Sub-structure-based screening and molecular docking studies of potential enteroviruses inhibitors

Rhinoviruses (RV), especially Human rhinovirus (HRVs) have been accepted as the most common cause for upper respiratory tract infections (URTIs). Pleconaril, a broad spectrum anti-rhinoviral compound, has been used as a drug of choice for URTIs for over a decade. Unfortunately, for various complications associated with this drug, it was rejected, and a replacement is highly desirable. In silico screening and prediction methods such as sub-structure search and molecular docking have been widely used to identify alternative compounds. In our study, we have utilised sub-structure search to narrow down our quest in finding relevant chemical compounds. Molecular docking studies were then used to study their binding interaction at the molecular level. Interestingly, we have identified 3 residues that is worth further investigation in upcoming molecular dynamics simulation systems of their contribution in stable interaction.     

2-methylindole analogs as cholinesterases and glutathione S-transferase inhibitors: Synthesis,biological evaluation,molecular docking,and pharmacokinetic studies

In this study, we aimed to (i) synthesize new 2-methylindole analogs containing various amino structures, pyrrolidine, piperidine, morpholine, and substituted phenyl groups through structural and molecular modifications, (ii) evaluate the pharmaceutical potential of 2-methylindole analogs via assessing enzyme inhibitory activity against glutathione S-transferase (GST), acetylcholinesterase (AChE), and butyrylcholinesterase (BChE), (iii) predict ADMET and pharmacokinetic properties of the synthesized 2-methylindole analogs, (iv) reveal the possible interactions between the synthesized 2-methylindole analogs with GST, AChE, and BChE enzymes using several molecular docking software. In vitro enzyme inhibition assays showed that the synthesized indole analogs exhibited moderate to good inhibitory activities against GST, AChE, and BChE enzymes. Briefly, the inhibitory activities of the analogs 4b and 4i against AChE, 4a and 4b against BChE, and analogs 1 and 4i against GST were detected to be higher or close to the standard inhibitor compounds. The analog 4b was detected to have the best inhibitory activity against both AChE and BChE enzymes with the lowest IC₅₀ values as 0.648 µM for AChE and 0.745 µM for BChE. The analyses of enzyme inhibition relationship with the synthesized analogs could help to design new analogs for the inhibitors of cholinergic and glutathione pathways based on the indole derivatives.     

Cluster‐based molecular docking study for in silico identification of novel 6‐fluoroquinolones as potential inhibitors against Mycobacterium tuberculosis

A classical protein sequence alignment and homology modeling strategy were used for building three Mycobacterium tuberculosis‐DNA gyrase protein models using the available topoII‐DNA‐6FQ crystal structure complexes originating from different organisms. The recently determined M. tuberculosis‐DNA gyrase apoprotein structures and topoII‐DNA‐6FQ complexes were used for defining the 6‐fluoroquinolones (6‐FQs) binding pockets. The quality of the generated models was initially validated by docking of the cocrystallized ligands into their binding site, and subsequently by quantitative evaluation of their discriminatory performances (identification of active/inactive 6‐FQs) for a set of 145 6‐FQs with known biological activity values. The M. tuberculosis‐DNA gyrase model with the highest estimated discriminatory power was selected and used afterwards in an additional molecular docking experiment on a mixed combinatorial set of 427 drug‐like 6‐FQ analogs for which the biological activity values were predicted using a prebuilt counter‐propagation artificial neural network model. A novel three‐level Boolean‐based [T/F (true/false)] clustering algorithm was used to assess the generated binding poses: Level 1 (geometry properties assessment), Level 2 (score‐based clustering and selection of the (T)‐signed highly scored Level 1 poses), and Level 3 (activity‐based clustering and selection of the most “active” (T)‐signed Level 2 hits). The frequency analysis of occurrence of the fragments attached at R₁ and R₇ position of the (T)‐signed 6‐FQs selected in Level 3 revealed several novel attractive fragments and confirmed some previous findings. We believe that this methodology could be successfully used in establishing novel possible structure‐activity relationship recommendations in the 6‐FQs optimization, which could be of great importance in the current antimycobacterial hit‐to‐lead processes. © 2012 Wiley Periodicals, Inc.     

Machine learning optimization of cross docking accuracy

Performance of small molecule automated docking programs has conceptually been divided into docking -, scoring -, ranking - and screening power, which focuses on the crystal pose prediction, affinity prediction, ligand ranking and database screening capabilities of the docking program, respectively. Benchmarks show that different docking programs can excel in individual benchmarks which suggests that the scoring function employed by the programs can be optimized for a particular task. Here the scoring function of Smina is re-optimized towards enhancing the docking power using a supervised machine learning approach and a manually curated database of ligands and cross docking receptor pairs. The optimization method does not need associated binding data for the receptor-ligand examples used in the data set and works with small train sets. The re-optimization of the weights for the scoring function results in a similar docking performance with regard to docking power towards a cross docking test set. A ligand decoy based benchmark indicates a better discrimination between poses with high and low RMSD. The reported parameters for Smina are compatible with Autodock Vina and represent ready-to-use alternative parameters for researchers who aim at pose prediction rather than affinity prediction.     

Identification of novel Plasmodium falciparum PI4KB inhibitors as potential anti-malarial drugs: Homology modeling,molecular docking and molecular dynamics simulations

The current study was set to discover selective Plasmodium falciparum phosphatidylinositol-4-OH kinase type III beta (pfPI4KB) inhibitors as potential antimalarial agents using combined structure-based and ligand-based drug discovery approach. A comparative model of pfPI4KB was first constructed and validated using molecular docking techniques. Performance of Autodock4.2 and Vina4 software in predicting the inhibitor-PI4KB binding mode and energy was assessed based on two Test Sets: Test Set I contained five ligands with resolved crystal structures with PI4KB, while Test Set II considered eleven compounds with known IC50 value towards PI4KB. The outperformance of Autodock as compared to Vina was reported, giving a correlation coefficient (R²) value of 0.87 and 0.90 for Test Set I and Test Set II, respectively. Pharmacophore-based screening was then conducted to identify drug-like molecules from ZINC database with physicochemical similarity to two potent pfPI4KB inhibitors –namely cpa and cpb. For each query inhibitor, the best 1000 hits in terms of TanimotoCombo scores were selected and subjected to molecular docking and molecular dynamics (MD) calculations. Binding energy was then estimated using molecular mechanics–generalized Born surface area (MM-GBSA) approach over 50 ns MD simulations of the inhibitor-pfPI4KB complexes. According to the calculated MM-GBSA binding energies, ZINC78988474 and ZINC20564116 were identified as potent pfPI4KB inhibitors with binding energies better than those of cpa and cpb, with ΔG_binding ≥ −34.56 kcal/mol. The inhibitor-pfPI4KB interaction and stability were examined over 50 ns MD simulation; as well the selectivity of the identified inhibitors towards pfPI4KB over PI4KB was reported.     

A merged molecular docking,ADME-T and dynamics approaches towards the genus of Arisaema as herpes simplex virus type 1 and type 2 inhibitors

An attempt toward screening of phytoconstituents (Arisaema genus) against herpes viruses (HSV-1 and HSV-2) was carried out using in silico approaches. Human HSV-1 and HSV-2 are accountable for cold sores genital herpes, respectively. Two drug targets, namely thymidine kinase (TK; PDB: 2ki5) serine protease (PDB: 1at3) were selected for HSV-1 and HSV-2. Initially, molecular docking tool was employed to screened apex hits phytoconstituents against herpes infections. ADME-T studies of top ranked were also further highlighted to achieve their effectiveness. Following, molecular dynamics studies were also examined to further optimize the stability of ligands. Glide scores and binding interactions of phytoconstituents were compared with Acyclovir, the main drug used in treatment of HSV, the screened top hits exhibited more glide scores and better binding for both HSV-1 and HSV-2 receptors. Additionally, ADME-T showed an ideal range for top hits while molecular dynamics results also illustrated stability of models. Ultimately, the whole efforts reveal to top three most promising hits for HSV-1 (39, 21, 19) and HSV-2 (20, 51, 19) receptors which can be explored further in wet lab experiments as promising agents against HSV infections.     

Identification of critical chemical features for Aurora kinase-B inhibitors using Hip-Hop, virtual screening and molecular docking

This study was performed to find the selective chemical features for Aurora kinase-B inhibitors using the potent methods like Hip-Hop, virtual screening, homology modeling, molecular dynamics and docking. The best hypothesis, Hypo1 was validated toward a wide range of test set containing the selective inhibitors of Aurora kinase-B. Homology modeling and molecular dynamics studies were carried out to perform the molecular docking studies. The best hypothesis Hypo1 was used as a 3D query to screen the chemical databases. The screened molecules from the databases were sorted based on ADME and drug like properties. The selective hit compounds were docked and the hydrogen bond interactions with the critical amino acids present in Aurora kinase-B were compared with the chemical features present in the Hypo1. Finally, we suggest that the chemical features present in the Hypo1 are vital for a molecule to inhibit the Aurora kinase-B activity.     

Computational insights into factor affecting the potency of diaryl sulfone analogs as Escherichia coli dihydropteroate synthase inhibitors

Dihydropteroate synthase (DHPS) is an alluring target for designing novel drug candidates to prevent infections caused by pathogenic Escherichia coli strains. Diaryl Sulfone (SO) compounds are found to inhibit DHPS competitively with respect to the substrate pABA (p-aminobenzoate). The extra aromatic ring of diaryl sulfone compounds found to stabilize them in highly flexible pABA binding loops. In this present study, a statistically significant 3D-QSAR model was developed using a data set of diaryl sulfone compounds. The favourable and unfavourable contributions of substitutions in sulfone compounds were illustrated by contour plot obtained from the developed 3D-QSAR model. Molecular docking calculations were performed to investigate the putative binding mode of diaryl sulfone compounds at the catalytic pocket. DFT calculations were carried out using SCF approach, B3LYP- 6-31 G (d) basis set to compute the HOMO, LUMO energies and their respective location at pABA binding pocket. Further, the developed model was validated by FEP (Free Energy Perturbation) calculations. The calculated relative free energy of binding between the highly potent and less potent sulfone compound was found to be −3.78 kcal/ mol which is comparable to the experimental value of −5.85 kcal/mol. A 10 ns molecular dynamics simulation of inhibitor and DHPS confirmed its stability at pABA catalytic site. Outcomes of the present work provide deeper insight in designing novel drug candidates for pathogenic Escherichia coli strains.     

Repurposing approved drugs as potential inhibitors of 3CL-protease of SARS-CoV-2: Virtual screening and structure based drug design

3CL proteases (3CL^pro) are only found in RNA viruses and have a central role in polyprotein processing during replication. Therefore, 3CL^pro has emerged as promising drug target for therapeutic treatment of infections caused by Coronaviruses. In the light of the recent major outbreak of the SARS-CoV-2 virus and the continuously rising numbers of infections and casualties, there is an urgent need for quickly available drugs or vaccines to stop the current COVID-19 pandemic. Repurposing of approved drugs as 3CL^pro inhibitors could dramatically shorten the period up to approval as therapeutic against SARS-CoV-2, since pharmacokinetics and toxicity is already known. Several known drugs, e.g. oxytetracycline, doxorubicin, kanamycin, cefpiramide, teniposide, proanthocyanidin and salvianolic acid B, but also not-approved active compounds from the ZINC15 library were identified as new potential inhibitors of 3CL^pro by using different complementary virtual screening and docking approaches. These compounds have the potential to be further optimized using structure based drug design as demonstrated for oxytetracycline.     

In silico drug design and molecular docking of novel amidophosphonates and sulfamidophosphonates as inhibitors of urokinase-type plasminogen activator

Cancer is one of the most serious health problems worldwide, affecting individuals from different sexes, ages, and races. However, the most frequent cancer types in the world are lung, prostate, stomach, colorectal, and esophagus in men; and breast, lung, stomach, colorectal and cervical in women. Currently, the search for new active substances used in oral targeted therapies are legitimate and opens up the possibility of an "ambulatory shift" in cancer treatment. In order to design anti-tumor drug candidates endowed with oral bioavailability, we studied trough an in silico approach the oral bioavailability of newly synthesized biomolecules; α-sulfamidophosphonates and α-amidophosphonates as well as their mechanism of action on the new target urokinase-type plasminogen activator (uPA). The studied compounds have been found to meet the five criteria of. Lipinski's rule. The Osiris, Molinspiration and SWISS/ADME calculations related to the compounds (1d, 2a) have shown that these compounds could be good candidates for interacting with the different targets, they have convincing characteristics in relation to the standard drug used. It can be concluded that these compounds are biologically important and possessing molecular properties desirable for being a drug candidate for oral use.The molecular docking results of the studied compounds revealed a good ligand-target interactions, the compounds (1d, 2a) presented a possibility of interacting as an inhibitor of the anticancer target: urokinase-type plasminogen activator (uPA).     

Molecular docking evaluation of celecoxib on the boron nitride nanostructures for alleviation of cardiovascular risk and inflammatory

Celecoxib (CXB) is a nonsteroidal anti-inflammatory drug (NSAID) that can be used to treat rheumatoid arthritis and ischemic heart disease. In this research, density functional theory (DFT) and molecular docking simulations were performed to study the interaction of boron nitride nanotube (BNNT) and boron nitride nanosheet (BNNS) with CXB and its inhibitor effect on pro-inflammatory cytokines. The calculated adsorption energies of CXB with the BNNT were determined in aqueous phase. The results revealed that adsorption of CXB molecule via its SO₂ group on BNNT is thermodynamically favored than the NH₂ and CF₃ groups in the solvent environment. Adsorption of CXB on BN nanomaterials are weak physisorption in nature. This can be attributed to the fact that both phenyl groups in CXB are not on the same plane and require significant activation energies for conformational changes to obtain greater H-$\pi$ interaction. Both BNNT and BNNS materials had huge sensitivity in electronic change and short recovery time during CXB interaction, thus having potential as molecular sensor and biomedical carrier for the delivery of CXB drug. IL-1A and TNF-α were implicated as vital cytokines in diverse diseases, and they have been a validated therapeutic target to manage cardiovascular risk in patients with inflammatory bowel disease. A molecular docking simulation confirms that the BNNT loaded CXB could inhibit more pro-inflammatory cytokines including IL-1A and TNF-α receptors as compared to BNNS loaded to CXB.     

Identification of novel PfDHODH inhibitors as antimalarial agents via pharmacophore-based virtual screening followed by molecular docking and in vivo antimalarial activity

Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) catalyses the fourth reaction of de novo pyrimidine biosynthesis in parasites, and represents an important target for the treatment of malaria. In this study, we describe pharmacophore-based virtual screening combined with docking study and biological evaluation as a rational strategy for identification of novel hits as antimalarial agents. Pharmacophore models were established from known PfDHODH inhibitors using the GALAHAD module with IC₅₀ values ranging from 0.033 μM to 142 μM. The best pharmacophore model consisted of three hydrogen bond acceptor, one hydrogen bond donor and one hydrophobic features. The pharmacophore models were validated through receiver operating characteristic and Günere–Henry scoring methods. The best pharmacophore model as a 3D search query was searched against the IBS database. Several compounds with different structures (scaffolds) were retrieved as hit molecules. Among these compounds, those with a Q_FIT value of more than 81 were docked in the PfDHODH enzyme to further explore the binding modes of these compounds. In silico pharmacokinetic and toxicities were predicted for the best docked molecules. Finally, the identified hits were evaluated in vivo for their antimalarial activity in a parasite inhibition assay. The hits reported here showed good potential to become novel antimalarial agents.     

1,3-Oxazole derivatives of cytisine as potential inhibitors of glutathione reductase of Candida spp.: QSAR modeling,docking analysis and experimental study of new anti-Candida agents

Natural products as well as their derivatives play a significant role in the discovery of new biologically active compounds in the different areas of our life especially in the field of medicine. The synthesis of compounds produced from natural products including cytisine is one approach for the wider use of natural substances in the development of new drugs. QSAR modeling was used to predict and select of biologically active cytisine-containing 1,3-oxazoles. The eleven most promising compounds were identified, synthesized and tested. The activity of the synthesized compounds was evaluated using the disc diffusion method against C. albicans M 885 (ATCC 10,231) strain and clinical fluconazole-resistant Candida krusei strain. Molecular docking of the most active compounds as potential inhibitors of the Candida spp. glutathione reductase was performed using the AutoDock Vina. The built classification models demonstrated good stability, robustness and predictive power. The eleven cytisine-containing 1,3-oxazoles were synthesized and their activity against Candida spp. was evaluated. Compounds 10, 11 as potential inhibitors of the Candida spp. glutathione reductase demonstrated the high activity against C. albicans M 885 (ATCC 10,231) strain and clinical fluconazole-resistant Candida krusei strain. The studied compounds 10, 11 present the interesting scaffold for further investigation as potential inhibitors of the Candida spp. glutathione reductase with the promising antifungal properties. The developed models are publicly available online at http://ochem.eu/article/120720 and could be used by scientists for design of new more effective drugs.     

Synthesis of novel bridged dinitrogen heterocycles and their evaluation as potential fragments for the design of biologically active compounds

A library of saturated bridged heterocycles based on 3,6-diazabicyclo[3.2.1]octane-2,4-dione and bispidine scaffolds (mean compound molecular weight is approximately 300 Da) with up to three stereocenters and four diversity points has been synthesized. Synthetic scaffold modifications leading to an increase in molecular complexity were studied. Well-defined stereochemical structures of both compound sets was confirmed by X-ray studies and halogenoaryl substituents were inserted appropriately for the design of novel non-basic serine protease inhibitors. Comprehensive molecular modeling has been performed for all synthesized compounds giving rationales of ligand–enzyme interactions with thrombin and trypsin. Biological testing confirmed moderate inhibitory activity of halogen-substituted saturated diazabicyclic small molecules towards thrombin.