NMR as a “gold standard” method in drug design and discovery

Studying disease models at the molecular level is vital for drug development in order to improve treatment and prevent a wide range of human pathologies. Microbial infections are still a major challenge because pathogens rapidly and continually evolve developing drug resistance. Cancer cells also change genetically, and current therapeutic techniques may be (or may become) ineffective in many cases. The pathology of many neurological diseases remains an enigma, and the exact etiology and underlying mechanisms are still largely unknown. Viral infections spread and develop much more quickly than does the corresponding research needed to prevent and combat these infections; the present and most relevant outbreak of SARS-CoV-2, which originated in Wuhan, China, illustrates the critical and immediate need to improve drug design and development techniques. Modern day drug discovery is a time-consuming, expensive process. Each new drug takes in excess of 10 years to develop and costs on average more than a billion US dollars. This demonstrates the need of a complete redesign or novel strategies. Nuclear Magnetic Resonance (NMR) has played a critical role in drug discovery ever since its introduction several decades ago. In just three decades, NMR has become a “gold standard” platform technology in medical and pharmacology studies. In this review, we present the major applications of NMR spectroscopy in medical drug discovery and development. The basic concepts, theories, and applications of the most commonly used NMR techniques are presented. We also summarize the advantages and limitations of the primary NMR methods in drug development

4,6-Diphenyl-pyridines/pyrimidines and pyrazolo[3,4-d]pyrimidines: promising scaffolds as antiviral, anticancer and theranostic agents.

Nitrogen-based heterocyclic molecules received increasing attention in biological and chemical sciences, becoming a significant moiety in drug design. In this thesis, the research work has been focused on the design and the synthesis of novel derivatives based on the 4,6-diphenyl-pyridine/pyrimidine and pyrazolo[3,4-d]pyrimidine scaffolds as key pharmacophores for their antiviral and anticancer activities, respectively. The first part deals with the design and synthesis of a set of small molecules able to interfere with the Influenza (flu) RNA-dependent RNA Polymerase (RdRp) functions, exploiting the protein-protein interactions (PPIs) approach. An introduction of influenza disease and its pathogens is provided, focusing on the replicative mechanism of the influenza viruses and on the structural and functional information of the flu RdRp. The PPIs of the three polymerase subunits PA, PB1 and PB2, are reported and the inhibitors targeting the heterodimer PA-PB1 are introduced. Finally, the rational design and synthesis of new hybrid compounds bearing the 4,6-diphenyl-pyridine/pyrimidine cores are described togheter with the biological evaluation and molecular modeling studies. The second part of the dissertation focuses on the pyrazolo[3,4-d]pyrimidine compounds, on which both a lead optimization study and a theranostic design have been performed. The pyrazolo[3,4-d]pyrimidines have shown a promising activity both in in vitro and in in vivo as protein kinase inhibitors. The lead optimization study has been performed with the aim of obtaining a new class of derivatives as potent Src kinase inhibitors. The rational design, synthesis and biological analysis of the novel compounds are discussed. A further part of the project is dedicated to the design and development of potential theranostic prodrugs of two promising in-house pyrazolo[3,4-d]pyrimidines, SI306 and SI113. These prodrugs have been synthesized as potential agents for the diagnosis and the treatment of glioblastoma multiforme (GBM). The state of the art on theranostic applications of drugs, whose use is continually increasing, is also described

The in silico investigation of the perplexity of synergistic duality: inter-molecular mechanisms of communication in Bcr–Abl.

Doctoral Degree. University of KwaZulu-Natal, Durban.Due to their important role in normal cellular physiology, protein kinase activity is tightly regulated and their aberrant activation can lead to cancer. Chronic myeloid leukaemia (CML) is a blood cancer described by unregulated growth of myeloid cells caused by a fusion protein, Bcr-Abl, a constitutively active form of the Abelson tyrosine kinase (Abl). Drug targeting of either the ATP binding pocket or allosteric pocket has led to durable therapeutic response, however the development of drug resistance still poses a major clinical challenge. Recent studies exploring synergistic inhibition as an effective approach, by dual targeting of Bcr-Abl using both catalytic and allosteric binding inhibitors. This thesis implements the use of advanced computational tools to unravel molecular insights to aid in the suppression of the emergence of resistance to Bcr-Abl when Nilotinib and ABL001 are co-administered to target both the catalytic and allosteric binding site of Bcr-Abl protein, respectively. Our studies revealed co-binding induced a stable Bcr-Abl protein structure, increased the degree of compactness of binding site residues around Nilotinib and subsequently improved the binding affinity of Nilotinib. Findings in this thesis further provide an atomistic perspective underlying the developed resistance of Nilotinib by point mutation at the catalytic active site only and both catalytic and activation loop sites. We also recognized and rationalized the structural interplay of this single and double mutation upon co-binding of Nilotinib with the novel inhibitor, ABL001. Our findings report the distortion of the overall conformational landscape of Bcr-Abl fusion oncoprotein caused by the mutation, resulting in a reduction of binding affinity of Nilotinib upon single binding. Interesting, co-administration with ABL001 impacted by the mutation results in a more compact and stable protein conformation. Findings reveal a structural mechanism by which the novel inhibitor ABL001 stabilizes Bcr-Abl fusion oncoprotein upon co-binding with Nilotinib, thus suppressing Nilotinib resistance. We also provide vital conformational dynamics and structural mechanisms of the mutant enzyme at the catalytic site-ligand interaction and mutant enzyme at both catalytic and activation loop ligand interactions which could potentially shift the current therapeutic protocol in chronic myeloid leukemia treatment, thus aiding in the design of novel inhibitors with improved therapeutic features against the mutant proteins

Correlation between cell line chemosensitivity and protein expression pattern as new approach for the design of targeted anticancer small molecules

BACKGROUND AND RATIONALE: Over the past few decades, several databases with a significant amount of biological data related to cancer cells and anticancer agents (e.g.: National Cancer Institute database, NCI; Cancer Cell Line Encyclopedia, CCLE; Genomic and Drug Sensitivity in Cancer portal, GDSC) have been developed. The huge amount of heterogeneous biological data extractable from these databanks (among all, drug response and protein expression) provides a real foundation for predictive cancer chemogenomics, which aims to investigate the relationships between genomic traits and the response of cancer cells to drug treatment with the aim to identify novel therapeutic molecules and targets. In very recent times many computational and statistical approaches have been proposed to integrate and correlate these heterogeneous biological data sequences (protein expression – drug response), with the aim to assign the putative mechanism of action of anticancer small molecules with unknown biological target/s. The main limitation of all these computational methods is the need for experimental drug response data (after screening data). From this point of view, the possibility to predict in silico the antiproliferative activity of new/untested small molecules against specific cell lines, could enable correlations to be found between the predicted drug response and protein expression of the desired target from the very earliest stages of research. Such an innovative approach could allow to select the compounds with molecular mechanisms that are more likely to be connected with the target of interest preliminary to the in vitro assays, which would be a critical aid in the design of new targeted anticancer agents. RESULTS: In the present study, we aimed to develop a new innovative computational protocol based on the correlation of drug activity and protein expression data to support the discovery of new targeted anticancer agents. Compared with the approaches reported in the literature, the main novelty of the proposed protocol was represented by the use of predicted antiproliferative activity data, instead of experimental ones. To this aim, in the first phase of the research the new in silico Antiproliferative Activity Predictor (AAP) tool able to predict the anticancer activity (expressed as GI50) of new/untested small molecules against the NCI-60 panel was developed. The ligand-based tool, which took the advantages of the consolidated expertise of the research group in the manipulation of molecular descriptors, was adequately validated and the reliability of the prediction was further confirmed by the analysis of an in-house database and subsequent evaluation of a set of molecules selected by the NCI for the one-dose/five-doses antiproliferative assays. In the second part of the study, a new computational method to correlate drug activity data and protein expression pattern data was proposed and evaluated by analysing several case studies of targeted drugs tested by NCI, confirming the reliability of the proposed method for the biological data analysis. In the last part of the project the proposed correlation approach was applied to design new small molecules as selective inhibitors of Cdc25 phosphatase, a well-known protein involved in carcinogenic processes. By means of this innovative approach, integrated with other classical ligand/structures-based techniques, it was possible to screen a large database of molecular structures, and to select the ones with optimal relationship with the focused target. In vitro antiproliferative and enzymatic inhibition assays of the selected compounds led to the identification of new structurally heterogeneous inhibitors of Cdc25 proteins and confirmed the results of the in silico analysis. CONCLUSIONS: Collectively, the obtained results showed that the correlation between protein expression pattern and chemosensitivity is an innovative, alternative, and effective method to identify new modulators for the selected targets. In contrast to traditional in silico methods, the proposed protocol allows for the selection of molecular structures with heterogeneous scaffolds, which are not strictly related to the binding sites and with chemical-physical features that may be more suitable for all the pathways involved in the overall mechanism. The biological assays further corroborate the robustness and the reliability of this new approach and encourage its application in the anticancer targeted drug discovery field