imagine (Institute of molecular genetics and genetic engineering)
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Impact of Protein Representations on Drug-Target Affinity Prediction
No full textand target proteins can significantly hasten the drug discovery and development process.
Utilizing artificial intelligence (AI) models to predict drug-target affinity (DTA) is an affordable
and efficient strategy for sifting out undesirable molecules and identifying promising drug
candidates. This approach allows researchers to focus on the most promising compounds
for further in silico and wet lab experiments, thereby streamlining the overall workflow.
Advancements in AI research, such as the development and implementation of graph
neural networks (GNN) and attention mechanisms, have significantly improved methods
for processing small molecules as potential drug candidates. These developments now
allow for very efficient and accurate DTA prediction, without the need for extensive protein
processing resources. While this progress marks a significant step forward in computational
drug discovery, models that heavily rely on efficient molecule processing may still lack the
incorporation of highly specific protein information into their algorithms, which could be
crucial for further improvement.
In this study, we present a comprehensive analysis of the impact of different protein
representations on the accuracy of DTA prediction using two datasets, by implementing and
modifying AI models that are based on GNNs and large language models (LLM).
Motivated by the intuitive resemblance between traditional motif search methods for protein
sequence analysis and conventional one-dimensional convolution in AI signal processing,
we propose a protein representation model based on transposed convolutional neural
network (NN) layers. Preliminary results indicate that such embeddings improve the overall
affinity prediction accuracy, compared to similar models from the literature. Additionally,
implementing LLMs to generate protein embeddings independently of other NN layers has
demonstrated potential to significantly enhance the accuracy of predicting drug-target pairs
that have a very low or unmeasurable affinity.Book of abstracts: 5th Belgrade Bioinformatics Conference, Serbia, Belgrade,17-20 june 2024
A novel approach to SARS CoV-2 classification
No full textThis paper presents an approach for clustering of particular SARS-CoV-2 protein types based
on Codon Usage (CU) bias measures. Our previous research has shown that clustering based
on CU bias measures is very close to the natural clustering by protein type, regardless of virus
affiliation. Relative Synonymous Codon Usage, RSCU, Effective Number of Codons, ENC along
with Effective Number of Codons for individual AAc, ENCAA and Relative Codon Bias Strength,
RCBS were calculated to measure the CU bias in different proteins coding sequences.
The dataset contains 928.850 SARS-CoV-2 complete virus isolates with non-ambiguous
nucleotide sequences. It contains 1.145.168 unique (out of a total of 15.564.504) protein
nucleotide sequences and the corresponding AAc sequences. Protein coding sequences are
associated with metadata, including the collection date and the WHO virus strain annotation.
Protein coding sequences within the same type (for each of the 12 most abundant types)
were clustered. Different clustering algorithms (BIRCH, Kohonen Neural Network, fuzzy and
probabilistic clustering) were performed for clustering proteins based on RSCU, ENC and RCBS
with a variable number of clusters. WHO group annotations were used for additional cluster
description. Most clusters in all results are homogeneous (with a maximum size of about 19-35%
of the input material) and are almost pure related to specific WHO group. Each result contains one
or two small cardinality heterogeneous clusters with mixed WHO groups. These heterogeneous
clusters likely denotes proteins (isolates) that were present at the transition between the two
WHO groups. Combining results from different clustering algorithms the membership to WHO
groups of SARS-CoV-2 proteins can be described with very high accuracy using protein clustering
based on the results of CU bias measures.Book of abstracts: 5th Belgrade Bioinformatics Conference, Serbia, Belgrade,17-20 june 2024
Book of abstracts: 5th Belgrade Bioinformatics Conference, Serbia, Belgrade,17-20 june 2024.
No full textAntibiotic persistence refers to a phenomenon where a subset of genetically identical
bacteria enters a dormant state, becoming highly resistant to environmental stresses.
This phenomenon is crucial in understanding why biofilms, communities of bacteria
attached to surfaces, often resist antibiotic treatments, leading to persistent and recurrent
infections. Despite being recognized for almost a century, the precise processes triggering
persister formation remain elusive.
Among the various biological systems implicated in persister formation, toxin-antitoxin
systems within bacteria stand out. These systems consist of a toxic protein and its
corresponding antitoxin, which neutralizes the toxin’s effects. In this study, we propose
a biophysical model focusing on a type I toxin-antitoxin system where the antitoxin is
a small RNA molecule. Our analysis involves both theoretical calculations and computer
simulations to explore the stability of the model and its behavior under deterministic and
stochastic conditions.
Our model successfully reproduces two distinct states within bacterial populations: a
low-toxin state associated with normal growth and a high-toxin state leading to persister
formation. We analytically derive a system stability diagram, allowing us to map under
which conditions the low and high toxin states coexist in an isogenic bacterial population.
Furthermore, we observe a stochastic transition from low to high-toxin. This bistability in
our model arises from feedback loops governing toxin production. Specifically, a positive
feedback loop controls toxin dilution rate, while a negative feedback loop slows down
antitoxin degradation.
Our findings have significant implications for understanding bacterial persistence
mechanisms. We have shown that type I toxin-antitoxin systems may play a role in stressinduced
persister formation. However, they are unlikely to account for “spontaneous”
persister formation, as toxin expression is markedly reduced during normal growth
phases. These insights could lead to developing new therapeutic approaches that target
the specific mechanisms of stress-induced persister formation, thereby improving the
effectiveness of antibiotic treatments.Book of abstracts: 5th Belgrade Bioinformatics Conference, Serbia, Belgrade,17-20 june 2024
Novel cellular factors connecting genome stability and population recovery after massive stress in Ustilago maydis
No full textDeath is an essential part of the life cycle of all organisms. It is fundamental to biological processes and the evolution of life. In
most organisms, the impact of dying individuals on others stops after death. However, it seems that in the microbial community,
the way of death can make a significant difference for the surviving population. The unicellular basidiomycete Ustilago maydis is a
yeast-like organism that can recover population abundance after devastating stress using biomolecules released from dying cells.
This phenomenon is called Repopulation under Starvation (RUS) [1]. We have investigated the recovery dynamics of U. maydis
when using nutrients originating from cells killed with four different treatments (heat, UV radiation, hydrogen-peroxide and
hypoxia). Although the cellular ability to recycle biomolecules released from dead cells can be useful in terms of ecological success,
the nutrient-rich substrates come with significant risks. We have shown that some of them exhibit a genotoxic nature. To cope
with this, U. maydis needs to employ complex machinery to protect its genome from DNA damage and mutational changes. By
employing two strategies, i.e., transcriptome analysis and mutant hunt, we identified six novel cellular factors important for efficient
population recovery after massive stress. Some of these factors are proteins with unknown functions and others are well-known
for their role in maintaining genome stability and cytoskeletal organisation.Book of abstracts: The 52nd EEMGS & 15th ICAW Meeting, Rovinj, Croatia, 23rd - 27th September 202
Inhibition of Salmonella Enteritidis adhesion and biofilm formation by β-glucosidase B from Microbacterium sp. BG28
No full textSalmonellaEnteritidis is the most commonly reported pathogen for foodborne illness outbreaks in both underdeveloped and developed regions. S. Enteritidis biofilms, which form on various food contact surfaces, are resistant to conventional physical and chemical cleaning and disinfection procedures routinely used in food processing. The aim of this study was to identify novel, industrially applicable enzymes that are active against S. Enteritidis biofilms. We describe the properties and anti-biofilm activity of heterologously expressed β-glucosidase B derived from the environmental strain Microbacterium sp. BG28 (BglB-BG28) collected from gills of bream fish. The enzyme inhibited adhesion and the early stages of biofilm formation in clinical isolates of S. Enteritidis. At a concentration of 200 μg/mL, BglB-BG28 effectively reduced biofilm formation, by decreasing biofilm biomass by 50% and metabolic activity within biofilms by 80%. The enzyme reduced the formation of air-liquid biofilms on various surfaces, including plastic, glass and metal, as observed by fluorescence microscopy. BglB-BG28 inhibited biofilm formation in Escherichia coli, another important food pathogen that also forms cellulose-rich biofilms. Using o-NPG as substrate, the enzyme showed activity at temperatures up to 50 °C and in a pH range between 4 and 8, high tolerance to sodium chloride and glucose, and compatibility with nonionic detergents. Importantly, no toxicity was observed in the model system Caenorhabditis elegans even at an enzyme concentration of 1 mg/mL. These results suggest that the β-glucosidase BglB-BG28 is a promising candidate for the development of a new enzyme-based disinfection protocol that can be used in food processing facilities.This is the peer reviewed version of the paper: Atanaskovic, M., Moric, I., Rokic, M. B., Djokic, A., Pantovic, J., Despotović, D., & Senerovic, L. (2024). Inhibition of Salmonella Enteritidis adhesion and biofilm formation by β-glucosidase B from Microbacterium sp. BG28. Food Bioscience, 57, 103543. [https://doi.org/10.1016/j.fbio.2023.103543
STREAMLINE HUB: a high capacity hub for research of neurodevelopmental disorders in the Western Balkan region
Get PDFNeurodevelopmental disorders (NDDs) are caused by alterations in early brain development. They are a group of geographically dispersed, complex and heterogeneous disorders that give rise to the psychiatric conditions such as autism spectrum disorders, intellectual disability, schizophrenia and bipolar disorder. In order to build global research activity for study of NDDs, the main goals of the Twinning project STREAMLINE are to enhanced strategic networking and reinforce research and innovation potential of the Institute of Molecular Genetics and Genetic Engineering, University of Belgrade (IMGGE) in order to develop IMGGE as a high capacity hub for research of NDDs in the Western Balkans. This will be achieved by twinning IMGGE with three top-class research institutions in Europe (Cardiff University, University of Maastricht and Centre for Research and Technology Hellas) with an exceptional expertise in the stem cells based research of NDDs, -OMICS technologies, bioinformatics data analysis and drug testing and through staff exchanges, training, and organization of summer schools, Industry Open Days, symposia and workshops
A 3D in vitro cell culture model based on perfused bone-like scaffolds for healthy and pathological bone research
Get PDFComprehensive research, particularly in evaluating drug efficacy, still heavily relies on the results obtained by the utilization of cell monolayers and animals. However, the inherent limitations of these models such as their physiological disparities from humans pose significant obstacles to acquiring reliable results thus impeding further scientific progression. To address this challenge, 3D in vitro cell culture models emerged as physiologically relevant models having the potential to enhance research and drug discovery. Our study aimed to develop a 3D in vitro cell culture model based on bone-like scaffolds in conjunction with a perfusion bioreactor (“3D Perfuse”, Innovation Center FTM, Belgrade, Serbia) for studying both physiological and pathological (i.e. tumors) bone conditions
SHORT-CHAIN FATTY ACID-PRODUCING FAECALIMONAS SP. NGB245 STRAIN REGULATES THE EXPRESSION OF NEURONAL ACTIVITY-REGULATED GENES AND ATTENUATES THE SYMPTOMS OF EXPERIMENTAL AUTOIMMUNE ENCEPHALOMYELITIS
Get PDFAlterations in gut microbiota and deregulation
of the gut immune system are recognized
as important events in autoimmune diseases.
The knowledge about the important role of anaerobic
gut bacteria that produce short-chain
fatty acids (SCFAs), in the regulation of intestinal
barrier and immune response made a way
for the development of microbiota-based interventions.
Our research aimed to isolate the
strains with the potential to produce SCFAs,
from healthy volunteer fecal material, and to
test their effects on IL-8 production in the culture
of intestinal epithelial cells (Caco2) as an in
vitro system imitating initial intestinal inflammation,
the effects on the expression of neuronal
activity-regulated genes of Caenorhabditis
elegans, and the effect on the development
of experimental autoimmune encephalomyelitis
(EAE), a mouse model of multiple sclerosis.
Three isolated butyric acid (BA)-producing
strains, and three acetic acid (AA)-producing
strains diminished the production of IL-8 in Caco-
2 cells treated with IL-1β/TNF-α. Further, all
BA-producing strains stimulated the expression
of important neuro-related genes in C. elegans.
Based on the strongest effects in these
assays an isolate identified as Faecalimonas sp.
NGB245 strain was further tested in EAE model.
The oral treatment of EAE-induced mice with
this strain for 16h per day for 15 days resulted
in alleviated daily clinical scores, maximal
clinical scores, and the duration of the illness
in comparison to the effect of media used for
strain cultivation. These results point to the potential
of NGB245 to modify the gut-brain axis
opening the field for future development of microbiota-
based therapy for the diseases associated
with immune response dysfunctions.Book of abstract: From biotechnology to human and planetary health XIII congress of microbiologists of Serbia with international participation Mikromed regio 5, ums series 24: 4th – 6th april 2024, Mona Plaza hotel, Belgrade, Serbi
FROM SOIL TO LAB: EXPLORING TOXICOLOGY WITH CAENORHABDITIS ELEGANS
Get PDFCaenorhabditis elegans is a free-living, non-parasitic,
fully transparent, bacteriovorous soil nematode.
Typically found in temperate climates, it
primarily inhabits organic-rich soil and decaying
fruit. Nearly six decades ago, Sydney Brenner
foresaw its potential as an ideal model system
for problems related developmental biology.
Over time, C. elegans has become instrumental
in investigations spanning aging, longevity,
host-pathogen interactions, developmental biology,
evolution, toxicology and ecotoxicology.
With more than 1200 research articles published
each year, today C. elegans is actively studied in
over a thousand laboratories worldwide. Despite
its small size, with adult hermaphrodites possessing
only 959 somatic cells and 302 neurons, C.
elegans exhibits a diverse array of specialized
tissues, including reproductive, digestive, endocrine,
neuromuscular, and sensory systems.
Moreover, this nematode shares a remarkable
number of conserved genes and signalling
pathways with humans, further enhancing its
relevance not only in biomedical research but
also in toxicology and ecotoxicology. In 1998, C.
elegans became the first multicellular organism
whose genome was completely sequenced. This
nematode is an excellent animal model for ecotoxicity
assessment because of its translucent
body, genetic manipulability, ease of cultivation,
rapid and short life cycle that is easily controlled
by temperature changes. The assessment endpoints
for the toxicology researches are various
and include number of live/dead worms, broad
size, number of eggs, embryo hatchability, locomotion
behaviours, germline apoptosis, oxidative
stress and gene expression in C. elegans. In
our laboratory, C. elegans is used in safety and ecotoxicological
evaluations of plastic degradation
products, artificial and natural materials, as well
as antimicrobial substances obtained through
the activity of specific microorganisms and their
chemical modification in the laboratory.Book of abstract: From biotechnology to human and planetary health XIII congress of microbiologists of Serbia with international participation Mikromed regio 5, ums series 24: 4th – 6th april 2024, Mona Plaza hotel, Belgrade, Serbi
Novel cinnamic acid-based PET derivatives as quorum sensing modulators
No full textPoly(ethylene terephthalate) (PET) is widely used material in the healthcare due to its mechanical properties including resistance to chemicals and abrasion. However, it is susceptible to bacterial attachment and contamination. This study addresses some newly designed model compounds of PET with antimicrobial properties that could potentially be incorporated into PET materials. All compounds were synthesized for the first time by labeling an integral part of PET with chromophores in the form of esters of cinnamic and ferulic acids. After complete structural characterization, the effect of new compounds on microbial growth and communication (quorum sensing, QS) was analyzed and further investigated using molecular docking. The obtained results indicate that the introduction of chromophores that have one part of cinnamic acid enriched with a methoxy functional group in them acts as QS modulators. Moreover, compounds exhibited dose-dependent selectivity toward QS signaling pathways and the highest tested concentration of compounds showed Pseudomonas Quinolone Signal (PQS) inhibitory activity suggesting that these compounds have a potential effect on pyocyanin production. Docking studies demonstrated that compounds hold binding power to all four QS protein targets (LuxP, periplasmatic protein that binds AI-2 inducer and forms a complex able to transduce the autoinducer signal, RhIR protein that is a key QS transcriptional regulator that activates the genes involved in the synthesis of rhamnolipids and pyocyanin, AbaI protein that has a role in QS signal transduction, and LasR protein which is a key QS transcriptional regulator that activates transcription of genes coding for some virulence-associated traits) while the highest binding strength is observed with compounds 2 and 6 containing single cinnamic acid fragment, suggesting their further biomedical application