Evaluation of the FLEXX incremental construction algorithm for protein-ligand docking

3-styrylcoumarin scaffold-based derivatives as a new approach for leishmaniasis intervention: biological and molecular modeling studies

Seven 3-styrylcoumarins were tested for antileishmanial activity against Leishmania (Viannia) panamensis amastigotes. Cytotoxic activity was also evaluated against mammalian U-937 cells. The 3-methoxy-4-hydroxy coumarin derivative 6 was the most active with an IC50 of 40.5 µM, and did not reveal any conspicuous toxicity toward mammalian U-937 cells. Therefore, it may have potential to be considered as candidate for antileishmanial drug development. Further, among several druggable Leishmania targets, molecular docking studies revealed that compound 6 had docking preference by the N-myristoyltransferase (Lp-NMT) of Leishmania panamensis, showing a higher docking score of - 10.1 kcal mol-1 than positive controls and making this protein as a presumably druggable target for this compound. On the other hand, molecular dynamics simulations affirm the docking hypothesis, showing a conformational stability of the 6/Lp-NMT complex throughout 100 ns simulation. Moreover, the molecular mechanics/Poisson-Boltzmann surface area method also support the docking findings, revealing a total free energy of binding of - 47.26 ± 0.08 kcal mol-1, and identifying through energy decomposition analysis that those key aminoacids are contributing strongly to ligand binding. Finally, an optimal pharmacokinetic profile was also estimated for 6. Altogether, coumarin 6 could be addressed as starting point for further pharmacological studies concerning the therapeutic leishmaniasis intervention.

Graphical abstract

VSpipe-GUI, an Interactive Graphical User Interface for Virtual Screening and Hit Selection

Virtual screening of large chemical libraries is essential to support computer-aided drug development, providing a rapid and low-cost approach for further experimental validation. However, existing computational packages are often for specialised users or platform limited. Previously, we developed VSpipe, an open-source semi-automated pipeline for structure-based virtual screening. We have now improved and expanded the initial command-line version into an interactive graphical user interface: VSpipe-GUI, a cross-platform open-source Python toolkit functional in various operating systems (e.g., Linux distributions, Windows, and Mac OS X). The new implementation is more user-friendly and accessible, and considerably faster than the previous version when AutoDock Vina is used for docking. Importantly, we have introduced a new compound selection module (i.e., spatial filtering) that allows filtering of docked compounds based on specified features at the target binding site. We have tested the new VSpipe-GUI on the Hepatitis C Virus NS3 (HCV NS3) protease as the target protein. The pocket-based and interaction-based modes of the spatial filtering module showed efficient and specific selection of ligands from the virtual screening that interact with the HCV NS3 catalytic serine 139.

The role and potential of computer-aided drug discovery strategies in the discovery of novel antimicrobials

Antimicrobial resistance (AMR) has become more of a concern in recent decades, particularly in infections associated with global public health threats. The development of new antibiotics is crucial to ensuring infection control and eradicating AMR. Although drug discovery and development are essential processes in the transformation of a drug candidate from the laboratory to the bedside, they are often very complicated, expensive, and time-consuming. The pharmaceutical sector is continuously innovating strategies to reduce research costs and accelerate the development of new drug candidates. Computer-aided drug discovery (CADD) has emerged as a powerful and promising technology that renews the hope of researchers for the faster identification, design, and development of cheaper, less resource-intensive, and more efficient drug candidates. In this review, we discuss an overview of AMR, the potential, and limitations of CADD in AMR drug discovery, and case studies of the successful application of this technique in the rapid identification of various drug candidates. This review will aid in achieving a better understanding of available CADD techniques in the discovery of novel drug candidates against resistant pathogens and other infectious agents.

Design, synthesis, and biological activity evaluation of new tankyrase-2 directed inhibitors

A new series of flavonoids and quinolone derivatives were designed, synthesized and, evaluated for their biological activity. Among them, compound 14e showed better inhibition potency against TNKS2 in comparison with G007-LK, one of the most potent preclinical stage TNKS inhibitor. Molecular docking results showed that 14e occupied both the adenosine and nicotinamide pockets and formed a hydrogen bond with Met1054 of TNKS2. This study provides a lead for the design and discovery of potent and selective TNKS2 inhibitors.

Identification of new benzimidazole-triazole hybrids as anticancer agents: multi-target recognition, in vitro and in silico studies

Multi-target inhibitors represent useful anticancer agents with superior therapeutic attributes. Here in, two novel series of benzimidazole-triazole hybrids were designed, synthesised as multi-target EGFR, VEGFR-2 and Topo II inhibitors, and evaluated for anticancer activity. Compounds 5a and 6g were the most potent analogues against four cancer cell lines, HepG-2, HCT-116, MCF-7 and HeLa, and were further evaluated for EGFR, VEGFR-2, and Topo II inhibition. Compound 5a was especially good inhibitor for EGFR (IC₅₀ = 0.086 µM) compared to Gefitinib (IC₅₀ = 0.052 µM), moderate VEGFR-2 inhibitor (IC₅₀ = 0.107 µM) compared to Sorafenib (IC₅₀ = 0.0482 µM), and stronger Topo II inhibitor (IC₅₀ = 2.52 µM) than Doxorubicin (IC₅₀ = 3.62 µM). Compound 6g exhibited moderate EGFR and VEGFR-2 inhibition and weaker Topo II inhibition. DNA binding assay, cell cycle analysis, apoptotic induction, molecular docking, and physicochemical studies were additionally implemented to explore the plausible mechanism of the active compounds.

New benzothiazole hybrids as potential VEGFR-2 inhibitors: design, synthesis, anticancer evaluation, and in silico study

A new series of 2-aminobenzothiazole hybrids linked to thiazolidine-2,4-dione 4a-e, 1,3,4-thiadiazole aryl urea 6a-d, and cyanothiouracil moieties 8a-d was synthesised. The in vitro antitumor effect of the new hybrids was assessed against three cancer cell lines, namely, HCT-116, HEPG-2, and MCF-7 using Sorafenib (SOR) as a standard drug. Among the tested compounds, 4a was the most potent showing IC50 of 5.61, 7.92, and 3.84 µM, respectively. Furthermore, compounds 4e and 8a proved to have strong impact on breast cancer cell line with IC50 of 6.11 and 10.86 µM, respectively. The three compounds showed a good safety profile towards normal WI-38 cells. Flow cytometric analysis of the three compounds in MCF-7 cells revealed that compounds 4a and 4c inhibited cell population in the S phase, whereas 8a inhibited the population in the G1/S phase. The most promising compounds were subjected to a VEGFR-2 inhibitory assay where 4a emerged as the best active inhibitor of VEGFR-2 with IC50 91 nM, compared to 53 nM for SOR. In silico analysis showed that the three new hybrids succeeded to link to the active site like the co-crystallized inhibitor SOR.

Molecular properties and In silico bioactivity evaluation of (4-fluorophenyl)[5)-3-phen-(4-nitrophenyl yl-4,5-dihydro-1H-pyrazol-1-yl]methanone derivatives: DFT and molecular docking approaches

Objectives

Molecular structures, spectroscopic properties, charge distributions, frontier orbital energies, nonlinear optical (NLO) properties and molecular docking simulations were analyzed to examine the bio-usefulness of a series of (4-fluorophenyl)[5-(4-nitrophenyl)-3-phenyl-4,5-dihydro-1H-pyrazol-1-yl]methanone derivatives.

Methods

The compounds were studied through computational methods. Equilibrium optimization of the compounds was performed at the B3LYP/6-31G(d,p) level of theory, and geometric parameters, frequency vibration, UV-vis spectroscopy and reactivity properties were predicted on the basis of density functional theory (DFT) calculations.

Results

The energy gap (ΔEg), electron donating/accepting power (ω-/ω+) and electron density response toward electrophiles/nucleophiles calculated for M1 and M2 revealed the importance of substituent positioning on compound chemical behavior. In addition, ω-/ω+ and ΔEn/ΔEe indicated that M6 is more electrophilic because of the presence of two NO₂ groups, which enhanced its NLO properties. The hyperpolarizability (β₀) of the compounds ranged from 5.21 × 10^-30 to 7.26 × 10^-30 esu and was greater than that of urea; thus, M1-M6 were considered possible candidates for NLO applications. Docking simulation was also performed on the studied compounds and targets (PDB ID: 5ADH and 1RO6), and the calculated binding affinity and non-bonding interactions are reported.

Conclusion

The calculated ω^- and ω⁺ indicated the electrophilic nature of the compounds; M6, a compound with two NO₂ groups, showed enhanced effects. Molecular electrostatic potential (MEP) analysis indicated that amide and nitro groups on the compounds were centers of electrophilic attacks. The magnitude of the molecular hyperpolarizability suggested that the entire compound had good NLO properties and therefore could be explored as a candidate NLO material. The docking results indicated that these compounds have excellent antioxidant and anti-inflammatory properties.

Crystal structure determination, molecular docking and dynamics of arylidene cyanoacetates as potential JNK-3 inhibitors for Ischemia reperfusion injury

Ischemia reperfusion injury is a cardiovascular condition which causes hypoxia by means of obstruction of arterial blood flow eventually leads to reduced synthesis of adenosine tri-phosphate in the mitochondria. c-Jun N-terminal kinase-3 are related to several cascade of events like apoptosis, oxidative stress and mitochondrial dysfunction which can be further related to Ischemia-reperfusion injury. The present study was aimed at determining crystal structure of the ligand by x-ray methods and to perform molecular docking and molecular dynamics studies of the arylidene cyano-acetates with c-Jun N-terminal kinase-3. The binding energy of Ethyl (2E)-2-cyano-3-(4-methoxyphenyl)prop-2-enoate is -4.462 kcal/mol and ethyl (2E)-2-cyano-3-phenylprop-2-enoate is -6.135 kcal/mol. This has created a new rational approach to drug design, where the structure of drug is designed, based on its fit to structures of receptor site, rather than basing it on analogies to other active structures. The above compounds are binding strongly with c-Jun N-terminal kinase-3 protein.[Figure: see text]Communicated by Ramaswamy H. Sarma.

Computational and biophysical methods for the discovery and optimization of covalent drugs

Drugs that act by covalently attaching to their targets have been used to treat human diseases for over a hundred years. However, the deliberate design of covalent drugs was discouraged due to concerns of toxicity and off-target effects. Recent successes in covalent drug discovery have sparked fresh interest in this field. New screening and testing methods aimed at covalent inhibitors can play pivotal roles in facilitating the discovery process. This feature article focuses on computational and biophysical advances originating from our labs over the past decade and how these approaches have contributed to the design of prolyl oligopeptidase (POP) and SARS-CoV-2 3CLpro covalent inhibitors.

Design, Synthesis, and Biological Evaluation of Novel Indanone Derivatives as Cholinesterase Inhibitors for Potential Use in Alzheimer's Disease

Indanone derivatives containing meta/para-substituted aminopropoxy benzyl/benzylidene moieties were designed based on the structures of donepezil and ebselen analogs as the cholinesterase inhibitors. The designed compounds were synthesized and their acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitory activities were measured. Inhibitory potencies (IC50 values) for the synthesized compounds ranged from 0.12 to 11.92 μM and 0.04 to 24.36 μM against AChE and BChE, respectively. Compound 5 c showed the highest AChE inhibitory potency with IC50 value of 0.12 μM, whereas the highest BChE inhibition was achieved by structure 7 b (IC50 =0.04 μM). Structure-activity relationship (SAR) analysis revealed that there is no significant difference between meta and para-substituted derivatives in AChE and BChE inhibition. However, the most potent AChE inhibitor 5 c belongs to meta-substituted compounds, while the most active BChE inhibitor is para-substituted derivative 7 b. The order of enzyme inhibition potency based on the substituted amine group is dimethyl amine>piperidine>morpholine. Compounds containing C=C linkage are more potent AChE inhibitors than the corresponding saturated structures. Molecular docking studies indicated that 5 c interacts with AChE in a very similar way to that observed experimentally for donepezil. The introduced indanone-aminopropoxy benzylidenes could be used in drug-discovery against Alzheimer's disease.

Cryo-EM structures of actin binding proteins as tool for drug discovery

Cellular actin dynamic is controlled by a plethora of actin binding proteins (ABPs), including actin nucleating, bundling, cross-linking, capping, and severing proteins. In this review, regulation of actin dynamics by ABPs will be introduced, and the role of the F-actin severing protein cofilin-1 and the F-actin bundling protein L-plastin in actin dynamics discussed in more detail. Since up-regulation of these proteins in different kinds of cancers is associated with malignant progression of cancer cells, we suggest the cryogenic electron microscopy (Cryo-EM) structure of F- actin with the respective ABP as template for in silico drug design to specifically disrupt the interaction of these ABPs with F-actin.

Prediction of Sites of Metabolism of CYP3A4 Substrates Utilizing Docking-Derived Geometric Features

Cytochrome P450 3A4 (CYP3A4) is one of the major drug-metabolizing enzymes in the human body and is responsible for the metabolism of ∼50% of clinically used drugs. Therefore, the identification of the compound's sites of metabolism (SOMs) mediated by CYP3A4 is of utmost importance in the early stage of drug discovery and development. Herein, docking-based approaches incorporating geometric features were used for SOMs prediction of CYP3A4 substrates. The cross-docking poses of a relatively large data set containing 474 substrates were analyzed in depth, and a widely observed geometric pattern called the close proximity of SOMs was derived from the poses. On the basis of the close proximity, several structure-based models have been constructed, which demonstrated better performance than those structure-based models using the criterion of Fe-SOM distance. For further improving the prediction performance, the structure-based models were also combined with the well-known ligand-based model SMARTCyp. One combined model exhibited good performance on the SOMs prediction of an external substrate set containing kinase inhibitors, PROTACs, approved drugs, and some lead compounds.

Structure-Based Design of Novel MAO-B Inhibitors: A Review

With the significant growth of patients suffering from neurodegenerative diseases (NDs), novel classes of compounds targeting monoamine oxidase type B (MAO-B) are promptly emerging as distinguished structures for the treatment of the latter. As a promising function of computer-aided drug design (CADD), structure-based virtual screening (SBVS) is being heavily applied in processes of drug discovery and development. The utilization of molecular docking, as a helping tool for SBVS, is providing essential data about the poses and the occurring interactions between ligands and target molecules. The current work presents a brief discussion of the role of MAOs in the treatment of NDs, insight into the advantages and drawbacks of docking simulations and docking software, and a look into the active sites of MAO-A and MAO-B and their main characteristics. Thereafter, we report new chemical classes of MAO-B inhibitors and the essential fragments required for stable interactions focusing mainly on papers published in the last five years. The reviewed cases are separated into several chemically distinct groups. Moreover, a modest table for rapid revision of the revised works including the structures of the reported inhibitors together with the utilized docking software and the PDB codes of the crystal targets applied in each study is provided. Our work could be beneficial for further investigations in the search for novel, effective, and selective MAO-B inhibitors.

Computer-aided drug design in seeking viral capsid modulators

Approved or licensed antiviral drugs have limited applications because of their drug resistance and severe adverse effects. By contrast, by stabilizing or destroying the viral capsid, compounds known as capsid modulators prevent viral replication by acting on new targets and, therefore, overcoming the problem of clinical drug resistance. For example. computer-aided drug design (CADD) methods, using strategies based on structures of biological targets (structure-based drug design; SBDD), such as docking, molecular dynamics (MD) simulations, and virtual screening (VS), have provided opportunities for fast and effective development of viral capsid modulators. In this review, we summarize the application of CADD in the discovery, optimization, and mechanism prediction of capsid-targeting small molecules, providing new insights into antiviral drug discovery modalities. Teaser: Computer-aided drug design will accelerate the development of viral capsid regulators, which brings new hope for the treatment of refractory viral diseases.

Pharmacological Chaperones and Protein Conformational Diseases: Approaches of Computational Structural Biology

Whenever a protein fails to fold into its native structure, a profound detrimental effect is likely to occur, and a disease is often developed. Protein conformational disorders arise when proteins adopt abnormal conformations due to a pathological gene variant that turns into gain/loss of function or improper localization/degradation. Pharmacological chaperones are small molecules restoring the correct folding of a protein suitable for treating conformational diseases. Small molecules like these bind poorly folded proteins similarly to physiological chaperones, bridging non-covalent interactions (hydrogen bonds, electrostatic interactions, and van der Waals contacts) loosened or lost due to mutations. Pharmacological chaperone development involves, among other things, structural biology investigation of the target protein and its misfolding and refolding. Such research can take advantage of computational methods at many stages. Here, we present an up-to-date review of the computational structural biology tools and approaches regarding protein stability evaluation, binding pocket discovery and druggability, drug repurposing, and virtual ligand screening. The tools are presented as organized in an ideal workflow oriented at pharmacological chaperones' rational design, also with the treatment of rare diseases in mind.

MetaDOCK: A Combinatorial Molecular Docking Approach

Molecular docking plays a major role in academic and industrial drug screening and discovery processes. Despite the availability of numerous docking software packages, there is a lot of scope for improvement for the docking algorithms in terms of becoming more reliable to replicate the experimental binding results. Here, we propose a combinatorial or consensus docking approach where complementary powers of the existing methods are captured. We created a meta-docking protocol by combining the results of AutoDock4.2, LeDock, and rDOCK programs as these are freely available, easy to use, and suitable for large-scale analysis and produced better performance on benchmarking studies. Rigorous benchmarking analyses were undertaken to evaluate the scoring, posing, and screening capability of our approach. Further, the performance measures were compared against one standard state-of-the-art commercial docking software, GOLD, and one freely available software, PLANTS. Performances of MetaDOCK for scoring, posing, and screening the protein-ligand complexes were found to be quite superior compared to the reference programs. Exhaustive molecular dynamics simulation and molecular mechanics Poisson-Boltzmann and surface area-based free energy estimation also suggest better energetic stability of the docking solutions produced by our meta-approach. We believe that the MetaDOCK approach is a useful packaging of the freely available software and provides a better alternative to the scientific community who are unable to afford costly commercial packages.

Density functional modeling, and molecular docking with SARS-CoV-2 spike protein (Wuhan) and omicron S protein (variant) studies of new heterocyclic compounds including a pyrazoline nucleus

Nowadays, different vaccines and antiviral drugs have been developed and their effectiveness has been proven against SARS-CoV-2. Pyrazoline derivatives are biologically active molecules and exhibit broad-spectrum biological activity properties. In this scope, four new molecules (4a-d) including a pyrazoline core were synthesized in order to predict their antiviral properties theoretically. Compounds 4a-d were purified by the crystallization method. The structures of 4a-d were completely characterized by NMR, IR, and elemental analysis. The molecular structures of the compounds in the ground state have been optimized using density functional theory with the B3LYP/6-31++G(d,p) level. The quantum chemical parameters were predicted by density functional theory calculations. Moreover, the molecular docking studies of 4a-d with SARS-CoV-2 Spike protein (Wuhan) and omicron S protein (variant) were presented to investigate and predict potential interactions. The binding sites, binding types and energies, bond distances of the non-covalent interactions and calculated inhibition constants (calc. Ki) as a consequence of molecular docking for 4a-d were presented in this study. Furthermore, the stability of the protein-4a complex obtained from the docking was investigated through molecular dynamics simulation.Communicated by Ramaswamy H. Sarma.

AlteQ: a new complementarity principle-centered method for the evaluation of docking poses

Molecular docking is the most popular and widely used method for identifying novel molecules against a target of interest. However, docking procedures and their validation are still under intense development. In the present investigation, we evaluate a quantum free-orbital AlteQ method for evaluating docking complexes generated by taking EGFR complexes as an example. The AlteQ method calculates the electron density using Slater's type atomic contributions in the interspace between the receptor and the ligand. Since the interactions are determined by the overlap of electron clouds, they follow the complementarity principle, and an equation can be obtained that describes these interactions. The AlteQ method evaluates the quality of the interaction between the receptor and the ligand, how complementary the interactions are, and due to this, it is used to reject less realistic structures obtained by docking methods. Here, three different equations were used to determine the quality of the interactions in experimental complexes and docked complexes obtained using AutoDock Vina and AutoDock 4.2.6.Communicated by Ramaswamy H. Sarma.

Deciphering the competitive inhibition of dihydropteroate synthase by 8 marcaptoguanine analogs: enhanced potency in phenylsulfonyl fragments

The emergence of sulfa-drug resistance and reduced efficacy of pterin-based analogs towards Dihydropteroate synthase (DHPS) inhibition dictate a pressing need of developing novel antimicrobial agents for immune-compromised patients. Recently, a series of 8-Marcaptoguanin (8-MG) derivatives synthesized for 6-Hydroxymethyl-7,8-dihydropterin pyrophosphokinase (experimental K_D ∼ 100-.0.36) showed remarkable homology with the pteroic-acid and serve as a template for product antagonism in DHPS. The present work integrates ligand-based drug discovery techniques with structure-based docking, enhanced MD simulation, and MM/PBSA techniques to demonstrate the essential features of 8-MG analogs which make it a potent inhibitor for DHPS. The delicate balance in hydrophilic, hydrophobic substitutions on the 8-MG core is the crucial signature for DHPS inhibition. It is found that the dynamic interactions of active compounds are mainly dominated by consistent hydrogen bonding network with Asp 96, Asn 115, Asp 185, Ser 222, Arg 255 and π-π stacking, π-cation interactions with Phe 190, Lys 221. Further, two new 8-MG compounds containing N-phenylacetamide (compound S1, ΔG_bind-eff = -62.03 kJ/mol) and phenylsulfonyl (compound S3, ΔG_bind-eff = -71.29 kJ/mol) fragments were found to be the most potent inhibitor of DHPS, which stabilize the flexible pABA binding loop, thereby increasing their binding affinity. MM/PBSA calculation shows electrostatic energy contribution to be the principal component in stabilizing the inhibitors in the binding pocket. This fact is further confirmed by the higher energy barrier obtained in umbrella sampling for this class of inhibitors.

A Guide to In Silico Drug Design

The drug discovery process is a rocky path that is full of challenges, with the result that very few candidates progress from hit compound to a commercially available product, often due to factors, such as poor binding affinity, off-target effects, or physicochemical properties, such as solubility or stability. This process is further complicated by high research and development costs and time requirements. It is thus important to optimise every step of the process in order to maximise the chances of success. As a result of the recent advancements in computer power and technology, computer-aided drug design (CADD) has become an integral part of modern drug discovery to guide and accelerate the process. In this review, we present an overview of the important CADD methods and applications, such as in silico structure prediction, refinement, modelling and target validation, that are commonly used in this area.

Phytochemical profiling, in vitro biological activity, docking studies, and cytotoxicity assessments of Rondeletia odorata Jacquin: An unexplored plant of the coffee family

Rondeletia odorata Jacquin is a flowering plant that belongs to the coffee family. As a rich source of polyphenols with significant antioxidant potential, R. odorata may have health benefits. Therefore, in the current work, ethanolic extract of aerial parts and its n-hexane, ethyl acetate, and n-butanol soluble fractions were analyzed for their antioxidant potential and various enzyme inhibition properties. The total phenolic and flavonoid contents of the crude ethanol extract (ROE) and its n-hexane (ROH), ethyl acetate (ROEA), and n-butanol (ROB) fractions were determined spectrophotometrically, while metabolic profiling was established through UHPLC-MS analysis, which revealed the presence of 58 phytochemicals. Total phenolic and flavonoid contents of ROE extract were measured as 51.92 mg GA.Eq./g of dry extract and 52.35 mg Qu.Eq./g of the dry extract, respectively. In the DPPH radical scavenging activity assay, ROE and ROEA showed the highest potential with values of 62.13 ± 0.62 and 76.31% ± 1.86%, respectively, comparable to quercetin (80.89% ± 0.54%). Similarly, in the FRAP assay, the same pattern of the activity was observed with ROE and ROEA, which displayed absorbance values of 1.32 ± 0.01 and 0.80 ± 0.02 at 700 nm, respectively, which are comparable (1.76 ± 0.02) with the reference compound quercetin, whereas the ROH showed maximum metal-chelating capacity (62.61% ± 1.01%) among all extracts and fractions. Antibacterial activity assay indicated that the ROEA fraction was the most active against Serratia marcescens, Stenotrophomonas maltophilia, Bacillus subtilis, Klebsiella pneumonia, and Staphylococcus aureus, while the rest of the fractions showed good to moderate activity. Enzyme inhibition assays showed that ROEA fraction exhibited the highest activity with IC50 values of 2.78 ± 0.42 and 3.95 ± 0.13 mg/mL against urease and carbonic anhydrase (CA), respectively. Furthermore, the docking studies of some of the major compounds identified in the extract revealed a strong correlation with their inhibitory activity. All extracts and fractions were also tested for their thrombolytic activity, and the ROB fraction showed a notable potential. Antiviral assay led to remarkable outcomes. Thus, it can be inferred that aerial parts of R. odorata are potential sources of bioactive components with several significant pharmacological activities.

Application of Computational Biology and Artificial Intelligence in Drug Design

Traditional drug design requires a great amount of research time and developmental expense. Booming computational approaches, including computational biology, computer-aided drug design, and artificial intelligence, have the potential to expedite the efficiency of drug discovery by minimizing the time and financial cost. In recent years, computational approaches are being widely used to improve the efficacy and effectiveness of drug discovery and pipeline, leading to the approval of plenty of new drugs for marketing. The present review emphasizes on the applications of these indispensable computational approaches in aiding target identification, lead discovery, and lead optimization. Some challenges of using these approaches for drug design are also discussed. Moreover, we propose a methodology for integrating various computational techniques into new drug discovery and design.

Dual Inhibitors of AChE and BACE-1 for Reducing Aβ in Alzheimer's Disease: From In Silico to In Vivo

Alzheimer's disease (AD) is a complex and widespread condition, still not fully understood and with no cure yet. Amyloid beta (Aβ) peptide is suspected to be a major cause of AD, and therefore, simultaneously blocking its formation and aggregation by inhibition of the enzymes BACE-1 (β-secretase) and AChE (acetylcholinesterase) by a single inhibitor may be an effective therapeutic approach, as compared to blocking one of these targets or by combining two drugs, one for each of these targets. We used our ISE algorithm to model each of the AChE peripheral site inhibitors and BACE-1 inhibitors, on the basis of published data, and constructed classification models for each. Subsequently, we screened large molecular databases with both models. Top scored molecules were docked into AChE and BACE-1 crystal structures, and 36 Molecules with the best weighted scores (based on ISE indexes and docking results) were sent for inhibition studies on the two enzymes. Two of them inhibited both AChE (IC₅₀ between 4-7 μM) and BACE-1 (IC₅₀ between 50-65 μM). Two additional molecules inhibited only AChE, and another two molecules inhibited only BACE-1. Preliminary testing of inhibition by F681-0222 (molecule 2) on APPswe/PS1dE9 transgenic mice shows a reduction in brain tissue of soluble Aβ42.

Synthesis and Chemopreventive Potential of 5-FU/Genistein Hybrids on Colorectal Cancer Cells

A series of 5-FU-Genistein hybrids were synthesized and their structures were elucidated by spectroscopic analysis. The chemopreventive potential of these compounds was evaluated in human colon adenocarcinoma cells (SW480 and SW620) and non-malignant cell lines (HaCaT and CHO-K1). Hybrid 4a displayed cytotoxicity against SW480 and SW620 cells with IC₅₀ values of 62.73 ± 7.26 µM and 50.58 ± 1.33 µM, respectively; compound 4g induced cytotoxicity in SW620 cells with an IC₅₀ value of 36.84 ± 0.71 µM. These compounds were even more selective than genistein alone, the reference drug (5-FU) and the equimolar mixture of genistein plus 5-FU. In addition, hybrids 4a and 4g induced time- and concentration-dependent antiproliferative activity and cell cycle arrest at the S-phase and G2/M. It was also observed that hybrid 4a induced apoptosis in SW620 cells probably triggered by the extrinsic pathway in response to the activation of p53, as evidenced by the increase in the levels of caspases 3/8 and the tumor suppressor protein (Tp53). Molecular docking studies suggest that the most active compound 4a would bind efficiently to proapoptotic human caspases 3/8 and human Tp53, which in turn could provide valuable information on the biochemical mechanism for the in vitro cytotoxic response of this compound in SW620 colon carcinoma cell lines. On the other hand, molecular dynamics (MD) studies provided strong evidence of the conformational stability of the complex between caspase-3 and hybrid 4a obtained throughout 100 ns all-atom MD simulation. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) analyses of the complex with caspase-3 showed that the interaction between the ligand and the target protein is stable. Altogether, the results suggest that the active hybrids, mainly compound 4a, might act by modulating caspase-3 activity in a colorectal cancer model, making it a privileged scaffold that could be used in future investigations.

1,5-Dichloroethanoanthracene Derivatives As Antidepressant Maprotiline Analogs: Synthesis, DFT Computational Calculations, and Molecular Docking

The chlorinated tetracyclic 1,5-dichloro-9,10-dihydro-9,10-ethanoanthracen-12-yl)-N-methylmethanamine 1, a maprotiline analog, has been synthesized via reduction and the Diels–Alder reaction followed by reductive amination of aldehyde 2.1D-NMR (DEPT) and 2D-NMR (HSQC, DQF-COSY) techniques were recruited for structural elucidation in addition to HRMS. Density functional theory calculations were performed to identify the possible isomers of the intermediate compound aldehyde 2; these calculations were in good agreement with experimental results where aldehyde 2 could exist in three isomers with comparable energies. In addition, the side chain of this aldehyde 2 was extended via the Wittig reaction to obtain the unsaturated ester 5 that was subjected to selective olefinic catalytic hydrogenation to obtain the corresponding saturated ester 6. Molecular docking simulation showed that all the compounds (1, 2, 5, and 6) have high antidepressant activities and form stable complexes with LeuT by inhibiting the neurotransmitter reuptake at the synapse and hence are good candidates as antidepressant drugs.

Developing New Treatments for COVID-19 through Dual-Action Antiviral/Anti-Inflammatory Small Molecules and Physiologically Based Pharmacokinetic Modeling

Broad-spectrum antiviral agents that are effective against many viruses are difficult to develop, as the key molecules, as well as the biochemical pathways by which they cause infection, differ largely from one virus to another. This was more strongly highlighted by the COVID-19 pandemic, which found health systems all over the world largely unprepared and proved that the existing armamentarium of antiviral agents is not sufficient to address viral threats with pandemic potential. The clinical protocols for the treatment of COVID-19 are currently based on the use of inhibitors of the inflammatory cascade (dexamethasone, baricitinib), or inhibitors of the cytopathic effect of the virus (monoclonal antibodies, molnupiravir or nirmatrelvir/ritonavir), using different agents. There is a critical need for an expanded armamentarium of orally bioavailable small-molecular medicinal agents, including those that possess dual antiviral and anti-inflammatory (AAI) activity that would be readily available for the early treatment of mild to moderate COVID-19 in high-risk patients. A multidisciplinary approach that involves the use of in silico screening tools to identify potential drug targets of an emerging pathogen, as well as in vitro and in vivo models for the determination of a candidate drug’s efficacy and safety, are necessary for the rapid and successful development of antiviral agents with potentially dual AAI activity. Characterization of candidate AAI molecules with physiologically based pharmacokinetics (PBPK) modeling would provide critical data for the accurate dosing of new therapeutic agents against COVID-19. This review analyzes the dual mechanisms of AAI agents with potential anti-SARS-CoV-2 activity and discusses the principles of PBPK modeling as a conceptual guide to develop new pharmacological modalities for the treatment of COVID-19.

Discovery of Inhibitors of DNA Methyltransferase 2, an Epitranscriptomic Modulator and Potential Target for Cancer Treatment

Selective manipulation of the epitranscriptome could be beneficial for the treatment of cancer and also broaden the understanding of epigenetic inheritance. Inhibitors of the tRNA methyltransferase DNMT2, the enzyme catalyzing the S-adenosylmethionine-dependent methylation of cytidine 38 to 5-methylcytidine, were designed, synthesized, and analyzed for their enzyme-binding and -inhibiting properties. For rapid screening of potential DNMT2 binders, a microscale thermophoresis assay was established. Besides the natural inhibitors S-adenosyl-l-homocysteine (SAH) and sinefungin (SFG), we identified new synthetic inhibitors based on the structure of N-adenosyl-2,4-diaminobutyric acid (Dab). Structure-activity relationship studies revealed the amino acid side chain and a Y-shaped substitution pattern at the 4-position of Dab as crucial for DNMT2 inhibition. The most potent inhibitors are alkyne-substituted derivatives, exhibiting similar binding and inhibitory potencies as the natural compounds SAH and SFG. CaCo-2 assays revealed that poor membrane permeabilities of the acids and rapid hydrolysis of an ethylester prodrug might be the reasons for the insufficient activity in cellulo.

Protein-Ligand Docking in the Machine-Learning Era

Molecular docking plays a significant role in early-stage drug discovery, from structure-based virtual screening (VS) to hit-to-lead optimization, and its capability and predictive power is critically dependent on the protein-ligand scoring function. In this review, we give a broad overview of recent scoring function development, as well as the docking-based applications in drug discovery. We outline the strategies and resources available for structure-based VS and discuss the assessment and development of classical and machine learning protein-ligand scoring functions. In particular, we highlight the recent progress of machine learning scoring function ranging from descriptor-based models to deep learning approaches. We also discuss the general workflow and docking protocols of structure-based VS, such as structure preparation, binding site detection, docking strategies, and post-docking filter/re-scoring, as well as a case study on the large-scale docking-based VS test on the LIT-PCBA data set.

Predicting Protein-Ligand Docking Structure with Graph Neural Network

Modern day drug discovery is extremely expensive and time consuming. Although computational approaches help accelerate and decrease the cost of drug discovery, existing computational software packages for docking-based drug discovery suffer from both low accuracy and high latency. A few recent machine learning-based approaches have been proposed for virtual screening by improving the ability to evaluate protein-ligand binding affinity, but such methods rely heavily on conventional docking software to sample docking poses, which results in excessive execution latencies. Here, we propose and evaluate a novel graph neural network (GNN)-based framework, MedusaGraph, which includes both pose-prediction (sampling) and pose-selection (scoring) models. Unlike the previous machine learning-centric studies, MedusaGraph generates the docking poses directly and achieves from 10 to 100 times speedup compared to state-of-the-art approaches, while having a slightly better docking accuracy.

Computational methods to assist in the discovery of pharmacological chaperones for rare diseases

Pharmacological chaperones are chemical compounds able to bind proteins and stabilize them against denaturation and following degradation. Some pharmacological chaperones have been approved, or are under investigation, for the treatment of rare inborn errors of metabolism, caused by genetic mutations that often can destabilize the structure of the wild-type proteins expressed by that gene. Given that, for rare diseases, there is a general lack of pharmacological treatments, many expectations are poured out on this type of compounds. However, their discovery is not straightforward. In this review, we would like to focus on the computational methods that can assist and accelerate the search for these compounds, showing also examples in which these methods were successfully applied for the discovery of promising molecules belonging to this new category of pharmacologically active compounds.

Potential of phytocompounds from Brassica oleracea targeting S2-domain of SARS-CoV-2 spike glycoproteins: Structural and molecular insights

By 24th Sep. 2021, there are more than 229 million COVID-19 cases worldwide, the researchers are tirelessly working to discover and develop an efficient drug molecule against this devastative viral infection. This study aims to evaluate the inhibitory efficiency of the organic acids and phenolic compounds present in Brassica oleracea (Tronchuda Cabbage) against spike glycoprotein in SARS-CoV-2. Thirty-seven phytocompounds are screened on the basis of their molecular weight (<500 g/mol) and 14 ligands are docked using Autodock Vina and Autodock4 (version 4.2.6). The stability of the top five docked complexes was analyzed using classical molecular dynamics (MD) simulation. ADMET analysis is performed for the top five compounds and their targets are identified using SwissTargetPrediction. Phytoactives from B. oleracea namely Astragalin, 3-p-coumaroylquinic acid, 4-p-coumaroylquinic acid and sinapoyl-D-glucoside showed high binding affinities and free energy of binding during molecular docking and MD simulation studies (∼ 8.5-9.0 kcal/mol) for the spike glycoprotein trimer of SARS-CoV2. The ADMET analysis revealed that these phytocompounds have good solubility in the aqueous phase and that they don't penetrate the blood brain barrier. Moreover, there is no P-gp substrate inhibition, CYP1A2 inhibition, CYP2C19 inhibition, CYP2C9 inhibition, CYP2D6 inhibition and CYP3A4 inhibition observed for these compounds. Additionally, zero PAINS alerts were reported. These findings from molecular docking and MD simulation studies suggest that astragalin and coumaroylquinic acids from Tronchuda cabbage possess potential inhibitory capacity against spike glycoprotein trimer of SARS-CoV-2 and could be further taken up as lead targets for drug discovery.

Design, synthesis, and biological activities of 3-((4,6-diphenylpyrimidin-2-ylamino)methylene)-2,3-dihydrochromen-4-ones

Novel (Z)-3-((4,6-diphenylpyrimidin-2-ylamino)methylene)-2,3-dihydrochromen-4-one derivatives were designed and synthesized to find chemotherapeutic agents. Derivative 9 was selected based on its clonogenicity against cancer cells and synthetic yield for further biological experiments. It showed decreases in aurora kinase A, B, and C phosphorylation from western blot analysis. Derivative 9 upregulated the expression of G1 cell cycle inhibitory proteins including p21 and p27, and G1 progressive cyclin D1, and downregulated G1-to-S progressive cyclins, resulting in cell cycle arrest at the G1/S boundary. It stimulated the cleavage of caspase-9, -3, -7, and poly (ADP-ribose) polymerase, resulting in triggering apoptosis through a caspase-dependent pathway. In addition, derivative 9 inhibited in vivo tumor growth in a syngeneic tumor implantation mouse model. The findings of this study suggest that derivative 9 can be considered as a lead compound for chemotherapeutic agents.

Conformational analysis, molecular structure, spectroscopic, NBO, reactivity descriptors, wavefunction and molecular docking investigations of 5,6-dimethoxy-1-indanone: A potential anti Alzheimer's agent

The objective of the present study is focused to elucidate the structure of potential anti-Alzheimer's compound 5,6-Dimethoxy-1-indanone (5,6-DMI) and study its binding interaction towards the active site by molecular docking studies. The structural and various spectroscopic tools are used to understand the various interaction behaviors of the title compound. The theoretical calculation of 5,6-DMI molecule is computed by Gaussian 09W software with Density functional B3LYP and CAM-B3LYP method utilizing 6-311G(d,p) as basis set. The Natural Bond Orbital (NBO) analysis has been performed to find all possible transition was correlate with electronic transition. The Non covalent interaction of 5,6-DMI molecule was examined by adopt Reduced Density Gradient (RDG) analysis and colour filled ELF diagram. Molecular docking results suggest that 5,6-DMI may exhibit inhibitory activity against apoE protein and may act as potential against Alzheimer's disease.

Computational study of quinoline-based thiadiazole compounds as potential antileishmanial inhibitors

Leishmaniasis is a severe disease caused by protozoan parasites of the genus Leishmania and it is accountable for sizable morbidity and mortality worldwide.

Anti-adipogenic effect of the flavonoids through the activation of AMPK in palmitate (PA)-treated HepG2 cells

BACKGROUND

Flavonoids are natural polyphenols found widely in citrus fruit and peel that possess anti-adipogenic effects. On the other hand, the detailed mechanisms for the anti-adipogenic effects of flavonoids are unclear.

OBJECTIVES

The present study observed the anti-adipogenic effects of five major citrus flavonoids, including hesperidin (HES), narirutin (NAR), nobiletin (NOB), sinensetin (SIN), and tangeretin (TAN), on AMP-activated protein kinase (AMPK) activation in palmitate (PA)-treated HepG2 cells.

METHODS

The intracellular lipid accumulation and triglyceride (TG) contents were quantified by Oil-red O staining and TG assay, respectively. The glucose uptake was assessed using 2-[N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)amino]-2-deoxy-d-glucose (2-NBDG) assay. The levels of AMPK, acetyl-CoA carboxylase (ACC), and glycogen synthase kinase 3 beta (GSK3β) phosphorylation, and levels of sterol regulatory element-binding protein 2 (SREBP-2) and 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) expression were analyzed by Western blot analysis. The potential interaction between the flavonoids and the γ-subunit of AMPK was investigated by molecular docking analysis.

RESULTS

The flavonoid treatment reduced both intracellular lipid accumulation and TG content in PA-treated HepG2 cells significantly. In addition, the flavonoids showed increased 2-NBDG uptake in an insulin-independent manner in PA-treated HepG2 cells. The flavonoids increased the AMPK, ACC, and GSK3β phosphorylation levels and decreased the SREBP-2 and HMGCR expression levels in PA-treated HepG2 cells. Molecular docking analysis showed that the flavonoids bind to the CBS domains in the regulatory γ-subunit of AMPK with high binding affinities and could serve as potential AMPK activators.

CONCLUSION

The overall results suggest that the anti-adipogenic effect of flavonoids on PA-treated HepG2 cells results from the activation of AMPK by flavonoids.

Natural inspired piperine-based ureas and amides as novel antitumor agents towards breast cancer

In this work, the natural piperine moiety was utilised to develop two sets of piperine-based amides (5a–i) and ureas (8a–y) as potential anticancer agents. The anticancer action was assessed against triple negative breast cancer (TNBC) MDA-MB-231, ovarian A2780CP and hepatocellular HepG2 cancer cell lines. In particular, 8q stood out as the most potent anti-proliferative analogue against TNBC MDA-MB-231 cells with IC₅₀ equals 18.7 µM, which is better than that of piperine (IC₅₀ = 47.8 µM) and 5-FU (IC₅₀ = 38.5 µM). Furthermore, 8q was investigated for its possible mechanism of action in MDA-MB-231 cells via Annexin V-FITC apoptosis assay and cell cycle analysis. Moreover, an in-silico analysis has proposed VEGFR-2 as a probable enzymatic target for piperine-based derivatives, and then has explored the binding interactions within VEGFR-2 active site (PDB:4ASD). Finally, an in vitro VEGFR-2 inhibition assay was performed to validate the in silico findings, where 8q showed good VEGFR-2 inhibitory activity with IC₅₀ = 231 nM.

The effects of naringenin and naringin on the glucose uptake and AMPK phosphorylation in high glucose treated HepG2 cells

Background

Naringin and its aglycone naringenin are citrus-derived flavonoids with several pharmacological effects. On the other hand, the mechanism for the anti-diabetic effects of naringenin and naringin are controversial and remain to be clarified further.

Objective

This study examined the relationship between glucose uptake and AMP-activated protein kinase (AMPK) phosphorylation by naringenin and naringin in high glucose-treated HepG2 cells.

Methods

Glucose uptake was measured using the 2-NBDG fluorescent D-glucose analog. The phosphorylation levels of AMPK and GSK3β (Glycogen synthase kinase 3 beta) were observed by Western blotting. Molecular docking analysis was performed to evaluate the binding affinity of naringenin and naringin to the γ-subunit of AMPK.

Results

The treatment with naringenin and naringin stimulated glucose uptake regardless of insulin stimulation in high glucose-treated HepG2 cells. Both flavonoids increased glucose uptake by promoting the phosphorylation of AMPK at Thr172 and increased the phosphorylation of GSK3β. Molecular docking analysis showed that both naringenin and naringin bind to the γ-subunit of AMPK with high binding affinities. In particular, naringin showed higher binding affinity than the true modulator, AMP with all three CBS domains (CBS1, 3, and 4) in the γ-subunit of AMPK. Therefore, both naringenin and naringin could be positive modulators of AMPK activation, which enhance glucose uptake regardless of insulin stimulation in high glucose-treated HepG2 cells.

Conclusions

The increased phosphorylation of AMPK at Thr172 by naringenin and naringin might enhance glucose uptake regardless of insulin stimulation in high glucose treated HepG2 cells.