Pursuing the leadlikeness concept in pharmaceutical research

In-silico assessment of novel peptidomimetics inhibitor targeting STAT3 and STAT4 N-terminal domain dimerization: A comprehensive study using molecular docking, molecular dynamics simulation, and binding free energy analysis

Dysregulation in Janus kinase-Signal Transducer and Activation of Transcription (JAK-STAT) pathway is closely linked to various cancer types. The N-terminal domain (NTD) of STAT proteins, upon dimerization, assumes a multifaceted role with remarkable adaptability in mediating interactions between proteins. Consequently, the strategic targeting of the N-terminal domain of STATs has emerged as a promising tactic for disrupting dimerization and impeding the translocation of STAT proteins. In this study, we have deployed an integrated in-silico methodology to rationally design Peptidomimetic foldamers as inhibitors of the N-terminal domains of STAT3 and STAT4, with the objective of disrupting protein dimerization. Consequently, we have judiciously designed a series of peptidomimetics that encompass β3-amino acids, bearing side chains that mimic the residues within interface II of the dimeric structures of the NTDs. Employing molecular docking techniques; we have assessed the binding affinity of these designed peptidomimetics toward both the NTDs. Furthermore, we have conducted an evaluation of the stability and conformational alterations within the docked complexes over an extensive Molecular Dynamics, subsequently computing the binding free energy utilizing MM/PBSA calculations. Our findings unequivocally demonstrate that the peptidomimetic foldamers we have devised (Peptide-A, Peptide-B, and Peptide-C) exhibit a propensity to bind to and impede the dimerization process of the NTDs of both STAT3 and STAT4. These outcomes serve to underscore the potential of these meticulously designed peptidomimetics as potential candidates meriting further exploration in the realm of cancer prevention and management.

Do Molecular Fingerprints Identify Diverse Active Drugs in Large-Scale Virtual Screening? (No)

Computational approaches for small-molecule drug discovery now regularly scale to the consideration of libraries containing billions of candidate small molecules. One promising approach to increased the speed of evaluating billion-molecule libraries is to develop succinct representations of each molecule that enable the rapid identification of molecules with similar properties. Molecular fingerprints are thought to provide a mechanism for producing such representations. Here, we explore the utility of commonly used fingerprints in the context of predicting similar molecular activity. We show that fingerprint similarity provides little discriminative power between active and inactive molecules for a target protein based on a known active-while they may sometimes provide some enrichment for active molecules in a drug screen, a screened data set will still be dominated by inactive molecules. We also demonstrate that high-similarity actives appear to share a scaffold with the query active, meaning that they could more easily be identified by structural enumeration. Furthermore, even when limited to only active molecules, fingerprint similarity values do not correlate with compound potency. In sum, these results highlight the need for a new wave of molecular representations that will improve the capacity to detect biologically active molecules based on their similarity to other such molecules.

Unveiling the Potential of Ent-Kaurane Diterpenoids: Multifaceted Natural Products for Drug Discovery

Natural products hold immense potential for drug discovery, yet many remain unexplored in vast libraries and databases. In an attempt to fill this gap and meet the growing demand for effective drugs, this study delves into the promising world of ent-kaurane diterpenoids, a class of natural products with huge therapeutic potential. With a dataset of 570 ent-kaurane diterpenoids obtained from the literature, we conducted an in silico analysis, evaluating their physicochemical, pharmacokinetic, and toxicological properties with a focus on their therapeutic implications. Notably, these natural compounds exhibit drug-like properties, aligning closely with those of FDA-approved drugs, indicating a high potential for drug development. The ranges of the physicochemical parameters were as follows: molecular weights-288.47 to 626.82 g/mol; number of heavy atoms-21 to 44; the number of hydrogen bond donors and acceptors-0 to 8 and 1 to 11, respectively; the number of rotatable bonds-0 to 11; fraction Csp3-0.65 to 1; and TPSA-20.23 to 189.53 Ų. Additionally, the majority of these molecules display favorable safety profiles, with only 0.70%, 1.40%, 0.70%, and 46.49% exhibiting mutagenic, tumorigenic, reproduction-enhancing, and irritant properties, respectively. Importantly, ent-kaurane diterpenoids exhibit promising biopharmaceutical properties. Their average lipophilicity is optimal for drug absorption, while over 99% are water-soluble, facilitating delivery. Further, 96.5% and 28.20% of these molecules exhibited intestinal and brain bioavailability, expanding their therapeutic reach. The predicted pharmacological activities of these compounds encompass a diverse range, including anticancer, immunosuppressant, chemoprotective, anti-hepatic, hepatoprotectant, anti-inflammation, antihyperthyroidism, and anti-hepatitis activities. This multi-targeted profile highlights ent-kaurane diterpenoids as highly promising candidates for further drug discovery endeavors.

AM-18002, a derivative of natural anmindenol A, enhances radiosensitivity in mouse breast cancer cells

Natural anmindenol A isolated from the marine-derived bacteria Streptomyces sp. caused potent inhibition of inducible nitric oxide synthase without any significant cytotoxicity. This compound consists of a structurally unique 3,10-dialkylbenzofulvene skeleton. We previously synthesized and screened the novel derivatives of anmindenol A and identified AM-18002, an anmindenol A derivative, as a promising anticancer agent. The combination of AM-18002 and ionizing radiation (IR) improved anticancer effects, which were exerted by promoting apoptosis and inhibiting the proliferation of FM3A mouse breast cancer cells. AM-18002 increased the production of reactive oxygen species (ROS) and was more effective in inducing DNA damage. AM-18002 treatment was found to inhibit the expansion of myeloid-derived suppressor cells (MDSC), cancer cell migration and invasion, and STAT3 phosphorylation. The AM-18002 and IR combination synergistically induced cancer cell death, and AM-18002 acted as a potent anticancer agent by increasing ROS generation and blocking MDSC-mediated STAT3 activation in breast cancer cells.

Current progress in high-throughput screening for drug repurposing

High-throughput screening (HTS) is a simple, rapid and cost-effective solution to determine active candidates from large library of compounds. HTS is gaining attention from Pharmaceuticals and Biotechnology companies for accelerating their drug discovery programs. Conventional drug discovery program is time consuming and expensive. In contrast drug repurposing approach is cost-effective and increases speed of drug discovery as toxicity profile is already known. The present chapter highlight HTS technology including microplate, microfluidics, lab-on-chip, organ-on-chip for drug repurposing. The current chapter also highlights the application of HTS for bacterial infections and cancer.

Discovery of novel inhibitor via molecular dynamics simulations against D-alanyl-D-alanine carboxypeptidase of Enterobacter cloacae

Antibiotics resistance by bacterial pathogens is a major concern to public health worldwide resulting in high health care costs and rising mortality. Subtractive proteomics prioritized D-alanyl-D-alanine carboxypeptidas (DacB) enzyme from Enterobacter cloacae ATCC 13047 as a potential candidate for drugs designing to block pathogen cell wall biosynthesis. Virtual screening of an antibacterial library against the target unraveled a hit compound (2-[(1-methylsulfonylpiperidin-3-yl)methyl]-6-(1H-pyrazol-4-yl) pyrazine) showing high affinity and stability with the target. The N-methyl-N-propyl-methanesulfonamide of the compound is seen as a closed affinity towards domain involving strong hydrogen bonds with Ser41, Lys44, Ser285, and Asn287. The 4-methyl-1H-pyrazole is posed towards the open cavity of domain I and II and formed hydrophobic and hydrophilic contacts. The system is highly stable with average carbon-alpha deviations of 1.69 Å over trajectories of 400-ns. Three vital residues projected: Arg437, Arg438 and Leu400 from enzyme pocket via Radial distribution function (RDF) assay, which actively engaged the inhibitor. Further confirmation is done by estimating binding free energies, which confirms the very low delta energy of -7.24 kcal/mol in Generalized Born (GB) method and -7.4363 kcal/mol in Poisson-Boltzmann (PB) method. WaterSwap calculations were performed that revealed the energies highly converged, an agreement on good system stability. Lastly, three DacB mutants were created to investigate the role of functional active residues and a decline in binding affinity of the residues was noticed. These computational results provide a gateway for experimentalists to further confirm their efficacy both in-vitro and in-vivo.Communicated by Ramaswamy H. Sarma.

Molecular fragmentation as a crucial step in the AI-based drug development pathway

The AI-based small molecule drug discovery has become a significant trend at the intersection of computer science and life sciences. In the pursuit of novel compounds, fragment-based drug discovery has emerged as a novel approach. The Generative Pre-trained Transformers (GPT) model has showcased remarkable prowess across various domains, rooted in its pre-training and representation learning of fundamental linguistic units. Analogous to natural language, molecular encoding, as a form of chemical language, necessitates fragmentation aligned with specific chemical logic for accurate molecular encoding. This review provides a comprehensive overview of the current state of the art in molecular fragmentation. We systematically summarize the approaches and applications of various molecular fragmentation techniques, with special emphasis on the characteristics and scope of applicability of each technique, and discuss their applications. We also provide an outlook on the current development trends of molecular fragmentation techniques, including some potential research directions and challenges.

New lead compounds identification against KRas mediated cancers through pharmacophore-based virtual screening and in vitro assays

Cancer remains the leading cause of mortality and morbidity in the world, with 19.3 million new diagnoses and 10.1 million deaths in 2020. Cancer is caused due to mutations in proto-oncogenes and tumor-suppressor genes. Genetic analyses found that Ras (Rat sarcoma) is one of the most deregulated oncogenes in human cancers. The Ras oncogene family members including NRas (Neuroblastoma ras viral oncogene homolog), HRas (Harvey rat sarcoma) and KRas are involved in different types of human cancers. The mutant KRas is considered as the most frequent oncogene implicated in the development of lung, pancreatic and colon cancers. However, there is no efficient clinical drug even though it has been identified as an oncogene for 30 years. Therefore there is an emerging need to develop potent, new anticancer drugs. In this study, computer-aided drug designing approaches as well as experimental methods were employed to find new and potential anti-cancer drugs. The pharmacophore model was developed from an already known FDA approved anti-cancer drug Bortezomib using the software MOE. The validated pharmacophore model was then used to screen the in-house and commercially available databases. The pharmacophore-based virtual screening resulted in 26 and 86 hits from in-house and commercial databases respectively. Finally, 6/13 (in-house database) and 24/64 hits (commercial databases) were selected with different scaffolds having good interactions with the significant active residues of KRasG12D protein that were predicted as potent lead compounds. Finally, the results of pharmacophore-based virtual screening were further validated by molecular dynamics simulation analysis. The 6 hits of the in-house database were further evaluated experimentally. The experimental results showed that these compounds have good anti-cancer activity which validate the protocol of our in silico studies. KRasG12D protein is a very important anti-cancer target and potent inhibitors for this target are still not available, so small lead compound inhibitors were identified to inhibit the activity of this protein by blocking the GTP-binding pocket.Communicated by Ramaswamy H. Sarma.

Identification of small-molecule inhibitors against the interaction of RNA-binding protein PSF and its target RNA for cancer treatment

Diverse cellular activities are modulated through a variety of RNAs, including long noncoding RNAs (lncRNAs), by binding to certain proteins. The inhibition of oncogenic proteins or RNAs is expected to suppress cancer cell proliferation. We have previously demonstrated that PSF interaction with its target RNAs, such as androgen-induced lncRNA CTBP1-AS, is critical for hormone therapy resistance in prostate and breast cancers. However, the action of protein-RNA interactions remains almost undruggable to date. High-throughput screening (HTS) has facilitated the discovery of drugs for protein-protein interactions. In the present study, we developed an in vitro alpha assay using Flag peptide-conjugated lncRNA, CTBP1-AS, and PSF. We then constructed an effective HTS screening system to explore small compounds that inhibit PSF-RNA interactions. Thirty-six compounds were identified and dose-dependently inhibited PSF-RNA interaction in vitro. Moreover, chemical optimization of these lead compounds and evaluation of cancer cell proliferation revealed two promising compounds, N-3 and C-65. These compounds induced apoptosis and inhibited cell growth in prostate and breast cancer cells. By inhibiting PSF-RNA interaction, N-3 and C-65 up-regulated signals that are repressed by PSF, such as the cell cycle signals by p53 and p27. Furthermore, using a mouse xenograft model for hormone therapy-resistant prostate cancer, we revealed that N-3 and C-65 can significantly suppress tumor growth and downstream target gene expression, such as the androgen receptor (AR). Thus, our findings highlight a therapeutic strategy through the development of inhibitors for RNA-binding events in advanced cancers.

Modeling the expansion of virtual screening libraries

Recently, 'tangible' virtual libraries have made billions of molecules readily available. Prioritizing these molecules for synthesis and testing demands computational approaches, such as docking. Their success may depend on library diversity, their similarity to bio-like molecules and how receptor fit and artifacts change with library size. We compared a library of 3 million 'in-stock' molecules with billion-plus tangible libraries. The bias toward bio-like molecules in the tangible library decreases 19,000-fold versus those 'in-stock'. Similarly, thousands of high-ranking molecules, including experimental actives, from five ultra-large-library docking campaigns are also dissimilar to bio-like molecules. Meanwhile, better-fitting molecules are found as the library grows, with the score improving log-linearly with library size. Finally, as library size increases, so too do rare molecules that rank artifactually well. Although the nature of these artifacts changes from target to target, the expectation of their occurrence does not, and simple strategies can minimize their impact.

Optimization of 3-aminotetrahydrothiophene 1,1-dioxides with improved potency and efficacy as non-electrophilic antioxidant response element (ARE) activators

Activating NRF2-driven transcription with non-electrophilic small molecules represents an attractive strategy to therapeutically target disease states associated with oxidative stress and inflammation. In this study, we describe a campaign to optimize the potency and efficacy of a previously identified bis-sulfone based non-electrophilic ARE activator 2. This work identifies the efficacious analog 17, a compound with a non-cytotoxic profile in IMR32 cells, as well as ARE activators 18 and 22, analogs with improved cellular potency. In silico drug-likeness prediction suggested the optimized bis-sulfones 17, 18, and 22 will likely be of pharmacological utility.

In Silico Identification of Lead Compounds for Pseudomonas Aeruginosa PqsA Enzyme: Computational Study to Block Biofilm Formation

Pseudomonas aeruginosa is an opportunistic Gram-negative bacterium implicated in acute and chronic nosocomial infections and a leading cause of patient mortality. Pseudomonas aeruginosa infections are frequently associated with the development of biofilms, which give the bacteria additional drug resistance and increase their virulence. The goal of this study was to find strong compounds that block the Anthranilate-CoA ligase enzyme made by the pqsA gene. This would stop the P. aeruginosa quorum signaling system. This enzyme plays a crucial role in the pathogenicity of P. aeruginosa by producing autoinducers for cell-to-cell communication that lead to the production of biofilms. Pharmacophore-based virtual screening was carried out utilizing a library of commercially accessible enzyme inhibitors. The most promising hits obtained during virtual screening were put through molecular docking with the help of MOE. The virtual screening yielded 7/160 and 10/249 hits (ZINC and Chembridge). Finally, 2/7 ZINC hits and 2/10 ChemBridge hits were selected as potent lead compounds employing diverse scaffolds due to their high pqsA enzyme binding affinity. The results of the pharmacophore-based virtual screening were subsequently verified using a molecular dynamic simulation-based study (MDS). Using MDS and post-MDS, the stability of the complexes was evaluated. The most promising lead compounds exhibited a high binding affinity towards protein-binding pocket and interacted with the catalytic dyad. At least one of the scaffolds selected will possibly prove useful for future research. However, further scientific confirmation in the form of preclinical and clinical research is required before implementation.

Targeting pleckstrin-2/Akt signaling reduces proliferation in myeloproliferative neoplasm models

Myeloproliferative neoplasms (MPNs) are characterized by the activated JAK2/STAT pathway. Pleckstrin-2 (Plek2) is a downstream target of the JAK2/STAT5 pathway and is overexpressed in patients with MPNs. We previously revealed that Plek2 plays critical roles in the pathogenesis of JAK2-mutated MPNs. The nonessential roles of Plek2 under physiologic conditions make it an ideal target for MPN therapy. Here, we identified first-in-class Plek2 inhibitors through an in silico high-throughput screening approach and cell-based assays, followed by the synthesis of analogs. Plek2-specific small-molecule inhibitors showed potent inhibitory effects on cell proliferation. Mechanistically, Plek2 interacts with and enhances the activity of Akt through the recruitment of downstream effector proteins. The Plek2-signaling complex also includes Hsp72, which protects Akt from degradation. These functions were blocked by Plek2 inhibitors via their direct binding to the Plek2 dishevelled, Egl-10 and pleckstrin (DEP) domain. The role of Plek2 in activating Akt signaling was further confirmed in vivo using a hematopoietic-specific Pten-knockout mouse model. We next tested Plek2 inhibitors alone or in combination with an Akt inhibitor in various MPN mouse models, which showed significant therapeutic efficacies similar to that seen with the genetic depletion of Plek2. The Plek2 inhibitor was also effective in reducing proliferation of CD34-positive cells from MPN patients. Our studies reveal a Plek2/Akt complex that drives cell proliferation and can be targeted by a class of antiproliferative compounds for MPN therapy.

Towards Arginase Inhibition: Hybrid SAR Protocol for Property Mapping of Chlorinated N-arylcinnamamides

A series of seventeen 4-chlorocinnamanilides and seventeen 3,4-dichlorocinnamanilides were characterized for their antiplasmodial activity. In vitro screening on a chloroquine-sensitive strain of Plasmodium falciparum 3D7/MRA-102 highlighted that 23 compounds possessed IC₅₀ < 30 µM. Typically, 3,4-dichlorocinnamanilides showed a broader range of activity compared to 4-chlorocinnamanilides. (2E)-N-[3,5-bis(trifluoromethyl)phenyl]-3-(3,4-dichlorophenyl)prop-2-en-amide with IC₅₀ = 1.6 µM was the most effective agent, while the other eight most active derivatives showed IC₅₀ in the range from 1.8 to 4.6 µM. A good correlation between the experimental logk and the estimated clogP was recorded for the whole ensemble of the lipophilicity generators. Moreover, the SAR-mediated similarity assessment of the novel (di)chlorinated N-arylcinnamamides was conducted using the collaborative (hybrid) ligand-based and structure-related protocols. In consequence, an 'averaged' selection-driven interaction pattern was produced based in namely 'pseudo-consensus' 3D pharmacophore mapping. The molecular docking approach was engaged for the most potent antiplasmodial agents in order to gain an insight into the arginase-inhibitor binding mode. The docking study revealed that (di)chlorinated aromatic (C-phenyl) rings are oriented towards the binuclear manganese cluster in the energetically favorable poses of the chloroquine and the most potent arginase inhibitors. Additionally, the water-mediated hydrogen bonds were formed via carbonyl function present in the new N-arylcinnamamides and the fluorine substituent (alone or in trifluoromethyl group) of N-phenyl ring seems to play a key role in forming the halogen bonds.

High-throughput phenotypic screen identifies a new family of potent anti-amoebic compounds

Entamoeba histolytica is a disease-causing parasitic amoeba which affects an estimated 50 million people worldwide, particularly in socioeconomically vulnerable populations experiencing water sanitation issues. Infection with E. histolytica is referred to as amoebiasis, and can cause symptoms such as colitis, dysentery, and even death in extreme cases. Drugs exist that are capable of killing this parasite, but they are hampered by downsides such as significant adverse effects at therapeutic concentrations, issues with patient compliance, the need for additional drugs to kill the transmissible cyst stage, and potential development of resistance. Past screens of small and medium sized chemical libraries have yielded anti-amoebic candidates, thus rendering high-throughput screening a promising direction for new drug discovery in this area. In this study, we screened a curated 81,664 compound library from Janssen pharmaceuticals against E. histolytica trophozoites in vitro, and from it identified a highly potent new inhibitor compound. The best compound in this series, JNJ001, showed excellent inhibition activity against E. histolytica trophozoites with EC50 values at 0.29 μM, which is better than the current approved treatment, metronidazole. Further experimentation confirmed the activity of this compound, as well as that of several structurally related compounds, originating from both the Janssen Jump-stARter library, and from chemical vendors, thus highlighting a new structure-activity relationship (SAR). In addition, we confirmed that the compound inhibited E. histolytica survival as rapidly as the current standard of care and inhibited transmissible cysts of the related model organism Entamoeba invadens. Together these results constitute the discovery of a novel class of chemicals with favorable in vitro pharmacological properties. The discovery may lead to an improved therapy against this parasite and in all of its life stages.

In silico design of HDAC6 inhibitors with neuroprotective effects

HDAC6 has emerged as a molecular target to treat neurodegenerative disorders, due to its participation in protein aggregate degradation, oxidative stress process, mitochondrial transport, and axonal transport. Thus, in this work we have designed a set of 485 compounds with hydroxamic and bulky-hydrophobic moieties that may function as HDAC6 inhibitors with a neuroprotective effect. These compounds were filtered by their predicted ADMET properties and their affinity to HDAC6 demonstrated by molecular docking and molecular dynamics simulations. The combination of in silico with in vitro neuroprotective results allowed the identification of a lead compound (FH-27) which shows neuroprotective effect that could be due to HDAC6 inhibition. Further, FH-27 chemical moiety was used to design a second series of compounds improving the neuroprotective effect from 2- to 10-fold higher (YSL-99, YSL-109, YSL-112, YSL-116 and YSL-121; 1.25 ± 0.67, 1.82 ± 1.06, 7.52 ± 1.78, 5.59 and 5.62 ± 0.31 µM, respectively). In addition, the R enantiomer of FH-27 (YSL-106) was synthesized, showing a better neuroprotective effect (1.27 ± 0.60 µM). In conclusion, we accomplish the in silico design, synthesis, and biological evaluation of hydroxamic acid derivatives with neuroprotective effect as suggested by an in vitro model. Communicated by Ramaswamy H. Sarma.

Label-free affinity screening, design and synthesis of inhibitors targeting the Mycobacterium tuberculosis L-alanine dehydrogenase

The ability of Mycobacterium tuberculosis (Mtb) to persist in its host may enable an evolutionary advantage for drug resistant variants to emerge. A potential strategy to prevent persistence and gain drug efficacy is to directly target the activity of enzymes that are crucial for persistence. We present a method for expedited discovery and structure-based design of lead compounds by targeting the hypoxia-associated enzyme L-alanine dehydrogenase (AlaDH). Biochemical and structural analyses of AlaDH confirmed binding of nucleoside derivatives and showed a site adjacent to the nucleoside binding pocket that can confer specificity to putative inhibitors. Using a combination of dye-ligand affinity chromatography, enzyme kinetics and protein crystallographic studies, we show the development and validation of drug prototypes. Crystal structures of AlaDH-inhibitor complexes with variations at the N6 position of the adenyl-moiety of the inhibitor provide insight into the molecular basis for the specificity of these compounds. We describe a drug-designing pipeline that aims to block Mtb to proliferate upon re-oxygenation by specifically blocking NAD accessibility to AlaDH. The collective approach to drug discovery was further evaluated through in silico analyses providing additional insight into an efficient drug development strategy that can be further assessed with the incorporation of in vivo studies.

Inverse design of molecule-metal nanoparticle systems interacting with light for desired photophysical properties

Molecules close to a metal nanoparticle (NP) have significantly different photophysical properties from those of the isolated one. In order to harness the potential of the molecule-NP system, appropriate design guidelines are required. Here, we propose an inverse design method of the optimal molecule-NP systems and incident electric field for desired photophysical properties. It is based on a gradient-based optimization search within the time-dependent quantum chemical description for the molecule and the continuum model for the metal NP. We designed the optimal molecule, relative molecule-NP spatial conformation, and incident electric field of a molecule-NP system to maximize the population transfer to the target electronic state of the molecule. The design results were presented and discussed. The present method is promising as the basis for designing molecule-NP systems and incident fields and accelerates discoveries of efficient molecular plasmonics systems.

Discovery of a novel nonsteroidal selective glucocorticoid receptor modulator by virtual screening and bioassays

Synthetic glucocorticoids (GCs) have been widely used in the treatment of a broad range of inflammatory diseases, but their clinic use is limited by undesired side effects such as metabolic disorders, osteoporosis, skin and muscle atrophies, mood disorders and hypothalamic-pituitary-adrenal (HPA) axis suppression. Selective glucocorticoid receptor modulators (SGRMs) are expected to have promising anti-inflammatory efficacy but with fewer side effects caused by GCs. Here, we reported HT-15, a prospective SGRM discovered by structure-based virtual screening (VS) and bioassays. HT-15 can selectively act on the NF-κB/AP1-mediated transrepression function of glucocorticoid receptor (GR) and repress the expression of pro-inflammation cytokines (i.e., IL-1β, IL-6, COX-2, and CCL-2) as effectively as dexamethasone (Dex). Compared with Dex, HT-15 shows less transactivation potency that is associated with the main adverse effects of synthetic GCs, and no cross activities with other nuclear receptors. Furthermore, HT-15 exhibits very weak inhibition on the ratio of OPG/RANKL. Therefore, it may reduce the side effects induced by normal GCs. The bioactive compound HT-15 can serve as a starting point for the development of novel therapeutics for high dose or long-term anti-inflammatory treatment.

Novel 1-hydroxy phenothiazinium-based derivative protects against bacterial sepsis by inhibiting AAK1-mediated LPS internalization and caspase-11 signaling

Sepsis is a life-threatening syndrome with disturbed host responses to severe infections, accounting for the majority of death in hospitalized patients. However, effective medicines are currently scant in clinics due to the poor understanding of the exact underlying mechanism. We previously found that blocking caspase-11 pathway (human orthologs caspase-4/5) is effective to rescue coagulation-induced organ dysfunction and lethality in sepsis models. Herein, we screened our existing chemical pools established in our lab using bacterial outer membrane vesicle (OMV)-challenged macrophages, and found 7-(diethylamino)-1-hydroxy-phenothiazin-3-ylidene-diethylazanium chloride (PHZ-OH), a novel phenothiazinium-based derivative, was capable of robustly dampening caspase-11-dependent pyroptosis. The in-vitro study both in physics and physiology showed that PHZ-OH targeted AP2-associated protein kinase 1 (AAK1) and thus prevented AAK1-mediated LPS internalization for caspase-11 activation. By using a series of gene-modified mice, our in-vivo study further demonstrated that administration of PHZ-OH significantly protected mice against sepsis-associated coagulation, multiple organ dysfunction, and death. Besides, PHZ-OH showed additional protection on Nlrp3^-/- and Casp1^-/- mice but not on Casp11^-/-, Casp1/11^-/-, Msr1^-/-, and AAK1 inhibitor-treated mice. These results suggest the critical role of AAK1 on caspase-11 signaling and may provide a new avenue that targeting AAK1-mediated LPS internalization would be a promising therapeutic strategy for sepsis. In particular, PHZ-OH may serve as a favorable molecule and an attractive scaffold in future medicine development for efficient treatment of bacterial sepsis.

Comparison of ATP-binding pockets and discovery of homologous recombination inhibitors

The ATP binding sites of many enzymes are structurally related, which complicates their development as therapeutic targets. In this work, we explore a diverse set of ATPases and compare their ATP binding pockets using different strategies, including direct and indirect structural methods, in search of pockets attractive for drug discovery. We pursue different direct and indirect structural strategies, as well as ligandability assessments to help guide target selection. The analyses indicate human RAD51, an enzyme crucial in homologous recombination, as a promising, tractable target. Inhibition of RAD51 has shown promise in the treatment of certain cancers but more potent inhibitors are needed. Thus, we design compounds computationally against the ATP binding pocket of RAD51 with consideration of multiple criteria, including predicted specificity, drug-likeness, and toxicity. The molecules designed are evaluated experimentally using molecular and cell-based assays. Our results provide two novel hit compounds against RAD51 and illustrate a computational pipeline to design new inhibitors against ATPases.

Exploration of novel ligands to target C-C Motif Chemokine Receptor 2 (CCR2) as a promising pharmacological treatment against traumatic brain injury

It is widely reported that the overexpression of the C-C Motif Chemokine Receptor 2 (CCR2) has negative implications in neuroinflammatory diseases such as traumatic brain injury (TBI), although promising drugs to tackle this have been less forthcoming. As of 2016, only 2 drugs specifically targeting this receptor have made their way to market, with unsuccessful outcome unfortunately, suggesting that the search for more specific and precise ligands is utterly necessary. In this paper we hypothesized that by targeting Glu291, Met295, Trp98, Leu45 and Val189 amino acids, essential in the binding of CCR2 with C-C Motif Chemokine Ligand 2 (CCL2), the endogenous substrate, mitigates its activity in TBI. We used a pharmacophore model to screen for suitable ligands that may bind to CCR2, which returned 871 ligands. Docking and molecular dynamics results uncovered that two ligands (A102) and (A435) contained several of those important residues and showed a stability and compactness when in complex with CCR2, with these results confirmed by MMGBSA calculations with A102 recording a better interaction compared to A435. Finally, a PPI network was built to explore downstream signaling being regulated by both ligands in TBI, showing amyloid precursor protein (APP) as a key target and neuroactive-ligand receptor interaction (1.80E-27) the top functional annotated category. In conclusion, for the first time we report novel ligands A102 and A435 targeting CCR2 as a potential new pharmacological approach to target inflammation post-TBI.

More is simpler: Decomposition of ligand-binding affinity for proteins being disordered

In statistical mechanics, it is well known that the huge number of degrees of freedom does not complicate the problem as it seems, but actually greatly simplifies the analysis (e.g., to give a Boltzmann distribution). Here, we reveal that the ensemble averaging from the vast conformations of intrinsically disordered proteins (IDPs) greatly simplifies the nature of binding affinity, which can be reliably decomposed into a sum of the ligandability of IDP and the capacity of ligand. Such an unexpected regularity is applied to facilitate the virtual screening upon IDPs. It also provides essential insight in understanding the specificity difference between IDPs and conventional ordered proteins since the specificity is caused by deviation from the baseline behavior of protein-ligand binding.

Design and Synthesis of a Novel 4-aryl-N-(2-alkoxythieno [2,3-b]pyrazine-3-yl)-4-arylpiperazine-1-carboxamide DGG200064 Showed Therapeutic Effect on Colon Cancer through G2/M Arrest

Cancer cells are characterized by an abnormal cell cycle. Therefore, the cell cycle has been a potential target for cancer therapeutic agents. We developed a new lead compound, DGG200064 (7c) with a 2-alkoxythieno [2,3-b]pyrazine-3-yl)-4-arylpiperazine-1-carboxamide core skeleton. To evaluate its properties, compound DGG200064 was tested in vivo through a xenograft mouse model of colorectal cancer using HCT116 cells. The in vivo results showed high cell growth inhibition efficacy. Our results confirmed that the newly synthesized DGG200064 inhibits the growth of colorectal cancer cells by inducing G2/M arrest. Unlike the known cell cycle inhibitors, DGG200064 (GI₅₀ = 12 nM in an HCT116 cell-based assay) induced G2/M arrest by selectively inhibiting the interaction of FBXW7 and c-Jun proteins. Additionally, the physicochemical properties of the lead compounds were analyzed. Based on the results of the study, we suggested further development of DGG200064 as a novel oral anti-colorectal cancer drug.

Fast fragment- and compound-screening pipeline at the Swiss Light Source

Over the last two decades, fragment-based drug discovery (FBDD) has emerged as an effective and efficient method to identify new chemical scaffolds for the development of lead compounds. X-ray crystallography can be used in FBDD as a tool to validate and develop fragments identified as binders by other methods. However, it is also often used with great success as a primary screening technique. In recent years, technological advances at macromolecular crystallography beamlines in terms of instrumentation, beam intensity and robotics have enabled the development of dedicated platforms at synchrotron sources for FBDD using X-ray crystallography. Here, the development of the Fast Fragment and Compound Screening (FFCS) platform, an integrated next-generation pipeline for crystal soaking, handling and data collection which allows crystallography-based screening of protein crystals against hundreds of fragments and compounds, at the Swiss Light Source is reported.

Natural product drug discovery in the artificial intelligence era

Natural products (NPs) are primarily recognized as privileged structures to interact with protein drug targets. Their unique characteristics and structural diversity continue to marvel scientists for developing NP-inspired medicines, even though the pharmaceutical industry has largely given up. High-performance computer hardware, extensive storage, accessible software and affordable online education have democratized the use of artificial intelligence (AI) in many sectors and research areas. The last decades have introduced natural language processing and machine learning algorithms, two subfields of AI, to tackle NP drug discovery challenges and open up opportunities. In this article, we review and discuss the rational applications of AI approaches developed to assist in discovering bioactive NPs and capturing the molecular "patterns" of these privileged structures for combinatorial design or target selectivity.

Library Synthesis: Building Block Selection, Handling, and Tracking

Careful selection and manipulation of small molecule building blocks is crucial to the success of a DNA-encoded library. Building block selection impacts the quality of the hits arising out of a selection assay, while proper sample handling and tracking ensure follow-up synthetic work is done with the appropriate synthetic map in mind. In this chapter, possible strategies for building block selection are outlined, as well as best practices for handling and tracking samples to be used for validation and library synthesis.

Structure-Based Virtual Screening for Ligands of G Protein-Coupled Receptors: What Can Molecular Docking Do for You?

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs. SIGNIFICANCE STATEMENT: Extraordinary advances in the structural biology of G protein-coupled receptors have revealed the molecular details of ligand recognition by this large family of therapeutic targets, providing novel avenues for rational drug design. Structure-based docking is an efficient computational approach to identify novel chemical probes from large compound libraries, which has the potential to accelerate the development of drug candidates.

Chalcone-inspired rA1 /A2A adenosine receptor ligands: Ring closure as an alternative to a reactive substructure

Over the past few years, great progress has been made in the development of high-affinity adenosine A₁ and/or A_2A receptor antagonists-promising agents for the potential treatment of Parkinson's disease. Unfortunately, many of these compounds raise structure-related concerns. The present study investigated the effect of ring closures on the rA₁ /A_2A affinity of compounds containing a highly reactive α,β-unsaturated carbonyl system, hence providing insight into the potential of heterocycles to address these concerns. A total of 12 heterocyclic compounds were synthesised and evaluated in silico and in vitro. The test compounds performed well upon qualitative assessment of drug-likeness and were generally found to be free from potentially problematic fragments. Most also showed low/weak cytotoxicity. Results from radioligand binding experiments confirm that heterocycles (particularly 2-substituted 3-cyanopyridines) can replace the promiscuous α,β-unsaturated ketone functional group without compromising A₁ /A_2A affinity. Structure-activity relationships highlighted the importance of hydrogen bonds in binding to the receptors of interest. Compounds 3c (rA₁ K_i  = 16 nM; rA_2A K_i  = 65 nM) and 8a (rA₁ K_i  = 102 nM; rA_2A K_i  = 37 nM), which both act as A₁ antagonists, showed significant dual A₁ /A_2A affinity and may, therefore, inspire further investigation into heterocycles as potentially safe and potent adenosine receptor antagonists.

Nonantimicrobial Actions of Macrolides: Overview and Perspectives for Future Development

Macrolides are among the most widely prescribed broad spectrum antibacterials, particularly for respiratory infections. It is now recognized that these drugs, in particular azithromycin, also exert time-dependent immunomodulatory actions that contribute to their therapeutic benefit in both infectious and other chronic inflammatory diseases. Their increased chronic use in airway inflammation and, more recently, of azithromycin in COVID-19, however, has led to a rise in bacterial resistance. An additional crucial aspect of chronic airway inflammation, such as chronic obstructive pulmonary disease, as well as other inflammatory disorders, is the loss of epithelial barrier protection against pathogens and pollutants. In recent years, azithromycin has been shown with time to enhance the barrier properties of airway epithelial cells, an action that makes an important contribution to its therapeutic efficacy. In this article, we review the background and evidence for various immunomodulatory and time-dependent actions of macrolides on inflammatory processes and on the epithelium and highlight novel nonantibacterial macrolides that are being studied for immunomodulatory and barrier-strengthening properties to circumvent the risk of bacterial resistance that occurs with macrolide antibacterials. We also briefly review the clinical effects of macrolides in respiratory and other inflammatory diseases associated with epithelial injury and propose that the beneficial epithelial effects of nonantibacterial azithromycin derivatives in chronic inflammation, even given prophylactically, are likely to gain increasing attention in the future. SIGNIFICANCE STATEMENT: Based on its immunomodulatory properties and ability to enhance the protective role of the lung epithelium against pathogens, azithromycin has proven superior to other macrolides in treating chronic respiratory inflammation. A nonantibiotic azithromycin derivative is likely to offer prophylactic benefits against inflammation and epithelial damage of differing causes while preserving the use of macrolides as antibiotics.

A phenotypic high-content, high-throughput screen identifies inhibitors of NLRP3 inflammasome activation

Inhibition of the NACHT, LRR and PYD domains-containing protein 3 (NLRP3) inflammasome has recently emerged as a promising therapeutic target for several inflammatory diseases. After priming and activation by inflammation triggers, NLRP3 forms a complex with apoptosis-associated speck-like protein containing a CARD domain (ASC) followed by formation of the active inflammasome. Identification of inhibitors of NLRP3 activation requires a well-validated primary high-throughput assay followed by the deployment of a screening cascade of assays enabling studies of structure–activity relationship, compound selectivity and efficacy in disease models. We optimized a NLRP3-dependent fluorescent tagged ASC speck formation assay in murine immortalized bone marrow-derived macrophages and utilized it to screen a compound library of 81,000 small molecules. Our high-content screening assay yielded robust assay metrics and identified a number of inhibitors of NLRP3-dependent ASC speck formation, including compounds targeting HSP90, JAK and IKK-β. Additional assays to investigate inflammasome priming or activation, NLRP3 downstream effectors such as caspase-1, IL-1β and pyroptosis form the basis of a screening cascade to identify NLRP3 inflammasome inhibitors in drug discovery programs.

Appraisal of the Role of In silico Methods in Pyrazole Based Drug Design

Pyrazole and its derivatives are a pharmacologically and significantly active scaffolds that have innumerable physiological and pharmacological activities. They can be very good targets for the discovery of novel anti-bacterial, anti-cancer, anti-inflammatory, anti-fungal, anti-tubercular, antiviral, antioxidant, antidepressant, anti-convulsant and neuroprotective drugs. This review focuses on the importance of in silico manipulations of pyrazole and its derivatives for medicinal chemistry. The authors have discussed currently available information on the use of computational techniques like molecular docking, structure-based virtual screening (SBVS), molecular dynamics (MD) simulations, quantitative structure activity relationship (QSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) to drug design using pyrazole moieties. Pyrazole based drug design is mainly dependent on the integration of experimental and computational approaches. The authors feel that more studies need to be done to fully explore the pharmacological potential of the pyrazole moiety and in silico method can be of great help.

Two Decades of 4D-QSAR: A Dying Art or Staging a Comeback?

A key question confronting computational chemists concerns the preferable ligand geometry that fits complementarily into the receptor pocket. Typically, the postulated ‘bioactive’ 3D ligand conformation is constructed as a ‘sophisticated guess’ (unnecessarily geometry-optimized) mirroring the pharmacophore hypothesis—sometimes based on an erroneous prerequisite. Hence, 4D-QSAR scheme and its ‘dialects’ have been practically implemented as higher level of model abstraction that allows the examination of the multiple molecular conformation, orientation and protonation representation, respectively. Nearly a quarter of a century has passed since the eminent work of Hopfinger appeared on the stage; therefore the natural question occurs whether 4D-QSAR approach is still appealing to the scientific community? With no intention to be comprehensive, a review of the current state of art in the field of receptor-independent (RI) and receptor-dependent (RD) 4D-QSAR methodology is provided with a brief examination of the ‘mainstream’ algorithms. In fact, a myriad of 4D-QSAR methods have been implemented and applied practically for a diverse range of molecules. It seems that, 4D-QSAR approach has been experiencing a promising renaissance of interests that might be fuelled by the rising power of the graphics processing unit (GPU) clusters applied to full-atom MD-based simulations of the protein-ligand complexes.

Synthesis and Hybrid SAR Property Modeling of Novel Cholinesterase Inhibitors

A library of novel 4-{[(benzyloxy)carbonyl]amino}-2-hydroxybenzoic acid amides was designed and synthesized in order to provide potential acetyl- and butyrylcholinesterase (AChE/BChE) inhibitors; the in vitro inhibitory profile and selectivity index were specified. Benzyl(3-hydroxy-4-{[2-(trifluoromethoxy)phenyl]carbamoyl}phenyl)carbamate was the best AChE inhibitor with the inhibitory concentration of IC₅₀ = 36.05 µM in the series, while benzyl{3-hydroxy-4-[(2-methoxyphenyl)carbamoyl]phenyl}-carbamate was the most potent BChE inhibitor (IC₅₀ = 22.23 µM) with the highest selectivity for BChE (SI = 2.26). The cytotoxic effect was evaluated in vitro for promising AChE/BChE inhibitors. The newly synthesized adducts were subjected to the quantitative shape comparison with the generation of an averaged pharmacophore pattern. Noticeably, three pairs of fairly similar fluorine/bromine-containing compounds can potentially form the activity cliff that is manifested formally by high structure–activity landscape index (SALI) numerical values. The molecular docking study was conducted for the most potent AChE/BChE inhibitors, indicating that the hydrophobic interactions were overwhelmingly generated with Gln119, Asp70, Pro285, Thr120, and Trp82 aminoacid residues, while the hydrogen bond (HB)-donor ones were dominated with Thr120. π-stacking interactions were specified with the Trp82 aminoacid residue of chain A as well. Finally, the stability of chosen liganded enzymatic systems was assessed using the molecular dynamic simulations. An attempt was made to explain the noted differences of the selectivity index for the most potent molecules, especially those bearing unsubstituted and fluorinated methoxy group.

On the search for COVID-19 therapeutics: identification of potential SARS-CoV-2 main protease inhibitors by virtual screening, pharmacophore modeling and molecular dynamics

COVID-19 also known as SARS-CoV-2 outbreak in late 2019 and its worldwide pandemic spread has taken the world by surprise. The minute-to-minute increasing coronavirus cases (>85 M) and progressive deaths (≈1.8 M) calls for finding a cure to this devastating pandemic. While there have been many attempts to find biologically active molecules targeting SARS-CoV-2 for treatment of this viral infection, none has found a way to the clinic yet. In this study, a 3-feature structure-based pharmacophore model was designed for SARS-CoV-2 main protease (M^Pro) that plays a vital role in the viral cellular penetration. High throughput virtual screening of the lead-like ZINC library was then performed to find a potent inhibitor employing the predesigned pharmacophore. In-silico pharmacokinetics/toxicity prediction study was subsequently applied towards the best hits. Finally, a 50 ns molecular dynamics simulation was carried out for the best hit and compared to the co-crystallized ligand where the hit compound displayed high binding and comparable interactions. The results identified new hits for SARS-CoV-2 M^Pro inhibition showing good docking score, pharmacokinetics and toxicity profile, drug-likeness, high binding energy in addition to a promising synthetic accessibility. Identifying new small compounds as potential leads for inhibiting SARS-CoV-2 is a very important step towards designing a synthesizing of promising drug candidates.Communicated by Ramaswamy H. Sarma.

Trends in Hit-to-Lead Optimization Following DNA-Encoded Library Screens

DNA-encoded library (DEL) screens have emerged as a powerful hit-finding tool for a number of biological targets. In this Innovations article, we review published hit-to-lead optimization studies following DEL screens. Trends in molecular property changes from hit to lead are identified, and specific optimization tactics are exemplified in case studies. Across the studies, physicochemical property and structural changes post-DEL screening are similar to those which occur during hit-to-lead optimization following high throughputscreens (HTS). However, unique aspects of DEL-the combinatorial synthetic methods which enable DEL synthesis and the linker effects at the DNA attachment point-impact the strategies and outcomes of hit-to-lead optimizations.

Discovery and optimization of novel 3-benzyl-N-phenyl-1H-pyrazole-5-carboxamides as bifunctional antidiabetic agents stimulating both insulin secretion and glucose uptake

A novel series of 3-benzyl-N-phenyl-1H-pyrazole-5-carboxamides was designed, synthesized and evaluated for their biological activities on glucose-stimulated insulin secretion (GSIS). The cytotoxicity of all 41 novel compounds was screened to assess their pharmacological safety in pancreatic β-cells. A two-step optimization process was carried out to establish the structure-activity relationship for this class and subsequently we identified the most active analogue 26. Further modification study of 26 evidenced the necessity of N-hydrogens in the core architecture. Protein expression analysis suggested that 26 increases insulin secretion via the activation of the upstream effector of pancreatic and duodenal homeobox 1 (PDX-1), which is an important factor promoting GSIS. Moreover, the administration of 26 effectively augmented glucose uptake in C2C12 myotube cells via the suppression of Mitsugumin 53 (MG53), an insulin receptor substrate 1 (IRS-1) ubiquitination E3 ligase.

Evolution of Novartis' Small Molecule Screening Deck Design

This article summarizes the evolution of the screening deck at the Novartis Institutes for BioMedical Research (NIBR). Historically, the screening deck was an assembly of all available compounds. In 2015, we designed a first deck to facilitate access to diverse subsets with optimized properties. We allocated the compounds as plated subsets on a 2D grid with property based ranking in one dimension and increasing structural redundancy in the other. The learnings from the 2015 screening deck were applied to the design of a next generation in 2019. We found that using traditional leadlikeness criteria (mainly MW, clogP) reduces the hit rates of attractive chemical starting points in subset screening. Consequently, the 2019 deck relies on solubility and permeability to select preferred compounds. The 2019 design also uses NIBR's experimental assay data and inferred biological activity profiles in addition to structural diversity to define redundancy across the compound sets.

Generating Multibillion Chemical Space of Readily Accessible Screening Compounds

An approach to the generation of ultra-large chemical libraries of readily accessible (“REAL”) compounds is described. The strategy is based on the use of two- or three-step three-component reaction sequences and available starting materials with pre-validated chemical reactivity. After the preliminary parallel experiments, the methods with at least ∼80% synthesis success rate (such as acylation – deprotection – acylation of monoprotected diamines or amide formation – click reaction with functionalized azides) can be selected and used to generate the target chemical space. It is shown that by using only on the two aforementioned reaction sequences, a nearly 29-billion compound library is easily obtained. According to the predicted physico-chemical descriptor values, the generated chemical space contains large fractions of both drug-like and “beyond rule-of-five” members, whereas the strictest lead-likeness criteria (the so-called Churcher's rules) are met by the lesser part, which still exceeds 22 million.

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A strategy for ultra-large readily accessible (REAL) compound libraries is described

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Pre-validated two- or three-step three-component reaction sequences are used

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A 29-billion chemical space with ∼80% synthesis success rate has been easily obtained

Consensus-Based Pharmacophore Mapping for New Set of N-(disubstituted-phenyl)-3-hydroxyl-naphthalene-2-carboxamides

A series of twenty-two novel N-(disubstituted-phenyl)-3-hydroxynaphthalene- 2-carboxamide derivatives was synthesized and characterized as potential antimicrobial agents. N-[3,5-bis(trifluoromethyl)phenyl]- and N-[2-chloro-5-(trifluoromethyl)phenyl]-3-hydroxy- naphthalene-2-carboxamide showed submicromolar (MICs 0.16–0.68 µM) activity against methicillin-resistant Staphylococcus aureus isolates. N-[3,5-bis(trifluoromethyl)phenyl]- and N-[4-bromo-3-(trifluoromethyl)phenyl]-3-hydroxynaphthalene-2-carboxamide revealed activity against M. tuberculosis (both MICs 10 µM) comparable with that of rifampicin. Synergistic activity was observed for the combinations of ciprofloxacin with N-[4-bromo-3-(trifluoromethyl)phenyl]- and N-(4-bromo-3-fluorophenyl)-3-hydroxynaphthalene-2-carboxamides against MRSA SA 630 isolate. The similarity-related property space assessment for the congeneric series of structurally related carboxamide derivatives was performed using the principal component analysis. Interestingly, different distribution of mono-halogenated carboxamide derivatives with the –CF₃ substituent is accompanied by the increased activity profile. A symmetric matrix of Tanimoto coefficients indicated the structural dissimilarities of dichloro- and dimetoxy-substituted isomers from the remaining ones. Moreover, the quantitative sampling of similarity-related activity landscape provided a subtle picture of favorable and disallowed structural modifications that are valid for determining activity cliffs. Finally, the advanced method of neural network quantitative SAR was engaged to illustrate the key 3D steric/electronic/lipophilic features of the ligand-site composition by the systematic probing of the functional group.

De Novo Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization

Artificial intelligence and multiobjective optimization represent promising solutions to bridge chemical and biological landscapes by addressing the automated de novo design of compounds as a result of a humanlike creative process. In the present study, we conceived a novel pair-based multiobjective approach implemented in an adapted SMILES generative algorithm based on recurrent neural networks for the automated de novo design of new molecules whose overall features are optimized by finding the best trade-offs among relevant physicochemical properties (MW, logP, HBA, HBD) and additional similarity-based constraints biasing specific biological targets. In this respect, we carried out the de novo design of chemical libraries targeting neuraminidase, acetylcholinesterase, and the main protease of severe acute respiratory syndrome coronavirus 2. Several quality metrics were employed to assess drug-likeness, chemical feasibility, diversity content, and validity. Molecular docking was finally carried out to better evaluate the scoring and posing of the de novo generated molecules with respect to X-ray cognate ligands of the corresponding molecular counterparts. Our results indicate that artificial intelligence and multiobjective optimization allow us to capture the latent links joining chemical and biological aspects, thus providing easy-to-use options for customizable design strategies, which are especially effective for both lead generation and lead optimization. The algorithm is freely downloadable at https://github.com/alberdom88/moo-denovo and all of the data are available as Supporting Information.

Current Approaches to Drug Discovery for Chagas Disease: Methodological Advances

BACKGROUND

In recent years, there has been an improvement in the in vitro and in vivo methodology for the screening of anti-chagasic compounds. Millions of compounds can now have their activity evaluated (in large compound libraries) by means of high throughput in vitro screening assays.

OBJECTIVE

Current approaches to drug discovery for Chagas disease.

METHOD

This review article examines the contribution of these methodological advances in medicinal chemistry in the last four years, focusing on Trypanosoma cruzi infection, obtained from the PubMed, Web of Science, and Scopus databases.

RESULTS

Here, we have shown that the promise is increasing each year for more lead compounds for the development of a new drug against Chagas disease.

CONCLUSION

There is increased optimism among those working with the objective to find new drug candidates for optimal treatments against Chagas disease.

Elucidation on the Physicochemical Properties of Potential and Clinically Approved Antiviral Drugs: A Search for Effective Therapies against SARS-CoV-2 Infection

COVID-19 has been confirmed in millions of individuals worldwide, rendering it a global medical emergency. In the absence of vaccines and the unavailability of effective drugs for the SARS-CoV-2 infection, vaccine development is being continuously explored and several antiviral compounds and immunotherapies are currently being investigated. Given the high similarity in genetic identity between SARS-CoV and SARS-CoV-2, the present investigation identified the interaction between the physicochemical properties and the antiviral activity of different potential and clinically approved antiviral drugs against SARS-CoV using hierarchically weighted principal component analysis. Representative drugs from the classes of neuraminidase inhibitors, reverse transcriptase inhibitors, protease inhibitors, nucleoside analogues, and other compounds with potential antiviral activity were examined. The pharmacologic classification and the biological activity of the different antiviral drugs were described using indices, namely, rotatable bond count, molecular weight, heavy atom count, and molecular complexity (92.32% contribution rate). The physicochemical properties and inhibitory action against SARS-CoV-2 of lopinavir, chloroquine, ivermectin, and ciclesonide validated the adequacy of the current computational approach. The findings of the present study provide additional information, although further investigation is warranted to identify potential targets and establish exact mechanisms, in the emergent search and design of antiviral drug candidates and their subsequent synthesis as effective therapies for COVID-19.

A Proof-of-Concept Fragment Screening of a Hit-Validated 96-Compounds Library against Human Carbonic Anhydrase II

Fragment screening is a powerful tool to identify and characterize binding pockets in proteins. We herein present the results of a proof-of-concept screening campaign of a versatile 96-entry fragment library from our laboratory against the drug target and model protein human carbonic anhydrase II. The screening revealed a novel chemotype for carbonic anhydrase inhibition, as well as less common non-covalent interaction types and unexpected covalent linkages. Lastly, different runs of the PanDDA tool reveal a practical hint for its application.

The impact of chemoinformatics on drug discovery in the pharmaceutical industry

Introduction: Even though there have been substantial advances in our understanding of biological systems, research in drug discovery is only just now beginning to utilize this type of information. The single-target paradigm, which exemplifies the reductionist approach, remains a mainstay of drug research today. A deeper view of the complexity involved in drug discovery is necessary to advance on this field.Areas covered: This perspective provides a summary of research areas where cheminformatics has played a key role in drug discovery, including of the available resources as well as a personal perspective of the challenges still faced in the field.Expert opinion: Although great strides have been made in the handling and analysis of biological and pharmacological data, more must be done to link the data to biological pathways. This is crucial if one is to understand how drugs modify disease phenotypes, although this will involve a shift from the single drug/single target paradigm that remains a mainstay of drug research. Moreover, such a shift would require an increased awareness of the role of physiology in the mechanism of drug action, which will require the introduction of new mathematical, computer, and biological methods for chemoinformaticians to be trained in.

Design and synthesis of tricyclic terpenoid derivatives as novel PTP1B inhibitors with improved pharmacological property and in vivo antihyperglycaemic efficacy

Overexpression of protein tyrosine phosphatase 1B (PTP1B) induces insulin resistance in various basic and clinical research. In our previous work, a synthetic oleanolic acid (OA) derivative C10a with PTP1B inhibitory activity has been reported. However, C10a has some pharmacological defects and cytotoxicity. Herein, a structure-based drug design approach was used based on the structure of C10a to elaborate the smaller tricyclic core. A series of tricyclic derivatives were synthesised and the compounds 15, 28 and 34 exhibited the most PTP1B enzymatic inhibitory potency. In the insulin-resistant human hepatoma HepG2 cells, compound 25 with the moderate PTP1B inhibition and preferable pharmaceutical properties can significantly increase insulin-stimulated glucose uptake and showed the insulin resistance ameliorating effect. Moreover, 25 showed the improved in vivo antihyperglycaemic potential in the nicotinamide–streptozotocin-induced T2D. Our study demonstrated that these tricyclic derivatives with improved molecular architectures and antihyperglycaemic activity could be developed in the treatment of T2D.

Fundamental physical and chemical concepts behind “drug-likeness” and “natural product-likeness”

The discovery of a drug is known to be quite cumbersome, both in terms of the microscopic fundamental research behind it and the industrial scale manufacturing process. A major concern in drug discovery is the acceleration of the process and cost reduction. The fact that clinical trials cannot be accelerated, therefore, emphasizes the need to accelerate the strategies for identifying lead compounds at an early stage. We, herein, focus on the definition of what would be regarded as a “drug-like” molecule and a “lead-like” one. In particular, “drug-likeness” is referred to as resemblance to existing drugs, whereas “lead-likeness” is characterized by the similarity with structural and physicochemical properties of a “lead”compound, i.e. a reference compound or a starting point for further drug development. It is now well known that a huge proportion of the drug discovery is inspired or derived from natural products (NPs), which have larger complexity as well as size when compared with synthetic compounds. Therefore, similar definitions of “drug-likeness” and “lead-likeness” cannot be applied for the NP-likeness. Rather, there is the dire need to define and explain NP-likeness in regard to chemical structure. An attempt has been made here to give an overview of the general concepts associated with NP discovery, and to provide the foundational basis for defining a molecule as a “drug”, a “lead” or a “natural compound.”