi, Parichya / Anand, Saket / Arora, Gaurav / Devshali, Charu Chandra / Jayaraman, T.

Analyzing Spatial, Temporal and Spectral Resolutions in Satellite Imagery

2022

Abstract: The integration of the modern Machine Learning (ML) models into remote sensing and agriculture has expanded the scope of the application of satellite images in the agriculture domain. In this paper, we present how the accuracy of crop type identification ...

Abstract	The integration of the modern Machine Learning (ML) models into remote sensing and agriculture has expanded the scope of the application of satellite images in the agriculture domain. In this paper, we present how the accuracy of crop type identification improves as we move from medium-spatiotemporal-resolution (MSTR) to high-spatiotemporal-resolution (HSTR) satellite images. We further demonstrate that high spectral resolution in satellite imagery can improve prediction performance for low spatial and temporal resolutions (LSTR) images. The F1-score is increased by 7% when using multispectral data of MSTR images as compared to the best results obtained from HSTR images. Similarly, when crop season based time series of multispectral data is used we observe an increase of 1.2% in the F1-score. The outcome motivates further advancements in the field of synthetic band generation. Comment: Supported by Google under AI4SG Workshop
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Machine Learning ; Electrical Engineering and Systems Science - Image and Video Processing
Subject code	006
Publishing date	2022-05-06
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Simulating SOC Dynamics under Different Temperature Regimes and FYM Addition in Bamboo Species Using RothC-Model

Kaushal, Rajesh / Panwar, Pankaj / Durai, Jayaraman / Tomar, Jag Mohan Singh / Mandal, Debashis / Dogra, Pradeep / Gupta, Anand / Reza, Selim / Singh, Charan / Madhu, Made

Forests. 2023 Mar. 31, v. 14, no. 4

2023

Abstract: To assess the impact of bamboo plantations on soil organic carbon (SOC) under prevailing climatic conditions, increase in temperature and soil amendments, the Roth C model was used. RothC is a promising model for the estimation of SOC changes in ... ...

Abstract	To assess the impact of bamboo plantations on soil organic carbon (SOC) under prevailing climatic conditions, increase in temperature and soil amendments, the Roth C model was used. RothC is a promising model for the estimation of SOC changes in different land use systems. In the present study, the RothC model was used to predict the dynamics of SOC in the plantation of seven bamboo species under a usual scenario: increase temperature by 1 °C and 2 °C and farm yard manure (FYM) addition. The result revealed that RothC fairly predicts the SOC. The root mean square error (RMSE) value varied from 0.74 to 3.2 among seven bamboo species while comparing modeled and measured data. The increase in temperature resulted in a decrease in SOC. The decrease in SOC varied from 0.46 to 5.96 per cent as compared to the usual scenario, and the extent of the decrease varied from species to species. Among all species, the application of 9 t ha⁻¹ FYM was found appropriate for maintaining the initial SOC level during the initial stage of bamboo growth.
Keywords	animal manures ; bamboos ; land use ; models ; soil ; soil organic carbon ; temperature
Language	English
Dates of publication	2023-0331
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article ; Online
ZDB-ID	2527081-3
ISSN	1999-4907
ISSN	1999-4907
DOI	10.3390/f14040722
Database	NAL-Catalogue (AGRICOLA)

Order via subito

Article ; Online: Machine Learning-Guided Antibody Engineering That Leverages Domain Knowledge To Overcome The Small Data Problem

Clark, Thomas / Subramanian, Vidya / Jayaraman, AKila / Fitzpatrick, Emmett / Gopal, Ranjani / Pentakota, Niharika / Rurak, Troy / Anand, Shweta / Viglione, Alexander / Tharakaraman, Kannan / Raman, Rahul / Sasisekharan, Ram

bioRxiv

Abstract: The application of Machine Learning (ML) tools to engineer novel antibodies having predictable functional properties is gaining prominence. Herein, we present a platform that employs an ML-guided optimization of the complementarity-determining region ( ... ...

Abstract	The application of Machine Learning (ML) tools to engineer novel antibodies having predictable functional properties is gaining prominence. Herein, we present a platform that employs an ML-guided optimization of the complementarity-determining region (CDR) together with a CDR framework (FR) shuffling method to engineer affinity-enhanced and clinically developable monoclonal antibodies (mAbs) from a limited experimental screen space (order of 10^2 designs) using only two experimental iterations. Although high-complexity deep learning models like graph neural networks (GNNs) and large language models (LLMs) have shown success in protein folding with large dataset sizes, the small and biased nature of the publicly available antibody-antigen interaction datasets is not sufficient to capture the diversity of mutations virtually screened using these models in an affinity enhancement campaign. To address this key gap, we introduced inductive biases learned from extensive domain knowledge of protein-protein interactions through feature engineering and selected model hyperparameters to reduce the overfitting of the limited interaction datasets. Notably, we show that this platform performs better than GNNs and LLMs on an in-house validation dataset that is enriched in diverse CDR mutations that go beyond alanine-scanning. To illustrate the broad applicability of this platform, we successfully solved a challenging problem of redesigning two different anti-SARS-COV-2 mAbs to enhance affinity (up to 2 orders of magnitude) and neutralizing potency against the dynamically evolving SARS-COV-2 Omicron variants.
Keywords	covid19
Language	English
Publishing date	2023-06-05
Publisher	Cold Spring Harbor Laboratory
Document type	Article ; Online
DOI	10.1101/2023.06.02.543458
Database	COVID19

Full text online

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Full text online

Kategorien

Inter-library loan at ZB MED