BioExcel’s webinar series continues with a special edition featuring student speakers who were awarded poster prizes at the BioExcel Summer School 2021. Read along to find out more about our speakers and their research.

Date: 21 September, 2021
Time: 15:00 CEST

Julián Fernández

Julian with black hair wearing a black tshirt

Julián obtained his Chemistry degree at the University of Buenos Aires in 2019. His undergraduate research focused on the organic synthesis of bioactive naphthoquinones. He is now a second year Ph.D. student at the Department of Organic Chemistry in the School of Exact and Natural Sciences at the University of Buenos Aires, under the supervision of Dr. Jorge Palermo and Dr. Martín Lavecchia. His primary research focuses on the rational design and synthesis of novel CK2 inhibitors inspired by a marine natural product previously discovered in the lab. In addition, during his Ph.D. he became interested in the interfaces between computational chemistry, organic synthesis and natural product research and, due to this multidisciplinary interest, he is now working in new methodologies for small molecule target prediction.


Small molecule stabilization of non-native protein-protein interactions of SARS-CoV-2 N protein as a mechanism of action against COVID-19

The outbreak of COVID-19, the disease caused by SARS-CoV-2, continues to affect millions of people around the world. The absence of a globally distributed effective treatment makes the exploration of new mechanisms of action a key step to address this situation. Stabilization of non-native Protein-Protein Interactions (PPIs) of the nucleocapsid protein of MERS-CoV has been recently reported as a valid strategy to inhibit viral replication. In this webinar, a computational analysis of the stabilization of non-native PPIs of SARS-CoV-2 N protein as a potential mechanism of action against COVID-19 is presented. A first comparison with MERS-CoV enabled us to explore its applicability towards SARS-CoV-2, where three inducible interfaces were built based on experimental data. Consequently, a drug discovery protocol was developed and applied with a drug repurposing approach. This allowed us to identify potential candidates that might take advantage of this mechanism, many of them with a common catechin skeleton that might be useful for further drug design. Even though further in vitro testing is needed to confirm these findings, we believe they provide valuable insights that might promote future research on this mechanism of action against COVID-19.

Eleonora Gianquinto

Woman smiling with black hair and white top

E.G. has been working since her Master’s thesis on drug discovery projects against resistant bacterial strains. During this period, she won an Erasmus+ mobility and spent four months at the CBDD group in Barcelona. E.G. graduated with honors in 2018 in Industrial Chemistry at the University of Turin, and a year later graduated with honors at Institution of Excellence and Higher Education for University Studies “Ferdinando Rossi”. E.G. is currently a third-year PhD student in Pharmaceutical and Biomolecular Sciences at the Department of Drug Science and Technology of the University of Turin, in Prof. Spyrakis’ research group. In her PhD project entitled “Discovery of new carbapenemase inhibitors by means of in silico innovative methodologies” computational techniques have been used to speed up the drug discovery process against clinically relevant beta-lactamases. Since last year, E.G. has been involved in drug discovery projects against SARS-CoV-2, and for working in this framework she received an HPC-Europa3 fellowship and an Erasmus+ traineeship mobility.

Twitter: @EleonoraGianV

An in Silico Pipeline Identifies Inhibitors with Cross-Class Activity on Clinically Relevant Serine- and Metallo-β-Lactamases

Antibiotic resistance is spreading worldwide, especially among the most dreaded ESKAPE bacteria[1]. A main resistance mechanism involves the production of beta lactamases (BLs, i.e. enzymes able to degrade beta lactam antibiotics), which are conventionally divided in four classes (A, B, C, or D)[2]. In particular, class A, C and D enzymes use a catalytic serine to degrade beta lactam antibiotics, while class B enzymes exploit a zinc-based catalytic hydrolysis. As the road to new classes of antibiotics is problematic, the inhibition of BLs constitutes an effective strategy to potentiate or restore current antibiotics. In this work, we focused on finding inhibitors against five relevant BLs (class A CTX-M-15 and KPC-2, class B NDM-1 and VIM-2 MBLs, and the class C AmpC). An in silico screening of a commercially available library selected a pool of promising candidates, which were tested against clinically relevant strains of bacteria producing BLs. The results highlighted that most effective compounds share electron donor moieties. In particular, we found few inhibitors able to target more than one class of BLs, thus exerting a cross-class inhibition against both serine-based and zinc-based hydrolysis. In vitro tests highlighted that compound 40 enhances imipenem activity against an NDM-1 producing E. coli clinical isolate. Finally, X-ray structures of the two most promising compounds in VIM-2 and NDM-1 gave important insights about the binding mode of triazole-thiol scaffolds. Being NDM-1 and VIM-2 two worldwide emergent carbapenemases, the following optimization of these compounds could lead to new tools in the fight against antibiotic resistance.

[1] WHO. Antimicrobial Resistance. Global Report on Surveillance (World Health Organization, Geneva, 2014).
[2] Ambler, R. P. The structure of beta-lactamases. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 289, 321–331 (1980).

Dheeraj Prakaash

A man with black hair and grey hoodie

Dheeraj obtained his BSc degree in Biotechnology, Microbiology, and Chemistry from Bangalore University, India, in 2014. He then pursued MSc in Bioinformatics at Manipal Academy of Higher Education, India, in 2016. He carried out his master’s thesis work on molecular dynamics and protein-lipid interactions of Aquaporin-Z at the National University of Singapore. In addition, during his MSc coursework, he worked on structural homology studies of metalloproteinases, and the regulation of toll-like receptors in diabetic conditions. After obtaining his MSc degree, he was part of an industrial organization, Robust Materials Technology Pvt. Ltd., where he conceptualized and worked on a project titled ‘Virtual Reality: A Railroad for Structural Bioinformatics towards Advanced Cancer Research’, funded by the Government of India. In this project, he researched on methods to incorporate a ‘sense of touch’ to a virtual molecular world, aiming to benefit education and scientific research. In 2018, he interned at the Computational & Data Science department, Indian Institute of Science, where he studied the architecture of a coarse-grained molecular dynamics forcefield and worked on implementing it into Gromacs. Since January 2019, he is a PhD student at the University of Leeds, UK, studying the molecular mechanisms of the T-cell receptor and LCK in a membrane environment using molecular dynamics simulations and modelling.

Elucidating the dynamics and lipid interactions of the T-cell receptor using molecular dynamics simulations and modelling.

The T-cell antigen receptor (TCR) initiates immune responses by recognising a wide variety of foreign peptides presented by Major Histocompatibility Complex (MHC) proteins. Cancers and autoimmune disorders are associated with the function of this receptor and thus studying the TCR in near-atomic resolution will ultimately aid in clinical therapeutics. Despite significant knowledge of the TCR structure and topology, the arrangement of its cytoplasmic region remains elusive and limits our understanding of the molecular mechanism of the initiation of T-cell signalling. In this study, we used molecular modelling to model the entire TCR structure, and performed coarse-grained and atomistic simulations with the complete TCR structure inserted in a membrane environment that mimics its native T-cell membrane activation domain. Our simulations revealed lipid interaction hotspots and preferred conformations of the TCR in its resting state. Our results also suggest that the TCR cytoplasmic region plays a significant role in forming an anionic lipid environment which potentially aids the recruitment of signalling proteins such as LCK via electrostatic interactions initiating T-cell signalling. Overall, these studies have provided novel information on the interaction of the complete TCR with lipids and how these interactions may regulate TCR dynamics and signalling. In addition, our study forms the basis to further understand the molecular mechanism of the initiation of TCR signalling.