Jérémie Mortier

The impact of molecular dynamics on drug design: applications for the characterization of ligand–macromolecule complexes

Among all tools available to design new drugs, molecular dynamics (MD) simulations have become an essential technique. Initially developed to investigate molecular models with a limited number of atoms, computers now enable investigations of large macromolecular systems with a simulation time reaching the microsecond range. The reviewed articles cover four years of research to give an overview on the actual impact of MD on the current medicinal chemistry landscape with a particular emphasis on studies of ligand-protein interactions. With a special focus on studies combining computational approaches with data gained from other techniques, this review shows how deeply embedded MD simulations are in drug design strategies and articulates what the future of this technique could be.

NF-κB inducing kinase (NIK) inhibitors: Identification of new scaffolds using virtual screening

As a wide variety of pro-inflammatory cytokines are involved in the development of rheumatoid arthritis (RA), there is an urgent need for the discovery of novel therapeutic strategies. Among these, the inhibition of the NF-kappaB inducing kinase (NIK), a key enzyme of the NF-kappaB alternative pathway activation, represents a potential interesting approach. In fact, NIK is involved downstream of many tumor necrosis factor receptors (TNFR) like CD40, RANK or LTbetaR, implicated in the pathogenesis of RA. But, up to now, the number of reported putative NIK inhibitors is extremely limited. In this work, we report a virtual screening (VS) study combining various filters including high-throughput docking using a 3D-homology model and ranking by using different scoring functions. This work led to the identification of two molecular fragments, 4H-isoquinoline-1,3-dione (5) and 2,7-naphthydrine-1,3,6,8-tetrone (6) which inhibit NIK with an IC(50) value of 51 and 90 microM, respectively. This study opens new perspectives in the field of the NF-kappaB alternative pathway inhibition.

Synthesis, biological activity and structure–activity relationships of new benzoic acid-based protein tyrosine phosphatase inhibitors endowed with insulinomimetic effects in mouse C2C12 skeletal muscle cells

Insulin resistance is a complex altered metabolic condition characterized by impaired insulin signaling and implicated in the pathogenesis of serious human diseases, such as diabetes, obesity, neurodegenerative pathologies. In pursuing our aim to identify new agents able to improve cellular insulin sensitivity, we have synthesized new 4-[(5-arylidene-4-oxo-2-phenylimino/oxothiazolidin-3-yl)methyl]benzoic acids (5, 8) and evaluated their inhibitory activity towards human protein tyrosine phosphatases PTP1B, LMW-PTP and TCPTP, enzymes which are involved in the development of insulin resistance. Compounds 5 and 8 showed from moderate to significant selectivity toward PTP1B over both the highly homologous TCPTP and the two isoforms of human LMW-PTP. In addition, most of the tested compounds selectively inhibited LMW-PTP IF1 over the isoform IF2. Docking studies into the active sites of PTP1B and LMW-PTP aided the rationalization of the observed PTP inhibitory profile. Moreover, most tested compounds were capable to induce the insulin metabolic pathway in mouse C2C12 skeletal muscle cells by remarkably stimulating both IRβ phosphorylation and 2-deoxyglucose cellular uptake.

Impact of fluorination on proteolytic stability of peptides: a case study with α-chymotrypsin and pepsin

Protease stability is a key consideration in the development of peptide-based drugs. A major approach to increase the bioavailability of pharmacologically active peptides is the incorporation of non-natural amino acids. Due to the unique properties of fluorine, fluorinated organic molecules have proven useful in the development of therapeutically active small molecules as well as in materials and crop science. This study presents data on the ability of fluorinated amino acids to influence proteolytic stability when present in peptide sequences that are based on ideal protease substrates. Different model peptides containing fluorinated amino acids or ethylglycine in the P2, P1′or P2′ positions were designed according to the specificities of the serine protease, α-chymotrypsin (EC 3.4.21.1) or the aspartic protease, pepsin (EC 3.4.23.1). The proteolytic stability of the peptides toward these enzymes was determined by an analytical RP-HPLC assay with fluorescence detection and compared to a control sequence. Molecular modeling was used to support the interpretation of the structure–activity relationship based on the analysis of potential ligand-enzyme interactions. Surprisingly, an increase in proteolytic stability was observed only in a few cases. Thus, this systematic study shows that the proteolytic stability of fluorinated peptides is not predictable, but rather is a very complex phenomenon that depends on the particular enzyme, the position of the substitution relative to the cleavage site and the fluorine content of the side chain.

Inhibitory potency of flavonoid derivatives on influenza virus neuraminidase

The constant risk of emerging new influenza virus strains that are resistant to established inhibitors like oseltamivir leaves influenza neuraminidase (NA) a prominent target for drug design. The inhibitory activity of several flavonoid derivatives was experimentally tested in comparison to oseltamivir for the NA expressed by the seasonal influenza virus strains A/California/7/09 (A(H1N1)pdm09), A/Perth/16/09 (A(H3N2)), and B/Brisbane/60/08. IC50 values of polyphenols confirmed moderate inhibition in the μM range. Structurally, the amount and site of glycosylation of tested flavonoids have no significant influence on their inhibitory potency. In a pharmacophore-based docking approach the structure-activity relationship was evaluated. Molecular dynamics simulations revealed highly flexible parts of the enzyme and the contribution of salt bridges to the structural stability of NA. The findings of this study elucidate the impact of flavonoids on viral neuraminidase activity and the analysis of their modes of action provide valuable information about the mechanism of NA inhibition.

Design, synthesis and molecular docking study of novel quinoxalin-2(1H)-ones as anti-tumor active agents with inhibition of tyrosine kinase receptor and studying their cyclooxygenase-2 activity

On continuation to our work, new quinoxalin-2(1H)-ones were synthesized to study their cytotoxic effect against HepG-2 and MCF-7 with their effect on the human tyrosine kinase (TRK). Compounds 12, 18, 15, 13, 11a, 20 and 16, respectively, were found to be more potent than cisplatin against HepG2 and selective to TRK. Also, compounds 12, 18, 20, 13, 14, and 22, respectively, exhibited decidedly activity against MCF-7 and selectivity against human TRK compared to cisplatin. A molecular docking study was also performed to gain comprehensive understanding into plausible binding modes and to conclude the structure activity relationships of the synthesized compounds. Moreover, anti-inflammatory activity was studied. Compounds 12, 15, 18 and 22 were found to be potent and selective against COX-2.

Computational close up on protein–protein interactions: how to unravel the invisible using molecular dynamics simulations?

As an essential part of many biological processes, protein–protein interactions (PPIs) offer exciting and promising opportunities for drug discovery by extension of the druggable target space. Over the last decade, studies on protein networks have significantly increased the number of identified PPIs. However, despite steadily growing data on PPIs, detailed understanding of the interaction surfaces and their dynamics remains limited. Furthermore, the development of small‐molecule inhibitors of PPIs faces technological challenges, leaving the question about the ‘druggability’ of PPIs open. Molecular dynamics (MD) simulations may facilitate the prediction of druggable binding sites on protein–protein interfaces by detecting binding hot spots and transient pockets. MD allows for a detailed analysis of structural and functional aspects of PPIs and thus provides valuable insights into PPI mechanisms and supports the design of PPI modulators. We provide an overview on the main areas of MD applications to PPIs including structural investigations and the design of PPI disruptors. Emphasizing the beneficial synergies between computational and experimental techniques, MD techniques are also frequently applied to low‐resolution structural data and have been used to elucidate structure and movements of complex macromolecular structures relevant for biological processes. WIREs Comput Mol Sci 2015, 5:345–359. doi: 10.1002/wcms.1222

Design, synthesis and structure-activity relationship of novel quinoxaline derivatives as cancer chemopreventive agent by inhibition of tyrosine kinase receptor.

The cancer chemopreventive activity of quinoxaline derivatives 1-20 has been evaluated by studying the inhibitory effect on Epstein-Barr virus early antigen (EBV-EA) activation. The quinoxaline derivatives 1-20 showed inhibitory effect on EBV-EA activation without cytotoxicity on Raji cells. All compounds exhibited dose dependent inhibitory activities, most of them showed significant activity at 1000 mol ratio/12-O-tetradecanoylphorbol-13-acetate (TPA). Compounds 7 and 9 exhibited stronger inhibitory effects on the EBV-EA activation than that of the representative control, oleanolic acid, at the highest measured concentration. In addition, compounds 7-10 showed potent and selective inhibition of human tyrosine kinase (TRK) in liver cancer HepG2 and breast cancer MCF-7 cell lines similar to the positive control, doxorubicin.

In silico virtual screening approaches for anti-viral drug discovery

Despite the considerable advances in medical and pharmaceutical research during the past years, diseases caused by viruses have remained a major burden to public health. Virtual in silico screening has repeatedly proven to be useful to meet the special challenges of antiviral drug discovery. Large virtual compound libraries are filtered by different computational screening methods such as docking, ligand-based similarity searches or pharmacophore-based screening, reducing the number of candidate molecules to a smaller set of promising candidates that are then tested biologically. This rational approach makes the drug discovery process more goal-oriented and saves resources in terms of time and money. In this review we discuss how different virtual screening techniques can be applied to antiviral drug discovery, present recent success stories in this field and finally address the main differences between the methods. Despite the considerable advances in medical and pharmaceutical research during the past years, diseases caused by viruses have remained a major burden to public health. Virtual in silico screening has repeatedly proven to be useful to meet the special challenges of antiviral drug discovery. Large virtual compound libraries are filtered by different computational screening methods such as docking, ligand-based similarity searches or pharmacophore-based screening, reducing the number of candidate molecules to a smaller set of promising candidates that are then tested biologically. This rational approach makes the drug discovery process more goal-oriented and saves resources in terms of time and money. In this review we discuss how different virtual screening techniques can be applied to antiviral drug discovery, present recent success stories in this field and finally address the main differences between the methods.

Computational Tools for In Silico Fragment-Based Drug Design

Fragment-based strategy in drug design involves the initial discovery of low-molecular mass molecules. Owing to their small-size, fragments are molecular tools to probe specific sub-pockets within a protein active site. Once their interaction within the enzyme cavity is clearly understood and experimentally validated, they represent a unique opportunity to design potent and efficient larger compounds. Computer-aided methods can essentially support the identification of suitable fragments. In this review, available tools for computational drug design are discussed in the frame of fragmentbased approaches. We analyze and review (i) available commercial fragment libraries with respect to their properties and size, (ii) computational methods for the construction of such a library, (iii) the different strategies and software packages for the selection of the fragments with predicted affinity to a given target, and (iv) tools for the in silico linkage of fragments into an actual high-affinity lead structure candidate.