The importance of employing computational resources for the automation of drug discovery

Potential suppression of multidrug-resistance-associated protein 1 by coumarin derivatives: an insight from molecular docking and MD simulation studies

Human MRP1 protein plays a vital role in cancer multidrug resistance. Coumarins show promising pharmacological properties. Virtual screening, ADMET, molecular docking and molecular dynamics (MD) simulations were utilized as pharmacoinformatic tools to identify potential MRP1 inhibitors among coumarin derivatives. Using in silico ADMET, 50 hits were further investigated for their selectivity toward the nucleotide-binding domains (NBDs) of MRP1 using molecular docking. Accordingly, coumarin, its symmetrical ketone derivative Lig. No. 4, and Reversan were candidates for focused docking study with the NBDs domains compared with ATP. The result indicates that Lig. No. 4, with the best binding score, interacts with NBDs via hydrogen bonds with residues: GLN713, LYS684, GLY683, CYS682 in NBD1, and GLY1432, GLY771, SER769 and GLN1374 in NBD2, which mostly overlap with ATP binding residues. Moreover, doxorubicin (Doxo) was docked to the transmembrane domains (TMDs) active site of MRP1. Doxo interaction with TMDs was subjected to MD simulation in the NBDs free and occupied with Lig. No. 4 states. The results showed that Doxo interacts more strongly with TMD residues in inward facing feature of TMDs helices. However, when Lig. No. 4 exists in NBDs, Doxo interactions are different, and TMD helices show more outward-facing conformation. This result may suggest a partial competitive inhibition mechanism for the Lig. No. 4 on MRP1 compared with ATP. So, it may inhibit active complex formation by interfering with ATP entrance to NBDs and locking MRP1 conformation in outward-facing mode. This study suggests a valuable coumarin derivative that can be further investigated for potent MRP1 inhibitors.Communicated by Ramaswamy H. Sarma.

Investigation on the mechanisms by which the herbal remedies induce anti-prostate cancer activity: uncovering the most practical natural compound

Prostate cancer (PCa) is one of the most reported cancers among men worldwide. Targeting the essential proteins associated with PCa could be a promising method for cancer treatment. Traditional and herbal remedies (HRs) are the most practical approaches for PCa treatment. Here, the proteins and enzymes associated with PCa were determined based on the information obtained from the DisGeNET database. The proteins with a gene-disease association (GDA) score greater than 0.7 and the genes that have a disease specificity index (DSI) = 1 were selected as the target proteins. 28 HRs with anti-PCa activity as a traditional treatment for PCa were chosen as potential bioactive compounds. More than 500 compound-protein complexes were screened to find the top-ranked bioactives. The results were further evaluated using the molecular dynamics (MD) simulation and binding free energy calculations. The outcomes revealed that procyanidin B2 3,3'-di-O-gallate (B2G2), the most active ingredient of grape seed extract (GSE), can act as an agonist for PTEN. PTEN has a key role in suppressing PCa cells by applying phosphatase activity and inhibiting cell proliferation. B2G2 exhibited a considerable binding affinity to PTEN (11.643 kcal/mol). The MD results indicated that B2G2 could stabilize the key residues of the phosphatase domain of PTEN and increase its activity. Based on the obtained results, the active ingredient of GSE, B2G2, could play an agonist role and effectively increase the phosphatase activity of PTEN. The grape seed extract is a useful nutrition that can be used in men's diets to inhibit PCa in their bodies.Communicated by Ramaswamy H. Sarma.

Augmenting DMTA using predictive AI modelling at AstraZeneca

Design-Make-Test-Analyse (DMTA) is the discovery cycle through which molecules are designed, synthesised, and assayed to produce data that in turn are analysed to inform the next iteration. The process is repeated until viable drug candidates are identified, often requiring many cycles before reaching a sweet spot. The advent of artificial intelligence (AI) and cloud computing presents an opportunity to innovate drug discovery to reduce the number of cycles needed to yield a candidate. Here, we present the Predictive Insight Platform (PIP), a cloud-native modelling platform developed at AstraZeneca. The impact of PIP in each step of DMTA, as well as its architecture, integration, and usage, are discussed and used to provide insights into the future of drug discovery.

Exploring cyclin-dependent kinase inhibitors: a comprehensive study in search of CDK-6 inhibitors using a pharmacophore modelling and dynamics approach

Cancer prevalence and resistance issues in cancer treatment are a significant public health concern globally. Among the existing strategies in cancer therapy, targeting cyclin-dependent kinases (CDKs), especially CDK-6 is found to be one of the most promising targets, as this enzyme plays a pivotal role in cell cycle stages and cell proliferation. Cell proliferation is the characteristic feature of cancer giving rise to solid tumours. Our research focuses on creating novel compounds, specifically, pyrazolopyrimidine fused azetidinones, using a groundbreaking molecular hybridization approach to target CDK-6. Through computational investigations, ligand-based pharmacophore modelling, pharmacokinetic studies (ADMET), molecular docking, and dynamics simulations, we identified 18 promising compounds. The pharmacophore model featured one aromatic hydrophobic centre (F1: Aro/Hyd) and two H-bond acceptors (F2 and F3: Acc). Molecular docking results showed favourable binding energies (-6.5 to -8.0 kcal mol-1) and effective hydrogen bonds and hydrophobic interactions. The designed compounds demonstrated good ADMET profiles. Specifically, B6 and B18 showed low energy conformation (-7.8 kcal and -7.6 kcal), providing insights into target inhibition compared to the standard drug Palbociclib. Extensive molecular dynamics simulations confirmed the stability of these derivatives. Throughout the 100 ns simulation, the ligand-protein complexes maintained structural stability, with acceptable RMSD values. These compounds hold promise as potential leads in cancer therapy.

In silico design and cell-based evaluation of two dual anti breast cancer compounds targeting Bcl-2 and GPER

According to WHO statistics, breast cancer (BC) disease represents about 2.3 million diagnosed and 685,000 deaths globally. Regarding histological classification of BC, the Estrogen (ER) and Progesterone (PR) receptors negative-expression cancer, named Triple-Negative BC (TNBC), represents the most aggressive type of this disease, making it a challenge for drug discovery. In this context, our research group, applying a well-established Virtual Screening (VS) protocol, in addition to docking and molecular dynamics simulations studies, yielded two ligands identified as 6 and 37 which were chemically synthesized and evaluated on MCF-7 and MDA-MB-231 cancer cell lines. Strikingly, 37 assayed on MDA-MB-231 (a TNBC cell model) depicted an outstanding value of 18.66 μM much lower than 65.67 μM yielded by Gossypol Bcl-2 inhibitor whose main disadvantage is to produce multiple toxic effects. Highlighted above, enforce the premise of the computational tools to find new therapeutic options against the most aggressive forms of breast cancer, as the results herein showed.

Computational investigations on the dynamic binding effect of molecular tweezer CLR01 toward intrinsically disordered HIV-1 Nef

Intrinsically disordered proteins (IDPs) are highly flexible molecules that undergo disorder to order transition through their interaction with other molecules. IDPs play a vital role in several biological processes ranging from molecular recognition to several human diseases through the protein-protein interaction. The dynamic flexibility of IDPs and their implications in several human diseases enable these molecules to serve as novel therapeutic targets. However, the challenging task is to develop novel drugs against IDPs because of their lack of stable structures and the nature of high conformational flexibility. In this study, we have calculated the dynamic binding effect of the supramolecular tweezer CLR01 against the intrinsically disordered HIV-1 Nef by employing molecular docking and dynamics simulation approaches. From docking results, we predicted the strong binding affinity of the tweezer with the target residues of Nef. The docking results were further validated from the molecular dynamics simulation studies confirming the conformational stability of Nef upon tweezer binding. These findings provide useful insights into the development of potent inhibitors for targeting Nef protein functions.

Molecular modeling and LC-MS-based metabolomics of a glutamine-valproic acid (Gln-VPA) derivative on HeLa cells

Glutaminase plays an important role in carcinogenesis and cancer cell growth. This biological target is interesting against cancer cells. Therefore, in this work, in silico [docking and molecular dynamics (MD) simulations] and in vitro methods (antiproliferative and LC-MS metabolomics) were employed to assay a hybrid compound derived from glutamine and valproic acid (Gln-VPA), which was compared with 6-diazo-5-oxo-L-norleucine (DON, a glutaminase inhibitor) and VPA (contained in Gln-VPA structure). Docking results from some snapshots retrieved from MD simulations show that glutaminase recognized Gln-VPA and DON. Additionally, Gln-VPA showed antiproliferative effects in HeLa cells and inhibited glutaminase activity. Finally, the LC-MS-based metabolomics studies on HeLa cells treated with either Gln-VPA (IC₆₀ = 8 mM) or DON (IC₅₀ = 3.5 mM) show different metabolomics behaviors, suggesting that they modulate different biological targets of the cell death mechanism. In conclusion, Gln-VPA is capable of interfering with more than one pharmacological target of cancer, making it an interesting drug that can be used to avoid multitherapy of classic anticancer drugs.

Structural dynamics of inosine triphosphate pyrophosphatase (ITPA) protein and two clinically relevant mutants: molecular dynamics simulations

The inosine triphosphate pyrophosphatase (ITPA) protein is responsible for removing noncanonical purine nucleoside triphosphates from intracellular nucleotide pools. Absence of ITPA results in genomic instability and increased levels of inosine in DNA and RNA. The proline to threonine substitution at position 32 (P32T) affects roughly 15% of the global population and can modulate treatment outcomes for cancer, lupus, and hepatitis C patients. The substitution of arginine with cysteine at position 178 (R178C) is extremely uncommon and has only been reported in a small cohort of early infantile encephalopathy patients suggesting that a functional ITPA protein is required for life in humans. Here we present molecular dynamic simulations that describe the structure and dynamics of the wild-type ITPA homodimer and two of its clinically relevant mutants, P32T and R178C. The simulation results indicate that both the P32T and R178C mutations alter the structure and dynamic properties of the protein and provide a possible explanation of the experimentally observed effect of the mutations on ITPA activity. Specifically, the mutations increased the overall flexibility of the protein and changed the dominant collective motions of the top lobe as well as the helix 2 of the lower lobe. Moreover, we have identified key active-site residues that are classified as essential or intermediate for inosine triphosphate (ITP) hydrolyzing activity based on their hydrogen bond occupancy. Here we also present biochemical data indicating that the R178C mutant has very low ITP hydrolyzing activity.Communicated by Ramaswamy H. Sarma.

Computational Study of the Binding Modes of Diverse DPN Analogues on Estrogen Receptors (ER) and the Biological Evaluation of a New Potential Antiestrogenic Ligand

Estrogen (17β-estradiol) is essential for normal growth and differentiation in the mammary gland. In the last three decades, previous investigations have revealed that Estrogen Receptor Alpha (ERα) plays a critical role in breast cancer. More recently, observations regarding the widespread expression of ERβ-like proteins in normal and neoplastic mammary tissues have suggested that ERβ is also involved in the mentioned pathology. Design of new drugs both steroidal and nonsteroidal that target any of these receptors represents a promise to treat breast cancer although it remains a challenge due to the sequence similarity between their catalytic domains. In this work, we propose a new set of compounds that could effectively target the estrogen receptors ERα and ERβ. These ligands were designed based on the chemical structure of the ERβ-selective agonist Diarylpropionitrile (DPN). The designed ligands were submitted to in silico ADMET studies, yielding in a filtered list of ligands that showed better drug-like properties. Molecular dynamics simulations of both estrogen receptors and docking analysis were carried-out employing the designed compounds, from which two were chosen due to their promising characteristics retrieved from theoretical results (docking analysis or targeting receptor predictions). They were chemically synthetized and during the process, two precursor ligands were also obtained. These four ligands were subjected to biological studies from which it could be detected that compound mol60b dislplayed inhibitory activity and its ability to activate the transcription via an estrogenic mechanism of action was also determined. Interestinly, this observation can be related to theoretical binding free energy calculations, where the complex: ERβ-mol60b showed the highest energy ΔGbind value in comparison to others.

Selection of a GPER1 Ligand via Ligand-based Virtual Screening Coupled to Molecular Dynamics Simulations and Its Anti-proliferative Effects on Breast Cancer Cells

BACKGROUND

Recent reports have demonstrated the role of the G Protein-Coupled Estrogen Receptor 1 (GPER1) on the proliferation of breast cancer. The coupling of GPER1 to estrogen triggers cellular signaling pathways related to cell proliferation.

OBJECTIVE

Develop new therapeutic strategies against breast cancer.

METHOD

We performed in silico studies to explore the binding mechanism of a set of G15 /G1 analogue compounds. We included a carboxyl group instead of the acetyl group from G1 to form amides with several moieties to increase affinity on GPER1. The designed ligands were submitted to ligand-based and structure-based virtual screening to get insights into the binding mechanism of the best designed compound and phenol red on GPER1.

RESULTS

According to the in silico studies, the best molecule was named G1-PABA ((3aS,4R,9bR)-4-(6- bromobenzo[d][1,3]dioxol-5-yl)-3a,4,5,9b-tetrahydro-3H-cyclopenta[c]quinoline-8-carboxylic acid). It was synthesized and assayed in vitro in breast cancer (MCF-7 and MDA-MB-231) and normal (MCF-10A) cell lines. Experimental studies showed that the target compound was able to decrease cell proliferation, IC50 values of 15.93 µM, 52.92 µM and 32.45 µM in the MCF-7, MDA-MB-231 and MCF-10A cell lines, respectively, after 72 h of treatment. The compound showed better IC50 values without phenol red, suggesting that phenol red interfere with the G1-PABA action at GPER1, as observed through in silico studies, which is present in MCF-7 cells according to PCR studies and explains the cell proliferation effects.

CONCLUSION

Concentration-dependent inhibition of cell proliferation occurred with G1-PABA in the assayed cell lines and could be due to its action on GPER1.

Structural and biological overview of Boron-containing amino acids in the medicinal chemistry field

Amino acids are the basic structural units of proteins as well as the precursors of many compounds with biological activity. The addition of boron reportedly induces changes in the chemical-biological profile of amino acids.

METHODS

We compiled information on the biological effect of some compounds and discuss the structure-activity relationship of the addition of boron. The specific focus presently is on borinic derivatives of α-amino acids, the specific changes in biological activity caused by the addition of a boron-containing moiety, and the identification of some attractive compounds for testing as potential new drugs.

RESULTS

Borinic derivatives of α-amino acids have been widely synthesized and tested as potential new therapeutic tools. The B-N (1.65 A°) or B-C (1.61 A°) or B-O (1.50 A°) bond is often key for the stability at different pHs and temperatures and activity of these compounds. The chemical features of synthesized derivatives, such as the specific moieties and the logP, polarizability and position of the boron atom are clearly linked to their pharmacodynamic and pharmacokinetic profiles. Some mechanisms of action have been suggested or demonstrated, while those responsible for other effects remain unknown.

CONCLUSION

The increasing number of synthetic borinic derivatives of α-amino acids as well as the recently reported crystal structures are providing new insights into the stability of these compounds at different pHs and temperatures, their interactions on drug targets, and the ring formation of five-membered heterocycles. Further research is required to clarify the ways to achieve specific synthesis, the mechanisms involved in the observed biological effect, and the toxicological profile of this type of boron-containing compounds (BCCs).

ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database

Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main reason for R&D failures is the efficacy and safety deficiencies which are related largely to absorption, distribution, metabolism and excretion (ADME) properties and various toxicities (T). Therefore, rapid ADMET evaluation is urgently needed to minimize failures in the drug discovery process. Here, we developed a web-based platform called ADMETlab for systematic ADMET evaluation of chemicals based on a comprehensively collected ADMET database consisting of 288,967 entries. Four function modules in the platform enable users to conveniently perform six types of drug-likeness analysis (five rules and one prediction model), 31 ADMET endpoints prediction (basic property: 3, absorption: 6, distribution: 3, metabolism: 10, elimination: 2, toxicity: 7), systematic evaluation and database/similarity searching. We believe that this web platform will hopefully facilitate the drug discovery process by enabling early drug-likeness evaluation, rapid ADMET virtual screening or filtering and prioritization of chemical structures. The ADMETlab web platform is designed based on the Django framework in Python, and is freely accessible at http://admet.scbdd.com/ .

Design and synthesis of an indol derivative as antibacterial agent against Staphylococcus aureus

Several indole derivatives with antibacterial activity have been prepared using different protocols; however, some require special reagents and conditions. The aim of this study involved the synthesis of some indole derivatives using estrone and OTBS-estrone as chemical tools. The synthesis of the indole derivatives involves reactions such as follows: (1) synthesis of two indol derivatives (4 or 5) by reaction of estrone or OTBS-estrone with phenylhydrazine in medium acid; (2) reaction of 4 or 5 with 6-cloro-1-hexyne in medium basic to form two hexynyl-indol (7 or 8); (3) preparation of indol-propargylic alcohol derivatives (10 or 11) by reaction of benzaldehyde with 7 or 8 in medium basic; (4) synthesis of indol-aldehydes (12 or 13) via oxidation of 10 or 11 with DMSO; (5) synthesis of indeno-indol-carbaldehyde (15 or 16) via alkynylation/cyclization of 12 or 13 with hexyne in presence of copper(II); (6) preparation indeno-indol-carbaldehyde complex (19 or 20) via alkynylation/cyclization of 12 or 13 with 1-(hex-5-yn-1-yl)-2-phenyl-1H-imidazole. The antibacterial effect exerted by the indol-steroid derivatives against Streptococcus pneumoniae and Staphylococcus aureus bacteria was evaluated using dilution method and the minimum inhibitory concentration (MIC). The results showed that only the compound 19 inhibit the growth bacterial of S. aureus. In conclusion, these data indicate that antibacterial activity of 19 can be due mainly to functional groups involved in the chemical structure in comparison with the compounds studied.

Design and synthesis of a new steroid-macrocyclic derivative with biological activity

The aims of this study were to evaluate the positive inotropic effect of a new macrocyclic derivative (compound 11) and characterize the molecular mechanism involved in its biological activity. The first step was achieved by synthesis of a macrocyclic derivative involving a series of reactions for the preparation of several steroid derivatives such as (a) steroid-pyrimidinone (3 and 4), (b) steroid-amino (5), (c) steroid-imino (6), (d) ester-steroid (7 and 8), and (e) amido-steroid (9 and 10). Finally, 11 was prepared by removing the tert-butyldimethylsilane fragment of 10. The biological activity of compounds on perfusion pressure and vascular resistance was evaluated on isolated rat heart using the Langendorff model. The inotropic activity of 11 was evaluated in presence of prazosin, metoprolol, indomethacin, nifedipine, and flutamide to characterize its molecular mechanism. Theoretical experiments were carried out with a Docking model, to assess potential interactions of androgen receptor with 11. The results showed that only this macrocyclic derivative exerts changes on perfusion pressure and vascular resistance translated as the positive inotropic effect, and this effect was blocked with flutamide; these data indicate that the positive inotropic activity induced by this macrocyclic derivative was via androgen receptor activation. The theoretical results indicated that the interaction of the macrocyclic derivative with the androgen receptor involves several amino acid residues such as Leu704, Asn705, Met780, Cys784, Met749, Leu762, Phe764, Ser778, and Met787. In conclusion, all these data suggest that the positive inotropic activity of the macrocyclic derivative may depend on its chemical structure.