How life began and what drives evolution? How can it be that more than 60% of the human genome is of viral origin? We now know that viruses have seriously influenced the course of life on our planet and that retro-transposable elements in some species make up the majority of their genome.
The concept of “dark DNA” has been adopted by the field of astrophysics, where cosmologists for many years refer to the part of matter and energy that cannot pinpoint or detect with the existing technology, as dark. However, it has been proven that this dark side of matter and energy is not just very real, but it also makes up more than 90% of the universe. Likewise, in genetics, dark DNA refers to that part of the genome, whose role is not clear, or seems to do not much in the cellular processes essential to life. Consequently, the role of non-coding RNA and the role of introns in alternative splicing is of uttermost priority in our research.
We develop and apply our research to a repertoire of scientific domains. Namely, we have been investigating the role of nuclear receptors in gene expression and regulation and in particular the role of the glucocorticoid receptor in stress. Then, we look into the realm of viruses and in particular into the ssRNA family of flaviviridae and ebola virus for the investigation of the genetic elasticity of viral genomes (antigenic drift/shift) and how epigenetics could annihilate current vaccination protocols. Finally, recently, we have embarked onto the very fascinating field of neurodegeneration, with the genetic and structural study of LRRK2.
In our lab we use a wide spectrum of methodologies ranging from state-of-the-art bioinformatics, molecular modelling and hypercomputing pipelines to traditional genetic and biochemistry in vitro and in vivo techniques. On one hand, we have developed our own software for machine learning, deep learning and data mining for multimodal fusion of information from genetic, structural and physicochemical analyses. On the other hand, we use DNA engineering, SDM, cloning, expression and protein purification techniques to biologically test and evaluate the validity and reliability of our models.
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.
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.
Evolutionary and developmental biology is focused on the investigation and the elucidation of the molecular mechanisms underlying embryonic development from one generation to the other. It started quite early with Darwin and Mendel, but soon it became apparent that it is a complicated network of interacting genes after stimuli from molecules, our microbiome, other organisms or species and the environment that we live in. However, in recent years the accumulation of big data in the fields of genomics, medical records and other relevant datasets has rendered the study of evo-devo impossible without the aid from advanced and highly sophisticated computational models, which aim to mine and fuse information from diverse disciplines in the realm of evolution and developmental biology. This book aims to address the new developments in the rapidly evolving field of evo-devo in the post genomics era. All recent biological and medical breakthroughs in the evo-devo field are welcomed. Finally, review articles encompassing recent advances, development current and future trends are also more than welcomed.
ISBN: 978-1-83962-170-3 / Print ISBN: 978-1-83962-169-7 / eBook (PDF) ISBN: 978-1-83962-171-0
Editors: Dr Dimitrios P. Vlachakis - Prof Elias Eliopoulos - Prof George Chrousos
We are fusing genomic information and investigate associations and synergies between various genes. We are interested in Nulcear Receptors and Stress responce.
A genetic and bioinformatic approach for pest control via inhibiting the key functional and metabolizing enzymes of endosymbiotic bacterial strains.
We have established our own tools and algorithms to cluster antibodies based on structural and physicochemical properties of both their Framework and CDR regions.
We showed that co-expression of fragments of LRRK2 that contain the FADD binding motif blocks the interaction with FADD, and is neuroprotective.
Targeting key enzymes in cell cycle, proliferation and genome processing that overexpress in cancer is a promising approach for novel chemo agents.
A comprehensive evolutionary and molecular modelling suite that comprises of a series of tools and workflows for drug design developed by our group.
Drugster is a freeware platform aimed to assist scientists in the field of Computer Aided Drug Design.
DrugOn is a fully interactive pipeline designed to overcome the command line barrier with two friendly environments for the user.
Drugena encompasses an up-to-date database of antibodies for neurological disorders and the NCI database for the in silico development of ADCs.
Antisoma application has been developed in order to provide the information found with this new approach and concerning the antibodies of the species.
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.
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.
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.
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.
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.
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.
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.
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.
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.