A genetic algorithm for flexible molecular overlay and pharmacophore elucidation

Fluorescence theranostic PROTACs for real-time visualization of ERα degradation

Proteolysis targeting chimera (PROTAC) technology, a groundbreaking strategy for degradation of pathogenic proteins by hijacking of the ubiquitin-proteasome-system has become a promising strategy in drug design. However, the real-time monitoring and visualization of protein degradation processes have been long-standing challenges in the realm of drug development. In this research, we sought to amalgamate the highly efficient protein-degrading capabilities of PROTAC technology with the visualization attributes of fluorescent probes, with the potential to pave the path for the design and development of a novel class of visual PROTACs. These novel PROTACs uniquely possess both fluorescence imaging and therapeutic characteristics, all with the goal of enabling real-time observations of protein degradation processes. Our approach involved the utilization of a high ER-targeting fluorescent probe, previously reported in our laboratory, which served as a warhead that specifically binds to the protein of interest (POI). Additionally, a VHL ligand for recruiting E3 ligase and linkers of various lengths were incorporated to synthesize a series of novel ER-inherent fluorescence PROTACs. Among them, compound A3 demonstrated remarkable efficiency in degrading ERα proteins (DC50 = 0.12 μM) and displaying exceptional anti-proliferative activity against MCF-7 cells (IC50 = 0.051 μM). Furthermore, it exhibited impressive fluorescence imaging performance, boasting an emission wavelength of up to 582 nm, a Stokes shift of 116 nm, and consistent optical properties. These attributes make it especially suitable for the real-time, in situ tracking of ERα protein degradation processes, thus may serve as a privileged visual theranostic PROTAC for ERα+ breast cancer. This study not only broadens the application spectrum of PROTAC technology but also introduces a novel approach for real-time visualization of protein degradation processes, ultimately enhancing the diagnostic and treatment efficacy of PROTACs.

Design, synthesis, and in-silico study of novel triarylethylene analogs with dual anti-estrogenic and serotonergic activity

Estrogen receptor is an important target in breast cancer. Serotonin receptors (5-HT2A and 5-HT2C , in particular) were investigated for a potential role in development and progression of breast cancer. Ligands that interact with estrogenic receptors influence the emotional state of females. Thus, designing selective estrogen receptor modulator (SERM) analogs with potential serotonergic activity is a plausible approach. The dual ligands can augment cytotoxic effect of SERMs, help in both physical and emotional menopausal symptom relief, enhance cognitive function and support bone health. Herein, we report triarylethylene analogs as potential candidates for treatment of breast cancer. Compound 2e showed (ERα relative β- galactosidase activity = 0.70), 5-HT2A (Ki  = 0.97 µM), and 5-HT2C (Ki  = 3.86 µM). It was more potent on both MCF-7 (GI50  = 0.27 µM) and on MDA-MB-231 (GI50  = 1.86 µM) compared to tamoxifen (TAM). Compound 4e showed 40 times higher antiproliferative activity on MCF-7 and 15 times on MDA-MBA compared to TAM. Compound 4e had higher average potency than TAM on all nine tested cell line panels. Our in-silico model revealed the binding interactions of compounds 2 and 2e in the three receptors; further structural modifications are suggested to optimize binding to the ERα, 5-HT2A , and 5-HT2C .

An Updated Review on Developing Small Molecule Kinase Inhibitors Using Computer-Aided Drug Design Approaches

Small molecule kinase inhibitors (SMKIs) are of heightened interest in the field of drug research and development. There are 79 (as of July 2023) small molecule kinase inhibitors that have been approved by the FDA and hundreds of kinase inhibitor candidates in clinical trials that have shed light on the treatment of some major diseases. As an important strategy in drug design, computer-aided drug design (CADD) plays an indispensable role in the discovery of SMKIs. CADD methods such as docking, molecular dynamic, quantum mechanics/molecular mechanics, pharmacophore, virtual screening, and quantitative structure-activity relationship have been applied to the design and optimization of small molecule kinase inhibitors. In this review, we provide an overview of recent advances in CADD and SMKIs and the application of CADD in the discovery of SMKIs.

3-Heptylidene-4,6-Dimethoxy-3H-Isobenzofuran-1-One Is Genotoxic, Increases the Frequency of Cell Death, and Potentiates the Effects of Cyclophosphamide and Cisplatin

3-heptylidene-4,6-dimethoxy-3H-isobenzofuran-1-one (Phthalide 1) is the precursor of three resorcinol lipids that have been described as potential chemotherapeutic agents and capable of potentiating the effects of cyclophosphamide. In this study, we evaluated the genotoxic potential, cell-killing potential, and interactions with cyclophosphamide and cisplatin of phthalide 1. Twelve groups were created from 120 mice: Negative Control, cyclophosphamide (100 mg/kg), cisplatin (6 mg/kg), Phthalide 1 (5, 10 and 20 mg/kg), and associations of 1 with cyclophosphamide and 1 with cisplatin. The results demonstrate that 1 increases (p < 0.05) the frequency of chromosomal damage, liver and kidney cell death, and splenic phagocytosis. The association of 1 with cyclophosphamide and cisplatin demonstrated a chemopreventive effect and, therefore, a reduction (p < 0.05) in the frequency of chromosomal damage. However, cell death and splenic phagocytosis did not suffer significant variations. As a result of the above, 1 has potential chemotherapeutic application and may be a candidate for developing a new generation of chemotherapeutics. In addition, it has characteristics to be used as a chemotherapy adjuvant in association with cyclophosphamide and cisplatin since it increases the frequency of cell death induced by chemotherapy. We also reported that the chemopreventive effect of 1, in association with cyclophosphamide and cisplatin, can prevent adverse effects (induction of DNA damage in non-tumor cells) without interfering with the mode of action of chemotherapy drugs and, therefore, without reducing the induction of cell death.

ZIM, a Norbornene Derived from 4-Aminoantipyrine, Induces DNA Damage and Cell Death but in Association Reduces the Effect of Commercial Chemotherapeutics

Cancer incidence is increasing, and the drugs are not very selective. These drugs cause adverse effects, and the cells become resistant. Therefore, new drugs are needed. Here, we evaluated the effects of ZIM, a candidate for chemotherapy, and 4-AA alone and in association with commercial chemotherapeutic agents. Subsequently, the results of ZIM and 4-AA were compared. Male Swiss mice were treated with doses of 12, 24, or 48 mg/kg ZIM or 4-AA alone or in association with cisplatin (6 mg/kg), doxorubicin (16 mg/kg), and cyclophosphamide (100 mg/kg). Biometric parameters, DNA damage (comet and micronuclei), cell death, and splenic phagocytosis were evaluated. DNA docking was also performed to confirm the possible interactions of ZIM and 4-AA with DNA. 4-AA has been shown to have low genotoxic potential, increase the frequency of cell death, and activate phagocytosis. ZIM causes genomic and chromosomal damage in addition to causing cell death and activating phagocytosis. In association with chemotherapeutical agents, both 4-AA and ZIM have a chemopreventive effect and, therefore, reduce the frequency of DNA damage, cell death, and splenic phagocytosis. The association of 4-AA and ZIM with commercial chemotherapeutic agents increased the frequency of lymphocytes compared to chemotherapeutic agents alone. Molecular docking demonstrated that ZIM has more affinity for DNA than 4-AA and its precursors (1 and 2). This was confirmed by the lower interaction energy of the complex (-119.83 kcal/mol). ZIM can break the DNA molecule and, therefore, its chemotherapeutic effect can be related to DNA damage. It is considered that ZIM has chemotherapeutic potential. However, it should not be used in combination with cisplatin, doxorubicin, and cyclophosphamide as it reduces the effects of these drugs.

ELIXIR-A: An Interactive Visualization Tool for Multi-Target Pharmacophore Refinement

Pharmacophore modeling is an important step in computer-aided drug design for identifying interaction points between the receptor and ligand complex. Pharmacophore-based models can be used for de novo drug design, lead identification, and optimization in virtual screening as well as for multi-target drug design. There is a need to develop a user-friendly interface to filter the pharmacophore points resulting from multiple ligand conformations. Here, we present ELIXIR-A, a Python-based pharmacophore refinement tool, to help refine the pharmacophores between multiple ligands from multiple receptors. Furthermore, the output can be easily used in virtual pharmacophore-based screening platforms, thereby contributing to the development of drug discovery.

Identification of New KRAS G12D Inhibitors through Computer-Aided Drug Discovery Methods

Owing to several mutations, the oncogene Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) is activated in the majority of cancers, and targeting it has been pharmacologically challenging. In this study, using an in silico approach comprised of pharmacophore modeling, molecular docking, and molecular dynamics simulations, potential KRAS G12D inhibitors were investigated. A ligand-based common feature pharmacophore model was generated to identify the framework necessary for effective KRAS inhibition. The chemical features in the selected pharmacophore model comprised two hydrogen bond donors, one hydrogen bond acceptor, two aromatic rings and one hydrophobic feature. This model was used for screening in excess of 214,000 compounds from InterBioScreen (IBS) and ZINC databases. Eighteen compounds from the IBS and ten from the ZINC database mapped onto the pharmacophore model and were subjected to molecular docking. Molecular docking results highlighted a higher affinity of four hit compounds towards KRAS G12D in comparison to the reference inhibitor, BI-2852. Sequential molecular dynamics (MD) simulation studies revealed all four hit compounds them possess higher KRAS G12D binding free energy and demonstrate stable polar interaction with key residues. Further, Principal Component Analysis (PCA) analysis of the hit compounds in complex with KRAS G12D also indicated stability. Overall, the research undertaken provides strong support for further in vitro testing of these newly identified KRAS G12D inhibitors, particularly Hit1 and Hit2.

Fundamental considerations in drug design

The drug discovery paradigm has been very time-consuming, challenging, and expensive; however, the disease conditions originating from bacteria, virus, protozoa, fungus and other microorganisms are steadily shooting up. For instance, COVID-19 is the latest viral infection that affects millions of people and the world’s economy very severely. Therefore, the quest for discovery of novel and potent drug compounds against deadly pathogens is crucial at the moment. Despite a lot of drawbacks in drug discovery and development and its pertaining technology, the advancement must be taken into account so the time duration and cost would be minimized. In this chapter, basic principles in drug design and discovery have been discussed together with advances in drug development.

An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19

The recent outbreak of the deadly coronavirus disease 19 (COVID-19) pandemic poses serious health concerns around the world. The lack of approved drugs or vaccines continues to be a challenge and further necessitates the discovery of new therapeutic molecules. Computer-aided drug design has helped to expedite the drug discovery and development process by minimizing the cost and time. In this review article, we highlight two important categories of computer-aided drug design (CADD), viz., the ligand-based as well as structured-based drug discovery. Various molecular modeling techniques involved in structure-based drug design are molecular docking and molecular dynamic simulation, whereas ligand-based drug design includes pharmacophore modeling, quantitative structure-activity relationship (QSARs), and artificial intelligence (AI). We have briefly discussed the significance of computer-aided drug design in the context of COVID-19 and how the researchers continue to rely on these computational techniques in the rapid identification of promising drug candidate molecules against various drug targets implicated in the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The structural elucidation of pharmacological drug targets and the discovery of preclinical drug candidate molecules have accelerated both structure-based as well as ligand-based drug design. This review article will help the clinicians and researchers to exploit the immense potential of computer-aided drug design in designing and identification of drug molecules and thereby helping in the management of fatal disease.

Discovery of novel inhibitors against main protease (Mpro) of SARS-CoV-2 via virtual screening and biochemical evaluation

SARS-CoV-2 is the pathogen that caused the global COVID-19 outbreak in 2020. Promising progress has been made in developing vaccines and antiviral drugs. Antivirals medicines are necessary complements of vaccines for post-infection treatment. The main protease (Mpro) is an extremely important protease in the reproduction process of coronaviruses which cleaves pp1ab over more than 11 cleavage sites. In this work, two active main protease inhibitors were found via docking-based virtual screening and bioassay. The IC₅₀ of compound VS10 was 0.20 μM, and the IC₅₀ of compound VS12 was 1.89 μM. The finding in this work can be helpful to understand the interactions of main protease and inhibitors. The active candidates could be potential lead compounds for future drug design.

A probable means to an end: exploring P131 pharmacophoric scaffold to identify potential inhibitors of Cryptosporidium parvum inosine monophosphate dehydrogenase

Compound P131 has been established to inhibit Cryptosporidium parvum's inosine monophosphate dehydrogenase (CpIMPDH). Its inhibitory activity supersedes that of paromomycin, which is extensively used in treating cryptosporidiosis. Through the per-residue energy decomposition approach, crucial moieties of P131 were identified and subsequently adopted to create a pharmacophore model for virtual screening in the ZINC database. This search generated eight ADMET-compliant hits that were examined thoroughly to fit into the active site of CpIMPDH via molecular docking. Three compounds ZINC46542062, ZINC58646829, and ZINC89780094, with favorable docking scores of - 8.3 kcal/mol, - 8.2 kcal/mol, and - 7.5 kcal/mol, were selected. The potential inhibitory mechanism of these compounds was probed using molecular dynamics simulation and Molecular Mechanics Generalized Poisson Boltzmann Surface Area (MM/PBSA) analyses. Results revealed that one of the hits (ZINC46542062) exhibited a lower binding free energy of - 39.52 kcal/mol than P131, which had - 34.6 kcal/mol. Conformational perturbation induced by the binding of the identified hits to CpIMPDH was similar to P131, suggesting a similarity in inhibitory mechanisms. Also, in silico investigation of the properties of the hit compounds implied superior physicochemical properties with regards to their synthetic accessibility, lipophilicity, and number of hydrogen bond donors and acceptors in comparison with P131. ZINC46542062 was identified as a promising hit compound with the highest binding affinity to the target protein and favorable physicochemical and pharmacokinetic properties relative to P131. The identified compounds can serve as a basis for conducting further experimental investigations toward the development of anticryptosporidials, which can overcome the challenges of existing therapeutic options. Graphical abstract P131 and the identified compounds docked in the NAD⁺ binding site of Cryptosporidium parvum IMPDH.

Structure- and Ligand-Based Virtual Screening on DUD-E+: Performance Dependence on Approximations to the Binding Pocket

Using the DUD-E⁺ benchmark, we explore the impact of using a single protein pocket or ligand for virtual screening compared with using ensembles of alternative pockets, ligands, and sets thereof. For both structure-based and ligand-based approaches, the precise characterization of the binding site in question had a significant impact on screening performance. Using the single original DUD-E protein, Surflex-Dock yielded mean ROC area of 0.81 ± 0.11. Using the cognate ligand instead, with the eSim method for screening, yielded 0.77 ± 0.14. Moving to ensembles of five protein pocket variants increased docking performance to 0.84 ± 0.09. Results for the analogous ligand-based approach (using the five crystallographically aligned cognate ligands) was 0.83 ± 0.11. Using the same ligands, but making use of an automatically generated mutual alignment, yielded mean AUC nearly as good as from single-structure docking: 0.80 ± 0.12. Detailed results and statistical analyses show that structure- and ligand-based methods are complementary and can be fruitfully combined to enhance screening efficiency. A hybrid approach combining ensemble docking with eSim-based screening produced the best and most consistent performance (mean ROC area of 0.89 ± 0.08 and 1% early enrichment of 46-fold). Based on results from both the docking and ligand-similarity approaches, it is clearly unwise to make use of a single arbitrarily chosen protein structure for docking or single ligand query for similarity-based screening.

Combining Virtual Screening Protocol and In Vitro Evaluation towards the Discovery of BACE1 Inhibitors

The treatment options for a patient diagnosed with Alzheimer’s disease (AD) are currently limited. The cerebral accumulation of amyloid-β (Aβ) is a critical molecular event in the pathogenesis of AD. When the amyloidogenic β-secretase (BACE1) is inhibited, the production of Aβ peptide is reduced. Henceforth, the main goal of this study is the discovery of new small bioactive molecules that potentially reach the brain and inhibit BACE1. The work was conducted by a customized molecular modelling protocol, including pharmacophore-based and molecular docking-based virtual screening (VS). Structure-based (SB) and ligand-based (LB) pharmacophore models were designed to accurately screen several drug-like compound databases. The retrieved hits were subjected to molecular docking and in silico filtered to predict their ability to cross the blood–brain barrier (BBB). Additionally, 34 high-scoring compounds structurally distinct from known BACE1 inhibitors were selected for in vitro screening assay, which resulted in 13 novel hit-compounds for this relevant therapeutic target. This study disclosed new BACE1 inhibitors, proving the utility of combining computational and in vitro approaches for effectively predicting anti-BACE1 agents in the early drug discovery process.

Binding Free Energy Calculation Using Quantum Mechanics Aimed for Drug Lead Optimization

The routine use of in silico tools is already established in drug lead design. Besides the use of molecular docking methods to screen large chemical libraries and thus prioritize compounds for purchase or synthesis, more accurate calculations of protein-ligand binding free energy has shown the potential to guide lead optimization, thus saving time and resources. Theoretical developments and advances in computing power have allowed quantum mechanical-based methods applied to calculations on biomacromolecules to be increasingly explored and used, with the purpose of providing a more accurate description of protein-ligand interactions and an enhanced level of accuracy in the calculation of binding affinities. It should be noted that the quantum mechanical formulation includes, in principle, all contributions to the energy, considering terms usually neglected in molecular mechanics force fields, such as electronic polarization, metal coordination, and covalent binding; moreover, quantum mechanical approaches are systematically improvable. By treating all elements and interactions on equal footing, and avoiding the need of system-dependent parameterizations, they provide a greater degree of transferability. In this review, we illustrate the increasing relevance of quantum mechanical methods for binding free energy calculation in the context of structure-based drug lead optimization, showing representative applications of the different approaches available.

Small-Molecule Intervention At The Dimerization Interface Of Survivin By Novel Rigidized Scaffolds

Introduction

Survivin is a nodal protein involved in several cellular pathways. It is a member of the IAP family and an integral component of the chromosomal passenger complex, where it binds to borealin and INCENP through its dimerization interface. By targeting survivin with a small molecule at its dimerization interface, inhibition of the proliferation of cancer cells has been suggested. With Abbott 8, a small-molecule dimerization inhibitor has been recently reported. The structure–activity relationship of this series of inhibitors implied that the middle pyridin-2(1H)-one ring did not tolerate modifications of any kind.

Methods

Based on the synthetic strategy of Abbott 8 using multicomponent reactions, we synthesized a series of small molecules bearing a novel rigidized core scaffold. This rigidization strategy was accomplished by integrating the pyridin-2(1H)-one and its 6-phenyl substituent into a tricyclic structure, linking position 5 of pyridin-2(1H)-one to the phenyl substituent by rings of different sizes. The new scaffolds were designed based on in silico molecular dynamics of survivin.

Results

Binding of these rigidized scaffolds to the recombinant L54M mutant of survivin was evaluated, revealing affinities in the low micromolar range.

Conclusion

This easily accessible, new class of survivin-dimerization modulators is an interesting starting point for further lead optimization.

Discovery and Biological Evaluation of Potent and Orally Active Human 11β-Hydroxysteroid Dehydrogenase Type 1 Inhibitors for the Treatment of Type 2 Diabetes Mellitus

We synthesized and evaluated novel 5-[2-(thiophen-2-yl)propan-2-yl]-4H-1,2,4-triazole derivatives as 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) inhibitors. Optimization of the thiophene ring and the substituents on the 1,2,4-triazole ring produced 3,4-dicyclopropyl-5-{2-[3-fluoro-5-(trifluoromethyl)thiophen-2-yl]propan-2-yl}-4H-1,2,4-triazole monohydrochloride (9a), which showed potent and selective inhibitory activity against human 11β-HSD1. Compound 9a was also metabolically stable against human and mouse liver microsomes. Oral administration of 9a to diabetic ob/ob mice lowered corticosterone levels in adipose tissue, and thereby reduced plasma glucose and insulin levels in a dose-dependent manner.

Synthesis, in vitro biological evaluation and in silico studies of certain arylnicotinic acids conjugated with aryl (thio)semicarbazides as a novel class of anti-leishmanial agents

Herein we introduce new compounds as conjugates of arylnicotinic acids with aryl (thio)semicarbazide derivatives. Based on a structure-guided approach, they were designed to possess anti-leishmanial activity through anti-folate mechanism, via targeting Leishmania major pteridine reductase 1 (Lm-PTR1). The in vitro anti-promastigote and anti-amastigote activity were promising for many thiosemicarbazide derivatives and superior to the reference miltefosine. The most active compounds 8i and 8j exhibited their anti-amastigote activity with IC₅₀ values of 4.2 and 3.3 μM, respectively, compared to reference miltefosine (IC₅₀ value of 7.3). Their anti-folate mechanism was confirmed via the ability of folic and folinic acids to reverse the anti-leishmanial activity of these compounds, comparably to Lm-PTR1 inhibitor trimethoprim. Interestingly, the in vitro cytotoxicity test of the most active compounds displayed higher selectivity indices than that of miltefosine emphasizing their safety on mammalian cells. Furthermore, the docking experiments on Lm-PTR1 as a putative target rationalized the in vitro anti-leishmanial activity. The in silico predictions exhibited promising pharmacokinetics and drug-likeness profiles of the most active compounds. Generally, this work introduces a fruitful matrix for new anti-leishmanial chemotype which would extend the chemical space for the anti-leishmanial activity.

Computational Simulations Identify Pyrrolidine-2,3-Dione Derivatives as Novel Inhibitors of Cdk5/p25 Complex to Attenuate Alzheimer's Pathology

: Mechanistically, neurotoxic insults provoke Ca2+-mediated calpain activation, which cleaves the cytoplasmic region of membrane-embedded p35 and produces its truncated form p25. Upon physical interaction, cyclin-dependent kinase 5 (Cdk5) and p25 forms hyperactivated Cdk5/p25 complex and causes severe neuropathological aberrations including hyperphosphorylated tau-mediated neurofibrillary tangles formation, Alzheimer's symptoms, and neuronal death. Therefore, the inhibition of Cdk5/p25 complex may relieve p-tau-mediated Alzheimer's pathology. Herein, computational simulations have identified pyrrolidine-2,3-dione derivatives as novel inhibitors of Cdk5/p25 complex. A ligand-based pharmacophore was designed and employed as 3D query to retrieve drug-like molecules from chemical databases. By molecular docking, drug-like molecules obtaining dock score > 67.67 (Goldcore of the reference compound) were identified. Molecular dynamics simulation and binding free energy calculation retrieved four pyrrolidine-2,3-dione derivatives as novel candidate inhibitors of Cdk5/p25. The root means square deviation of Cdk5/p25 in complex with candidate inhibitors obtained an average value of ~2.15 Å during the 30 ns simulation period. Molecular interactions analysis suggested that each inhibitor occupied the ATP-binding site of Cdk5/p25 and formed stable interactions. Finally, the binding free energy estimation suggested that each inhibitor had lowest binding energy than the reference compound (-113.10 kJ/mol) to recapitulate their strong binding with Cdk5/p25. Overall, these inhibitors could mitigate tau-mediated Alzheimer's phenotype.

Optimization of 5,6,7,8-tetrahydropyrido[4,3-d]pyrimidines to generate a highly selective PI3Kδ inhibitor

Chemical optimization of the 5,6,7,8-tetrahydropyrido[4,3-d]pyrimidine (THPP) scaffold was conducted with a focus on cellular potency while maintaining high selectivity against PI3K isoforms. Compound 11f was identified as a potent, highly selective and orally available PI3Kδ inhibitor. In addition, 11f exhibited efficacy in an in vivo antibody production model. The desirable drug-like properties and in vivo efficacy of 11f suggest its potential as a drug candidate for the treatment of autoimmune diseases and leukocyte malignancies.

Understanding the structural features of JAK2 inhibitors: a combined 3D-QSAR, DFT and molecular dynamics study

JAK2 plays a critical role in JAK/STAT signaling pathway and in patho-mechanism of myeloproliferative disorders and autoimmune diseases. Thus, effective JAK2 inhibitors provide a promising opportunity for the pharmaceutical intervention of many diseases. In this work, 3D-QSAR study was performed on a series of 1-amino-5H-pyrido-indole-4-carboxamide derivatives as JAK2 inhibitors to obtain reliable comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) models with three different alignment methods. Among the different alignment methods, ligand-based (CoMFA: q² = 0.676, r² = 0.979; CoMSIA: q² = 0.700, r² = 0.953) and pharmacophore-based alignment (CoMFA: q² = 0.710, r² = 0.982; CoMSIA: q² = 0.686, r² = 0.960) has produced better statistical results when compared to receptor-based alignment (CoMFA: q² = 0.507, r² = 0.979; CoMSIA: q² = 0.544, r² = 0.917). Statistical parameters indicated that data are well fitted and have high predictive ability. The presence of electrostatic and hydrophobic field is highly desirable for potent inhibitory activity, and the steric field plays a minor role in modulating the activity. The contour analysis indicates ARG980, ASN981, ASP939 and LEU937 have more possibility of interacting with bulky, hydrophobic groups in pyrido and positive and negative groups in pyrazole ring. Based on our findings, we have designed sixteen molecules and predicted its activity and drug-like properties. Subsequently, molecular docking, molecular dynamics and DFT calculations were performed to evaluate its potency.

Synthesis, molecular modeling and biological screening of some pyrazole derivatives as antileishmanial agents

Aim: Novel open chain and cyclized derivatives containing pyrazole scaffold were designed, synthesized and evaluated as antileishmanial compounds. Methodology & results: In silico reverse docking experiment suggested Leishmania major pteridine reductase (Lm-PTR1) as a putative target for the synthesized compounds. In vitro antileishmanial screening against L. major promastigotes and amastigotes using miltefosine and amphotericin B as references showed that the majority of the compounds displayed activity higher than miltefosine. Compounds 3i and 5 showed the highest antileishmanial activity with IC50 values of 1.45 ± 0.08 μM and 2.30 ± 0.09 μM, respectively, for the amastigote form. In silico drug-likeness and toxicity predictions showed acceptable profiles for most of the compounds, which were validated by experimental toxicity studies. Conclusion: This study offers promising entities for antileishmanial activity.

Synthesis, anti-inflammatory screening, molecular docking, and COX-1,2/-5-LOX inhibition profile of some novel quinoline derivatives

New quinoline compounds comprising pyrazole scaffold through different amide linkages were synthesized. The synthesized compounds were evaluated for their anti-inflammatory activity. Eight compounds (5c, 11b,c, 12c, 14a,b, 20a and 21a) were found to exhibit promising anti-inflammatory profiles in acute and sub-acute inflammatory models. They were screened for their ulcerogenic activity and none of them showed significant ulcerogenic activity comparable to the reference drug celecoxib and are well tolerated by experimental animals with high safety margin (ALD50 > 0.3 g/kg). Compounds 5c, 11b,c, 12c, 14a,b, 20a and 21a showed significant in vitro LOX inhibitory activity higher than that of zileuton. In vitro COX-1/COX-2 inhibition study revealed that compounds 12c, 14a,b and 20a showed higher selectivity towards COX-2 than COX-1. Among the tested compounds, 12c, 14a and 14b showed the highest inhibitory activity against COX-2 with an IC50 values of 0.1, 0.11 and 0.11 μM respectively. The docking experiments attempted to postulate the binding mode for the most active compounds in the binding site of COX-2 enzymes and confirmed the high selectivity binding towards COX-2 enzyme over COX-1.

Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose

We introduce the QuanSA method for inducing physically meaningful field-based models of ligand binding pockets based on structure-activity data alone. The method is closely related to the QMOD approach, substituting a learned scoring field for a pocket constructed of molecular fragments. The problem of mutual ligand alignment is addressed in a general way, and optimal model parameters and ligand poses are identified through multiple-instance machine learning. We provide algorithmic details along with performance results on sixteen structure-activity data sets covering many pharmaceutically relevant targets. In particular, we show how models initially induced from small data sets can extrapolatively identify potent new ligands with novel underlying scaffolds with very high specificity. Further, we show that combining predictions from QuanSA models with those from physics-based simulation approaches is synergistic. QuanSA predictions yield binding affinities, explicit estimates of ligand strain, associated ligand pose families, and estimates of structural novelty and confidence. The method is applicable for fine-grained lead optimization as well as potent new lead identification.

In silico identification and design of potent peptide inhibitors against PDZ-3 domain of Postsynaptic Density Protein (PSD-95)

Unique intrinsic properties of peptides like low toxicity, high biological activity, and specificity make them attractive therapeutic agents. PDZ-binding peptide inhibitors have been demonstrated for curing of Alzheimer, Parkinson, Dementia, and other central nervous system ailments. In this article, we report the successful use of an integrated computational protocol to analyze the structural basis of how peptides bind to the shallow groove of the third PDZ domain (PDZ-3) from the postsynaptic density (PSD-95) protein. This protocol employs careful and precise computational techniques for design of new strategy for predicting novel and potent peptides against PDZ protein. We attempted to generate a pharmacophore model using crystal structure of peptide inhibitor bound to the PDZ-3. A highly specific and sensitive generated pharmacophore model was used for screening virtual database generated using different combination of amino acid substitutions as well as decoy peptide database for its sensitivity and specificity. Identified hit peptides were further analyzed by docking studies, and their stability analyzed using solvated molecular dynamics. Quantum Mechanics/Molecular Mechanics (QM/MM) interaction energy and GMX-PBSA scoring schemes were used for ranking of stable peptides. Computational approach applied here generated encouraging results for identifying peptides against PDZ interaction model. The workflow can be further exercised as a virtual screening technique for reducing the search space for candidate target peptides against PDZ domains.

Fully Automated Quantum-Chemistry-Based Computation of Spin-Spin-Coupled Nuclear Magnetic Resonance Spectra

We present a composite procedure for the quantum‐chemical computation of spin–spin‐coupled ¹H NMR spectra for general, flexible molecules in solution that is based on four main steps, namely conformer/rotamer ensemble (CRE) generation by the fast tight‐binding method GFN‐xTB and a newly developed search algorithm, computation of the relative free energies and NMR parameters, and solving the spin Hamiltonian. In this way the NMR‐specific nuclear permutation problem is solved, and the correct spin symmetries are obtained. Energies, shielding constants, and spin–spin couplings are computed at state‐of‐the‐art DFT levels with continuum solvation. A few (in)organic and transition‐metal complexes are presented, and very good, unprecedented agreement between the theoretical and experimental spectra was achieved. The approach is routinely applicable to systems with up to 100–150 atoms and may open new avenues for the detailed (conformational) structure elucidation of, for example, natural products or drug molecules.

Synthesis, modeling and biological evaluation of hybrids from pyrazolo[1,5c]pyrimidine as antileishmanial agents

Aim: A new series of pyrazolo[1,5-c]pyrimidines were synthesized by different hybridization strategies. Methodology: All structures were confirmed by IR, 1H, 13C, 1H-13C heteronuclear multiple-quantum correlation (HMQC) spectra and microanalysis. They were evaluated for their in vitro antileishmanial activity against miltefosine and amphotericin B deoxycholate as reference drugs. Results: The most active compounds 2a and 9a demonstrated superior potencies to miltefosine by ten- and six-fold, respectively, for the promastigote form, and by 5.5-fold for the amastigote form. Their binding scenario to Leishmania major pteridine reductase was rationalized by docking experiments. In addition, all compounds were safe for the experimental animals orally up to 150 mg/kg and parenterally up to 75 mg/kg. Conclusion: This study provides novel chemotype class for antileishmanial activity.

[Formula: see text]

Synthesis, evaluation and modeling of some triazolothienopyrimidinones as anti-inflammatory and antimicrobial agents

AIM

New triazolotetrahydrobenzothienopyrimidinone derivatives were synthesized.

EXPERIMENTAL

Their structures were confirmed, and their anti-inflammatory, antimicrobial activities and ulcerogenic potentials were evaluated.

RESULTS

Compounds 7a, 10a and 11a showed minimal ulcerogenic effect and high selectivity toward human recombinant COX-2 over COX-1 enzyme with IC₅₀ values of 1.39, 1.22 and 0.56 μM, respectively. Their docking outcome correlated with their biological activity and confirmed the high selectivity binding toward COX-2. Compound 12b displayed antimicrobial activity comparable to that of ampicillin against Escherichia coli while compounds 6 and 11c were similar to ampicillin against Staphylococcus aureus. In addition, compounds 7a, 9a, 10b and 11c showed dual anti-inflammatory/antimicrobial activities.

CONCLUSION

This work represents a promising matrix for developing new potential anti-inflammatory, antimicrobial and dual antimicrobial/anti-inflammatory candidates. [Formula: see text].

GaudiMM: A modular multi-objective platform for molecular modeling

GaudiMM (for Genetic Algorithms with Unrestricted Descriptors for Intuitive Molecular Modeling) is here presented as a modular platform for rapid 3D sketching of molecular systems. It combines a Multi-Objective Genetic Algorithm with diverse molecular descriptors to overcome the difficulty of generating candidate models for systems with scarce structural data. Its grounds consist in transforming any molecular descriptor (i.e. those generally used for analysis of data) as a guiding objective for PES explorations. The platform is written in Python with flexibility in mind: the user can choose which descriptors to use for each problem and is even encouraged to code custom ones. Illustrative cases of its potential applications are included to demonstrate the flexibility of this approach, including metal coordination of multidentate ligands, peptide folding, and protein-ligand docking. GaudiMM is available free of charge from https://github.com/insilichem/gaudi. © 2017 Wiley Periodicals, Inc.

Synthesis and pharmacological evaluation of glycine amide derivatives as novel vascular adhesion protein-1 inhibitors without CYP3A4 and CYP2C19 inhibition

Vascular adhesion protein-1 (VAP-1) is a promising therapeutic target for the treatment of diabetic nephropathy. Here, we conducted optimization studies of our lead compound 1, which we previously reported as a novel VAP-1 inhibitor, to enhance the inhibition of human VAP-1 and to reduce CYP3A4 and CYP2C19 inhibition. As a result, we identified 3-chloro-4-{4-[5-(3-{[glycyl(methyl)amino]methyl}phenyl)pyrimidin-2-yl]piperazin-1-yl}benzoic acid (17h) as a novel orally active VAP-1 inhibitor, with 14-fold increased human VAP-1 inhibitory activity compared to 1, without CYP3A4 and CYP2C19 inhibition. Oral administration of 17h significantly inhibited the progression of proteinuria in streptozotocin (STZ) induced diabetic rats at 0.3 and 1mg/kg, suggesting that this compound has potential to be a therapeutic agent for the treatment of diabetic nephropathy.

Mechanistic Insights into the Binding of Class IIa HDAC Inhibitors toward Spinocerebellar Ataxia Type-2: A 3D-QSAR and Pharmacophore Modeling Approach

Spinocerebellar ataxia (SCA-2) type-2 is a rare neurological disorder among the nine polyglutamine disorders, mainly caused by polyQ (CAG) trinucleotide repeats expansion within gene coding ataxin-2 protein. The expanded trinucleotide repeats within the ataxin-2 protein sequesters transcriptional cofactors i.e., CREB-binding protein (CBP), Ataxin-2 binding protein 1 (A2BP1) leading to a state of hypo-acetylation and transcriptional repression. Histone de-acetylases inhibitors (HDACi) have been reported to restore transcriptional balance through inhibition of class IIa HDAC's, that leads to an increased acetylation and transcription as demonstrated through in-vivo studies on mouse models of Huntington's. In this study, 61 di-aryl cyclo-propanehydroxamic acid derivatives were used for developing three dimensional (3D) QSAR and pharmacophore models. These models were then employed for screening and selection of anti-ataxia compounds. The chosen QSAR model was observed to be statistically robust with correlation coefficient (r²) value of 0.6774, cross-validated correlation coefficient (q²) of 0.6157 and co-relation coefficient for external test set (pred_r²) of 0.7570. A high F-test value of 77.7093 signified the robustness of the model. Two potential drug leads ZINC 00608101 (SEI) and ZINC 00329110 (ACI) were selected after a coalesce procedure of pharmacophore based screening using the pharmacophore model ADDRR.20 and structural analysis using molecular docking and dynamics simulations. The pharmacophore and the 3D-QSAR model generated were further validated for their screening and prediction ability using the enrichment factor (EF), goodness of hit (GH), and receiver operating characteristics (ROC) curve analysis. The compounds SEI and ACI exhibited a docking score of −10.097 and −9.182 kcal/mol, respectively. An evaluation of binding conformation of ligand-bound protein complexes was performed with MD simulations for a time period of 30 ns along with free energy binding calculations using the g_mmpbsa technique. Prediction of inhibitory activities of the two lead compounds SEI (7.53) and ACI (6.84) using the 3D-QSAR model reaffirmed their inhibitory characteristics as potential anti-ataxia compounds.

Rational Drug Design Rational Drug Design

For the past three decades rationale drug design (RDD) has been developing as an innovative, rapid and successful way to discover new drug candidates. Many strategies have been followed and several targets with diverse structures and different biological roles have been investigated. Despite the variety of computational tools available, one can broadly divide them into two major classes that can be adopted either separately or in combination. The first class involves structure-based drug design, when the target's 3-dimensional structure is available or it can be computationally generated using homology modeling. On the other hand, when only a set of active molecules is available, and the structure of the target is unknown, ligand-based drug design tools are usually used. This review describes some recent advances in rational drug design, summarizes a number of their practical applications, and discusses both the advantages and shortcomings of the various techniques used.

Synthesis and structure activity relationships of glycine amide derivatives as novel Vascular Adhesion Protein-1 inhibitors

Vascular Adhesion Protein-1 (VAP-1) is a promising therapeutic target for the treatment of several inflammatory-related diseases including diabetic microvascular complication. We identified glycine amide derivative 3 as a novel structure with moderate VAP-1 inhibitory activity. Structure-activity relationship studies of glycine amide derivatives revealed that the tertiary amide moiety is important for stability in rat blood and that the position of substituents on the left phenyl ring plays an important role in VAP-1 inhibitory activity. We also found that low TPSA values and weak basicity are both important for high PAMPA values for glycine amide derivatives. These findings led to the identification of a series of orally active compounds with enhanced VAP-1 inhibitory activity. Of these compounds, 4g exhibited the most potent ex vivo efficacy, with plasma VAP-1 inhibitory activity of 60% after oral administration at 1mg/kg.

Chemoinformatics at the University of Sheffield 2002-2014

This paper summarises work in chemoinformatics carried out in the Information School of the University of Sheffield during the period 2002-2014. Research studies are described on fingerprint-based similarity searching, data fusion, applications of reduced graphs and pharmacophore mapping, and on the School's teaching in chemoinformatics.

Chemoinformatics Research at the University of Sheffield: A History and Citation Analysis

This paper reviews the work of the Chemoinformatics Research Group in the Department of Information Studies at the University of Sheffield, focusing particularly on the work carried out in the period 1985-2002. Four major research areas are discussed, these involving the development of methods for: substructure searching in databases of three-dimensional structures, including both rigid and flexible molecules; the representation and searching of the Markush structures that occur in chemical patents; similarity searching in databases of both two-dimensional and three-dimensional structures; and compound selection and the design of combinatorial libraries. An analysis of citations to 321 publications from the Group shows that it attracted a total of 3725 residual citations during the period 1980-2002. These citations appeared in 411 different journals, and involved 910 different citing organizations from 54 different countries, thus demonstrating the widespread impact of the Group's work.