Molecular Field Extrema as Descriptors of Biological Activity: Definition and Validation

Hybrid Virtual Screening Approach to Predict Novel Natural Compounds against HIV-1 CCR5

BACKGROUND

Human immunodeficiency virus (HIV) infection continues to pose a major global health challenge. HIV entry into host cells via membrane fusion mediated by the viral envelope glycoprotein gp120/gp41 is a key step in the HIV life cycle. CCR5, expressed on CD4+ T cells and macrophages, acts as a coreceptor facilitating HIV-1 entry. The CCR5 antagonist maraviroc is used to treat HIV infection. However, it can cause adverse effects and has limitations such as only inhibiting CCR5-tropic viruses. There remains a need to develop alternative CCR5 inhibitors with improved safety profiles.

PROBLEM STATEMENT

Natural products may offer advantages over synthetic inhibitors including higher bioavailability, binding affinity, effectiveness, lower toxicity, and molecular diversity. However, screening the vast chemical space of natural compounds to identify novel CCR5 inhibitors presents challenges. This study aimed to address this gap through a hybrid ligand-based pharmacophore modeling and molecular docking approach to virtually screen large natural product databases.

METHODS

A reliable pharmacophore model was developed based on 311 known CCR5 antagonists and validated against an external data set. Five natural product databases containing over 306,000 compounds were filtered based on drug-likeness rules. The validated pharmacophore model screened the databases to identify 611 hits. Key residues of the CCR5 receptor crystal structure were identified for docking. The top hits were docked, and interactions were analyzed. Molecular dynamics simulations were conducted to examine complex stability. Computational prediction evaluated pharmacokinetic properties.

RESULTS

Three compounds exhibited similar interactions and binding energies to maraviroc. MD simulations demonstrated complex stability comparable to maraviroc. One compound showed optimal predicted absorption, minimal metabolism, and a lower likelihood of interactions than maraviroc.

CONCLUSION

This computational screening workflow identified three natural compounds with promising CCR5 inhibition and favorable pharmacokinetic profiles. One compound emerged as a lead based on bioavailability potential and minimal interaction risk. These findings present opportunities for developing alternative CCR5 antagonists and warrant further experimental investigation. Overall, the hybrid virtual screening approach proved effective for mining large natural product spaces to discover novel molecular entities with drug-like properties.

Field-based 3D-QSAR for tyrosine protein kinase JAK-2 inhibitors

The present work aimed to develop a Field-based 3D-QSAR model with existing JAK-2 inhibitors. The JAK-STAT pathway is known to play a role in the development of autoimmune diseases, including rheumatoid arthritis, ulcerative colitis, and Crohn's disease. Dysregulation of JAK-STAT is also linked to the development of myelofibrosis and other myeloproliferative diseases. JAK antagonists can be used in many areas of medicine. There are many compounds that already show inhibition of Jak-2. We have developed a Field-based 3D QSAR model which showed good correlation values (r2 0.884 and q2 0.67) with an external test set regression pred_r2 0.562. Various properties, such as electronegativity, electro positivity, hydrophobicity, and shape features, were studied under the activity atlas to determine the inhibitory potential of ligands. These were also identified as important structural features responsible for biological activity. We performed virtual screening based on the pharmacophore features of the co-crystal ligand (PDB ID: 3KRR) and a dataset of NPS was selected with a RMSD value less than 0.8. The developed 3D QSAR model was used to screen ligands and calculate the predicted JAK-2 inhibition activity (pKi). The results of the virtual screening were validated using molecular docking and molecular dynamics simulations. SNP1 (SN00154718) and SNP2 (SN00213825) showed binding affinity of -11.16 and -11.08 kcal/mol, respectively, which were very close to the crystal ligand of 3KRR, -11.67 kcal/mol. The RMSD plot of the protein-ligand complex of SNP1 and 3KRR showed stable interactions with an average RMSD of 2.89 Å. Thus, a statistically robust 3D QSAR model could reveal more inhibitors and aid in the design of novel JAK-2 inhibitors.

Screening of bioactive compounds from selected mushroom species against putative drug targets in Mycobacterium tuberculosis: a multi-target approach

Mycobacterium tuberculosis (Mtb) is a notorious pathogen that causes one of the highest mortalities globally. Due to a pressing demand to identify novel therapeutic alternatives, the present study aims to focus on screening the putative drug targets and prioritizing their role in antibacterial drug development. The most vital proteins involved in the Biotin biosynthesis pathway and the Lipoarabinomannan (LAM) pathway such as biotin synthase (bioB) and alpha-(1->6)-mannopyranosyltransferase A (mptA) respectively, along with other essential virulence proteins of Mtb were selected as drug targets. Among these, the ones without native structures were modelled and validated using standard bioinformatics tools. Further, the interactions were performed with naturally available lead molecules present in selected mushroom species such as Agaricus bisporus, Pleurotus djamor, Hypsizygus ulmarius. Through Gas Chromatography-Mass Spectrometry (GC-MS), 15 bioactive compounds from the methanolic extract of mushrooms were identified. Further, 4 were selected based on drug-likeness and pharmacokinetic screening for molecular docking analysis against our prioritized targets wherein Benz[e]azulene from Pleurotus djamor illustrated a good binding affinity with a LF rank score of -9.036 kcal mol -1 against nuoM (NADH quinone oxidoreductase subunit M) and could be used as a prospective candidate in order to combat Tuberculosis (TB). Furthermore, the stability of the complex are validated using MD Simulations and subsequently, the binding free energy was calculated using MM-GBSA analysis. Thus, the current in silico analysis suggests a promising role of compounds extracted from mushrooms in tackling the TB burden.Communicated by Ramaswamy H. Sarma.

Design, Synthesis, and Cytotoxic Assessment of New Haloperidol Analogues as Potential Anticancer Compounds Targeting Sigma Receptors

Sigma receptors (SRs), including SR1 and SR2 subtypes, have attracted increasing interest in recent years due to their involvement in a wide range of activities, including the modulation of opioid analgesia, neuroprotection, and potential anticancer activity. In this context, haloperidol (HAL), a commonly used antipsychotic drug, also possesses SR activity and cytotoxic effects. Herein, we describe the identification of novel SR ligands, obtained by a chemical hybridization approach. There wereendowed with pan-affinity for both SR subtypes and evaluated their potential anticancer activity against SH-SY5Y and HUH-7 cancer cell lines. Through a chemical hybridization approach, we identified novel compounds (4d, 4e, 4g, and 4j) with dual affinity for SR1 and SR2 receptors. These compounds were subjected to cytotoxicity testing using a resazurin assay. The results revealed potent cytotoxic effects against both cancer cell lines, with IC50 values comparable to HAL. Interestingly, the cytotoxic potency of the novel compounds resembled that of the SR1 antagonist HAL rather than the SR2 agonist siramesine (SRM), indicating the potential role of SR1 antagonism in their mechanism of action. The further exploration of their structure-activity relationships and their evaluation in additional cancer cell lines will elucidate their therapeutic potential and may pave the way for the development of novel anticancer agents that target SRs.

Development of a novel representation of drug 3D structures and enhancement of the TSR-based method for probing drug and target interactions

Understanding the mechanisms underlying interactions between drugs and target proteins is critical for drug discovery. In our earlier studies, we introduced the Triangular Spatial Relationship (TSR)-based algorithm, which enables the representation of a protein's 3D structure as a vector of integers (TSR keys). These TSR keys correspond to substructures of the 3D structure of a protein and are computed based on the triangles constructed by all possible triples of Cα atoms within the protein. In this study, we report on a new TSR-based algorithm for probing drug and target interactions. Specifically, we have extended the previous algorithm in three novel directions: TSR keys for representing the 3D structure of a drug or a ligand, cross TSR keys between drugs and their targets and intra-residual TSR keys for phosphorylated amino acids. The outcomes illustrate the key contributions as follows: (i) The TSR-based method, which uses the TSR keys as features, is unique in its capability to interpret hierarchical relationships of drugs as well as drug - target complexes using common and specific TSR keys. (ii) The method can distinguish not only the binding sites from the rest of the protein structures, but also the binding sites of primary targets from those of off-targets. (iii) The method has the potential to correlate the 3D structures of drugs with their functions. (iv) Representation of 3D structures by TSR keys has its unique advantage in terms of ease of making searching for similar substructures across structure datasets easier. In summary, this study presents a novel computational methodology, with significant advantages, for providing insights into the mechanism underlying drug and target interactions.

Fenamates and ibuprofen as foundational components in the synthesis of innovative, targeted COX-2 anti-inflammatory drugs, undergoing thorough biopharmacological assessments and in-silico computational studies

Cyclooxygenase-2 plays a vital role in inflammation by catalyzing arachidonic acid conversion toward prostaglandins, making it a prime therapeutic objective. Selective COX-2 inhibitors represent significant progress in anti-inflammatory therapy, offering improved efficacy and fewer side effects. This study describes the synthesis of novel anti-inflammatory compounds from established pharmaceutically marketed agents like fenamates III-V and ibuprofen VI. Through rigorous in vitro testing, compounds 7b-c, and 12a-b demonstrated substantial in vitro selective inhibition, with IC50 values of 0.07 to 0.09 μM, indicating potent pharmacological activity. In vivo assessment, particularly focusing on compound 7c, revealed significant anti-inflammatory effects. Markedly, it demonstrated the highest inhibition of paw thickness (58.62 %) at the 5-hr mark compared to the carrageenan group, indicating its potency in mitigating inflammation. Furthermore, it exhibited a rapid onset of action, with a 54.88 % inhibition observed at the 1-hr mark. Subsequent comprehensive evaluations encompassing analgesic efficacy, histological characteristics, and toxicological properties indicated that compound 7c did not induce gastric ulcers, in contrast to the ulcerogenic tendency associated with mefenamic acid. Moreover, compound 7c underwent additional investigations through in silico methodologies such as molecular modelling, field alignment, and density functional theory. These analyses underscored the therapeutic potential and safety profile of this novel compound, warranting further exploration and development in the realm of pharmaceutical research.

Sire: An interoperability engine for prototyping algorithms and exchanging information between molecular simulation programs

Sire is a Python/C++ library that is used both to prototype new algorithms and as an interoperability engine for exchanging information between molecular simulation programs. It provides a collection of file parsers and information converters that together make it easier to combine and leverage the functionality of many other programs and libraries. This empowers researchers to use sire to write a single script that can, for example, load a molecule from a PDBx/mmCIF file via Gemmi, perform SMARTS searches via RDKit, parameterize molecules using BioSimSpace, run GPU-accelerated molecular dynamics via OpenMM, and then display the resulting dynamics trajectory in a NGLView Jupyter notebook 3D molecular viewer. This functionality is built on by BioSimSpace, which uses sire's molecular information engine to interconvert with programs such as GROMACS, NAMD, Amber, and AmberTools for automated molecular parameterization and the running of molecular dynamics, metadynamics, and alchemical free energy workflows. Sire comes complete with a powerful molecular information search engine, plus trajectory loading and editing, analysis, and energy evaluation engines. This, when combined with an in-built computer algebra system, gives substantial flexibility to researchers to load, search for, edit, and combine molecular information from multiple sources and use that to drive novel algorithms by combining functionality from other programs. Sire is open source (GPL3) and is available via conda and at a free Jupyter notebook server at https://try.openbiosim.org. Sire is supported by the not-for-profit OpenBioSim community interest company.

Ligandability Assessment of IL-1β by Integrated Hit Identification Approaches

Human interleukin-1β (IL-1β) is a pro-inflammatory cytokine that plays a critical role in the regulation of the immune response and the development of various inflammatory diseases. In this publication, we disclose our efforts toward the discovery of IL-1β binders that interfere with IL-1β signaling. To this end, several technologies were used in parallel, including fragment-based screening (FBS), DNA-encoded library (DEL) technology, peptide discovery platform (PDP), and virtual screening. The utilization of distinct technologies resulted in the identification of new chemical entities exploiting three different sites on IL-1β, all of them also inhibiting the interaction with the IL-1R1 receptor. Moreover, we identified lysine 103 of IL-1β as a target residue suitable for the development of covalent, low-molecular-weight IL-1β antagonists.

Synthesis and Anti-Trypanosoma cruzi Activity of 3-Cyanopyridine Derivatives

Chagas disease (CD) is a parasitic neglected tropical disease (NTD) caused by the protozoan Trypanosoma cruzi that affects 6 million people worldwide, often resulting in financial burden, morbidity, and mortality in endemic regions. Given a lack of highly efficient and safe treatments, new, affordable, and fit-for-purpose drugs for CD are urgently needed. In this work, we present a hit-to-lead campaign for novel cyanopyridine analogues as antichagasic agents. In a phenotypic screening against intracellular T. cruzi, hits 1 and 2 were identified and displayed promising potency combined with balanced physicochemical properties. As part of the Lead Optimization Latin America consortium, a set of 40 compounds was designed, synthesized, and tested against T. cruzi intracellular amastigotes and relevant human cell lines. The structural modifications were focused on three positions: cyanopyridine core, linker, and right-hand side. The ADME properties of selected compounds, lipophilicity, kinetic solubility, permeability, and liver microsomal stability, were evaluated. Compounds 1-9 displayed good potency (EC50T. cruzi amastigote <1 μM), and most compounds did not present significant cytotoxicity (CC50 MRC-5 = 32-64 μM). Despite the good balance between potency and selectivity, the antiparasitic activity of the series appeared to be driven by lipophilicity, making the progression of the series unfeasible due to poor ADME properties and potential promiscuity issues.

In Silico Prediction of Oral Acute Rodent Toxicity Using Consensus Machine Learning

Acute oral toxicity (AOT) is required for the classification and labeling of chemicals according to the global harmonized system (GHS). Acute oral toxicity studies are optimized to minimize the use of animals. However, with the advent of the three Rs principles and machine learning in toxicology, alternative in silico methods became a reasonable alternative approach for addressing the AOT of new chemical matter. Here, we describe the compilation of AOT data from a commercial database and the development of a consensus classification model after evaluating different combinations of molecular representations and machine learning algorithms. The model shows significantly better performance compared to publicly available AOT models. Its performance was evaluated on an external validation data set, which was compiled from the literature, and an applicability domain was deduced.

Computational Insights into Prostaglandin E2 Ligand Binding and Activation of G-Protein-Coupled Receptors

G-protein coupled receptors (GPCRs) are eukaryotic integral membrane proteins that regulate signal transduction cascade pathways implicated in a variety of human diseases and are consequently of interest as drug targets. For this reason, it is of interest to investigate the way in which specific ligands bind and trigger conformational changes in the receptor during activation and how this in turn modulates intracellular signaling. In the present study, we investigate the way in which the ligand Prostaglandin E2 interacts with three GPCRs in the E-prostanoid family: EP1, EP2, and EP3. We examine information transfer pathways based on long-time scale molecular dynamics simulations using transfer entropy and betweenness centrality to measure the physical transfer of information among residues in the system. We monitor specific residues involved in binding to the ligand and investigate how the information transfer behavior of these residues changes upon ligand binding. Our results provide key insights that enable a deeper understanding of EP activation and signal transduction functioning pathways at the molecular level, as well as enabling us to make some predictions about the activation pathway for the EP1 receptor, for which little structural information is currently available. Our results should advance ongoing efforts in the development of potential therapeutics targeting these receptors.

Identification of selective dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) inhibitors and their effects on tau and microtubule

The overexpression of dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A), commonly observed in neurodegenerative diseases like Alzheimer's disease (AD) and Down syndrome (DS), can induce the formation of neurofibrillary tangles (NFTs) and amyloid plaques. Hence, designing a selective DYRK1A inhibitor would result in a promising small molecule for treating neurodegenerative diseases. Developing selective inhibitors for DYRK1A has been a difficult challenge due to the highly preserved ATP-binding site of protein kinases. In this study, we employed a structure-based virtual screening (SBVS) campaign targeting DYRK1A from a database containing 1.6 million compounds. Enzymatic assays were utilized to verify inhibitory properties, confirming that Y020-3945 and Y020-3957 showed inhibitory activity towards DYRK1A. In particular, the compounds exhibited high selectivity for DYRK1A over a panel of 120 kinases, reduced the phosphorylation of tau, and reversed the tubulin polymerization for microtubule stability. Additionally, treatment with the compounds significantly reduced the secretion of inflammatory cytokines IL-6 and TNF-α activated by DYRK1A-assisted NFTs and Aβ oligomers. These identified inhibitors possess promising therapeutic potential for conditions associated with DYRK1A in neurodegenerative diseases. The results showed that Y020-3945 and Y020-3957 demonstrated structural novelty compared to known DYRK1A inhibitors, making them a valuable addition to developing potential treatments for neurodegenerative diseases.

Synthesis and insecticidal activity of N-(5-phenylpyrazin-2-yl)-benzamide derivatives: Elucidation of mode of action on chitin biosynthesis through symptomology and genetic studies

Among the six-membered heterocycles, the pyrazine ring is poorly explored in crop protection and does not feature in any product listed in the current IRAC MoA classification. In an effort to identify new leads for internal research, we synthesized a series of N-(5-phenylpyrazin-2-yl)-benzamide derivatives and evaluated them for their insecticidal activity. N-(5-phenylpyrazin-2-yl)-benzamide derivatives 3 were prepared using an automated two-step synthesis protocol. These compounds were tested for their initial biological activity against a wide range of sucking and chewing insect pests and found to be active against lepidopterans only. More detailed experiments, including symptomology studies on the diamondback moth, Plutella xylostella (L.) and the Egyptian cotton leafworm, Spodoptera littoralis (Boisduval) showed that analog 3q causes severe abnormalities in the lepidopteran cuticle leading to larval mortality. Compound 3q shows strong potency against both P. xylostella and S. littoralis, whereas analog 3i shows better potency against S. littoralis causing also impaired cuticular structure and death of the larvae. Additionally, P. xylostella genetic studies showed that compound 3q resistance is linked to Chitin Synthase 1. Our studies show that N-(5-phenylpyrazin-2-yl)-benzamide derivatives 3, and in particular analogs 3i and 3q, act as insect growth modulator insecticides. Conformational similarities with lufenuron are discussed.

Scaffold hopping based designing of selective ALDH1A1 inhibitors to overcome cyclophosphamide resistance: synthesis and biological evaluation

Aldehyde dehydrogenase 1A1 (ALDH1A1) is an isoenzyme that catalyzes the conversion of aldehydes to acids. However, the overexpression of ALDH1A1 in a variety of malignancies is the major cause of resistance to an anti-cancer drug, cyclophosphamide (CP). CP is a prodrug that is initially converted into 4-hydroxycyclophosphamide and its tautomer aldophosphamide, in the liver. These compounds permeate into the cell and are converted as active metabolites, i.e., phosphoramide mustard (PM), through spontaneous beta-elimination. On the other hand, the conversion of CP to PM is diverted at the level of aldophosphamide by converting it into inactive carboxyphosphamide using ALDH1A1, which ultimately leads to high drug inactivation and CP resistance. Hence, in combination with our earlier work on the target of resistance, i.e., ALDH1A1, we hereby report selective ALDH1A1 inhibitors. Herein, we selected a lead molecule from our previous virtual screening and implemented scaffold hopping analysis to identify a novel scaffold that can act as an ALDH1A1 inhibitor. This results in the identification of various novel scaffolds. Among these, on the basis of synthetic feasibility, the benzimidazole scaffold was selected for the design of novel ALDH1A1 inhibitors, followed by machine learning-assisted structure-based virtual screening. Finally, the five best compounds were selected and synthesized. All synthesized compounds were evaluated using in vitro enzymatic assay against ALDH1A1, ALDH2, and ALDH3A1. The results disclosed that three molecules A1, A2, and A3 showed significant selective ALDH1A1 inhibitory potential with an IC50 value of 0.32 μM, 0.55 μM, and 1.63 μM, respectively, and none of the compounds exhibits potency towards the other two ALDH isoforms i.e. ALDH2 and ALDH3A1. Besides, the potent compounds (A1, A2, and A3) have been tested for in vitro cell line assay in combination with mafosfamide (analogue of CP) on two cell lines i.e. A549 and MIA-PaCa-2. All three compounds show significant potency to reverse mafosfamide resistance by inhibiting ALDH1A1 against these cell lines.

Harmaline to Human Mitochondrial Caseinolytic Serine Protease Activation for Pediatric Diffuse Intrinsic Pontine Glioma Treatment

Diffuse intrinsic pontine glioma (DIPG), affecting children aged 4-7 years, is a rare, aggressive tumor that originates in the pons and then spreads to nearby tissue. DIPG is the leading cause of death for pediatric brain tumors due to its infiltrative nature and inoperability. Radiotherapy has only a palliative effect on stabilizing symptoms. In silico and preclinical studies identified ONC201 as a cytotoxic agent against some human cancer cell lines, including DIPG ones. A single-crystal X-ray analysis of the complex of the human mitochondrial caseinolytic serine protease type C (hClpP) and ONC201 (PDB ID: 6DL7) allowed hClpP to be identified as its main target. The hyperactivation of hClpP causes damage to mitochondrial oxidative phosphorylation and cell death. In some DIPG patients receiving ONC201, an acquired resistance was observed. In this context, a wide program was initiated to discover original scaffolds for new hClpP activators to treat ONC201-non-responding patients. Harmaline, a small molecule belonging to the chemical class of β-carboline, was identified through Fingerprints for Ligands and Proteins (FLAP), a structure-based virtual screening approach. Molecular dynamics simulations and a deep in vitro investigation showed interesting information on the interaction and activation of hClpP by harmaline.

Molecular medicinal insights into scaffold hopping-based drug discovery success

In both academia and the pharmaceutical industry, innovative hypotheses, methodologies and technologies that can shorten the drug research and development, leading to higher success rates, are vital. In this review, we demonstrate how innovative variations of the scaffold-hopping strategy have been used to create new druggable molecular spaces, drugs, clinical candidates, preclinical candidates, and bioactive agents. We also analyze molecular modulations that enabled improvements of the pharmacodynamic (PD), physiochemical, and pharmacokinetic (PK) properties (P3 properties) of the drugs resulting from these scaffold-hopping strategies.

Alchemical Free Energy Workflows for the Computation of Protein-Ligand Binding Affinities

Alchemical free energy methods can be used for the efficient computation of relative binding free energies during preclinical drug discovery stages. In recent years, this has been facilitated further by the implementation of workflows that enable non-experts to quickly and consistently set up the required simulations. Given the correct input structures, workflows handle the difficult aspects of setting up perturbations, including consistently defining the perturbable molecule, its atom mapping and topology generation, perturbation network generation, running of the simulations via different sampling methods, and analysis of the results. Different academic and commercial workflows are discussed, including FEW, FESetup, FEPrepare, CHARMM-GUI, Transformato, PMX, QLigFEP, TIES, ProFESSA, PyAutoFEP, BioSimSpace, FEP+, Flare, and Orion. These workflows differ in various aspects, such as mapping algorithms or enhanced sampling methods. Some workflows can accommodate more than one molecular dynamics (MD) engine and use external libraries for tasks. Differences between workflows can present advantages for different use cases, however a lack of interoperability of the workflows' components hinders systematic comparisons.

Machine learning and traditional QSAR modeling methods: a case study of known PXR activators

Pregnane X receptor (PXR), extensively expressed in human tissues related to digestion and metabolism, is responsible for recognizing and detoxifying diverse xenobiotics encountered by humans. To comprehend the promiscuous nature of PXR and its ability to bind a variety of ligands, computational approaches, viz., quantitative structure-activity relationship (QSAR) models, aid in the rapid dereplication of potential toxicological agents and mitigate the number of animals used to establish a meaningful regulatory decision. Recent advancements in machine learning techniques accommodating larger datasets are expected to aid in developing effective predictive models for complex mixtures (viz., dietary supplements) before undertaking in-depth experiments. Five hundred structurally diverse PXR ligands were used to develop traditional two-dimensional (2D) QSAR, machine-learning-based 2D-QSAR, field-based three-dimensional (3D) QSAR, and machine-learning-based 3D-QSAR models to establish the utility of predictive machine learning methods. Additionally, the applicability domain of the agonists was established to ensure the generation of robust QSAR models. A prediction set of dietary PXR agonists was used to externally-validate generated QSAR models. QSAR data analysis revealed that machine-learning 3D-QSAR techniques were more accurate in predicting the activity of external terpenes with an external validation squared correlation coefficient (R2) of 0.70 versus an R2 of 0.52 in machine-learning 2D-QSAR. Additionally, a visual summary of the binding pocket of PXR was assembled from the field 3D-QSAR models. By developing multiple QSAR models in this study, a robust groundwork for assessing PXR agonism from various chemical backbones has been established in anticipation of the identification of potential causative agents in complex mixtures.

3D-QSAR and ADMET studies of morpholino-pyrimidine inhibitors of DprE1 from Mycobacterium tuberculosis

DprE1 is involved in the synthesis of Mycobacterium tuberculosis cell wall and is a potent drug target for Tuberculosis (TB) treatment. The structure and dynamics of the loops L-I and L-II flanking the inhibitor binding site was studied using molecular dynamics (MD) simulation and MMPBSA in Amber v18. Docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) of 55 Morpholino-pyrimidine (MP) inhibitors was carried out using Autodock v1.2.0 and Forge v10. ADMET analysis was done using SwissADME and pkCSM. All MP inhibitors docked in the DprE1 binding pocket, making contacts with L-II residues. MD studies showed that L-I and L-II unfold in the absence of the inhibitor but fold stably structure with reduced protein motions in the presence of MP-38, the highest affinity inhibitor. This was confirmed by k-means clustering and secondary structure analysis. L-II residues, L317, F320 and R325 contributed most towards the MMPBSA binding free energy of MP-38. A robust field-based 3D-QSAR model showed values of r2train = 0.982, r2test = 0.702 and q2 = 0.516. The MP inhibitor field points were broadly divided into negative electrostatics near the A, B rings and hydrophobic electrostatics near the D, E rings. Addition of negative groups at methanone position and ring B as well as addition of hydrophobic and bulky groups at ring E will improve activity. Highly active compounds 47, 49 and 50 of MP series exhibited highly favourable drug-like properties. SAR and ADMET insights attained from this model will help in the development of active DprE1 inhibitors in future.Communicated by Ramaswamy H. Sarma.

3D-QSAR assisted identification of selective CYP1B1 inhibitors: an effective bioisosteric replacement/molecular docking/electrostatic complementarity analysis

Cytochrome P450-1B1 is a majorly overexpressed drug-metabolizing enzyme in tumors and is responsible for inactivation and subsequent resistance to a variety of anti-cancer drugs, i.e., docetaxel, tamoxifen, and cisplatin. In the present study, a 3D quantitative structure-activity relationship (3D-QSAR) model has been constructed for the identification, design, and optimization of novel CYP1B1 inhibitors. The model has been built using a set of 148 selective CYP1B1 inhibitors. The developed model was evaluated based on certain statistical parameters including q2 and r2 which showed the acceptable predictive and descriptive capability of the generated model. The developed 3D-QSAR model assisted in understanding the key molecular fields which were firmly related to the selective CYP1B1 inhibition. A theoretic approach for the generation of new lead compounds with optimized CYP1B1 receptor affinity has been performed utilizing bioisosteric replacement analysis. These generated molecules were subjected to a developed 3D-QSAR model to predict the inhibitory activity potentials. Furthermore, these compounds were scrutinized through the activity atlas model, molecular docking, electrostatic complementarity, molecular dynamics, and waterswap analysis. The final hits might act as selective CYP1B1 inhibitors which could address the issue of resistance. This 3D-QSAR includes several chemically diverse selective CYP1B1 receptor ligands and well accounts for the individual ligand's inhibition affinities. These features of the developed 3D-QSAR model will ensure future prospective applications of the model to speed up the identification of new potent and selective CYP1B1 receptor ligands.

An Exploration of Small Molecules That Bind Human Single-Stranded DNA Binding Protein 1

Human single-stranded DNA binding protein 1 (hSSB1) is critical to preserving genome stability, interacting with single-stranded DNA (ssDNA) through an oligonucleotide/oligosaccharide binding-fold. The depletion of hSSB1 in cell-line models leads to aberrant DNA repair and increased sensitivity to irradiation. hSSB1 is over-expressed in several types of cancers, suggesting that hSSB1 could be a novel therapeutic target in malignant disease. hSSB1 binding studies have focused on DNA; however, despite the availability of 3D structures, small molecules targeting hSSB1 have not been explored. Quinoline derivatives targeting hSSB1 were designed through a virtual fragment-based screening process, synthesizing them using AlphaLISA and EMSA to determine their affinity for hSSB1. In parallel, we further screened a structurally diverse compound library against hSSB1 using the same biochemical assays. Three compounds with nanomolar affinity for hSSB1 were identified, exhibiting cytotoxicity in an osteosarcoma cell line. To our knowledge, this is the first study to identify small molecules that modulate hSSB1 activity. Molecular dynamics simulations indicated that three of the compounds that were tested bound to the ssDNA-binding site of hSSB1, providing a framework for the further elucidation of inhibition mechanisms. These data suggest that small molecules can disrupt the interaction between hSSB1 and ssDNA, and may also affect the ability of cells to repair DNA damage. This test study of small molecules holds the potential to provide insights into fundamental biochemical questions regarding the OB-fold.

Tetrazole and oxadiazole derivatives as bioisosteres of tariquidar and elacridar: New potent P-gp modulators acting as MDR reversers

New 2,5- and 1,5-disubstituted tetrazoles, and 2,5-disubstituted-1,3,4-oxadiazoles were synthesized as tariquidar and elacridar derivatives and studied as multidrug resistance (MDR) reversers. Their behaviour on the three ABC transporters P-gp, MRP1 and BCRP was investigated. All compounds inhibited the P-gp transport activity in MDCK-MDR1 cells overexpressing P-gp, showing EC50 values even in the low nanomolar range (compounds 15, 22). Oxadiazole derivatives were able to increase the antiproliferative effect of doxorubicin in MDCK-MDR1 and in HT29/DX cells confirming their nature of P-gp modulators, with derivative 15 being the most potent in these assays. Compound 15 also displayed a dual inhibitory effect showing good activities towards both P-gp and BCRP. A computational study suggested a common interaction pattern on P-gp for most of the potent compounds. The bioisosteric substitution of the amide group of lead compounds allowed identifying a new set of potent oxadiazole derivatives that modulate MDR through inhibition of the P-gp efflux activity. If compared to previous amide derivatives, the introduction of the heterocycle rings greatly enhances the activity on P-gp, introduces in two compounds a moderate inhibitory activity on MRP1 and maintains in some cases the effect on BCRP, leading to the unveiling of dual inhibitor 15.

Structure-Activity Relationships, Tolerability and Efficacy of Microtubule-Active 1,2,4-Triazolo[1,5-a]pyrimidines as Potential Candidates to Treat Human African Trypanosomiasis

Tubulin and microtubules (MTs) are potential protein targets to treat parasitic infections and our previous studies have shown that the triazolopyrimidine (TPD) class of MT-active compounds hold promise as antitrypanosomal agents. MT-targeting TPDs include structurally related but functionally diverse congeners that interact with mammalian tubulin at either one or two distinct interfacial binding sites; namely, the seventh and vinca sites, which are found within or between α,β-tubulin heterodimers, respectively. Evaluation of the activity of 123 TPD congeners against cultured Trypanosoma brucei enabled a robust quantitative structure-activity relationship (QSAR) model and the prioritization of two congeners for in vivo pharmacokinetics (PK), tolerability and efficacy studies. Treatment of T. brucei-infected mice with tolerable doses of TPDs significantly decreased blood parasitemia within 24 h. Further, two once-weekly doses at 10 mg/kg of a candidate TPD significantly extended the survival of infected mice relative to infected animals treated with vehicle. Further optimization of dosing and/or the dosing schedule of these CNS-active TPDs may provide alternative treatments for human African trypanosomiasis.

Optimization of 4-amino-pyridazin-3(2H)-one as a valid core scaffold for FABP4 inhibitors

Current clinical research suggests that fatty acid-binding protein 4 inhibitors (FABP4is), which are of biological and therapeutic interest, may show potential in treating cancer and other illnesses. We sought to uncover new structures through the optimization of the previously reported 4-amino and 4-ureido pyridazinone-based series of FABP4is as part of a larger research effort to create more potent FABP4 inhibitors. This led to the identification of 14e as the most potent analog with IC50  = 1.57 μM, which is lower than the IC50 of the positive control. Advanced modeling investigations and in silico absorption, distribution, metabolism, and excretion - toxicity calculations suggested that 14e represents a potential candidate for in vivo studies such as FABP4i.

Fragment merging approach for the design of thiazole/thiazolidine clubbed pyrazoline derivatives as anti-inflammatory agents: Synthesis, biopharmacological evaluation and molecular modeling studies

Fragment merging approach was applied for the design of thiazole/thiazolidinone clubbed pyrazoline derivatives 5a-e, 6a-c, 7 and 10a-d as dual COX-2 and 5-LOX inhibitors. Compounds 5a, 6a, and 6b were the most potent and COX-2 selective inhibitors (IC50= 0.03-0.06 μM, SI = 282.7-472.9) with high activity against 5-LOX (IC50 = 4.36-4.86 μM), while compounds 5b and 10a were active and selective 5-LOX inhibitors with IC50 = 2.43 and 1.58 μM, respectively. In vivo assay and histopathological examination for most active candidate 6a revealed significant decrease in inflammation with higher safety profile in comparison to standard drugs. Compound 6a exhibited the same orientation and binding interactions as the reference COX-2 and 5-LOX inhibitors (celecoxib and quercetin, respectively). Consequently, compound 6a has been identified as a potential lead for further optimization and the development of safe and effective anti-inflammatory drugs.

Molecular mechanisms of caramel-like odorant-olfactory receptor interactions based on a computational chemistry approach

Molecular mechanisms of caramel-like odorant-olfactory receptor interactions were investigated based on molecular docking and molecular dynamics simulations. The transmembrane regions TM-3, TM-5 and TM-6 of receptors were main contributors of amino acid residues in the docking. Molecular docking results showed that hydrogen bonding and pi-pi stacking were the key forces for the stabilization of caramel-like odorants. The binding energies were positively correlated with the molecular weight of caramel-like odorants. Residues Asn155 (84%, OR2W1), Asn206 (86%, OR8D1), Ser155 (77%, OR8D1), Asp179 (87%, OR5M3), Val182 (84%, OR2J2) and Tyr260 (94%, OR2J2) with high frequencies played an important role in the complexes formation. Odorants 4-hydroxy-5-methylfuran-3(2H)-one (16#) and methylglyoxal (128#) were screened by molecular field-based similarity analysis, which tended to bind to the receptors OR1G1 and OR52H1 respectively, resulting a caramel-like aroma perception. The obtained results are useful for better understanding the perception of caramel-like odorants and their high-throughput screening.

Identification of the Seaweed Metabolites as Potential Anti-tubercular Agents Against Human Pantothenate synthetase: An In Silico Approach

Tuberculosis is the disease which is caused due to the contagion of Mycobacterium tuberculosis. The multidrug resistance Mycobacterium tuberculosis is the main hassle in the treatment of this worldwide health threats. Pantothenate synthase is a legitimate goal for rational drug designing against Mycobacterium tuberculosis. The enzyme is most active in the presence of magnesium or manganese. Marine algal cell wall is rich in sulfated polysaccharides such as fucoidans (brown algae), κ-carrageenans (red algae), and ulvan (green algae) with various favorable biological activities such as anticoagulant, antiviral, antioxidative, anticancer, and immunomodulating activities. In this study, we have modeled binding modes of selected known anti-tubercular compounds and different solvent extract against pantothenate synthase using advanced docking program AutoDock 4.2 tool. In our current study, in silico experiments were carried out to determine if fucoidan, κ-carrageenan, and ulvan sulfated polysaccharides could be a potential target against PANc (pantothenate synthetase), with the goal of identifying potential inhibitors as anti-TB leads targeting PANc for further wet lab validation. Two bioactive compounds were docked to the Mtb pantothenate synthetase protein binding site, with docking scores ranging from - 5.57 to - 2.73. κ-carrageenan had the best pose and docking score, with a Ligand fit score of - 5.815. Ulvan did not dock with the protein. The molecular dynamics simulations were conducted with substrate and ligand bounded fucoidan and κ-carrageenan for 150 ns and the protein Mtb pantothenate synthetase showed a stable conformation in the simulation, with tight amino acid contributions binding to the ligand molecule. RMSD characterizes the conformation and stability of protein ligand complexes, with higher fluctuations indicating low stability and minimal low-level fluctuations indicating equilibration and stability. The graph for RMSF shows significant peaks due to fluctuations in active site regions and other peaks indicating the adaptation of the ligand molecule to the protein binding pocket. From the molecular dynamics study, it is clear that the compounds are having good binding affinity in the active site. The root mean square deviation, root mean square fluctuations, and radius of gyration are supportive evidences which helped us to conclude that the compounds κ-carrageenan and fucoidan are suitable lead molecules for inhibiting pantothenate synthetase. Based on these evidences, the natural compounds from seaweeds can be tested clinically either alone or in combinations against the protein, which could facilitate the designing or the synthesis of new lead molecules as drugs against the tuberculosis.

Design and Evaluation of a Low Hydrogen Bond Donor Count Fragment Screening Set to Aid Hit Generation of PROTACs Intended for Oral Delivery

The development of orally bioavailable PROTACs presents a significant challenge due to the inflated physicochemical properties of such heterobifunctional molecules. Molecules occupying this "beyond rule of five" space often demonstrate limited oral bioavailability due to the compounding effects of elevated molecular weight and hydrogen bond donor count (among other properties), but it is possible to achieve sufficient oral bioavailability through physicochemical optimization. Herein, we disclose the design and evaluation of a low hydrogen bond donor count (≤1 HBD) fragment screening set to aid hit generation of PROTACs intended for an oral route of delivery. We demonstrate that application of this library can enhance fragment screens against PROTAC proteins of interest and ubiquitin ligases, yielding fragment hits containing ≤1 HBD suitable for optimizing toward orally bioavailable PROTACs.

Antiviral Activity of Acetylsalicylic Acid against Bunyamwera Virus in Cell Culture

The Bunyavirales order is a large group of RNA viruses that includes important pathogens for humans, animals and plants. With high-throughput screening of clinically tested compounds we have looked for potential inhibitors of the endonuclease domain of a bunyavirus RNA polymerase. From a list of fifteen top candidates, five compounds were selected and their antiviral properties studied with Bunyamwera virus (BUNV), a prototypic bunyavirus widely used for studies about the biology of this group of viruses and to test antivirals. Four compounds (silibinin A, myricetin, L-phenylalanine and p-aminohippuric acid) showed no antiviral activity in BUNV-infected Vero cells. On the contrary, acetylsalicylic acid (ASA) efficiently inhibited BUNV infection with a half maximal inhibitory concentration (IC₅₀) of 2.02 mM. In cell culture supernatants, ASA reduced viral titer up to three logarithmic units. A significant dose-dependent reduction of the expression levels of Gc and N viral proteins was also measured. Immunofluorescence and confocal microscopy showed that ASA protects the Golgi complex from the characteristic BUNV-induced fragmentation in Vero cells. Electron microscopy showed that ASA inhibits the assembly of Golgi-associated BUNV spherules that are the replication organelles of bunyaviruses. As a consequence, the assembly of new viral particles is also significantly reduced. Considering its availability and low cost, the potential usability of ASA to treat bunyavirus infections deserves further investigation.

A pharmacophore-based approach to demonstrating the scope of alcohol dehydrogenases

Barriers to the ready adoption of biocatalysis into asymmetric synthesis for early stage medicinal chemistry are addressed, using ketone reduction by alcohol dehydrogenase as a model reaction. An efficient substrate screening approach is used to show the wide substrate scope of commercial alcohol dehydrogenase enzymes, with a high tolerance to chemical groups employed in drug discovery (heterocycle, trifluoromethyl and nitrile/nitro groups) observed. We use our screening data to build a preliminary predictive pharmacophore-based screening tool using Forge software, with a precision of 0.67/1, demonstrating the potential for developing substrate screening tools for commercially available enzymes without publicly available structures. We hope that this work will facilitate a culture shift towards adopting biocatalysis alongside traditional chemical catalytic methods in early stage drug discovery.

An Investigation of the Antiviral Potential of Phytocompounds against Avian Infectious Bronchitis Virus through Template-Based Molecular Docking and Molecular Dynamics Simulation Analysis

Vaccination is widely used to control Infectious Bronchitis in poultry; however, the limited cross-protection and safety issues associated with these vaccines can lead to vaccination failures. Keeping these limitations in mind, the current study explored the antiviral potential of phytocompounds against the Infectious Bronchitis virus using in silico approaches. A total of 1300 phytocompounds derived from fourteen botanicals were screened for their potential ability to inhibit the main protease, papain-like protease or RNA-dependent RNA–polymerase of the virus. The study identified Methyl Rosmarinate, Cianidanol, Royleanone, and 6,7-Dehydroroyleanone as dual-target inhibitors against any two of the key proteins. At the same time, 7-alpha-Acetoxyroyleanone from Rosmarinus officinalis was found to be a multi-target protein inhibitor against all three proteins. The potential multi-target inhibitor was subjected to molecular dynamics simulations to assess the stability of the protein–ligand complexes along with the corresponding reference ligands. The findings specified stable interactions of 7-alpha-Acetoxyroyleanone with the protein targets. The results based on the in silico study indicate that the phytocompounds can potentially inhibit the essential proteins of the Infectious Bronchitis virus; however, in vitro and in vivo studies are required for validation. Nevertheless, this study is a significant step in exploring the use of botanicals in feed to control Infectious Bronchitis infections in poultry.

Steered Molecular Dynamics Simulations Study on FABP4 Inhibitors

Ordinary small molecule de novo drug design is time-consuming and expensive. Recently, computational tools were employed and proved their efficacy in accelerating the overall drug design process. Molecular dynamics (MD) simulations and a derivative of MD, steered molecular dynamics (SMD), turned out to be promising rational drug design tools. In this paper, we report the first application of SMD to evaluate the binding properties of small molecules toward FABP4, considering our recent interest in inhibiting fatty acid binding protein 4 (FABP4). FABP4 inhibitors (FABP4is) are small molecules of therapeutic interest, and ongoing clinical studies indicate that they are promising for treating cancer and other diseases such as metabolic syndrome and diabetes.

Structure-Activity Relationships, Tolerability and Efficacy of Microtubule-Active 1,2,4-Triazolo[1,5- a ]pyrimidines as Potential Candidates to Treat Human African Trypanosomiasis

Tubulin and microtubules (MTs) are potential protein targets to treat parasitic infections and our previous studies have shown that the triazolopyrimidine (TPD) class of MT- active compounds hold promise as antitrypanosomal agents. MT-targeting TPDs include structurally related but functionally diverse congeners that interact with mammalian tubulin at either one or two distinct interfacial binding sites; namely, the seventh and vinca sites, which are found within or between α,β-tubulin heterodimers, respectively. Evaluation of the activity of 123 TPD congeners against cultured Trypanosoma brucei enabled a robust quantitative structure-activity relationship (QSAR) model and the prioritization of two congeners for in vivo pharmacokinetics (PK), tolerability and efficacy studies. Treatment of T. brucei -infected mice with tolerable doses of TPDs 3 and 4 significantly decreased blood parasitemia within 24 h. Further, two once-weekly doses of 4 at 10 mg/kg significantly extended the survival of infected mice relative to infected animals treated with vehicle. Further optimization of dosing and/or the dosing schedule of these CNS-active TPDs may provide alternative treatments for human African trypanosomiasis.

Accelerated Discovery of Macrocyclic CDK2 Inhibitor QR-6401 by Generative Models and Structure-Based Drug Design

Selective CDK2 inhibitors have the potential to provide effective therapeutics for CDK2-dependent cancers and for combating drug resistance due to high cyclin E1 (CCNE1) expression intrinsically or CCNE1 amplification induced by treatment of CDK4/6 inhibitors. Generative models that take advantage of deep learning are being increasingly integrated into early drug discovery for hit identification and lead optimization. Here we report the discovery of a highly potent and selective macrocyclic CDK2 inhibitor QR-6401 (23) accelerated by the application of generative models and structure-based drug design (SBDD). QR-6401 (23) demonstrated robust antitumor efficacy in an OVCAR3 ovarian cancer xenograft model via oral administration.

In Silico Identification of Novel Derivatives of Rifampicin Targeting Ribonuclease VapC2 of M. tuberculosis H37Rv: Rifampicin Derivatives Target VapC2 of Mtb H37Rv

The emergence of multi-drug-resistant Mycobacterium tuberculosis (Mtb) strains has rendered many of the currently available anti-TB drugs ineffective. Hence, there is a pressing need to discover new potential drug targets/candidates. In this study, attempts have been made to identify novel inhibitors of the ribonuclease VapC2 of Mtb H37Rv using various computational techniques. Ribonuclease VapC2 Mtb H37Rv's protein structure was retrieved from the PDB databank, 22 currently used anti-TB drugs were retrieved from the PubChem database, and protein-ligand interactions were analyzed by docking studies. Out of the 22 drugs, rifampicin (RIF), being a first-line drug, showed the best binding energy (-8.8 Kcal/mol) with Mtb H37Rv VapC2; hence, it was selected as a parent molecule for the design of its derivatives. Based on shape score and radial plot criteria, out of 500 derivatives designed through SPARK (Cresset^®, Royston, UK) program, the 10 best RIF derivatives were selected for further studies. All the selected derivatives followed the ADME criteria concerning drug-likeness. The docking of ribonuclease VapC2 with RIF derivatives revealed the best binding energy of -8.1 Kcal/mol with derivative 1 (i.e., RIF-155841). A quantitative structure-activity relationship study revealed that derivative 1's activity assists in the inhibition of ribonuclease VapC2. The stability of the VapC2-RIF155841 complex was evaluated using molecular dynamics simulations for 50 ns and the complex was found to be stable after 10 nsec. Further, a chemical synthesis scheme was designed for the newly identified RIF derivative (RIF-155841), which verified that its chemical synthesis is possible for future in vitro/in vivo experimental validation. Overall, this study evaluated the potential of the newly designed RIF derivatives with respect to the Mtb VapC2 protein, which is predicted to be involved in some indispensable processes of the related pathogen. Future experimental studies regarding RIF-155841, including the exploration of the remaining RIF derivatives, are warranted to verify our current findings.

Rational design of novel nucleoside analogues reveals potent antiviral agents for EV71

Different viruses belonging to distinct viral families, such as enterovirus 71, rely on the host methyltransferase METTL3 for the completion of fundamental cytoplasmic stages of their life cycle. Modulation of the activity of this enzyme could therefore provide a broad-spectrum approach to interfere with viral infections caused by viruses that depend on its activity for the completion of their viral cycle. With the aim to identify antiviral therapeutics with this effect, a series of new nucleoside analogues was rationally designed to act as inhibitors of human METTL3, as a novel approach to interfere with a range of viral infections. Guided by molecular docking studies on the SAM binding pocket of the enzyme, 24 compounds were prepared following multiple-step synthetic protocols, and evaluated for their ability to interfere with the replication of different viruses in cell-based systems, and to directly inhibit the activity of METTL3. While different molecules displayed moderate inhibition of the human methyltransferase in vitro, multiple novel, potent and selective inhibitors of enterovirus 71 were identified.

1,2-Dibenzoylhydrazine as a Multi-Inhibitor Compound: A Morphological and Docking Study

In the framework of the multitarget inhibitor study, we report an in silico analysis of 1,2-dibenzoylhydrazine (DBH) with respect to three essential receptors such as the ecdysone receptor (EcR), urease, and HIV-integrase. Starting from a crystallographic structural study of accidentally harvested crystals of this compound, we performed docking studies to evaluate the inhibitory capacity of DBH toward three selected targets. A crystal morphology prediction was then performed. The results of our molecular modeling calculations indicate that DBH is an excellent candidate as a ligand to inhibit the activity of EcR receptors and urease. Docking studies also revealed the activity of DBH on the HIV integrase receptor, providing an excellent starting point for developing novel inhibitors using this molecule as a starting lead compound.

Rapid discovery and classification of inhibitors of coronavirus infection by pseudovirus screen and amplified luminescence proximity homogeneous assay

To identify potent antiviral compounds, we introduced a high-throughput screen platform that can rapidly classify hit compounds according to their target. In our platform, we performed a compound screen using a lentivirus-based pseudovirus presenting a spike protein of coronavirus, and we evaluated the hit compounds using an amplified luminescence proximity homogeneous assay (alpha) test with purified host receptor protein and the receptor binding domain of the viral spike. With our screen platform, we were able to identify both spike-specific compounds (class I) and broad-spectrum antiviral compounds (class II). Among the hit compounds, thiosemicarbazide was identified to be selective to the interaction between the viral spike and its host cell receptor, and we further optimized the binding potency of thiosemicarbazide through modification of the pyridine group. Among the class II compounds, we found raloxifene and amiodarone to be highly potent against human coronaviruses including Middle East respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), and SARS-CoV-2. In particular, using analogs of the benzothiophene moiety, which is also present in raloxifene, we have identified benzothiophene as a novel structural scaffold for broad-spectrum antivirals. This work highlights the strong utility of our screen platform using a pseudovirus assay and an alpha test for rapid identification of potential antiviral compounds and their mechanism of action, which can lead to the accelerated development of therapeutics against newly emerging viral infections.

Integration of molecular modelling and in vitro studies to inhibit LexA proteolysis

Introduction

As antibiotic resistance has become more prevalent, the social and economic impacts are increasingly pressing. Indeed, bacteria have developed the SOS response which facilitates the evolution of resistance under genotoxic stress. The transcriptional repressor, LexA, plays a key role in this response. Mutation of LexA to a non-cleavable form that prevents the induction of the SOS response sensitizes bacteria to antibiotics. Achieving the same inhibition of proteolysis with small molecules also increases antibiotic susceptibility and reduces drug resistance acquisition. The availability of multiple LexA crystal structures, and the unique Ser-119 and Lys-156 catalytic dyad in the protein enables the rational design of inhibitors.

Methods

We pursued a binary approach to inhibit proteolysis; we first investigated β-turn mimetics, and in the second approach we tested covalent warheads targeting the Ser-119 residue. We found that the cleavage site region (CSR) of the LexA protein is a classical Type II β-turn, and that published 1,2,3-triazole compounds mimic the β-turn. Generic covalent molecule libraries and a β-turn mimetic library were docked to the LexA C-terminal domain using molecular modelling methods in FlexX and CovDock respectively. The 133 highest-scoring molecules were screened for their ability to inhibit LexA cleavage under alkaline conditions. The top molecules were then tested using a RecA-mediated cleavage assay.

Results

The β-turn library screen did not produce any hit compounds that inhibited RecA-mediated cleavage. The covalent screen discovered an electrophilic serine warhead that can inhibit LexA proteolysis, reacting with Ser-119 via a nitrile moiety.

Discussion

This research presents a starting point for hit-to-lead optimisation, which could lead to inhibition of the SOS response and prevent the acquisition of antibiotic resistance.

Insilico Screening of Pentacyclic Triterpenoids against Vascular Dementia Target's

Vascular dementia (VaD) accounts to 30% of cases and is predicted as second most common form of dementia after Alzheimer's disease by WHO. Earlier studies reported that plant-derived pentacyclic triterpenoids possess a wide range of pharmacological activities but these compounds are not extensively studied for their neuroprotective potential against VaD. This in silico approach was designed to screen 20 pentacyclic triterpenoid plant compounds against known targets of VaD using Flare software. S-Adenyl homocysteine hydrolase, Acetylcholinesterase, and Butyrylcholinesterase were selected as important VaD targets, and various parameters like intermolecular interaction energies, binding energy, and dock scores were analyzed and compared between selected ligands. Our results showed that Ursolic acid has lowest binding energy when docked with most of the target proteins, and among all 20 pentacyclic triterpenoids studied, only three ligands Betulinic acid, Ambolic acid, and Madecassic acid, showed better binding energy scores, and they can be shortlisted as lead compounds to further study their therapeutic potential against VaD using in vitro and in vivo animal models.

Identification of potent and selective inhibitors of PKR via virtual screening and traditional design

Protein Kinase RNA-activated (PKR) inhibition is thought to be relevant for immunology due to the potential to reduce macrophage and dendritic cell responses to bacteria and its signaling downstream of TNFα. PKR is also associated with neuroscience indications such as Alzheimer's disease due to its activation by the double stranded DNA (dsDNA) virus HSV1, a virus suggested to be important in the development of AD. Studies exploring the mechanistic role of PKR with existing tool molecules such as the tricyclic oxindole C16 are clouded by the poor selectivity profile of this ATP-competitive, Type I kinase inhibitor. Type II kinase leads such as the benzothiophene or pyrazolopyrimidine scaffolds from literature are equally poor in their selectivity profiles. As such, it became necessary to identify more potent and selective chemical matter to better understand PKR biology. A dual approach was taken. The first step of the strategy included virtual screening of the AbbVie compound collection. A combination of pharmacophore-based and GPU shape-based screening was pursued to identify selective chemical matter from promiscuous leads. The second step of the strategy followed traditional compound design. This step initiated from a literature lead with PKR cross reactivity. Combined, the two parallel efforts led to identification of more selective leads for investigation of PKR biology.

3D QSAR based Virtual Screening of Flavonoids as Acetylcholinesterase Inhibitors

In an attempt to develop therapeutic agents to treat Alzheimer's disease, a series of flavonoid analogues were collected, which already had established acetylcholinesterase (AChE) enzyme inhibition activity. For each molecule we also collected biological activity data (Ki). Then, 3D-QSAR (quantitative structure-activity relationship model) was developed which showed acceptable predictive and descriptive capability as represented by standard statistical parameters r2 and q2. This SAR data can explain the key descriptors which can be related to AChE inhibitory activity. Using the QSAR model, pharmacophores were developed based on which, virtual screening was done and a dataset was obtained which loaded as a prediction set to fit the developed QSAR model. Top 10 compounds fitting the QSAR model were subjected to molecular docking. CHEMBL1718051 was found to be the lead compound. This study is offering an example of a computationally-driven tool for prioritisation and discovery of probable AChE inhibitors. Further, in vivo and in vitro testing will show its therapeutic potential.

Design, synthesis, and biological evaluation of novel HSP27 inhibitors to sensitize lung cancer cells to clinically available anticancer agents

Expression of heat shock protein (HSP) correlates with the oncogenic status of malignant cells and plays an important role in tumorigenesis. HSP27 is constitutively expressed at specific stages of cancer development, and several clinical trials have reported correlations between HSP27 expression and tumor progression, metastasis, and chemoresistance in various types of cancer cells. These findings indicate that HSP27 is a major drug target, particularly in chemo-resistant cancers. As part of our ongoing efforts to improve the previously identified J2, a HSP27 cross-linker, we, in this study, report the identification of NK16 as a novel inducer of abnormal HSP27 dimers that did not affect the expression of HSP90 in an NCI-H460 lung cancer cell model. When NCI-H460 cells were treated with NK16 in combination with the anticancer drug cisplatin or paclitaxel, cleavage of PARP and caspase-3 was increased compared to administration of cisplatin or paclitaxel alone. Similar results were obtained in an NCI-H460-xenografted mouse model, in which tumor growth was suppressed more by co-administration of NK16 and paclitaxel than by paclitaxel alone. We propose NK16 as a meaningful strategy to improve the anticancer efficacy of cisplatin and paclitaxel.

QSAR, molecular docking, molecular dynamics and MM-GBSA approach for identification of prospective benzotriazole-based SARS-CoV 3CL protease inhibitors

The 3CL Protease of severe acute respiratory syndrome coronavirus (SARS-CoV), responsible for viral replication, has emerged as an essential target for designing anti-coronaviral inhibitors in drug discovery. In recent years, small molecule and peptidomimetic inhibitors have been used to target the inhibition of SARS-CoV 3CL Protease. In this study, we have developed 2D and 3D Quantitative structure activity relationship (QSAR) models on 3CL protease inhibitors with good predictive capability to propose inhibitors with improved affinities. Based on the 3 D contour maps, three new inhibitors were designed in silico, which were further subjected to molecular docking to explore their binding modes. The newly designed compounds showed improved interaction energies toward SARS-CoV-3CLPro due to additional interactions with the active site residues. The molecular docking studies of the most potent compounds revealed specific interactions with Glu 166 and Cys 145. Furthermore, absorption, distribution, metabolism, elimination (ADME) and drug-likeness evaluation revealed improved pharmacokinetic properties for these compounds. The molecular dynamics simulations confirmed the stability of the interactions identified by docking. The results presented would guide the development of new 3CL protease inhibitors with improved affinities in the future.Communicated by Ramaswamy H. Sarma.

Synthesis, characterization, anticancer and in silico studies of a pyrazole-tethered thiazolidine-2,4-dione derivative

A new pyrazole-tethered thiazolidine-2,4-dione derivative (8) has been synthesized by the Knoevenagel condensation of 3-(4-nitrophenyl)-1-phenyl-1H-pyrazole-4-carbaldehyde (4) and 3-(2,4-dioxothiazolidin-3-yl)propanenitrile (7). The structure of the final compound was confirmed by standard spectroscopic techniques including IR spectroscopy, ¹H-NMR spectroscopy, and ESI-MS mass spectrometry. Molecular features including frontier molecular orbital (HOMO-LUMO) energies, reactivity descriptors and molecular electrostatic potential (ESP) of the title molecule were determined using density functional theory (DFT) calculation. The in vitro cytotoxicity of both the intermediate (4) and final (8) compounds were investigated against cancerous (SW-480 and MCF-7) and normal (HEK-293) cell lines by MTT assay. Compound (8) displayed higher activity than (4) with higher sensitivity against breast cancer cell line and lesser toxicity. The experimental data were further complemented by docking and absorption, distribution, metabolism, and excretion (ADME) studies.Communicated by Ramaswamy H. Sarma.

[5]-Helistatins: Tubulin-Binding Helicenes with Antimitotic Activity

Helicenes are high interest synthetic targets with unique conjugated helical structures that have found important technological applications. Despite this interest, helicenes have had limited impact in chemical biology. Herein, we disclose a first-in-class antimitotic helicene, helistatin 1 (HA-1), where the helicene scaffold acts as a structural mimic of colchicine, a known antimitotic drug. The synthesis proceeds via sequential Pd-catalyzed coupling reactions and a π-Lewis acid cycloisomerization mediated by PtCl₂. HA-1 was found to block microtubule polymerization in both cell-free and live cell assays. Not only does this demonstrate the feasibility of using helicenes as bioactive scaffolds against protein targets, but also suggests wider potential for the use of helicenes as isosteres of biaryls or cis-stilbenes-themselves common drug and natural product scaffolds. Overall, this study further supports future opportunities for helicenes for a range of chemical biological applications.

Concepts and applications of chemical fingerprint for hit and lead screening

Molecular fingerprints are used to represent chemical (structural, physicochemical, etc.) properties of large-scale chemical sets in a low computational cost way. They have a prominent role in transforming chemical data sets into consistent input formats (bit strings or numeric values) suitable for in silico approaches. In this review, we summarize and classify common and state-of-the-art fingerprints into eight different types (dictionary based, circular, topological, pharmacophore, protein-ligand interaction, shape based, reinforced, and multi). We also highlight applications of fingerprints in early drug research and development (R&D). Thus, this review provides a guide for the selection of appropriate fingerprints of compounds (or ligand-protein complexes) for use in drug R&D.

Ligand Growing Experiments Suggested 4-amino and 4-ureido pyridazin-3(2H)-one as Novel Scaffold for FABP4 Inhibition

Fatty acid binding protein (FABP4) inhibitors are of synthetic and therapeutic interest and ongoing clinical studies indicate that they may be a promise for the treatment of cancer, as well as other diseases. As part of a broader research effort to develop more effective FABP4 inhibitors, we sought to identify new structures through a two-step computing assisted molecular design based on the established scaffold of a co-crystallized ligand. Novel and potent FABP4 inhibitors have been developed using this approach and herein we report the synthesis, biological evaluation and molecular docking of the 4-amino and 4-ureido pyridazinone-based series.