...the dark DNA group...

We are part of the Genetics Laboratory, Biotechnology Department, School of Applied Biology and Biotechnology at the Agricultural University of Athens.

Our research interests revolve around four distinct, yet intersecting, areas:

--> Drug Design, Drug Repurposing and Molecular Modelling
--> Genetics of Stress Mechanisms and Precision Medicine
--> Exosomics, Exosome Cargo & Function, Exosome based RDTs
--> Artificial Intelligence, Machine Learning and Big Data

The darkDNA group encompasses all aspects of modern genetics, bioinformatics, structural and systems biology approaches. The aim is to combine multi-dimensional genomic information, to investigate complex molecular systems, heredity, population genetics and even complex diseases. In fact, the darkDNA group coalesces various fields of state of the art research in genetics into a multidiscipline approach adjusted to meet the needs of the post-Genomic era.

Of particular interest is the development of statistical and computational methodologies to analyze high-throughput microarray and sequencing gene expression experiments, genetic mapping and integrate gene expression profiles, agricultural, animal and human genetics, animal biotechnology, molecular markers and complex phenotypic traits. Special emphasis is given on the development of tools to study of protein fold and structure. Our focus is also on computational statistics, stochastic search algorithms, partition modelling, Bayesian analysis of change-point models, as well as to integrate, store, organize, visualize and enhance the understanding of complex genetic and structural datasets.

The darkDNA group of the Genetics Laboratory of the Agricultural University of Athens, is fully equipped with state of art laboratories for both in vitro and in silico research. Our facilities cover all aspects of gene handling, cloning, protein expression and purification as well as crystallization and structural analysis. On the other hand, there is large infrastructure on the computational biology axis that comprises of local (in house) server and workstation solutions as well as more advances virtual machines and cloud solutions through successful competitive grants and ongoing research projects.

All in all, our research covers several areas of genetics, bioinformatics, functional genomics, transcriptomics, statistics, genome analysis and annotation, by combining both theoretical and empirical analyses; and involves collaborative and independent research. Research at darkDNA is fixated on the integration of multidiscipline and multidimensional approaches into a rather focused and unified study of biological systems. Our pipelines are based on genomic and structural datasets, whose size has recently skyrocketed, providing the means to spawn biological insights, whose deciphering may establish the basis for rapid and reliable scientific success.

CHECK out darkDNA for:

Our Lab at
Medical School
Our Lab at BRF


Novel Anti-viral Gene Editing Platforms

Developing a new drug entity, from drafting its structure to market launching, is a complex process which can take many years and cost millions of dollars. It may also take many years to grow an idea of supporting evidence before selecting the appropriate pharmacological target for a rather costly drug discovery program to be deployed. This reflects a massive investment in terms of time, money, human and other potential resources. Only for the human immunodeficiency virus (HIV) vaccine, scientists have been working over 30 years and it is estimated that $500 million is being spent every year over the last decade on a candidate HIV vaccine. Creating an effective drug against viral infections represents one of the greatest biological and medical challenges of a generation. Despite the new entry vaccines in clinical trials and the medical achievements, the fight against the fatal global epidemic virus continues. However, the scientific community has failed to address the scourge of viruses beyond the use of some drugs to control symptomatically the infection and to reduce viral load. The use of hitherto classical techniques had no promising results since the life expectancy upon viral infection with Ebola, HIV or some of the Flaviviridae family is very short in many cases indeed. The landscape of anti-viral treatment must be changed dramatically, and new horizons should arise including new strategies for the fight against viruses in the near future.

Novel genetic engineering technologies have been developed enabling precise editing of genomes and these have numerous important clinical applications including the treatment of genetic diseases, viral infections, and cancer. These new classes of reagents can specifically target nucleotide sequences within the cellular genome. The ability to correct gene associated mutations is an attractive approach as a treatment option. Based on recent studies, the CRISPR/Cas9 gene editing system has been used to target the HIV-1 long terminal repeat (LTR) of integrated pro-viral DNA in the genome of cell in tissue culture and was able to inactivate viral gene expression and replication in a variety of latently infected cells. This is an important first step in a potentially promising approach towards a new therapeutic pipeline that aims to eliminate all the permanently integrated DNA proviral copies of HIV-1 in an infected individual. It can also be used as a measure of the efficacy of CRISPR/Cas9 in cells to which it is delivered, independent to cell type.

In this direction, many issues must be addressed including the massive amount of data, the multiple sequence alignments based on homolog blocks, the hybrid sequence alignments, the classification of different viral strains in clusters, the statistical analysis of genetic variations, the conserved motifs and patterns exploration and the nuclear genome comparisons between infected and non-infected cells. Therefore, fast, flexible and memory efficient bioinformatics techniques must be deployed to facilitate analysis of thousands of samples simultaneously. New virus-specific sequence patterns can be identified using genome-wide scale computational analysis. Furthermore, significant insights on the duplicative stepwise viral evolution are investigated. All-in-all, collecting and separating the different forms of viral species in groups using deep learning and hyper-computing pipelines will increase the likelihood of finding the most representative sequence and structure specific conserved motifs for gene editing-based startegies on viral targets and eventually will lead to a powerful and effective treatment against viral infections.

Exosomes in Breast Milk & Epigenetics

An innovative research project to unravel the special features of human breast milk and enrich formula milk using omics technologies.

In particular, a high-quality, quantitative and qualitative study will be conducted for the analysis of the membrane and intracellular composition of the major classes of secreted extracellular vesicles and other transported microparticles. The long term aim is to establish topological networks of phylogenetic distance across human biopolymers. The proposed multidimensional bioinformatics analysis will show which animal milk has the highest phylogenetic affinity for human milk based on specific nucleotide and amino acid sequences, and thus the highest nutritional value for neonates. Application of high-throughput techniques in combination with comparative genomic analysis of mRNAs, non-coding RNAs, proteins, and small molecules that bind or are encapsulated in secreted lipid membranes (exosomes) will be included.

The multi‑dimensional nature of their roles in cellular homeostasis, cell‑to‑cell and tissue‑to‑tissue communication at the level of the organism, as well as their actions on the holobiome (intra‑/interspecies interaction), have garnered the interest of a large number of researchers. Exosomes are one of the most researched classes of extracellular vesicles because they are carriers of targeted protein and DNA/RNA loads. Their multi‑functional cargo have been indicated to regulate a vast number of biological pathways in target cells. However, the mechanisms governing these interactions have not yet been fully determined. Endocrinology, by definition, focuses on homeostatic, and cell‑to‑cell and tissue‑to‑tissue communication mechanisms. Therefore exosomes should be included in this research topic. Exosomes have previously been associated with a number of endocrine disorders, including obesity, type 2 diabetes mellitus, disorders of the reproductive system and cancer. Furthermore, their biogenesis, composition and function have been associated with viruses, an entirely different domain of life. The profound roles of exosomes in homeostasis, stress and several pathological conditions, in conjunction with their selective and cell‑specific composition/function, allude to their use as promising circulating clinical biomarkers of systemic stress and specific pathologic states, and as biocompatible vehicles of therapeutic cargo.

Dimitrios P. Vlachakis

Biochemical Adjustments of native EBOLA Virus Glycoprotein in Patient Sample to Unmask target-Epitopes for Rapid Diagnostic Testing

Post translational modifications of EBOV glycoproptein (GP) mask target epitopes from detection by mAbs.

Ebolavirus and Marburgvirus (EBOV and MARV, respectively) are two genera of the negative sense RNA virus family Filoviridae, order mononegavirales. Filoviruses cause rare but fatal viral hemorrhagic fevers (VHF) in equatorial Africa, wth potential for regional and international urban spread. Filovirus VHFs present with a similar prodrome; mimicking several tropical infectious diseases. Early detection is important for response and control. Existing technologies for filovirus detection are, however, not suited for point of care (POC). While 2 rapid diagnostic tests (RDTs) for EBOV have recently emerged, there are no pan-filovirus targeted RDTs.

The overall goal of this project is to develop biochemical treatments that adjust native EBOV GP in patient sample as a target for rapid diagnostic testing.

Four specific aims are contingent to this goal:
i: pre-treatment with various mixtures ( namely a. glycosidases to remove glycans, b. endopeptidases to denature secondary structure, and c. reducing agents to break disulfide bond) to expose target conserved epitopes
ii: Optimization of concentrations of buffer mixture
iii: ROC-characterization of the optimized sandwich EIA for filovirus rapid diagnostic testing
iv: Prototype testing within the setting of the on-going EVD outbreak in Kivu, Democratic Republic of Congo-DRC.

Dimitrios P. Vlachakis

The DARK side of Life...

For many years researchers have been doing gene and protein comparisons using similarity indexes of sequenced entries. In our group, we chose to turn 180 degrees and look for the exact opposite; to develop evolutionary measures based on de-similarity and the DARK side of the genome and proteome (i.e. what we know is there, but cannot find it).

In this direction, we investigate the role of minimal absent words (MAWs) and cryptides. MAWs are very short sequences of DNA that do not occur in the genome of a species, even though they are theoretically possible. The chances of not finding an 11-mere DNA sequence in 3.2 billion bases of human genome are zero, provided that DNA is a 4-letter code. So, how come CGCTCGACGTA, GTCCGAGCGTA, CGACGAACGGT or CCGATACGTCG are nowhere to be found in any human genome? We speculate that if they appear, they lead to non-survivors and therefore elucidating their function could be huge in understanding disease. Likewise, cryptides are peptide fragments generated during maturation or degadation processes of functional proteins showing various biological activities distinct from those of the parent proteins. Peptides are involved in many cellular processes, however, their origin may not be directly from the ribosome after mRNA processing, but from fragments of degraded proteins.

Accordingly, in our group we are interested in the development of novel DARK-omics platforms for the functional screening of new MAWs and cryptides, for the investigation of gene and peptido-mimetics with variegate applications.

On the origins of life

A molecular and a cellular journey driven by genentropy

The most prominent scenario on the origins of life is that life began with RNA. This is a rather convenient hypothesis that has been based on an acceleration of complexity in the evolutionary time trajectory, including life. The negentropy introduced with life, and the progressively increasing complexity and specialized molecular mechanisms began with the genetic molecules of life and, in fact, with the least complicated one, which is the RNA. However, there are no solid explanations on key questions, such as the process through which the RNA was formed, and why those four bases and not five or two. Even if by an unbelievable turn of events and abundant evolutionary time, RNA was formed out of pure chance, the questions remain of where are the other molecules that should also have been made by chance and the process through which the RNA self-replicated. Herein, a novel approach identifying steroids as the first molecules to have started life is being suggested. The hypothesis presented herein describes early steroid-like clusters, organized in the three-dimensional space, which might have led to the formation of RNA. Molecular dynamic (MD) simulations support the initial formation of cyclohexanes that, through their physicochemical properties and a chemical cascade in the prehistoric earth could lead to the first early version of an RNA molecule. All in all, the herein proposed path for the creation of RNA, is a good Newtonian approximation that is compatible with human senses and observations. It is obvious that quantum mechanics, physics, and chemistry orchestrated at subatomic level the creation of the first molecules that gave rise to the first living cell and eventually life as we know it.

Precision Endosymbiomics in Agriculture

Molecular and Geoinformatics Management & Intervention System of eDNA Metagenomics, Plant-Soil-Ecosystem Microbiome and Climate Change

Major changes in the environment and socio-economic factors, combined with the steady increase in the earth's population, are impeding the food industry. Agriculture is one of the most exposed fields to increased climate variability, adversely affecting plant health. Soil degradation, loss of biodiversity, increased pollution of the air and water, have affected the viability and quality of the cultivation. The importance of soil microbiome in establishing ecosystem stability is recognized in the past decade along with its high involvement in sustainable agriculture.
Soil microbiome affects crop growth and soil functions, especially biological soil activity and fertility. Soil microorganisms contribute to soil health by cycling nutrients (such as nitrogen and phosphate) essential for plant growth and global biogeochemical cycles, they improve soil structure by increasing organic matter content, they enhance the resilience of the plants by responding to environmental stresses, and confer disease resistance to crops by out-competing pathogenic microbes. Making use of the metabolic capabilities of the soil microbiome and exploiting beneficial native microbes that promote plant health and quality are ultimate practices for achieving stable yield and reduced impact on the agroecosystem. However, microbiome members may also be associated with diseases and pathogenic effects on plants. The application of pesticides and agrochemicals against phytopathogens in intensive farming leads to impairment of soil functions and long-term crop yield losses, along with negative effects on beneficial soil microbiota.
Thus, the management of the microbial communities and the study of their diversity, connectivity and impact on the soil health is a key component to maintain agricultural productivity and protect the environment.

Dimitrios P. Vlachakis

Bioinformatics Software developed by our group

The Dark Suite

A comprehensive evolutionary and molecular modelling suite that comprises of a series of tools and workflows for drug design developed by our group.
(Download here)

Drugster Suite

Drugster is a freeware platform aimed to assist scientists in the field of Computer Aided Drug Design.
(Download here)

DrugOn Suite

DrugOn is a fully interactive pipeline designed to overcome the command line barrier with two friendly environments for the user.
(Download here)

Drugena Suite

Drugena encompasses an up-to-date database of antibodies for neurological disorders and the NCI database for the in silico development of ADCs.
(Download here)

Antisoma Suite

Antisoma application has been developed in order to provide the information found with this new approach and concerning the antibodies of the species.
(Download here)

Xplatform Suite

With the extensive use of microarray technology as a potential prognostic and diagnostic tool, the comparison and reproducibility of results obtained from the use of different platforms is of interest.
(Download here)

Space Suite

Space Suite, a new homology modelling approach, successfully applied to the homology modelling of the RNA-dependent RNA polymerase (RdRp) of dengue (type II) virus.
(Download here)

Structuprint Suite

A 'molecular cartography' suite for the two-dimensional transformation of protein structures the multidimensional analysis of their physicochemical properties.
(more info here)
(Download here)

Taggo Suite

Taggo takes advantage of the Gene Ontology (GO) to extract the proteins’ main attributes and combines the potential of discarding annotations that are supported by not so reliable Ecs.
(Download here)

Brukin2d Suite

The Brukin2d software, is a visualization tool for large data sets produced from LC-MS. Specifically the chromatograph and the mass spectra that correspond to its peaks is the focus of this work.
(Download here)

Giba Suite

GIBA is an effective and easy to use tool for the detection of protein complexes through clustering PPI networks. GIBA surpasses other methods in quality approximations of protein complexes.
(Download here)

AHC Suite

AHC is a hierarchical algorithm that performs successive min–cuts until it identifies dense subgraphs. AHC leads to the selection of more dense subgraphs as protein complexes candidates.
(Download here)

GAppi Suite

GAppi performs clustering in PPI networks to identify protein complexes. The algorithm has been tested exhaustively and results showed that GAppi outperforms other techniques producing feasible and very efficient solutions.
(Download here)

GOmir Suite

GOmir (by using up to four different databases) introduces, for the first time, miRNA predicted targets accompanied by (a) full gene description, (b) functional analysis and (c) detailed gene ontology clustering.
(Download here)

FED & SAFE Suites

A tool that encompasses retrieval and analysis of fusion events used to identify putative protein-protein interactions in completely sequenced genomes of various prokaryotes, and eukaryotes.
(Download FED here)
(Download SAFE here)

Thetis Suite

A suite of computer programs that has been developed for monitoring structural changes on a-helical secondary structural elements during molecular dynamics (MD) simulations on protein systems.
(Download here)


You can (usually) find us at:
Agricultural University of Athens,
Iera Odos 75, 11855, Athens, Greece
(click for MAP)

Email Address

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Phone Number

You can (try to) call us at:
+30 210 5294323