Computer-aided Drug Design Technology Research Articles

Current perspectives and trend of computer-aided drug design: a review and bibliometric analysis.

Computer-aided drug design (CADD) is a drug design technique for computing ligand‒receptor interactions and is involved in various stages of drug development. To better grasp the frontiers and hotspots of CADD, we conducted a review analysis through bibliometrics. A systematic review of studies published between 2000 and July 20, 2023 was conducted following the PRISMA guidelines. Literature on CADD was selected from the Web of Science Core Collection. General information, publications, output trends, countries/regions, institutions, journals, keywords, and influential authors were visually analysed using software such as Excel, VOSviewer, RStudio, and CiteSpace. A total of 2,031 publications were included. These publications primarily originated from 99 countries or regions, led by the U.S. and China. Among the contributors, MacKerell AD had the highest number of articles and greatest influence. The Journal of Medicinal Chemistry was the most cited journal, whereas the Journal of Chemical Information and Modeling had the highest number of publications. Influential authors in the field were identified. Current research shows active collaboration between countries, institutions, and companies. CADD technologies such as homology modelling, pharmacophore modelling, quantitative conformational relationships, molecular docking, molecular dynamics simulation, binding free energy prediction, and high-throughput virtual screening can effectively improve the efficiency of new drug discovery. Artificial intelligence-assisted drug design and screening based on CADD represent key topics direction for future development. Furthermore, this paper will be helpful for better understanding the frontiers and hotspots of CADD.

FvOshC Is a Key Global Regulatory Target in Fusarium verticillioides for Fumonisin Biosynthesis and Disease Control.

Fusarium verticillioides has a substantial impact on maize production, commonly leading to maize ear rot and the production of fumonisin, a mycotoxin that poses health risks to both humans and animals. Currently, there is a lack of molecular targets for preventing the disease and controlling the toxin. The biological functions of oxysterol-binding proteins (OSBP) in filamentous fungi remain unclear. In this research, 7 oxysterol-binding protein-related proteins were identified in F. verticillioides, and these proteins were obtained through prokaryotic expression and purification. FvOshC was identified as the specific protein that binds to ergosterol through fluorescence titration. Gene knockout complementation techniques confirmed that FvOSHC plays a positive role, establishing it as a novel global regulatory protein involved in the pathogenicity and FB1 biosynthesis in F. verticillioides. Additionally, the interaction between FvOshC and FvSec14 was identified using yeast two-hybrid techniques. Moreover, computer-aided drug design technology was utilized to identify the receptor molecule Xanthatin based on FvOshC. The inhibitory effect of Xanthatin on the growth of F. verticillioides and the synthesis of FB1 was significantly demonstrated. These findings provide valuable insights that can aid in the management of mycotoxin pollution.

Lysine-Specific Demethylase 1 Inhibitors: A Comprehensive Review Utilizing Computer-Aided Drug Design Technologies.

Lysine-specific demethylase 1 (LSD1/KDM1A) has emerged as a promising therapeutic target for treating various cancers (such as breast cancer, liver cancer, etc.) and other diseases (blood diseases, cardiovascular diseases, etc.), owing to its observed overexpression, thereby presenting significant opportunities in drug development. Since its discovery in 2004, extensive research has been conducted on LSD1 inhibitors, with notable contributions from computational approaches. This review systematically summarizes LSD1 inhibitors investigated through computer-aided drug design (CADD) technologies since 2010, showcasing a diverse range of chemical scaffolds, including phenelzine derivatives, tranylcypromine (abbreviated as TCP or 2-PCPA) derivatives, nitrogen-containing heterocyclic (pyridine, pyrimidine, azole, thieno[3,2-b]pyrrole, indole, quinoline and benzoxazole) derivatives, natural products (including sanguinarine, phenolic compounds and resveratrol derivatives, flavonoids and other natural products) and others (including thiourea compounds, Fenoldopam and Raloxifene, (4-cyanophenyl)glycine derivatives, propargylamine and benzohydrazide derivatives and inhibitors discovered through AI techniques). Computational techniques, such as virtual screening, molecular docking and 3D-QSAR models, have played a pivotal role in elucidating the interactions between these inhibitors and LSD1. Moreover, the integration of cutting-edge technologies such as artificial intelligence holds promise in facilitating the discovery of novel LSD1 inhibitors. The comprehensive insights presented in this review aim to provide valuable information for advancing further research on LSD1 inhibitors.

Computer-Aided Drug Design in Anticancer Drugs

The fight against cancer is a significant global health issue, and creating effective anticancer medications is crucial to addressing this challenge. Traditional methods of developing these drugs are time-consuming and require substantial financial investment. However, computer-aided drug design technology can reduce the time and cost associated with research and development. This paper summarizes various studies that have utilized computer-aided drug design technology to create anticancer drugs. It explores the application of this technology in cancer research and serves as a reference for future development of anticancer medications.

Design, synthesis, and antitumor activity of novel oleanolic acid analogues targeting EGFR

Based on the simulated docking of Epidermal growth factor receptor inhibitors with known active small molecule compounds, computer-aided drug design technology was used to analyze key amino acid fragments and determine the active groups binding with key sites. Then, twelve novel analogues of oleanolic acid (OA) were synthesized by introducing active groups at the C-3 and C-28 positions of OA. The structures of these novel analogues were confirmed by NMR and MS. Furthermore, the antitumor activities of these novel analogues were evaluated by MTT assay. As a result, compounds I3 and II3 showed stronger cytotoxicity on tumor cells than positive controls. In conclusion, our study synthesized twelve novel analogues of OA and determined compounds I3 and II3 had better antitumor effect, which may be potential candidate compounds for tumor therapy.

Design and synthesis of ERα agonists: Effectively reduce lipid accumulation.

In recent years, the incidence of non-alcoholic fatty liver disease (NAFLD) has been increasing worldwide. Hepatic lipid deposition is a major feature of NAFLD, and insulin resistance is one of the most important causes of lipid deposition. Insulin resistance results in the disruption of lipid metabolism homeostasis characterized by increased lipogenesis and decreased lipolysis. Estrogen receptor α (ERα) has been widely reported to be closely related to lipid metabolism. Activating ERa may be a promising strategy to improve lipid metabolism. Here, we used computer-aided drug design technology to discover a highly active compound, YRL-03, which can effectively reduce lipid accumulation. Cellular experimental results showed that YRL-03 could effectively reduce lipid accumulation by targeting ERα, thereby achieving alleviation of insulin resistance. We believe this study provides meaningful guidance for future molecular development of drugs to prevent and treat NAFLD.

It all clicks together: In silico drug discovery becoming mainstream

It all clicks together: In silico drug discovery becoming mainstream

Discovery of traditional Chinese medicines against porcine reproductive and respiratory syndrome virus

Porcine reproductive and respiratory syndrome (PRRS) is a highly contagious disease caused by the porcine reproductive and respiratory syndrome virus (PRRSV). It is characterized by reproductive disorders in pregnant sows and respiratory symptoms in pigs of all ages. Although antiviral drugs, vaccines, and improved management have played a role in the prevention and control of the PRRS, this disease is still prevalent in pig farms. Hence, the prevention, control, and purification of the PRRS have been the main focus. As we all know, traditional Chinese medicines (TCMs) have played a significant role in the history of ancient medicine. Therefore, exploring effective anti-PRRSV TCMs is an essential way to solve the prevention and treatment of PRRSV. In this study, the active sites of the fifth scavenger receptor cysteine-rich domain of the CD163 receptor was first studied by computer-aided drug design technology. Second, virtual screening of TCMs monomers that may bind to active site was conducted. Third, the crude extracts of TCMs rich in the matching monomer were obtained. Finally, the anti-PRRSV effect of crude extracts of TCMs were verified in vitro. To sum up, it was found that Plantago ovata, Rhus chinensis, and Persicaria orientalis had anti-PRRSV effects in vitro, which laid a theoretical foundation for the research and development of anti-PRRSV TCMs. In addition, this exploration strategy could provide a research template for the discovery of TCMs for human viral diseases.

Structure–activity relationship analysis of a series of nonsteroidal analogues as androgen receptor antagonists

Computer-aided drug design technology was used to screen drugs in large-scale and to accelerate the progress of drug design of nonsteroidal compounds deriving from the hybridization of FDA-approved Enzalutamide and Abiraterone.

3D Printing Technology: A New Milestone in the Development of Pharmaceuticals.

The global market of pharmaceuticals has witnessed a new revolution recently in the form of threedimensional printing (3D) technology. 3D printing has its existence since the 1980s that uses a 3D printer to manufacture the different dosage forms through computer-aided drug design technology. The need for 3D printing is due to numerous advantages like personalized medicine, tailored doses, rapid disintegration in case of SLS technique, incorporation of high doses and taste masking capacity. The different techniques used in 3D printing are Powder based (PB), Semi-solid extrusion (EXT), Fused deposition modeling (FDM), Stereolithographic (SLA) and Selective laser sintering (SLS) 3D printing. However, from the latest reports of association of pharmaceutical 3D printing technology, it is evidenced that this technology is still in its infancy and its potential is yet to be fully explored. The present review includes sections for introduction and scope of 3D printing, personalized medicines and their approaches, historical aspects, research milestones, and various 3D printing techniques.

Computer-aided design of temozolomide derivatives based on alkylglycerone phosphate synthase structure with isothiocyanate and their pharmacokinetic/toxicity prediction and anti-tumor activity in vitro.

Despite the development of temozolomide (TMZ), a novel type of glioma therapeutic drug, malignant glioma remains to cause severe damage to human health. The present study aimed to utilize the molecular biological differences between tumor and normal cells to design TMZ derivatives with improved selectivity and targeting using computer-aided drug design (CADD). Taking alkylglycerone phosphate synthase (AGPS) as a target, a 3D structure-activity relationship model was built using CADD technology; molecular docking of isothiocyanate (ITC) and TMZ compounds was conducted; ITC-TMZ derivatives were designed; and predictions on the absorption, distribution, metabolism and excretion (ADME) processes and toxicity of the ITC-TMZ derivatives were established in order to obtain improved understanding of the structure-activity relationship of the candidate compounds. Using these techniques, it was identified that the docking scores of the structural derivatives S1-9 were higher than that of TMZ. Additionally, S3, −6, −7, −8, −9 and −10 exhibited enhanced ADME and similar toxicity to that of TMZ. The half maximal inhibitory concentrations of the CADD derivatives were also assessed in the glioma U87MG and U251 cell lines, and the activities of S1, −3, −8 and −10 were determined to be greater than that of TMZ, suggesting their potential as anti-cancer drugs with adequate AGPS targeting, ADME/toxicity and anti-tumor activity.

Modern drug design: the implication of using artificial neuronal networks and multiple molecular dynamic simulations

We report the implementation of molecular modeling approaches developed as a part of the 2016 Grand Challenge 2, the blinded competition of computer aided drug design technologies held by the D3R Drug Design Data Resource (https://drugdesigndata.org/). The challenge was focused on the ligands of the farnesoid X receptor (FXR), a highly flexible nuclear receptor of the cholesterol derivative chenodeoxycholic acid. FXR is considered an important therapeutic target for metabolic, inflammatory, bowel and obesity related diseases (Expert Opin Drug Metab Toxicol 4:523-532, 2015), but in the context of this competition it is also interesting due to the significant ligand-induced conformational changes displayed by the protein. To deal with these conformational changes we employed multiple simulations of molecular dynamics (MD). Our MD-based protocols were top-ranked in estimating the free energy of binding of the ligands and FXR protein. Our approach was ranked second in the prediction of the binding poses where we also combined MD with molecular docking and artificial neural networks. Our approach showed mediocre results for high-throughput scoring of interactions.

Identification of JL1037 as a novel, specific, reversible lysine-specific demethylase 1 inhibitor that induce apoptosis and autophagy of AML cells.

Lysine-specific demethylase 1 (LSD1) has been recognized as a potential therapeutic target for acute myeloid leukemia (AML). Herein, we identified a novel LSD1 inhibitor, JL1037, via Computer Aided Drug Design technology. JL1037 is a potent, selective and reversible LSD1 inhibitor with IC50s of 0.1 μM and >1.5 μM for LSD1 and monoamine oxidases A/B (MAO-A/B), respectively. Treatment of THP-1 and Kasumi-1 cell lines with JL1037 resulted in dose dependent accumulation of H3K4me1 and H3K4me2, the major substrates of LSD1, as well as inhibition of cell proliferation, blockade of cell cycle and induction of apoptosis. Further investigations demonstrated that JL1037 could upregulate cell cycle-related proteins P21, P57, pro-apoptotic protein Bax and downregulate anti-apoptosis proteins Bcl-2 and Bcl-XL. JL1037 appeared to activate autophage response in AML cell lines as well as primary cells from AML patients by increasing LC3-II expression and the formation of autophagosomes and autolysosomes in cytoplasm. Co-treatment with autophagy inhibitor chloroquine (CQ) enhanced JL1037-induced cell apoptosis. Moreover, daily intravenous administration of JL1037 tended to reduce tumor burden and prolong the survival of t(8;21) leukemia mice. In conclusion, JL1037 exhibited potent anti-leukemia effect and could be a potential therapeutic agent for AML treatment.

Current topics in computer-aided drug design technologies: Future aspects

Current topics in computer-aided drug design technologies: Future aspects

Rational Drug Design: The Search for Ras Protein Hydrolysis Intermediate Conformation Inhibitors with Both Affinity and Specificity

Computer-aided drug design (CADD) plays significant roles in all stages of today's drug discovery. Many CADD technologies and methods were employed in finding promising hits against different targets during the past several decades. In this review, the most common molecular modeling methods applied to computer-aided drug design are discussed. However, how to effectively integrate these computational methods and then combine them with experiments to improve the hit rate is still a challenge. In addition, the present study reviews the ISR (intrinsic specificity ratio) as a novel concept and quantitative criterion for binding specificity to be applied as a complement in addition to binding affinity for finding new leads. Using Ras protein as a case study, Molecular modeling calculations and the subsequent biological testings for the hits are performed, the specificity of these hits is also studies against the normal and cancer cells aiming at discovering the novel chemical compounds with minimal side effects. Herein, the case study also includes the evaluations for tumor-specific cytotoxicity on different cell lines. The current results suggest that ISR is useful for quantitative assessment of specificity of small molecules.

Progress of Computer-Aided Drug Design (CADD) of Proteasome Inhibitors

The target proteasome has been the focus of drug discovery since the first drug bortezomib was launched in 2003. Many structurally diverse proteasome inhibitors were discovered and even some of them entered the clinical trials. Due to rapid technological progress in chemistry, bioinformatics, structural biology and computer technology, computer-aided drug design (CADD) plays a more and more important role in today's drug discovery. Many CADD technologies were employed in designing various inhibitors of proteasome in the past years. This review gives a global description of the development of computer-aided proteasome inhibitor design by using different commercial or academic software. The binding modes of some structurally novel inhibitors with proteasome were visualized with these new technologies.

Combined ligand based pharmacophore modeling, virtual screening methods to identify critical chemical features of novel potential inhibitors for phosphodiesterase-5

The central role of phosphodiesterase-5 (PDE5) is to hydrolyze the cyclic guanidine monophosphate which leads male erectile dysfunction. To inhibit the PDE5 activity, integrated computer-aided drug design technologies were utilized to generate pharmacophore modeling, database screening and docking methodologies. 3D pharmacophore models are generated using HypoGen to identify the critical chemical features of PDE5 inhibitors. Among the top ten generated hypotheses, the first hypothesis (Hypo1) was selected as best one. The best pharmacophore model, Hypo1, characterized by one hydrogen bond acceptor-lipid ( HBAL), one hydrophobic ( H), two ring aromatic ( RA) features, also have high cost difference (111.04), good correlation coefficient (0.94) and low root mean square deviation (1.53). Hypo1 model was cross validated by using Fischer's randomization method, test and decoy sets. The well validated Hypo1 was used as 3D query to screen NCI database. The screened molecules were sorted by applying rule of five, ADMET properties and molecular docking study to refine the retrieved hits. Finally, 3 molecules were showed good interaction with important amino acids in PDE5 active site. All above said validation analysis strongly suggested that Hypo1 will act as reliable and useful tool to identify new potential leads against PDE5 by screen the large databases and also it predicted 3 compounds in our present study which may act as potent inhibitor of PDE5 and these 3 compounds were chosen for further development.