TumFlow: An AI Model for Predicting New Anticancer Molecules.

Melanoma is the fifth most common cancer in the United States. Conventional drug discovery methods are inherently time-consuming and costly, which imposes significant limitations. However, the advent of Artificial Intelligence (AI) has opened up new possibilities for simulating and evaluating numerous drug candidates, thereby mitigating the requisite time and resources. In this context, normalizing flow models by employing machine learning techniques to create new molecular structures holds promise for accelerating the discovery of effective anticancer therapies. This manuscript introduces TumFlow, a novel AI model designed to generate new molecular entities with potential therapeutic value in cancer treatment. It has been trained on the NCI-60 dataset, encompassing thousands of molecules tested across 60 tumour cell lines, with an emphasis on the melanoma SK-MEL-28 cell line. The model successfully generated new molecules with predicted improved efficacy in inhibiting tumour growth while being synthetically feasible. This represents a significant advancement over conventional generative models, which often produce molecules that are challenging or impossible to synthesize. Furthermore, TumFlow has also been utilized to optimize molecules known for their efficacy in clinical melanoma treatments. This led to the creation of novel molecules with a predicted enhanced likelihood of effectiveness against melanoma, currently undocumented on PubChem.

Structural Investigations on 2-Amidobenzimidazole Derivatives as New Inhibitors of Protein Kinase CK1 Delta.

Protein kinase CK1δ (CK1δ) is a serine-threonine/kinase that modulates different physiological processes, including the cell cycle, DNA repair, and apoptosis. CK1δ overexpression, and the consequent hyperphosphorylation of specific proteins, can lead to sleep disorders, cancer, and neurodegenerative diseases. CK1δ inhibitors showed anticancer properties as well as neuroprotective effects in cellular and animal models of Parkinson's and Alzheimer's diseases and amyotrophic lateral sclerosis. To obtain new ATP-competitive CK1δ inhibitors, three sets of benzimidazole-2-amino derivatives were synthesized (1-32), bearing different substituents on the fused benzo ring (R) and diverse pyrazole-containing acyl moieties on the 2-amino group. The best-performing derivatives were those featuring the (1H-pyrazol-3-yl)-acetyl moiety on the benzimidazol-2-amino scaffold (13-32), which showed CK1δ inhibitor activity in the low micromolar range. Among the R substituents, 5-cyano was the most advantageous, leading to a compound endowed with nanomolar potency (23, IC50 = 98.6 nM). Molecular docking and dynamics studies were performed to point out the inhibitor-kinase interactions.

Thermal titration molecular dynamics (TTMD): shedding light on the stability of RNA-small molecule complexes.

Ribonucleic acids are gradually becoming relevant players among putative drug targets, thanks to the increasing amount of structural data exploitable for the rational design of selective and potent binders that can modulate their activity. Mainly, this information allows employing different computational techniques for predicting how well would a ribonucleic-targeting agent fit within the active site of its target macromolecule. Due to some intrinsic peculiarities of complexes involving nucleic acids, such as structural plasticity, surface charge distribution, and solvent-mediated interactions, the application of routinely adopted methodologies like molecular docking is challenged by scoring inaccuracies, while more physically rigorous methods such as molecular dynamics require long simulation times which hamper their conformational sampling capabilities. In the present work, we present the first application of Thermal Titration Molecular Dynamics (TTMD), a recently developed method for the qualitative estimation of unbinding kinetics, to characterize RNA-ligand complexes. In this article, we explored its applicability as a post-docking refinement tool on RNA in complex with small molecules, highlighting the capability of this method to identify the native binding mode among a set of decoys across various pharmaceutically relevant test cases.

2-Pentadecyl-2-oxazoline inhibits lipopolysaccharide-induced microglia activation interfering with TLR4 signaling.

AIM: 2-Pentadecyl-2-oxazoline (PEA-OXA), the oxazoline derivative of N-palmitoylethanolamine, exerts anti-inflammatory activity; however, very little is known about the molecular mechanisms underlying this effect. Here, we tested the anti-neuroinflammatory effect of PEA-OXA in primary microglia and we also investigated the possible interaction of the molecule with the Toll-like receptor 4 (TLR4)-myeloid differentiation protein-2 (MD-2) complex. MAIN METHODS: The anti-inflammatory effect of PEA-OXA was analyzed by measuring the expression and release of pro-inflammatory mediators in primary microglia by real-time PCR and ELISA, respectively. The effect of PEA-OXA on the activation of TLR4 signaling was assessed using two stably TLR4-transfected cell lines (i.e., HEK-293 and Ba/F3 cells). Finally, the putative binding mode of PEA-OXA to TLR4-MD-2 was investigated by molecular docking simulations. KEY FINDINGS: Treatment with PEA-OXA resulted in the following effects: (i) it down-regulated gene expression of several pro-inflammatory molecules and the secretion of pro-inflammatory cytokines in LPS stimulated microglia cells; (ii) it did not prevent microglia activation after stimulation with TLR2 ligands; (iii) it prevented TLR4/NF-κB activation triggered by LPS in HEK-Blue™ hTLR4 cells; and (iv) it interfered with the binding of LPS to TLR4-MD-2 complex. Furthermore, molecular docking studies suggested that PEA-OXA could bind MD-2 with a 1:3 (MD-2/PEA-OXA) stoichiometry. CONCLUSION: We show for the first time that the anti-neuroinflammatory effect of PEA-OXA involves its activity against TLR4 signaling, making this molecule a valuable tool for the development of new compounds directed to control neuroinflammation via inhibiting TLR4 signaling.

Pyrazolo-triazolo-pyrimidine Scaffold as a Molecular Passepartout for the Pan-Recognition of Human Adenosine Receptors.

Adenosine receptors are largely distributed in our organism and are promising therapeutic targets for the treatment of many pathologies. In this perspective, investigating the structural features of the ligands leading to affinity and/or selectivity is of great interest. In this work, we have focused on a small series of pyrazolo-triazolo-pyrimidine antagonists substituted in positions 2, 5, and N8, where bulky acyl moieties at the N5 position and small alkyl groups at the N8 position are associated with affinity and selectivity at the A3 adenosine receptor even if a good affinity toward the A2B adenosine receptor has also been observed. Conversely, a free amino function at the 5 position induces high affinity at the A2A and A1 receptors with selectivity vs. the A3 subtype. A molecular modeling study suggests that differences in affinity toward A1, A2A, and A3 receptors could be ascribed to two residues: one in the EL2, E168 in human A2A/E172 in human A1, that is occupied by the hydrophobic residue V169 in the human A3 receptor; and the other in TM6, occupied by H250/H251 in human A2A and A1 receptors and by a less bulky S247 in the A3 receptor. In the end, these findings could help to design new subtype-selective adenosine receptor ligands.

A comprehensive study of SARS-CoV-2 main protease (Mpro) inhibitor-resistant mutants selected in a VSV-based system.

Nirmatrelvir was the first protease inhibitor (PI) specifically developed against the SARS-CoV-2 main protease (3CLpro/Mpro) and licensed for clinical use. As SARS-CoV-2 continues to spread, variants resistant to nirmatrelvir and other currently available treatments are likely to arise. This study aimed to identify and characterize mutations that confer resistance to nirmatrelvir. To safely generate Mpro resistance mutations, we passaged a previously developed, chimeric vesicular stomatitis virus (VSV-Mpro) with increasing, yet suboptimal concentrations of nirmatrelvir. Using Wuhan-1 and Omicron Mpro variants, we selected a large set of mutants. Some mutations are frequently present in GISAID, suggesting their relevance in SARS-CoV-2. The resistance phenotype of a subset of mutations was characterized against clinically available PIs (nirmatrelvir and ensitrelvir) with cell-based and biochemical assays. Moreover, we showed the putative molecular mechanism of resistance based on in silico molecular modelling. These findings have implications on the development of future generation Mpro inhibitors, will help to understand SARS-CoV-2 protease-inhibitor-resistance mechanisms and show the relevance of specific mutations in the clinic, thereby informing treatment decisions.

[1,2,4]Triazolo[1,5-c]pyrimidines as Tools to Investigate A3 Adenosine Receptors in Cancer Cell Lines.

The A3 adenosine receptor is an interesting target whose role in cancer is controversial. In this work, a structural investigation at the 2-position of the [1,2,4]triazolo[1,5-c]pyrimidine nucleus was performed, finding new potent and selective A3 adenosine receptor antagonists such as the ethyl 2-(4-methoxyphenyl)-5-(methylamino)-[1,2,4]triazolo[1,5-c]pyrimidine-8-carboxylate (20, DZ123) that showed a Ki value of 0.47 nM and an exceptional selectivity profile over the other adenosine receptor subtypes. Computational studies were performed to rationalize the affinity and the selectivity profile of the tested compounds at the A3 adenosine receptor and the A1 and A2A adenosine receptors. Compound 20 was tested on both A3 adenosine receptor positive cell lines (CHO-A3 AR transfected, THP1 and HCT16) and on A3 negative cancer cell lines, showing no effect in the latter and a pro-proliferative effect at a low concentration in the former. These interesting results pave the way to further investigation on both the mechanism involved and potential therapeutic applications.

Mediterranean fish communities are struggling to adapt to global warming. Evidence from the western coast of Italy.

Climate change has significant impacts on marine ecosystems, resulting in disruptions in biological interactions, shifts in community composition, and changes in the physiology of fish and other marine organisms. In this study conducted in the central Mediterranean Sea, the mean temperature of the catch (MTC) was employed as an indicator to investigate the climatological factors influencing the fish community. The MTC, which utilizes species-preferred temperatures, was calculated using bottom temperature (BT) data weighted against scientific catches. The estimated MTC increasing rates were 0.01 °C year-1 for the entire community, 0.017 °C year-1 for the shelf break, and 0.004 °C year-1 for the continental slope assemblage. We found that MTC is increasing at a lower rate compared to BT, suggesting a progressive under-adaptation of the fish community that seems not fully able to keep up with the ongoing pace of warming. The study identified sea surface temperature and bottom temperature as key drivers of changes in fish community composition. Notably, the fish community composition exhibited drastic changes over the studied period, and we suggest that the MTC can be a useful index to monitor such changes within the context of the EU's climate change adaptation strategy.

A small molecule targeting the interaction between human papillomavirus E7 oncoprotein and cellular phosphatase PTPN14 exerts antitumoral activity in cervical cancer cells.

Human papillomavirus (HPV)-induced cancers still represent a major health issue for worldwide population and lack specific therapeutic regimens. Despite substantial advancements in anti-HPV vaccination, the incidence of HPV-related cancers remains high, thus there is an urgent need for specific anti-HPV drugs. The HPV E7 oncoprotein is a major driver of carcinogenesis that acts by inducing the degradation of several host factors. A target is represented by the cellular phosphatase PTPN14 and its E7-mediated degradation was shown to be crucial in HPV oncogenesis. Here, by exploiting the crystal structure of E7 bound to PTPN14, we performed an in silico screening of small-molecule compounds targeting the C-terminal CR3 domain of E7 involved in the interaction with PTPN14. We discovered a compound able to inhibit the E7/PTPN14 interaction in vitro and to rescue PTPN14 levels in cells, leading to a reduction in viability, proliferation, migration, and cancer-stem cell potential of HPV-positive cervical cancer cells. Mechanistically, as a consequence of PTPN14 rescue, treatment of cancer cells with this compound altered the Yes-associated protein (YAP) nuclear-cytoplasmic shuttling and downstream signaling. Notably, this compound was active against cervical cancer cells transformed by different high-risk (HR)-HPV genotypes indicating a potential broad-spectrum activity. Overall, our study reports the first-in-class inhibitor of E7/PTPN14 interaction and provides the proof-of-principle that pharmacological inhibition of this interaction by small-molecule compounds could be a feasible therapeutic strategy for the development of novel antitumoral drugs specific for HPV-associated cancers.

Molecular Modeling Unveils the Effective Interaction of B-RAF Inhibitors with Rare B-RAF Insertion Variants.

The Food and Drug Administration (FDA) has approved MAPK inhibitors as a treatment for melanoma patients carrying a mutation in codon V600 of the BRAF gene exclusively. However, BRAF mutations outside the V600 codon may occur in a small percentage of melanomas. Although these rare variants may cause B-RAF activation, their predictive response to B-RAF inhibitor treatments is still poorly understood. We exploited an integrated approach for mutation detection, tumor evolution tracking, and assessment of response to treatment in a metastatic melanoma patient carrying the rare p.T599dup B-RAF mutation. He was addressed to Dabrafenib/Trametinib targeted therapy, showing an initial dramatic response. In parallel, in-silico ligand-based homology modeling was set up and performed on this and an additional B-RAF rare variant (p.A598_T599insV) to unveil and justify the success of the B-RAF inhibitory activity of Dabrafenib, showing that it could adeptly bind both these variants in a similar manner to how it binds and inhibits the V600E mutant. These findings open up the possibility of broadening the spectrum of BRAF inhibitor-sensitive mutations beyond mutations at codon V600, suggesting that B-RAF V600 WT melanomas should undergo more specific investigations before ruling out the possibility of targeted therapy.

Fighting Antimicrobial Resistance: Insights on How the Staphylococcus aureus NorA Efflux Pump Recognizes 2-Phenylquinoline Inhibitors by Supervised Molecular Dynamics (SuMD) and Molecular Docking Simulations.

The superbug Staphylococcus aureus (S. aureus) exhibits several resistance mechanisms, including efflux pumps, that strongly contribute to antimicrobial resistance. In particular, the NorA efflux pump activity is associated with S. aureus resistance to fluoroquinolone antibiotics (e.g., ciprofloxacin) by promoting their active extrusion from cells. Thus, since efflux pump inhibitors (EPIs) are able to increase antibiotic concentrations in bacteria as well as restore their susceptibility to these agents, they represent a promising strategy to counteract bacterial resistance. Additionally, the very recent release of two NorA efflux pump cryo-electron microscopy (cryo-EM) structures in complex with synthetic antigen-binding fragments (Fabs) represents a real breakthrough in the study of S. aureus antibiotic resistance. In this scenario, supervised molecular dynamics (SuMD) and molecular docking experiments were combined to investigate for the first time the molecular mechanisms driving the interaction between NorA and efflux pump inhibitors (EPIs), with the ultimate goal of elucidating how the NorA efflux pump recognizes its inhibitors. The findings provide insights into the dynamic NorA-EPI intermolecular interactions and lay the groundwork for future drug discovery efforts aimed at the identification of novel molecules to fight antimicrobial resistance.

Correction: Bassani, D.; Moro, S. Past, Present, and Future Perspectives on Computer-Aided Drug Design Methodologies. Molecules 2023, 28, 3906.

In the published publication [...].

"Dual Anta-Inhibitors" of the A2A Adenosine Receptor and Casein Kinase CK1delta: Synthesis, Biological Evaluation, and Molecular Modeling Studies.

Based on a screening of a chemical library of A2A adenosine receptor (AR) antagonists, a series of di- and tri-substituted adenine derivatives were synthesized and tested for their ability to inhibit the activity of the enzyme casein kinase 1 delta (CK1δ) and to bind adenosine receptors (ARs). Some derivatives, here called "dual anta-inhibitors", demonstrated good CK1δ inhibitory activity combined with a high binding affinity, especially for the A2AAR. The N6-methyl-(2-benzimidazolyl)-2-dimethyamino-9-cyclopentyladenine (17, IC50 = 0.59 µM and KiA2A = 0.076 µM) showed the best balance of A2AAR affinity and CK1δ inhibitory activity. Computational studies were performed to simulate, at the molecular level, the protein-ligand interactions involving the compounds of our series. Hence, the dual anta-inhibitor 17 could be considered the lead compound of new therapeutic agents endowed with synergistic effects for the treatment of chronic neurodegenerative and cancer diseases.

Structural Manipulations of Marine Natural Products Inspire a New Library of 3-Amino-1,2,4-Triazine PDK Inhibitors Endowed with Antitumor Activity in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the main aggressive types of cancer, characterized by late prognosis and drug resistance. Among the main factors sustaining PDAC progression, the alteration of cell metabolism has emerged to have a key role in PDAC cell proliferation, invasion, and resistance to standard chemotherapeutic agents. Taking into account all these factors and the urgency in evaluating novel options to treat PDAC, in the present work we reported the synthesis of a new series of indolyl-7-azaindolyl triazine compounds inspired by marine bis-indolyl alkaloids. We first assessed the ability of the new triazine compounds to inhibit the enzymatic activity of pyruvate dehydrogenase kinases (PDKs). The results showed that most of derivatives totally inhibit PDK1 and PDK4. Molecular docking analysis was executed to predict the possible binding mode of these derivatives using ligand-based homology modeling technique. Evaluation of the capability of new triazines to inhibit the cell growth in 2D and 3D KRAS-wild-type (BxPC-3) and KRAS-mutant (PSN-1) PDAC cell line, was carried out. The results showed the capacity of the new derivatives to reduce cell growth with a major selectivity against KRAS-mutant PDAC PSN-1 on both cell models. These data demonstrated that the new triazine derivatives target PDK1 enzymatic activity and exhibit cytotoxic effects on 2D and 3D PDAC cell models, thus encouraging further structure manipulation for analogs development against PDAC.

Past, Present, and Future Perspectives on Computer-Aided Drug Design Methodologies.

The application of computational approaches in drug discovery has been consolidated in the last decades. These families of techniques are usually grouped under the common name of "computer-aided drug design" (CADD), and they now constitute one of the pillars in the pharmaceutical discovery pipelines in many academic and industrial environments. Their implementation has been demonstrated to tremendously improve the speed of the early discovery steps, allowing for the proficient and rational choice of proper compounds for a desired therapeutic need among the extreme vastness of the drug-like chemical space. Moreover, the application of CADD approaches allows the rationalization of biochemical and interactive processes of pharmaceutical interest at the molecular level. Because of this, computational tools are now extensively used also in the field of rational 3D design and optimization of chemical entities starting from the structural information of the targets, which can be experimentally resolved or can also be obtained with other computer-based techniques. In this work, we revised the state-of-the-art computer-aided drug design methods, focusing on their application in different scenarios of pharmaceutical and biological interest, not only highlighting their great potential and their benefits, but also discussing their actual limitations and eventual weaknesses. This work can be considered a brief overview of computational methods for drug discovery.

Are Two Riboses Better Than One? The Case of the Recognition and Activation of Adenosine Receptors.

Traditionally, molecular recognition between the orthosteric site of adenosine receptors and their endogenous ligand occurs with a 1 : 1 stoichiometry. Inspired by previous mechanistic insights derived from supervised molecular dynamics (SuMD) simulations, which suggested an alternative 2 : 1 binding stoichiometry, we synthesized BRA1, a bis-ribosyl adenosine derivative, tested its ability to bind to and activate members of the adenosine receptor family, and rationalized its activity through molecular modeling.

Targeting the I7L Protease: A Rational Design for Anti-Monkeypox Drugs?

The latest monkeypox virus outbreak in 2022 showcased the potential threat of this viral zoonosis to public health. The lack of specific treatments against this infection and the success of viral protease inhibitors-based treatments against HIV, Hepatitis C, and SARS-CoV-2, brought the monkeypox virus I7L protease under the spotlight as a potential target for the development of specific and compelling drugs against this emerging disease. In the present work, the structure of the monkeypox virus I7L protease was modeled and thoroughly characterized through a dedicated computational study. Furthermore, structural information gathered in the first part of the study was exploited to virtually screen the DrugBank database, consisting of drugs approved by the Food and Drug Administration (FDA) and clinical-stage drug candidates, in search for readily repurposable compounds with similar binding features as TTP-6171, the only non-covalent I7L protease inhibitor reported in the literature. The virtual screening resulted in the identification of 14 potential inhibitors of the monkeypox I7L protease. Finally, based on data collected within the present work, some considerations on developing allosteric modulators of the I7L protease are reported.

The E2F4/p130 Repressor Complex Cooperates with Oncogenic ΔNp73α To Inhibit Gene Expression in Human Papillomavirus 38 E6/E7-Transformed Keratinocytes and in Cancer Cells.

Tumor suppressor p53 and its related proteins, p63 and p73, can be synthesized as multiple isoforms lacking part of the N- or C-terminal regions. Specifically, high expression of the ΔNp73α isoform is notoriously associated with various human malignancies characterized by poor prognosis. This isoform is also accumulated by oncogenic viruses, such as Epstein-Barr virus (EBV), as well as genus beta human papillomaviruses (HPV) that appear to be involved in carcinogenesis. To gain additional insight into ΔNp73α mechanisms, we have performed proteomics analyses using human keratinocytes transformed by the E6 and E7 proteins of the beta-HPV type 38 virus as an experimental model (38HK). We find that ΔNp73α associates with the E2F4/p130 repressor complex through a direct interaction with E2F4. This interaction is favored by the N-terminal truncation of p73 characteristic of ΔNp73 isoforms. Moreover, it is independent of the C-terminal splicing status, suggesting that it could represent a general feature of ΔNp73 isoforms (α, ß, γ, δ, ε, ζ, θ, η, and η1). We show that the ΔNp73α-E2F4/p130 complex inhibits the expression of specific genes, including genes encoding for negative regulators of proliferation, both in 38HK and in HPV-negative cancer-derived cell lines. Such genes are not inhibited by E2F4/p130 in primary keratinocytes lacking ΔNp73α, indicating that the interaction with ΔNp73α rewires the E2F4 transcriptional program. In conclusion, we have identified and characterized a novel transcriptional regulatory complex with potential implications in oncogenesis. IMPORTANCE The TP53 gene is mutated in about 50% of human cancers. In contrast, the TP63 and TP73 genes are rarely mutated but rather expressed as ΔNp63 and ΔNp73 isoforms in a wide range of malignancies, where they act as p53 antagonists. Accumulation of ΔNp63 and ΔNp73, which is associated with chemoresistance, can result from infection by oncogenic viruses such as EBV or HPV. Our study focuses on the highly carcinogenic ΔNp73α isoform and uses a viral model of cellular transformation. We unveil a physical interaction between ΔNp73α and the E2F4/p130 complex involved in cell cycle control, which rewires the E2F4/p130 transcriptional program. Our work shows that ΔNp73 isoforms can establish interactions with proteins that do not bind to the TAp73α tumor suppressor. This situation is analogous to the gain-of-function interactions of p53 mutants supporting cellular proliferation.

Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics.

Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19.

Drugging the Undruggable Trypanosoma brucei Monothiol Glutaredoxin 1.

Trypanosoma brucei is a species of kinetoplastid causing sleeping sickness in humans and nagana in cows and horses. One of the peculiarities of this species of parasites is represented by their redox metabolism. One of the proteins involved in this redox machinery is the monothiol glutaredoxin 1 (1CGrx1) which is characterized by a unique disordered N-terminal extension exclusively conserved in trypanosomatids and other organisms. This region modulates the binding profile of the glutathione/trypanothione binding site, one of the functional regions of 1CGrx1. No endogenous ligands are known to bind this protein which does not present well-shaped binding sites, making it target particularly challenging to target. With the aim of targeting this peculiar system, we carried out two different screenings: (i) a fragment-based lead discovery campaign directed to the N-terminal as well as to the canonical binding site of 1CGrx1; (ii) a structure-based virtual screening directed to the 1CGrx1 canonical binding site. Here we report a small molecule that binds at the glutathione binding site in which the binding mode of the molecule was deeply investigated by Nuclear Magnetic Resonance (NMR). This compound represents an important step in the attempt to develop a novel strategy to interfere with the peculiar Trypanosoma Brucei redox system, making it possible to shed light on the perturbation of this biochemical machinery and eventually to novel therapeutic possibilities.