Assessing Molecular Docking Tools to Guide Targeted Drug Discovery of CD38 Inhibitors

Spiro-Acridine Compound as a Pteridine Reductase 1 Inhibitor: in silico Target Fishing and in vitro Studies

Among the many neglected tropical diseases, leishmaniasis ranks second in mortality rate and prevalence. In a previous study, acridine derivatives were synthesized and tested for their antileishmanial activity against L. chagasi. The most active compound identified in that study (1) showed a single digit IC50 value against the parasite (1.10 μg/mL), but its macromolecular target remained unknown. Aiming to overcome this limitation, this work exploited inverse virtual screening to identify compound 1's putative molecular mechanism of action. In vitro assays confirmed that compound 1 binds to Leishmania chagasi pteridine reductase 1 (LcPTR1), with moderate affinity (Kd=33,1 μM), according to differential scanning fluorimetry assay. Molecular dynamics simulations confirm the stability of LcPTR1-compound 1 complex, supporting a competitive mechanism of action. Therefore, the workflow presented in this work successfully identified PTR1 as a macromolecular target for compound 1, allowing the designing of novel potent antileishmanial compounds.

Exploring NAD+ metabolism and NNAT: Insights from structure, function, and computational modeling

Nicotinamide Adenine Dinucleotide (NAD+), a coenzyme, is ubiquitously distributed and serves crucial functions in diverse biological processes, encompassing redox reactions, energy metabolism, and cellular signalling. This review article explores the intricate realm of NAD + metabolism, with a particular emphasis on the complex relationship between its structure, function, and the pivotal enzyme, Nicotinate Nucleotide Adenylyltransferase (NNAT), also known as nicotinate mononucleotide adenylyltransferase (NaMNAT), in the process of its biosynthesis. Our findings indicate that NAD + biosynthesis in humans and bacteria occurs via the same de novo synthesis route and the pyridine ring salvage pathway. Maintaining NAD homeostasis in bacteria is imperative, as most bacterial species cannot get NAD+ from their surroundings. However, due to lower sequence identity and structurally distant relationship of bacteria, including E. faecium and K. pneumonia, to its human counterpart, inhibiting NNAT, an indispensable enzyme implicated in NAD + biosynthesis, is a viable alternative in curtailing infections orchestrated by E. faecium and K. pneumonia. By merging empirical and computational discoveries and connecting the intricate NAD + metabolism network with NNAT's crucial role, it becomes clear that the synergistic effect of these insights may lead to a more profound understanding of the coenzyme's function and its potential applications in the fields of therapeutics and biotechnology.

In silico construction of a focused fragment library facilitating exploration of chemical space

Fragment-based drug design (FBDD) has emerged as a captivating subject in the realm of computer-aided drug design, enabling the generation of novel molecules through the rearrangement of ring systems within known compounds. The construction of focused fragment library plays a pivotal role in FBDD, necessitating the compilation of all potential bioactive ring systems capable of interacting with a specific target. In our study, we propose a workflow for the development of a focused fragment library and combinatorial compound library. The fragment library comprises seed fragments and collected fragments. The extraction of seed fragments is guided by receptor information, serving as a prerequisite for establishing a focused libraries. Conversely, collected fragments are obtained using the feature graph method, which offers a simplified representation of fragments and strikes a balance between diversity and similarity when categorizing different fragments. The utilization of feature graph facilitates the rational partitioning of chemical space at fragment level, enabling the exploration of desired chemical space and enhancing the efficiency of screening compound library. Analysis demonstrates that our workflow enables the enumeration of a greater number of entirely new potential compounds, thereby aiding in the rational design of drugs.

Bavachinin protects the liver in NAFLD by promoting regeneration via targeting PCNA

INTRODUCTION

Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease all over the world, and no drug is approved for the treatment of NAFLD. Bavachinin (BVC) is proven to possess liver-protecting effect against NAFLD, but its mechanism is still blurry.

OBJECTIVES

With the use of Click Chemistry-Activity-Based Protein Profiling (CC-ABPP) technology, this study aims to identify the target of BVC, and investigate the mechanism by which BVC exerts its liver-protecting effect.

METHODS

The high fat diet induced hamster NAFLD model is introduced to investigate BVC's lipid-lowering and liver-protecting effects. Then, a small molecular probe ofBVC is designed and synthesized based on theCC-ABPP technology, and BVC's target is fished out. A series of experiments are performed to identify the target, including competitive inhibition assay, surface-plasmon resonance (SPR), cellular thermal shift assay (CETSA), drug affinity responsive target stability (DARTS) assay, and co-immunoprecipitation (Co-IP). Afterward, the pro-regeneration effects of BVC are validated in vitro and in vivo through flow cytometry, immunofluorescence, and the terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL).

RESULT

In the hamster NAFLD model, BVC shows lipid-lowing effect and improvement on the histology. PCNA is identified as the target of BVC with the method mentioned above, and BVC facilitates the interaction between PCNA and DNA polymerase delta. BVC promotes HepG2 cells proliferation which is inhibited by T2AA, an inhibitor suppresses the interaction between PCNA and DNA polymerase delta. In NAFLD hamsters, BVC enhances PCNA expression and liver regeneration, reduces hepatocyte apoptosis.

CONCLUSION

This study suggests that, besides the anti-lipemic effect, BVC binds to the pocket of PCNA facilitating its interaction with DNA polymerase delta and pro-regeneration effect, thereby exerts the protective effect against HFD induced liver injury.

The Search for Antidotes Against Ricin

The castor plant (Ricinus communis) is primarily known for its seeds, which contain a unique fatty acid called ricinoleic acid with several industrial and commercial applications. Castor seeds also contain ricin, a toxin considered a chemical and biological warfare agent. Despite years of investigation, there is still no effective antidote or vaccine available. However, some progress has been made, and the development of an effective treatment may be on the horizon. To provide an updated overview of this issue, we have conducted a comprehensive review of the literature on the current state of research in the fight against ricin. This review is based on the reported research and aims to address the challenges faced by researchers, as well as highlight the most successful cases achieved thus far. Our goal is to encourage the scientific community to continue their efforts in this critical search.

Comparative Assessment of Pose Prediction Accuracy in RNA-Ligand Docking

Structure-based virtual high-throughput screening is used in early-stage drug discovery. Over the years, docking protocols and scoring functions for protein-ligand complexes have evolved to improve the accuracy in the computation of binding strengths and poses. In the past decade, RNA has also emerged as a target class for new small-molecule drugs. However, most ligand docking programs have been validated and tested for proteins and not RNA. Here, we test the docking power (pose prediction accuracy) of three state-of-the-art docking protocols on 173 RNA-small molecule crystal structures. The programs are AutoDock4 (AD4) and AutoDock Vina (Vina), which were designed for protein targets, and rDock, which was designed for both protein and nucleic acid targets. AD4 performed relatively poorly. For RNA targets for which a crystal structure of a bound ligand used to limit the docking search space is available and for which the goal is to identify new molecules for the same pocket, rDock performs slightly better than Vina, with success rates of 48% and 63%, respectively. However, in the more common type of early-stage drug discovery setting, in which no structure of a ligand-target complex is known and for which a larger search space is defined, rDock performed similarly to Vina, with a low success rate of ∼27%. Vina was found to have bias for ligands with certain physicochemical properties, whereas rDock performs similarly for all ligand properties. Thus, for projects where no ligand-protein structure already exists, Vina and rDock are both applicable. However, the relatively poor performance of all methods relative to protein-target docking illustrates a need for further methods refinement.

Synthesis of Pyrrolo[3,4-b]pyridin-5-ones via Ugi-Zhu Reaction and In Vitro-In Silico Studies against Breast Carcinoma

An Ugi-Zhu three-component reaction (UZ-3CR) coupled in a one-pot manner to a cascade process (N-acylation/aza Diels-Alder cycloaddition/decarboxylation/dehydration) was performed to synthesize a series of pyrrolo[3,4-b]pyridin-5-ones in 20% to 92% overall yields using ytterbium triflate as a catalyst, toluene as a solvent, and microwaves as a heat source. The synthesized molecules were evaluated in vitro against breast cancer cell lines MDA-MB-231 and MCF-7, finding that compound 1f, at a concentration of 6.25 μM, exhibited a potential cytotoxic effect. Then, to understand the interactions between synthesized compounds and the main proteins related to the cancer cell lines, docking studies were performed on the serine/threonine kinase 1 (AKT1) and Orexetine type 2 receptor (Ox2R), finding moderate to strong binding energies, which matched accurately with the in vitro results. Additionally, molecular dynamics were performed between proteins related to the studied cell lines and the three best ligands.

Developmental landscape of computational techniques to explore the potential phytochemicals from Punica granatum peels for their antioxidant activity in Alzheimer's disease

Alzheimer's disease (AD) is more commonly found in women than in men as the risk increases with age. Phytochemicals are screened in silico from Punica granatum peels for their antioxidant activity to be utilized for Alzheimer's disease. Alzheimer's disease is inhibited by the hormone estrogen, which protects the brain from the bad effects of amyloid beta and acetylcholine (ACh), and is important for memory processing. For the purpose, a library of about 1,000 compounds from P. granatum were prepared and studied by applying integrated computational calculations like 3D-QSAR, molecular docking, MD simulation, ADMET, and density functional theory (DFT). The 3D-QSAR model screened the active compounds B25, B29, B35, B40, B45, B46, B48, B61, and B66 by the field points and activity atlas model from the prepared library. At the molecular level, docking was performed on active compounds for leading hit compounds such as B25 and B35 that displayed a high MolDock score, efficacy, and compatibility with drug delivery against the antioxidant activity. Optimization of the structure and chemical reactivity parameter of the hit compound was calculated by DFT. Moreover, ADMET prediction was evaluated to check the bioavailability and toxicity of the hit compound. Hesperidin (B25) is found to be a hit compound after the whole study and can be synthesized for potent drug discovery in the future.

The role of miRNAs carried by extracellular vesicles in type 2 diabetes and its complications

Diabetes poses severe global public health problems and places heavy burdens on the medical and economic systems of society. Type 2 diabetes (T2D) accounts for 90% of these cases. Diabetes also often accompanies serious complications that threaten multiple organs such as the brain, eyes, kidneys, and the cardiovascular system. MicroRNAs (miRNAs) carried by extracellular vesicles (EV-miRNAs) are considered to mediate cross-organ and cross-cellular communication and have a vital role in the pathophysiology of T2D. They also offer promising sources of diabetes-related biomarkers and serve as effective therapeutic targets. Here, we briefly reviewed studies of EV-miRNAs in T2D and related complications. Specially, we innovatively explore the targeting nature of miRNA action due to the target specificity of vesicle binding, aiding mechanism understanding as well as the detection and treatment of diseases.

Screening compounds for treating the diabetes and COVID-19 from Miao medicine by molecular docking and bioinformatics

Both diabetes and Corona Virus Disease 2019 (COVID-19) are seriously harmful to human health, and they are closely related. It is of great significance to find drugs that can simultaneously treat diabetes and COVID-19. Based on the theory of traditional Chinese medicine for treating COVID-19, this study first sorted out the compounds of Guizhou Miao medicine with "return to the lung channel" and "clear heat and detoxify" effects in China. The active components against COVID-19 were screened by molecular docking with SARS-CoV-2 PLpro and angiotensin-converting enzyme II as targets. Furthermore, the common target dipeptidyl peptidase 4 (DPP4) of diabetes and COVID-19 was used as a screening protein, and molecular docking was used to obtain potential components for the treatment of diabetes and COVID-19. Finally, the mechanism of potential ingredients in the treatment of diabetes and COVID-19 was explored with bioinformatics. More than 80 kinds of Miao medicine were obtained, and 584 compounds were obtained. Further, 110 compounds against COVID-19 were screened, and top 6 potential ingredients for the treatment of diabetes and COVID-19 were screened, including 3-O-β-D-Xylopyranosyl-(1-6)-β-D-glucopyranosyl-(1-6)-β-D-glucopyranosyl oleanolic acid 28-O-β-D-glucopyranosyl ester, Glycyrrhizic acid, Sequoiaflavone, 2-O-Caffeoyl maslinic acid, Pholidotin, and Ambewelamide A. Bioinformatics analysis found that their mechanism of action in treating diabetes and COVID-19 may be related to regulating the expression of DPP4, angiotensin II type 1 receptor, vitamin D receptor, plasminogen, chemokine C-C-motif receptor 6, and interleukin 2. We believe that Guizhou Miao medicine is rich in potential ingredients for the treatment of diabetes and COVID-19.

Development and application of fragment-based de novo inhibitor design approaches against Plasmodium falciparum GST

CONTEXT

Modulation of disease progression is frequently started by identifying biochemical pathway catalyzed by biomolecule that is prone to inhibition by small molecular weight ligands. Such ligands (leads) can be obtained from natural resources or synthetic libraries. However, de novo design based on fragments assembly and optimization is showing increasing success. Plasmodium falciparum parasite depends on glutathione-S-transferase (PfGST) in buffering oxidative heme as an approach to resist some antimalarials. Therefore, PfGST is considered an attractive target for drug development. In this research, fragment-based approaches were used to design molecules that can fit to glutathione (GSH) binding site (G-site) of PfGST.

METHODS

The involved approaches build molecules from fragments that are either isosteric to GSH sub-moieties (ligand-based) or successfully docked to GSH binding sub-pockets (structure-based). Compared to reference GST inhibitor of S-hexyl GSH, ligands with improved rigidity, synthetic accessibility, and affinity to receptor were successfully designed. The method involves joining fragments to create ligands. The ligands were then explored using molecular docking, Cartesian coordinate's optimization, and simplified free energy determination as well as MD simulation and MMPBSA calculations. Several tools were used which include OPENEYE toolkit, Open Babel, Autodock Vina, Gromacs, and SwissParam server, and molecular mechanics force field of MMFF94 for optimization and CHARMM27 for MD simulation. In addition, in-house scripts written in Matlab were used to control fragments connection and automation of the tools.

Computational Exploration of Potential CFTR Binding Sites for Type I Corrector Drugs

Cystic fibrosis (CF) is a recessive genetic disease that is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) protein. The recent development of a class of drugs called "correctors", which repair the structure and function of mutant CFTR, has greatly enhanced the life expectancy of CF patients. These correctors target the most common disease causing CFTR mutant F508del and are exemplified by the FDA-approved VX-809. While one binding site of VX-809 to CFTR was recently elucidated by cryo-electron microscopy, four additional binding sites have been proposed in the literature and it has been theorized that VX-809 and structurally similar correctors may engage multiple CFTR binding sites. To explore these five binding sites, ensemble docking was performed on wild-type CFTR and the F508del mutant using a large library of structurally similar corrector drugs, including VX-809 (lumacaftor), VX-661 (tezacaftor), ABBV-2222 (galicaftor), and a host of other structurally related molecules. For wild-type CFTR, we find that only one site, located in membrane spanning domain 1 (MSD1), binds favorably to our ligand library. While this MSD1 site also binds our ligand library for F508del-CFTR, the F508del mutation also opens a binding site in nucleotide binding domain 1 (NBD1), which enables strong binding of our ligand library to this site. This NBD1 site in F508del-CFTR exhibits the strongest overall binding affinity for our library of corrector drugs. This data may serve to better understand the structural changes induced by mutation of CFTR and how correctors bind to the protein. Additionally, it may aid in the design of new, more effective CFTR corrector drugs.

Scaffold repositioning of spiro-acridine derivatives as fungi chitinase inhibitor by target fishing and in vitro studies

The concept of "one target, one drug, one disease" is not always true, as compounds with previously described therapeutic applications can be useful to treat other maladies. For example, acridine derivatives have several potential therapeutic applications. In this way, identifying new potential targets for available drugs is crucial for the rational management of diseases. Computational methodologies are interesting tools in this field, as they use rational and direct methods. Thus, this study focused on identifying other rational targets for acridine derivatives by employing inverse virtual screening (IVS). This analysis revealed that chitinase enzymes can be potential targets for these compounds. Subsequently, we coupled molecular docking consensus analysis to screen the best chitinase inhibitor among acridine derivatives. We observed that 3 compounds displayed potential enhanced activity as fungal chitinase inhibitors, showing that compound 5 is the most active molecule, with an IC₅₀ of 0.6 ng/µL. In addition, this compound demonstrated a good interaction with the active site of chitinases from Aspergillus fumigatus and Trichoderma harzianum. Additionally, molecular dynamics and free energy demonstrated complex stability for compound 5. Therefore, this study recommends IVS as a powerful tool for drug development. The potential applications are highlighted as this is the first report of spiro-acridine derivatives acting as chitinase inhibitors that can be potentially used as antifungal and antibacterial candidates.

Combining In Vitro and In Silico New Approach Methods to Investigate Type 3 Iodothyronine Deiodinase Chemical Inhibition Across Species

New approach methodologies (NAMs) are being developed to reduce and replace vertebrate animal testing in support of ecotoxicology and risk assessment. The US Environmental Protection Agency's Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) bioinformatic tool was used to evaluate amino acid sequence conservation of the type 3 iodothyronine deiodinase (DIO3) enzyme across species to demonstrate NAM applications for understanding effects of chemical interactions with a specific protein target. Existing literature was used to identify critical amino acids for thyroid hormone binding and interaction with a reducing cofactor. The SeqAPASS tool identifies whether known critical amino acids involved in ligand binding are exact, partial, or not matches across species compared with a template species based on molecular weight and side chain classification. This evaluation guided the design of variant proteins representing critical amino acid substitutions found in various species. Site-directed mutagenesis of the wild-type (WT) human DIO3 gene sequence was used to create six variant proteins expressed in cell culture, which were then tested in vitro for chemical inhibition. Significant differences in in vitro median inhibitory concentration results were observed among variants for potential competitive inhibitors. A molecular model representing the WT human DIO3 was constructed using Molecular Operating Environment (MOE) software and mutated in silico to create the six variants. The MOE Site Finder tool identified the proposed catalytic and cofactor sites and potential alternative binding sites. Virtual docking did not provide affinity scores with sufficient resolution to rank the potency of the chemical inhibitors. Chemical characteristics, function and location of substituted amino acids, and complexities of the protein target are important considerations in developing NAMs to evaluate chemical susceptibility across species. Environ Toxicol Chem 2023;42:1032-1048. © 2023 University of Wisconsin-Madison. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Molecular dynamics-derived pharmacophores of Schistosoma glutathione transferase in complex with bromosulfophthalein: Screening and analysis of potential inhibitors

Schistosoma glutathione transferases (GSTs) have been identified as attractive drug targets for the design of novel antischistosomals. Here, we used in silico methods to validate the discriminative inhibitory properties of bromosulfophthalein (BSP) against the 26-kDa GST from S. japonicum (Sj26GST), and the 28-kDa GST from S. haematobium (Sh28GST), versus human GST (hGST) isoforms alpha (hGSTA), mu (hGSTM) and pi (hGSTP). The use of BSP as an archetypal selective inhibitor was harnessed to produce molecular dynamics-derived pharmacophores of the two targets. Pharmacophore-based screening using a large dataset of experimental and approved drug compounds was performed to produce a shortlist of candidates. The top candidate for each target was prioritised via molecular docking, yielding guanosine-3'-monophosphate-5'-diphosphate (G3D) for Sj26GST, and quercetin-3'-O-phosphate (Q3P) for Sh28GST. Comparative molecular dynamics studies of both candidates compared to BSP showed similar characteristics of binding stability and strength, suggesting their potential to emulate the inhibitory effects of BSP.

Comparative Assessment of Docking Programs for Docking and Virtual Screening of Ribosomal Oxazolidinone Antibacterial Agents

Oxazolidinones are a broad-spectrum class of synthetic antibiotics that bind to the 50S ribosomal subunit of Gram-positive and Gram-negative bacteria. Many crystal structures of the ribosomes with oxazolidinone ligands have been reported in the literature, facilitating structure-based design using methods such as molecular docking. It would be of great interest to know in advance how well docking methods can reproduce the correct ligand binding modes and rank these correctly. We examined the performance of five molecular docking programs (AutoDock 4, AutoDock Vina, DOCK 6, rDock, and RLDock) for their ability to model ribosomal–ligand interactions with oxazolidinones. Eleven ribosomal crystal structures with oxazolidinones as the ligands were docked. The accuracy was evaluated by calculating the docked complexes’ root-mean-square deviation (RMSD) and the program’s internal scoring function. The rankings for each program based on the median RMSD between the native and predicted were DOCK 6 > AD4 > Vina > RDOCK >> RLDOCK. Results demonstrate that the top-performing program, DOCK 6, could accurately replicate the ligand binding in only four of the eleven ribosomes due to the poor electron density of said ribosomal structures. In this study, we have further benchmarked the performance of the DOCK 6 docking algorithm and scoring in improving virtual screening (VS) enrichment using the dataset of 285 oxazolidinone derivatives against oxazolidinone binding sites in the S. aureus ribosome. However, there was no clear trend between the structure and activity of the oxazolidinones in VS. Overall, the docking performance indicates that the RNA pocket’s high flexibility does not allow for accurate docking prediction, highlighting the need to validate VS. protocols for ligand-RNA before future use. Later, we developed a re-scoring method incorporating absolute docking scores and molecular descriptors, and the results indicate that the descriptors greatly improve the correlation of docking scores and pMIC values. Morgan fingerprint analysis was also used, suggesting that DOCK 6 underpredicted molecules with tail modifications with acetamide, n-methylacetamide, or n-ethylacetamide and over-predicted molecule derivatives with methylamino bits. Alternatively, a ligand-based approach similar to a field template was taken, indicating that each derivative’s tail groups have strong positive and negative electrostatic potential contributing to microbial activity. These results indicate that one should perform VS. campaigns of ribosomal antibiotics with care and that more comprehensive strategies, including molecular dynamics simulations and relative free energy calculations, might be necessary in conjunction with VS. and docking.

Structure-based approach: molecular insight of pyranocumarins against α-glucosidase through computational studies

α-glucosidase is an enzyme that catalyzes the release of α-glucose molecules through hydrolysis reactions. Regulation of this enzyme can increase sugar levels in type-2 diabetes mellitus (DM) patients. Pyranocoumarin derivatives have been identified as α-glucosidase inhibitors. Through an in silico approach, this work studied the inhibition of three pyranocoumarin compounds against the α-glucosidase at the molecular level. Molecular docking and molecular dynamics simulation were performed to understand the dynamics behavior of pyranocoumarin derivatives against α-glucosidase. The prediction of free binding energy (ΔG _bind) using the Quantum Mechanics/Molecular Mechanics-Generalized Born (QM/MM-GBSA) approach for each system had the following results, PC1-α-Glu: -13.97 kcal mol^-1, PC2-α-Glu: -3.69 kcal mol^-1, and PC3-α-Glu: -13.68 kcal mol^-1. The interaction energy of each system shows that the grid score, ΔG _bind, and ΔG _exp values had a similar correlation, that was PC1-α-Glu > PC3-α-Glu > PC2-α-Glu. Additionally, the decomposition energy analysis (ΔG ^residue _bind) was carried out to find out the contribution of the key binding residue. The results showed that there were 15 key binding residues responsible for stabilizing pyranocumarin binding with criteria of ΔG ^residue _bind < -1.00 kcal mol^-1. The evaluation presented in this work could provide information on the molecular level about the inhibitory efficiency of pyranocoumarin derivatives against a-glucosidase enzyme based on computational studies.

Molecular docking-based virtual screening: Challenges in hits identification for Anti-SARS-Cov-2 activity

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) requires finding new drugs or repurposing drugs for clinical use. Molecular docking belongs to structure-based drug design providing a fast method for identifying the hit compounds with antiviral activity against SARS-Cov-2. However, the weakness of the docking method is compounded by the limited crystallographic information and comparison drugs due to the novelty of this virus can present challenges in identifying hits of anti-SARS-Cov-2. In the current review, we highlighted several aspects, especially those related to the target structure, docking validation, and virtual hit selection, that need to be considered to obtain reliable docking results. Here, we discussed several cases pertaining to the issue highlighted and approaches that could be used to solve them.

Flavonoid Constituents and Alpha-Glucosidase Inhibition of Solanum stramonifolium Jacq. Inflorescence with In Vitro and In Silico Studies

Solanum stramonifolium Jacq. (Solanaceae) is widely found in South East Asia. In Thailand, it is used as vegetable and as a component in traditional recipes. The results of an alpha-glucosidase inhibitory screening test found that the crude extract of S. stramonifolium inflorescence exhibited the potential effect with IC₅₀ 81.27 μg/mL. The separation was performed by the increasing solvent polarity method. The ethyl acetate, ethanol, and water extracts of S. stramonifolium inflorescence showed the synergistic effect together with acarbose standard. The phytochemical investigation of these extracts was conducted by chromatographic and spectroscopic techniques. Six flavonoid compounds, myricetin 3, 4', 5', 7-tetramethyl ether (1), combretol (2), kaempferol (3), kaempferol 7-O-glucopyranoside (4), 5-hydroxy 3-7-4'-5'-tetramethoxyflavone-3'-O-glucopyranoside (5), and a mixture (6) of isorhamnetin 3-O-glucopyranoside (6a) and astragalin (6b) were isolated. This discovery is the first report of flavonoid-glycoside 5. Moreover, the selected flavonoids, kaempferol and astragalin, were representatives to explore the mechanism of action. Both of them performed mixed-type inhibition. The molecular docking gave a better understanding of flavonoid compounds' ability to inhibit the alpha-glucosidase enzyme.

Flavonoids as dual inhibitors of cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX): molecular docking and in vitro studies

Background

Inflammation is known to involve in many pathological processes of different diseases, but the current therapy causes adverse effects. Thus, there is a great interest for the discovery of flavonoids as a valuable alternative to classical analgesic and anti-inflammatory agent with dual-inhibitory action, especially on both COX-2 and 5-LOX which can minimize or overcome this problem.

Results

In the present work, drug-likeness properties of the synthesized flavonoids via Lipinski’s Rule of Five were predicted using QikProp prior to evaluation of their COX and LOX inhibitory activities using enzyme assays. Subsequently, molecular docking was performed using GLIDE to analyse their binding behaviour. The results showed that all compounds obeyed the Lipinski’s Rule of Five. NPC6 and NPC7 had displayed better selectivity towards COX-2 as compared to Indomethacin with less than 50% inhibition against COX-1. In addition, these compounds also inhibited activity of 5-LOX. Their selectivity to COX-2 was due to the binding to hydrophobic region and extends to lobby region near the entrance of COX binding site forming hydrogen bond with Ser530. Interestingly, these compounds showed a similar binding mode as Zileuton in the active site of 5-LOX and formed hydrogen bond interaction with Ala424.

Conclusion

NPC6 and NPC7 had potential as dual inhibitor of COX-2 and 5-LOX. The scaffolds of these chemical entities are useful to be as lead compounds for the dual inhibition of COX-2 and 5-LOX.

Effect of Flavonoid-Rich Extract From Dalbergiella welwitschii Leaf on Redox, Cholinergic, Monoaminergic, and Purinergic Dysfunction in Oxidative Testicular Injury: Ex Vivo and In Silico Studies

The antioxidant, cholinergic, monoaminergic, and purinergic activities of flavonoid-rich extract from Dalbergiella welwitschii leaf (FEDW) were investigated on oxidative testicular injury (ex vivo) due to the local report on the use of this plant as anti-testicular injury. Flavonoid extract was obtained from FEDW using a standard procedure. Five male albino rats were used, testes harvested and incubated with FeSO₄ for accessing the cholinergic, monoaminergic, and purinergic activities of the FEDW (ex vivo). Testicular tissues incubated with FeSO₄ demonstrated a significant decrease in antioxidant biomarkers, arginase, ATPase, ENTPDase, 5'-nucleotidase, and PDE-5 activities, as well as Zn and sialic acid levels with an upsurge in malondialdehyde (MDA), and NO levels, myeloperoxidase, cholinesterases, monoamine oxidase (MAO), and angiotensin-converting enzyme (ACE) activities. Treatment of testicular tissues incubated with FeSO₄ via different concentrations of FEDW significantly increased the activities of antioxidant, arginase, ATPase, E-NTPDase, 5'-nucleotidase, phosphodiesterase-5 (PDE-5), as well as Zn and sialic acid levels with a significant decrease in MDA, nitric oxide (NO), myeloperoxidase, cholinesterases, MAO, and ACE levels. Molecular docking revealed the molecular interactions of cyclooxygenase-2 (COX-2) with ellagic acid, piperine, and caffeine with piperine and caffeine obeyed the druggability and pharmacokinetic. These findings point to FEDW as a possible potential for the treatment of oxidative testicular injury.

Structure and surface analyses of a newly synthesized acyl thiourea derivative along with its in silico and in vitro investigations for RNR, DNA binding, urease inhibition and radical scavenging activities

N-((4-Acetylphenyl)carbamothioyl)-2,4-dichlorobenzamide (4) was synthesized by the treatment of 2,4-dichlorobenzoyl chloride with potassium thiocyanate in a 1 : 1 molar ratio in dry acetone to afford the 2,4-dichlorobenzoyl isothiocyanate in situ which on reaction with acetyl aniline furnished (4) in good yield and high purity. The compound was confirmed by FTIR, ¹H-NMR, and ¹³C-NMR and single crystal X-ray diffraction studies. The planar rings were situated at a dihedral angle of 33.32(6)°. The molecules, forming S(6) ring motifs with the intramolecular N–H⋯O hydrogen bonds, were linked through intermolecular C–H⋯O and N–H⋯S hydrogen bonds, enclosing R₂²(8) ring motifs, into infinite double chains along [101]. C–H⋯π and π⋯π interactions with an inter-centroid distance of 3.694 (1) Å helped to consolidate a three-dimensional architecture. Hirshfeld surface (HS) analysis further indicated that the most important contributions for the crystal packing were from H⋯C/C⋯H (20.9%), H⋯H (20.5%), H⋯Cl/Cl⋯H (19.4%), H⋯O/O⋯H (13.8%) and H⋯S/S⋯H (8.9%) interactions. Thus C–H⋯π (ring), π⋯π, van der Waals interactions and hydrogen bonding played the major roles in the crystal packing. The electronic structure and computed DFT (density functional theory) parameters identified the reactivity profile of compound (4). In silico binding of (4) with RNA indicated the formation of a stable protein–ligand complex via hydrogen bonding, while DNA docking studies inferred (4) as a potent groove binder. The experimentally observed hypochromic change (57.2%) in the UV-visible spectrum of (4) in the presence of varying DNA concentrations together with the evaluated binding parameters (K_b; 7.9 × 10⁴ M⁻¹, ΔG; −28.42 kJ mol⁻¹) indicated spontaneous interaction of (4) with DNA via groove binding and hence supported the findings obtained through docking analysis. This compound also showed excellent urease inhibition activity in both in silico and vitro studies with an IC₅₀ value of 0.0389 ± 0.0017 μM. However, the radical scavenging efficiency of (4) was found to be modest in comparison to vitamin C.

A new acyl thiourea derivative was explored for its binding interaction with RNR and DNA and for excellent urease inhibition activity.

An in silico predictive method to select multi-monomer combinations for peptide imprinting

In silico methods enable optimizing artificial receptors such that constructive mimics of natural antibodies can be envisaged. The introduction of combinatorial synthesis strategies via multi-monomer combinations has improved the performance of molecularly imprinted polymers (MIP) significantly. However, it remains experimentally challenging to screen thousands of combinations resulting from a large library of monomers. The present study introduces a molecular mechanics based multi-monomer simultaneous docking approach (MMSD) to computationally screen monomer combinations according to their potential, facilitating selective molecular imprints. Thereby, the diversity of multipoint interactions realizable with a peptide surface is efficiently explored yielding how individual monomer binding capacities constructively or adversely add up when docked together. Additionally, spatially distributed molecular models were mapped for analyzing intermolecular H-bonding and hydrophobic interactions resulting from single monomer docking, as well as bi- and tri-monomer simultaneous docking. A direct impact of complex formation on the binding capacity of the resulting MIPs has been observed. In a first small-scale study, the predictive potential of the MMSD approach was validated via experimentally applied polymer combinations for peptide imprinting via the scoring functions established during the screening process. MMSD clearly enables rational design of MIPs for synthesizing more sensitive and selective artificial receptor materials especially for peptide and protein-epitope templates.

Incorporating Target-Specific Pharmacophoric Information into Deep Generative Models for Fragment Elaboration

Despite recent interest in deep generative models for scaffold elaboration, their applicability to fragment-to-lead campaigns has so far been limited. This is primarily due to their inability to account for local protein structure or a user's design hypothesis. We propose a novel method for fragment elaboration, STRIFE, that overcomes these issues. STRIFE takes as input fragment hotspot maps (FHMs) extracted from a protein target and processes them to provide meaningful and interpretable structural information to its generative model, which in turn is able to rapidly generate elaborations with complementary pharmacophores to the protein. In a large-scale evaluation, STRIFE outperforms existing, structure-unaware, fragment elaboration methods in proposing highly ligand-efficient elaborations. In addition to automatically extracting pharmacophoric information from a protein target's FHM, STRIFE optionally allows the user to specify their own design hypotheses.

Identification of Putative Vaccine and Drug Targets against the Methicillin-Resistant Staphylococcus aureus by Reverse Vaccinology and Subtractive Genomics Approaches

Methicillin-resistant Staphylococcus aureus (MRSA) is an opportunistic pathogen and responsible for causing life-threatening infections. The emergence of hypervirulent and multidrug-resistant (MDR) S. aureus strains led to challenging issues in antibiotic therapy. Consequently, the morbidity and mortality rates caused by S. aureus infections have a substantial impact on health concerns. The current worldwide prevalence of MRSA infections highlights the need for long-lasting preventive measures and strategies. Unfortunately, effective measures are limited. In this study, we focus on the identification of vaccine candidates and drug target proteins against the 16 strains of MRSA using reverse vaccinology and subtractive genomics approaches. Using the reverse vaccinology approach, 4 putative antigenic proteins were identified; among these, PrsA and EssA proteins were found to be more promising vaccine candidates. We applied a molecular docking approach of selected 8 drug target proteins with the drug-like molecules, revealing that the ZINC4235426 as potential drug molecule with favorable interactions with the target active site residues of 5 drug target proteins viz., biotin protein ligase, HPr kinase/phosphorylase, thymidylate kinase, UDP-N-acetylmuramoyl-L-alanyl-D-glutamate-L-lysine ligase, and pantothenate synthetase. Thus, the identified proteins can be used for further rational drug or vaccine design to identify novel therapeutic agents for the treatment of multidrug-resistant staphylococcal infection.

Re-Exploring the Ability of Common Docking Programs to Correctly Reproduce the Binding Modes of Non-Covalent Inhibitors of SARS-CoV-2 Protease Mpro

In the latest few decades, molecular docking has imposed itself as one of the most used approaches for computational drug discovery. Several docking benchmarks have been published, comparing the performance of different algorithms in respect to a molecular target of interest, usually evaluating their ability in reproducing the experimental data, which, in most cases, comes from X-ray structures. In this study, we elucidated the variation of the performance of three docking algorithms, namely GOLD, Glide, and PLANTS, in replicating the coordinates of the crystallographic ligands of SARS-CoV-2 main protease (Mpro). Through the comparison of the data coming from docking experiments and the values derived from the calculation of the solvent exposure of the crystallographic ligands, we highlighted the importance of this last variable for docking performance. Indeed, we underlined how an increase in the percentage of the ligand surface exposed to the solvent in a crystallographic complex makes it harder for the docking algorithms to reproduce its conformation. We further validated our hypothesis through molecular dynamics simulations, showing that the less stable protein–ligand complexes (in terms of root-mean-square deviation and root-mean-square fluctuation) tend to be derived from the cases in which the solvent exposure of the ligand in the starting system is higher.

Apoptotic and anti-angiogenic effects of propolis against human bladder cancer: molecular docking and in vitro screening

INTRODUCTION

Bladder cancer is still of unknown initiation and progression, it is difficult to treat the patient once bladder cancer have a distant metastasis.

MATERIALS AND METHODS

In the present study, propolis extract was evaluated against bladder cancer cells (T24). Two independent pathways were investigated, apoptosis and angiogenesis, Bax, Bcl-2, P53, and caspase-3 for apoptosis, vascular endothelial growth factor receptor and protein kinase A as angiogenesis potential targets.

OBJECTIVES

Molecular docking studies will be conducted for the major known constituents of Egyptian propolis into apoptotic and angiogenic protein targets, to give better insights to the possible binding mode and interactions and investigate the ability of propolis constituents to target both apoptotic and angiogenic pathways.

RESULTS

Propolis showed anti-proliferative activity against T24 cancer cell line, the IC₅₀ value was 6.36 µg/ml. Also significant effects of propolis on Bax, Bcl-2, P53, and caspase-3 were observed.

DISCUSSION

These obtained results proved the ability of propolis to induce cell death. Also it has revealed noticeable effects on protein kinase A and vascular endothelial growth factor receptor.

CONCLUSION

The obtained results can encourage us to say that propolis extract can induce a programmed cell death in human bladder cancer cells, and also affect angiogenesis.

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard "lock and key" paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.

Identifying potential inhibitors of biofilm-antagonistic proteins to promote biofilm formation: a virtual screening and molecular dynamics simulations approach

Microbial biofilms play a critical role in environmental biotechnology and associated applications. Biofilm production can be enhanced by inhibiting the function of proteins that negatively regulate their formation. With this objective, an in silico approach was adopted to identify competitive inhibitors of eight biofilm-antagonistic proteins, namely AbrB and SinR (from Bacillus subtilis) and AmrZ, PDE (EAL), PslG, RetS, ShrA and TpbA (from Pseudomonas aeruginosa). Fifteen inhibitors that structurally resembled the natural ligand of each protein were shortlisted using ligand-based and structure-based virtual screening. The top four inhibitors obtained from molecular docking using Autodock Vina were further docked using SwissDock and DOCK 6.9 to obtain a consensus hit for each protein based on different scoring functions. Further analysis of the protein-ligand complexes revealed that these top inhibitors formed significant non-covalent interactions with their respective protein binding sites. The eight protein-ligand complexes were then subjected to molecular dynamics simulations for 30 ns using GROMACS. RMSD and radius of gyration values of 0.1-0.4 nm and 1.0-3.5 nm, respectively, along with hydrogen bond formation throughout the trajectory indicated that all the complexes remained stable, compact and intact during the simulation period. Binding energy values between -20 and -77 kJ/mol obtained from MM-PBSA calculations further confirmed the high affinities of the eight inhibitors for their respective receptors. The outcome of this study holds great promise to enhance biofilms that are central to biotechnological processes associated with microbial electrochemical technologies, wastewater treatment, bioremediation and the industrial production of value-added products.

Chemical Composition and Antioxidant, Anti-Inflammatory, and Enzyme Inhibitory Activities of an Endemic Species from Southern Algeria: Warionia saharae

Warionia saharae Benth. & Coss. (Asteraceae) is an endemic species of North Africa naturally grown in the southwest of the Algerian Sahara. In the present study, this species’ hydromethanolic leaf extract was investigated for its phenolic profile characterized by ultra-high-performance liquid chromatography coupled with a diode array detector and an electrospray mass spectrometer (UHPLC-DAD-ESI/MS). Additionally, the chemical composition of W. saharae was analyzed by gas chromatography–mass spectrometry, and its antioxidant potential was assessed through five in vitro tests: DPPH^● scavenging activity, ABTS^●+ scavenging assay, galvinoxyl scavenging activity, ferric reducing power (FRP), and cupric reducing antioxidant capacity. The UHPLC-DAD-ESI/MS analysis allowed the detection and quantification of 22 compounds, with taxifolin as the dominant compound. The GC–MS analysis allowed the identification of 37 compounds, and the antioxidant activity data indicate that W. saharae extract has a very high capacity to capture radicals due to its richness in compounds with antioxidant capacity. The extract also showed potent α-glucosidase inhibition as well as a good anti-inflammatory activity. However, weak anti-α-amylase and anticholinesterase activities were recorded. Moreover, an in silico docking study was performed to highlight possible interactions between three significant compounds identified in W. saharae extract and α-glucosidase enzyme.

'All That Glitters Is Not Gold': High-Resolution Crystal Structures of Ligand-Protein Complexes Need Not Always Represent Confident Binding Poses

Our understanding of the structure–function relationships of biomolecules and thereby applying it to drug discovery programs are substantially dependent on the availability of the structural information of ligand–protein complexes. However, the correct interpretation of the electron density of a small molecule bound to a crystal structure of a macromolecule is not trivial. Our analysis involving quality assessment of ~0.28 million small molecule–protein binding site pairs derived from crystal structures corresponding to ~66,000 PDB entries indicates that the majority (65%) of the pairs might need little (54%) or no (11%) attention. Out of the remaining 35% of pairs that need attention, 11% of the pairs (including structures with high/moderate resolution) pose serious concerns. Unfortunately, most users of crystal structures lack the training to evaluate the quality of a crystal structure against its experimental data and, in general, rely on the resolution as a ‘gold standard’ quality metric. Our work aims to sensitize the non-crystallographers that resolution, which is a global quality metric, need not be an accurate indicator of local structural quality. In this article, we demonstrate the use of several freely available tools that quantify local structural quality and are easy to use from a non-crystallographer’s perspective. We further propose a few solutions for consideration by the scientific community to promote quality research in structural biology and applied areas.

VirtualFlow Ants-Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization

The docking program PLANTS, which is based on ant colony optimization (ACO) algorithm, has many advanced features for molecular docking. Among them are multiple scoring functions, the possibility to model explicit displaceable water molecules, and the inclusion of experimental constraints. Here, we add support of PLANTS to VirtualFlow (VirtualFlow Ants), which adds a valuable method for primary virtual screenings and rescoring procedures. Furthermore, we have added support of ligand libraries in the MOL2 format, as well as on the fly conversion of ligand libraries which are in the PDBQT format to the MOL2 format to endow VirtualFlow Ants with an increased flexibility regarding the ligand libraries. The on the fly conversion is carried out with Open Babel and the program SPORES. We applied VirtualFlow Ants to a test system involving KEAP1 on the Google Cloud up to 128,000 CPUs, and the observed scaling behavior is approximately linear. Furthermore, we have adjusted several central docking parameters of PLANTS (such as the speed parameter or the number of ants) and screened 10 million compounds for each of the 10 resulting docking scenarios. We analyzed their docking scores and average docking times, which are key factors in virtual screenings. The possibility of carrying out ultra-large virtual screening with PLANTS via VirtualFlow Ants opens new avenues in computational drug discovery.

Establishing an Analogue Based In Silico Pipeline in the Pursuit of Novel Inhibitory Scaffolds against the SARS Coronavirus 2 Papain-Like Protease

The ongoing coronavirus pandemic has been a burden on the worldwide population, with mass fatalities and devastating socioeconomic consequences. It has particularly drawn attention to the lack of approved small-molecule drugs to inhibit SARS coronaviruses. Importantly, lessons learned from the SARS outbreak of 2002-2004, caused by severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1), can be applied to current drug discovery ventures. SARS-CoV-1 and SARS-CoV-2 both possess two cysteine proteases, the main protease (Mpro) and the papain-like protease (PLpro), which play a significant role in facilitating viral replication, and are important drug targets. The non-covalent inhibitor, GRL-0617, which was found to inhibit replication of SARS-CoV-1, and more recently SARS-CoV-2, is the only PLpro inhibitor co-crystallised with the recently solved SARS-CoV-2 PLpro crystal structure. Therefore, the GRL-0617 structural template and pharmacophore features are instrumental in the design and development of more potent PLpro inhibitors. In this work, we conducted scaffold hopping using GRL-0617 as a reference to screen over 339,000 ligands in the chemical space using the ChemDiv, MayBridge, and Enamine screening libraries. Twenty-four distinct scaffolds with structural and electrostatic similarity to GRL-0617 were obtained. These proceeded to molecular docking against PLpro using the AutoDock tools. Of two compounds that showed the most favourable predicted binding affinities to the target site, as well as comparable protein-ligand interactions to GRL-0617, one was chosen for further analogue-based work. Twenty-seven analogues of this compound were further docked against the PLpro, which resulted in two additional hits with promising docking profiles. Our in silico pipeline consisted of an integrative four-step approach: (1) ligand-based virtual screening (scaffold-hopping), (2) molecular docking, (3) an analogue search, and, (4) evaluation of scaffold drug-likeness, to identify promising scaffolds and eliminate those with undesirable properties. Overall, we present four novel, and lipophilic, scaffolds obtained from an exhaustive search of diverse and uncharted regions of chemical space, which may be further explored in vitro through structure-activity relationship (SAR) studies in the search for more potent inhibitors. Furthermore, these scaffolds were predicted to have fewer off-target interactions than GRL-0617. Lastly, to our knowledge, this work contains the largest ligand-based virtual screen performed against GRL-0617.

Ursodesoxycholic acid alleviates liver fibrosis via proregeneration by activation of the ID1-WNT2/HGF signaling pathway

BACKGROUND

The human liver possesses a remarkable capacity for self-repair. However, liver fibrosis remains a serious medical concern, potentially progressing to end-stage liver cirrhosis and even death. Liver fibrosis is characterized by excess accumulation of extracellular matrix in response to chronic injury. Liver regenerative ability, a strong indicator of liver health, is important in resisting fibrosis. In this study, we provide evidence that ursodesoxycholic acid (UDCA) can alleviate liver fibrosis by promoting liver regeneration via activation of the ID1-WNT2/hepatocyte growth factor (HGF) pathway.

METHODS

Bile duct ligation (BDL) and partial hepatectomy (PH) mouse models were used to verify the effects of UDCA on liver fibrosis, regeneration, and the ID1-WNT2/HGF pathway. An Id1 knockdown mouse model was also used to assess the role of Id1 in UDCA alleviation of liver fibrosis.

RESULTS

Our results demonstrate that UDCA can alleviate liver fibrosis in the BDL mice and promote liver regeneration via the ID1-WNT2/HGF pathway in PH mice. In addition, Id1 knockdown abolished the protection afforded by UDCA in BDL mice.

CONCLUSIONS

We conclude that UDCA protects against liver fibrosis by proregeneration via activation of the ID1-WNT2/HGF pathway.

Identification of novel potential ricin inhibitors by virtual screening, molecular docking, molecular dynamics and MM-PBSA calculations: a drug repurposing approach

Ricin is a potent cytotoxin with no available antidote. Its catalytic subunit, RTA, damages the ribosomal RNA (rRNA) of eukaryotic cells, preventing protein synthesis and eventually leading to cell death. The combination between easiness of obtention and high toxicity turns ricin into a potential weapon for terrorist attacks, urging the need of discovering effective antidotes. On this context, we used computational techniques, in order to identify potential ricin inhibitors among approved drugs. Two libraries were screened by two different docking algorithms, followed by molecular dynamics simulations and MM-PBSA calculations in order to corroborate the docking results. Three drugs were identified as potential ricin inhibitors: deferoxamine, leucovorin and plazomicin. Our calculations showed that these compounds were able to, simultaneously, form hydrogen bonds with residues of the catalytic site and the secondary binding site of RTA, qualifying as potential antidotes against intoxication by ricin.Communicated by Ramaswamy H. Sarma.

Current computer-aided drug design methodologies in discovery of novel drug candidates for neuropsychiatric and inflammatory diseases

Drug discovery and development is a very challenging, expensive and time-consuming process. Impressive technological advances in computer sciences and molecular biology have made it possible to use computer-aided drug design (CADD) methods in various stages of the drug discovery and development pipeline. Nowadays, CADD presents an efficacious and indispensable tool, widely used in medicinal chemistry, to lead rational drug design and synthesis of novel compounds. In this article, an overview of commonly used CADD approaches from hit identification to lead optimization was presented. Moreover, different aspects of design of multitarget ligands for neuropsychiatric and anti-inflammatory diseases were summarized. Apparently, designing multi-target directed ligands for treatment of various complex diseases may offer better efficacy, and fewer side effects. Antipsychotics that act through aminergic G protein-coupled receptors (GPCRs), especially Dopamine D2 and serotonin 5-HT2A receptors, are the best option for treatment of various symptoms associated with neuropsychiatric disorders. Furthermore, multi-target directed cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) inhibitors are also a successful approach to aid the discovery of new anti-inflammatory drugs with fewer side effects. Overall, employing CADD approaches in the process of rational drug design provides a great opportunity for future development, allowing rapid identification of compounds with the optimal polypharmacological profile.