Comparative Molecular Similarity Indices Analysis Research Articles

3D-QSAR and molecular docking studies of peptide-hybrids as dengue virus NS2B/NS3 protease inhibitors

Global warming and climate change have made dengue disease a global health issue. More than 50 % of the world's population is at danger of dengue virus (DENV) infection, according to the World Health Organization (WHO). Therefore, a clinically approved dengue fever vaccination and effective treatment are needed. Peptide medication development is new pharmaceutical research. Here we intend to recognize the structural features inhibiting the DENV NS2B/NS3 serine protease for a series of peptide-hybrid inhibitors (R1–R2-Lys-R3-NH2) by the 3D-QSAR technique. Comparative molecular field analysis (q2 = 0.613, r2 = 0.938, r2pred = 0.820) and comparative molecular similarity indices analysis (q2 = 0.640, r2 = 0.928, r2pred = 0.693) were established, revealing minor, electropositive, H-bond acceptor groups at the R1 position, minor, electropositive, H-bond donor groups at the R2 position, and bulky, hydrophobic groups at the R3 position for higher inhibitory activity. Docking studies revealed extensive H-bond and hydrophobic interactions in the binding of tripeptide analogues to the NS2B/NS3 protease. This study provides an insight into the key structural features for the design of peptide-based inhibitors of DENV NS2B/NS3 protease.

Study on β-glucosidase activators by 3D-QSAR, molecular docking and molecular dynamics simulation

To investigate the conformational relationship and mechanism of action of β-glucosidase (BGL) activators, a theoretical study of three-dimensional quantitative structure activity relationship, molecular docking, molecular dynamics (MD) simulations, and binding free energy analysis were performed. The results indicate that comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models had good stability and predictive ability, with r2cv/ r2pred values of 0.540/0.998 and 0.654/0.993, respectively. The derived contour maps of steric, electrostatic, and hydrogen bond donor field further displayed the modified information of these activators. Molecular docking and MD were performed on calcium diascorbate (CaAS) and L-Ascorbyl 2,6-Dipalmitate (L-ADP), which have good activating ability. The study indicates a positive interaction between the activators and the enzyme, and this interaction does not cause irreversible negative effects on the conformation of BGL. The MD results show that the total binding free energies of CaAS and L-ADP with BGL were −19.837 kJ/mol and −37.798 kJ/mol, respectively, and the binding force of the activators with BGL was mainly derived from hydrophobic interaction and hydrogen bonding. This study offers important guidance for the efficient use of BGL and for the research and development of effective activators.

Combined 3D-QSAR, molecular docking, ADMET, and drug-likeness scoring of novel diaminodihydrotriazines as potential antimalarial agents

Plasmodium falciparum dihydrofolate reductase (PfDHFR) is a promising therapeutic target for antimalarial interventions. Diaminodihydrotriazine derivatives have demonstrated their efficacy as antimalarial agents by targeting PfDHFR inhibition. In this study, we used a multifaceted approach including 3D-QSAR, in silico pharmacokinetic/ADMET evaluation, molecular docking techniques, and molecular dynamics simulation to explore a series of diaminodihydrotriazine compounds, to identify new antimalarial drug candidates featuring the diaminodihydrotriazine scaffold. Using comparative molecular similarity indices analysis (CoMSIA), we built a robust 3D-QSAR model exhibiting favorable statistical parameters, with Q2 and R2 values of 0.553 and 0.981, respectively. External validation using a test set yielded an R2pre value of 0.787, confirming the model's predictive ability. In addition, we performed comprehensive ADMET and drug similarity profile analyses for potent designed compounds, yielding promising results. Molecular docking studies further complemented our investigation facilitating the elucidation of optimal interaction modes between these inhibitors and their target receptor. Additionally, molecular dynamics simulation was conducted for the promising compound 8a. This study not only provides valuable insights into the design of new antimalarial agents but also highlights the importance of computational methods for accelerating drug discovery processes, particularly in the context of infectious disease control.

Strategic development and validation of Isoquinoline-Derived inhibitors targeting ROCK1 kinase

Rho-associated coiled-coil containing kinases (ROCKs) have emerged as pivotal downstream effectors of small guanosine triphosphatases. In recent years, isoquinoline derivatives have garnered substantial attention as potent inhibitors of ROCK1 (RKIs). To delve deeper into their pharmacological properties and to identify potential inhibitors, we conducted an in-depth exploration of a series of RKIs derived from isoquinoline derivatives. This exploration encompassed a multifaceted approach, combining three-dimensional quantitative structure–activity relationship modeling, induced fit docking, and virtual screening. Our comparative molecular field analysis model (q2 = 0.609, R2 = 0.991, ONC = 6, and r2pred = 0.973) and the most robust comparative molecular similarity indices analysis model (q2 = 0.712, R2 = 0.998, ONC = 7, and r2pred = 0.89) exhibited commendable predictive accuracy, bolstered by robust validation parameters. To gain deeper insights into the mechanism of action of isoquinoline-based RKIs, we harnessed precise docking techniques, including induced fit docking, structural interaction fingerprints, and binding pose metadynamics simulations. Employing the PRRR_2 pharmacophore, we meticulously screened Enamine's HLL-460 compound library, unearthing thousands of isoquinoline compounds that aligned with the desired profile. Subsequently, we identified three promising compounds (DS01, DS02, and DS03) through Glide docking, each assessed at varying precision levels. These compounds underwent comprehensive evaluation for their drug-like properties, leveraging QikProp and SwissADME, ultimately unveiling their potential as novel and efficacious RKIs. Furthermore, bolstered by molecular dynamics simulations and validated through activity assays, the bioactivity of the screened molecules DS02, and DS03 was corroborated. DS02 and DS03, previously unreported for their activity against ROCK1, delivered exceptionally promising results. This comprehensive study not only elucidates validated strategies for drug development but also imparts invaluable insights into the design of potent RKIs.

3D-QSAR and Molecular Dynamics Study of Isoxazole Derivatives to Identify the Structural Requirements for Farnesoid X Receptor (FXR) Agonists.

The farnesoid X receptor (FXR) has been recognized as a potential drug target for the treatment of non-alcoholic fatty liver disease (NAFLD). FXR agonists benefit NAFLD by modulating bile acid synthesis and transport, lipid metabolism, inflammation, and fibrosis pathways. However, there are still great challenges involved in developing safe and effective FXR agonists. To investigate the critical factors contributing to their activity on the FXR, 3D-QSAR molecular modeling was applied to a series of isoxazole derivatives, using comparative molecular field analysis (CoMFA (q2 = 0.664, r2 = 0.960, r2pred = 0.872)) and comparative molecular similarity indices analysis (CoMSIA (q2 = 0.706, r2 = 0.969, r2pred = 0.866)) models, which demonstrated strong predictive ability in our study. The contour maps generated from molecular modeling showed that the presence of hydrophobicity at the R2 group and electronegativity group at the R3 group in these compounds is crucial to their agonistic activity. A molecular dynamics (MD) simulation was carried out to further understand the binding modes and interactions between the FXR and its agonists in preclinical or clinical studies. The conformational motions of loops L: H1/H2 and L: H5/H6 in FXR-ligand binding domain (LBD) were crucial to the protein stability and agonistic activity of ligands. Hydrophobic interactions were formed between residues (such as LEU287, MET290, ALA291, HIS294, and VAL297) in helix H3 and ligands. In particular, our study found that residue ARG331 participated in salt bridges, and HIS447 participated in salt bridges and hydrogen bonds with ligands; these interactions were significant to protein-ligand binding. Eight new potent FXR agonists were designed according to our results, and their activities were predicted to be better than that of the first synthetic FXR agonist, GW4064.

Identification and Mechanistic Analysis of Toxic Degradation Products in the Advanced Oxidation Pathways of Fluoroquinolone Antibiotics.

The degradation of fluoroquinolones (FQs) via advanced oxidation processes (AOPs) is a promising avenue, yet the complete mineralization of certain FQ molecules remains elusive, raising concerns about the formation of toxic by-products. This study delineates five primary AOP degradation pathways for 16 commercially available FQ molecules, inferred from existing literature. Density functional theory (DFT) was employed to calculate the bond dissociation energies within these pathways to elucidate the correlation between bond strength and molecular architecture. Subsequently, Comparative Molecular Similarity Index Analysis (CoMSIA) models were constructed for various degradation reactions, including piperazine ring cleavage, defluorination, hydroxylation, and piperazine ring hydroxylation. Three-dimensional contour maps generated from these models provide a deeper understanding of the interplay between FQ molecular structure and bond dissociation energy. Furthermore, toxicity predictions for 16 FQ molecules and their advanced oxidation intermediates, conducted using VEGA 1.2.3 software, indicate that degradation products from pathways P2 and P5 pose a heightened health risk relative to their parent compounds. Furthermore, the application of the Multwfn program to compute the Fukui function for FQ molecules discerns the disparity in degradation propensities, highlighting that N atoms with higher f0 values can augment the likelihood of piperazine ring cleavage. HOMO-LUMO distribution diagrams further confirm that methoxy substitution at the 1-position leads to a dilution of HOMOs on the piperazine ring and an increased energy gap for free radical reactions, diminishing the reactivity with hydroxyl radicals. This study elucidates the pivotal role of structural characteristics in FQ antibiotics for their degradation efficiency within AOPs and unveils the underlying mechanisms of bond dissociation energy disparities. The toxicity parameter predictions for FQ molecules and their intermediates offer unique perspectives and theoretical underpinnings for mitigating the use of high-risk FQs and for devising targeted degradation strategies to circumvent the generation of toxic intermediates in AOPs through molecular structure optimization.

3D and 2D-QSAR Studies on Natural Flavonoids for Nitric Oxide Production Inhibitory Activity

Background: Nitric oxide (NO), an important second messenger molecule, regulates numerous physiological responses, while excessive NO generates negative effects on the circulatory, nervous and immune systems. Recently, some natural flavonoids were reported to possess the capability of inhibiting LPS-induced NO production. To fully understand the nature of their own NO inhibitory activity, it is necessary to address the structural requirements of flavonoids as NO inhibitors. Objective: The objective of this work was to develop efficient QSAR models for predicting the NOinhibitory activity of new flavonoids and improving insights into the critical properties of the chemical structures that were required for the ideal NO production inhibitory activities. Methods: To provide insights into the structural basis of flavonoids as NO inhibitors, 3D quantitative structure-activity relationship (3D-QSAR) and 2D-QSAR models were developed on a dataset of 55 flavonoids using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and hologram quantitative structure-activity relationship (HQSAR) approaches. method: CoMFA, CoMSIA combining HQSAR methods were employed on a series of flavonoids to generate 3D and 2D-QSAR models. Results: The statistically significant models for CoMFA, CoMSIA and HQSAR resulted in crossvalidated coefficient (q2) values of 0.523, 0.572 and 0.639, non-cross-validated coefficient (r2) values of 0.793, 0.828 and 0.852, respectively. The robustness of these models was further affirmed using a test set of 18 compounds, which resulted in predictive correlation coefficients (r2 pred) of 0.968, 0.954 and 0.906. Furthermore, the models-derived contour maps were appraised for activity trends for the molecules analyzed. result: Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Indices Analysis (CoMSIA) combining hologram quantitative structure-activity relationship (HQSAR) methods were employed on a series of flavonoids to generate 3D and 2D-QSAR models. Result: The obtained models can be used to predict the activities of new flavonoids and identify the key structural features affecting the NO inhibitory activities. Conclusion: The 3D and 2D-QSAR models constructed in this paper were efficient in estimating the NO inhibitory activities of flavonoids and facilitating the design of flavonoid-derived NO production inhibitors. other: none

Essential Structural Profile of Novel Adenosine Derivatives as Antiplatelet Aggregation Inhibitors based on 3D-QSAR Analysis

Aims: In this research, 3D-QSAR evaluation on a set of fresh purinoid compounds that we produced was conducted. This analysis aims to illustrate the correlation between the structure of purine and its ability to prevent platelet aggregation. Our findings could pave the way to discovering novel antithrombotic medications. background: Cardiovascular disease caused by platelet aggregation is a serious threat to human health. Purine derivatives are important molecules with antiplatelet aggregation activity. Background: The incidence of cardiovascular disease triggered by the clumping of platelets poses a significant danger to human health. Purine derivatives are important molecules with antiplatelet aggregation activity. Objective: The objectives of this research are to establish the correlation between the structure of purine and its ability to prevent platelet aggregation. Such a correlation could aid in the development of innovative antithrombotic medications. method: In this study, 3D-QSAR analysis was performed on a series of novel purine derivatives synthesized by us based on comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). Methods: In this study, 3D-QSAR investigation on a collection of 75 new purine derivatives, which we synthesized, was conducted, utilizing Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). result: Significant correlation coefficients (CoMFA, q2=0.843, r2=0.930, F value=266.755, SEE=0.165; CoMSIA, q2=0.869, r2=0.918, F value=222.571, SEE=0.179) were obtained, and the model prediction ability was validated using the test set. Results: Significant correlation coefficients (CoMFA, q2= 0.843, r2= 0.930, F value= 266.755, SEE= 0.165; CoMSIA, q2= 0.869, r2= 0.918, F value= 222.571, SEE= 0.179) were obtained, and assessed the model's predictive capabilities by validating it with the test set. conclusion: The results suggest that it is beneficial to introduce a group of appropriate size at position C-2 of the purine ring, and that an excessively large group is disadvantageous; a bulky substituent group cannot be directly attached at the C-6 position of the purine ring, and the attachment of a group with low electron cloud density increases the activity, and the attachment of a bulky group at the C-5' of the sugar ring is beneficial, and the presence of hydrogen bond receptors in this region also increases the activity. Conclusion: Our findings indicate that the introduction of an appropriately sized structure at position 2 of the compound yields significant benefits. Conversely, the attachment of an excessively large group is detrimental. Direct attachment of a bulky substituent at C-6 of the compound is not feasible, and its activity increases when the structure with low electron cloud density is added. Moreover, the presence of a voluminous functional group at the 5' position of the compound is advantageous, and its activity will be further increased by the presence of hydrogen bond receptors in this region. These discoveries furnish significant comprehension for the formation of innovative structures with heightened efficacy.

Rational design of novel phenol ether derivatives as non-covalent proteasome inhibitors through 3D-QSAR, molecular docking and ADMET prediction

Aim: The purpose of this paper is to use different structures and ligand-based drug design methods properly to provide theoretical guidance for the design of novel non-covalent proteasome inhibitors, and conduct theoretical analysis of the binding interaction mode between receptors and ligands. At the same time, the pharmacokinetic (PK) prediction, drug-likeness, and synthesis prediction were made for the screened novel drugs. Therefore, potentially attractive non-covalent proteasome inhibitors with low toxicity could be found as anticancer drugs. Methods: In this work, computer-aided drug design methods, including quantitative structure-activity relationship (QSAR), molecular docking, absorption, distribution, metabolism, excretion, and toxicology (ADMET) prediction, and drug-likeness prediction methods were performed. Results: In this study, the structure-activity relationship (SAR) of a series of non-covalent proteasome inhibitors were studied and the optimal comparative molecular field analysis (CoMFA; Q2 = 0.574, r2 = 0.999, r2pred = 0.755) and comparative molecular similarity indices analysis (CoMSIA)-SEHA (Q2 = 0.584, r2 = 0.989, r2pred = 0.921) models were obtained. According to the results of the QSAR model, some vital clues were found that would effectively enhance the biological activity of the compound. Based on these clues, 24 novel non-covalent proteasome inhibitors (D01–D24) were finally designed and screened. While the binding models between proteasome [protein data bank (PDB) code: 3MG6] and three representative compounds (15, 20, and D24) were also analyzed by using the molecular docking method. The results suggested that hydrogen bond and hydrophobic interaction played a key role in binding interaction between the receptor and ligand. In addition, the results of ADMET prediction indicated that the new designed compounds had reasonable PK parameters and drug-like properties. Conclusions: These statistical results can provide theoretical guidance for structural optimization, design, and synthesis of more effective non-covalent proteasome inhibitors in the future.

Computation-Directed Molecular Design, Synthesis, and Fungicidal Activity of Succinate Dehydrogenase Inhibitors.

Succinate dehydrogenase inhibitors (SDHIs) are a class of fungicides targeting the pathogenic fungi mitochondrial SDH. Here, molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR), and molecular dynamics (MD) simulations were used to guide SDHI innovation. Molecular docking was performed to explore the binding modes of SDH and its inhibitors. 3D-QSAR models were carried out on 33 compounds with activity against Rhizoctonia cerealis (R. cerealis); their structure-activity relationships were analyzed using comparative molecular field analysis and comparative molecular similarity indices analysis. MD simulations were used to assess the stability of the complexes under physiological conditions, and the results were consistent with molecular docking. Binding free energy was calculated through the molecular mechanics generalized born surface area method, and the binding free energy was decomposed. The results are consistent with the activity of bioassay and indicate that van der Waals and lipophilic interactions contribute the most in the molecular binding process. Afterward, we designed and synthesized 12 compounds under the guidance of the above-mentioned analyses, bioassay found that F9 was active against R. cerealis with the EC50 value of 9.43 μg/mL, and F4, F5, and F9 were active against Botrytis cinerea with an EC50 values of 5.80, 3.17, and 1.63 μg/mL, respectively. They all showed good activity between positive controls of pydiflumetofen and thifluzamide. Our study provides new considerations for effective SDHIs discovery.

Modelling of novel bornoel analogs as Influenza A Virus inhibitors through genetic function approximation, comparative molecular fields, molecular docking, and ADMET/Pharmacokinetic studies

Influenza A Virus (IAV) is a human respiratory pathogen prone to mutations and genome re-assortment leading to global pandemics. In this study, we applied the molecular modelling strategies such as, two-dimensional (2D), three-dimensional (3D)-quantitative structure–activity relationship (QSAR), and molecular docking simulation on a novel series of borneol compounds as influenza inhibitors. The best developed 2D-QSAR models, MLR (Q2 ​= ​0.8735, R2(train) ​= ​0.9096) and ANN [3-2-1] (Q2 ​= ​0.8987, R2(train) ​= ​0.9171) revealed good and acceptable statistical validation metrics for the inhibitory activity predictions. The 3D-QSAR models were generated using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), which showed CoMFA_S ​+ ​E (Q2 ​= ​0.559, R2(train) ​= ​0.939) and CoMSIA_S ​+ ​E (Q2 ​= ​0.577, R2(train) ​= ​0.941) as the best-observed models in accordance with the model acceptability standards. In addition, the contour maps generated from the CoMFA and CoMSIA models illustrates the steric and electrostatic molecular field relationships with the inhibitory effects of the studied molecules. Moreover, the binding modes of the active ligands were studied through molecular docking simulation with the Human Hemagglutinin (HA) receptor of influenza A virus (A/Puerto Rico/8/34(H1N1)). The studied compounds revealed the formation of H-bonds, CH-bonds, and hydrophobic interactions with the active amino acid residues such as Asn 543, Asn 614, Asn 617, Leu 618, Ser 540, Lys 539, and Lys 621 in the HA binding cavity. The prediction of drug-likeness and ADMET properties of the compounds revealed their good bioavailability and pharmacokinetic profiling. This study may provide a valuable in-silico guideline for discovering novel potent influenza inhibitors.

Design of novel small molecules derived from styrylpyridine as potent HDAC1 inhibitors for the treatment of gastric cancer using 3D-QSAR, drug similarity, ADMET prediction, molecular docking, and molecular dynamics studies

Histone deacetylase (HDAC) dysregulation plays an important role in cancer progression and is an important therapeutic target for anticancer drug development. A series of molecules derived from styrylpyridine have HDAC inhibitory activity for the treatment of gastric cancer and could have great potential as drugs against gastric cancer.The objective of this work is to modify the styrylpyridine backbone in order to design new inhibitors with high activity and favorable pharmacokinetic properties for drug discovery. Based on the three-dimensional quantitative structure- activity study, robust and reliable comparative molecular field analysis and comparative molecular similarity index analysis models were developed and validated, then used to design seven new molecules and predict in silico their biological activity.As a result, the seven newly designed molecules have a higher biological activity than the synthesized template molecule N21. The designed molecules are submitted to tests for drug-like properties, pharmacokinetics properties, and molecular docking. These tests enabled us to select the two newly-designed molecules T5 and T6 as the best HDAC1 inhibitors, compared with the model molecule N21. Subsequently, molecular dynamics simulations were carried out to study the stability of styrylpyridine derivatives in the active site of HDAC1.The designed molecules T5 and T6 have the potential to be drugs for treating gastric cancer. The synthesis, in vitro and in vivo evaluation of the biological activity of newly designed molecules T5 and T6 are interesting proposal for the conception of new drugs to treat gastric cancer.

Structural optimization of pyrrolopyrimidine BTK inhibitors based on molecular simulation.

BTK is a critical regulator involved in the proliferation, differentiation, and apoptosis of B cells. BTK inhibitors can effectively alleviate various diseases such as tumors, leukemia, and asthma. During this study, a range of novel BTK inhibitors were designed using 3D-QSAR, molecular docking, and molecular dynamics (MD) simulation. We selected 41 pyrrolopyrimidine derivatives as BTK inhibitors to structure a 3D-QSAR model. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were adopted to research the connection between the pharmacological activities and chemical structures of the compounds. The CoMFA model (q2= 0.519,R2= 0.971), CoMSIA model (q2= 0.512,R2= 0.990), and external validation demonstrated excellent predictive performance and reliability of the 3D-QSAR model. We designed eight novel molecules with higher inhibitory activities according to the three-dimensional equipotential fields and explored the interactions between the compounds and BTK by molecular docking, which showed that the novel molecules had higher binding affinities with BTK than the template molecule 18. Then, the results of molecular docking were further verified by MD simulation, which showed that amino acid residues such as Leu528, Val416, and Met477 played vital parts in the interaction, and the binding free energy analysis showed that the novel molecules had higher stability with BTK. Finally, the ADME/T properties were predicted for all of the novel compounds, and the results showed that the majority of them had favorable pharmacokinetic properties. Therefore, this study provides strong support for the development of novel BTK inhibitors.

3D-QSAR Combination with Molecular Dynamics Simulations to Effectively Design the Active Ryanodine Receptor Agonists against Spodoptera frugiperda.

Computer-aided molecular modeling was applied to design a series of Spodoptera frugiperda RyR agonists. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to generate 3D-QSAR models. MD simulations in the complex with S. frugiperda native, mutant RyR, and mammalian RyR1 under physiological conditions were used to validate the detailed binding mechanism. Binding free energy calculation by molecular mechanics generalized surface area (MM-GBSA) explained the role of key amino acid residues in ligand-receptor binding. Therefore, 14 new compounds were effectively designed and synthesized, and a bioassay indicated that compounds A-2 and A-3 showed comparable activity to that of chloranthraniliprole with LC50 values of 0.27, 0.18, and 0.20 mg L-1, respectively, against S. frugiperda. Most target compounds also displayed good activity against Mythinma separata at 0.1 mg L-1. Molecular docking and MM-GBSA calculations demonstrated that A-3 had a better binding capacity with native and mutant S. frugiperda RyRs.

Molecular design of environment-friendly amide herbicide substitutes with high efficacy, low phytotoxicity and medication safety

The primary goal of this investigation was to formulate an ecologically sustainable alternative to amide herbicides (AHs) characterized by robust herbicidal effectiveness, minimal corn phytotoxicity, and commendable pharmaceutical safety. We employed comparative molecular similarity index analysis (CoMSIA), a three-dimensional quantitative structure-activity relationship (3D-QSAR) model, which systematically outlined parameters such as herbicidal effectiveness, corn phytotoxicity, and AHs biodegradability. Subsequently, after thorough evaluation, we carefully selected a group of fourteen stable AH-substitute compounds known for their safety and environmental compatibility, considering aspects like pharmacokinetics, toxicokinetics, functional properties, and environmental friendliness. This resulted in a significant increase in herbicidal effectiveness, ranging from 21.64% to 34.07%, alongside a decrease in corn phytotoxicity within the range of 12.19–20.87%. Furthermore, we achieved an improvement in biodegradability, measured within the spectrum of 4.92–9.40%. Importantly, these changes also correlated with the reduction of hepatotoxicity, mutagenicity, and cutaneous health risks. Finally, we delved into the mechanisms underlying the improved herbicidal effectiveness, reduced corn phytotoxicity, and enhanced biodegradability of AHs substitutes through molecular docking and analysis of amino acid interactions. The investigation concluded that non-covalent forces governing the interaction between AHs substitutes and receptor proteins are crucial in determining herbicidal effectiveness, corn phytotoxicity, and biodegradability. Specifically, Van der Waals and electrostatic forces emerged as key factors governing the binding affinities of AH molecules with receptor proteins, both before and after modification. In summary, this study introduces innovative approaches in the field of agricultural chemical weeding technology and provides a theoretical framework for the environmentally responsible management of AHs herbicides.

Convergent QSAR Models for the Prediction of Cruzain Inhibitors.

Chagas disease is a parasitosis caused by Trypanosoma cruzi. Cruzain, the major cysteine protease from T. cruzi, is an excellent therapeutic target in the search for antichagasic drugs. It is important in the role of cell invasion, replication, differentiation, and metabolism of the parasite. In this work, we developed and assessed multiple quantitative structure-activity relationship (QSAR) models for a set of 61 cruzain inhibitors. These models include two-dimensional (2D) QSAR, three-dimensional (3D) QSAR, such as comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), and Hologram QSAR (HQSAR). In total, we generated 10 major and 114 minor model variations. Molecular docking was used to successfully align the molecules. All CoMFA and CoMSIA models, which incorporate multiple fields, demonstrated robustness in our analysis. Steric fields exhibited satisfactory convergence in the contour maps, while the electrostatic field converged into a single small region. The HQSAR model taking into consideration only Atoms and Connectivity, with fragment sizes ranging from two to five atoms, was considered the best of the HQSAR variations, despite exhibiting a higher level of deviance. In total, 78 model variations meet the minimum requirements to be considered acceptable. We found that using as few as five descriptors it is possible to obtain robust results with 2D-QSAR. Models such as Random Forest, Tree Ensemble, Linear Regression, and HQSAR are recommended for working with large data sets, while the 3D-QSAR models are intended to study the geometry of the ligands, to optimize them into new and better performing antichagasics. Virtual Screening of a set of hydrazones, guided by the top-performing models, identified promising candidates for experimental validation. Among them, dv007 and dv015 exhibited consistently high predicted pIC50 values (7.26 and 7.24, respectively), making them compelling candidates for further drug development.

In silico screening-based discovery of benzamide derivatives as inhibitors of Rho-associated kinase-1 (ROCK1)

As a pivotal node in modulating various cell behaviors, Rho-associated kinase-1 (ROCK1) has attracted significant attention as a promising therapeutic target in a variety of diseases. Benzamide has been widely reported as a ROCK1 inhibitors in recent years. To better understand its pharmacological properties and to explore its potential inhibitors, a series of ROCK1 inhibitors derived from N-methyl-4-(4-pyrazolidinyl) benzamides (MPBs) were investigated by using three-dimensional quantitative structure-activity relationship (3D-QSAR) models, pharmacophore models, molecular docking, and molecular dynamics (MD) simulation. The comparative Molecular Field Analysis (CoMFA) model (q2 = 0.616, R2 = 0.972, ONC = 4, and r2 pred = 0.983) and the best Comparative Molecular Similarity Indices Analysis (CoMSIA) model (q2 = 0.740, R2 = 0.982, ONC = 6, and r2 pred = 0.824) exhibited reliable predictability with satisfactory validation parameters. In the subsequent virtual screening, VS03 and VS05 were identified to have superior predicted activities and higher docking scores, meanwhile they demonstrated to be reasonably stable in the binding pocket through MD simulations. These results provide a significant theoretical direction for the rational design and development of novel ROCK1 inhibitors. Communicated by Ramaswamy H. Sarma

Identification of Pyrroloimidazoles as Potential Inhibitors of WDR5-WIN-Site by 3D-QSAR Molecular Simulation

Background: WD repeat structural domain 5 (WDR5), which plays an important role in various biological functions through epigenetic regulation, is aberrantly expressed in human cancers, and is an effective target for the discovery of anticancer drugs. Methods: In this paper, QSAR modeling analysis, including comparative molecular field (CoMFA) and comparative molecular similarity index analysis field (CoMSIA), was first performed using 41 pyrroloimidazole analogs. The results showed q2=0.667 and r2=0.981 in CoMFA and q2=0.662 and r2=0.983 in CoMSIA. Molecular docking and molecular dynamics simulations further confirmed the interaction and binding affinity of the inhibitors with key residues of the proteins, for example, PHE149, PHE133, and CYS261. Results: Based on QSAR and docking studies, seven new compounds with high scores and qualified ADMET performance were designed. Conclusion: In this study, new ideas have been provided for exploring new WDR5 inhibitors.

Computational Prediction of 3,5-Diaryl-1H-Pyrazole and spiropyrazolines derivatives as potential acetylcholinesterase inhibitors for alzheimer disease treatment by 3D-QSAR, molecular docking, molecular dynamics simulation, and ADME-Tox

The efficacy of 40 synthesized variants of 3,5-diaryl-1H-pyrazole and spiropyrazoline’ derivatives as acetylcholinesterase inhibitors is verified using a quantitative three-dimensional structure-activity relationship (3D-QSAR) by comparative molecular field analysis (CoMFA) and molecular similarity index analysis (CoMSIA) models. In this research, different field models proved that CoMSIA/SE model is the best model with high predictive power compared to several models (Qved2 = O.65; R2 = 0.980; R2test = 0.727). Also, contour maps produced by CoMSIA/SE model have been employed to prove the key structural needs of the activity. Consequently, six new compounds have been generated. Among these compounds, M4 and M5 were the most active but remained toxic and had poor absorption capacities. While the M1, M2, M3 and M6 remained highly active while respecting ADMET's characteristics. Molecular docking results showed compound M2 better with acetylcholinesterase than compound 22. The interactions are classical hydrogen bonding with residues TYR:124, TYR:72, and SER:293, which play a critical role in the biological activity as AChE inhibitors. MD results confirmed the docking results and showed that compound M2 had satisfactory stability with (ΔGbinding = −151.225 KJ/mol) in the active site of AChE receptor compared with compound 22 (ΔGbinding = −133.375 KJ/mol). In addition, both compounds had good stability regarding RMSD, Rg, and RMSF. The previous results show that the newly designed compound M2 is more active in the active site of AChE receptor than compound 22. Communicated by Ramaswamy H. Sarma

Design of novel anti-cancer agents targeting COX-2 inhibitors based on computational studies

The overexpression of cyclooxygenase-2 (COX-2) was clearly associated with carcinogenesis, and COX-2 as a possible target has long been exploited for cancer therapy. A group of 29 derivatives of 1, 5-diarylpyrazole was used to study its structural requirements using three-dimensional quantitative structure–activity relationship (3D-QSAR), the density functional theory method, molecular docking, and molecular dynamics. Four 3D-QSAR models were developed, and the predictive capability of the four selected models was also successfully tested using different validation methods. The contribution contours of the comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models effectively illustrate the relationships between the various chemical characteristics and their biological activities. Using the density functional theory method with the 6-31G (d, p) basis set and the Becke, 3-parameter, Lee-Yang-Parr (B3LYP) function to evaluate chemical reactivity properties, the results obtained from energy gaps of 3.431, 3.446, and 2.727 ev for molecules numbers 21, 22, and 23 indicate that these three molecules have good chemical stability and reactivity and select the most reactive regions in the three molecules studied. Molecular docking results revealed that the active sites of the COX-2 protein (PDB code: 3PGH) were residues ARG222, THR212, HIS386, HIS207, TYR148, and ASP382, in which the most active ligands and now ligands can inhibit the COX-2 enzyme. Based on the various results obtained by molecular modeling, four new compounds (N1, N2, N3, and N4) were proposed with significant predicted activity by different 3D-QSAR models. A molecular docking study and molecular dynamics simulations of the proposed new molecules (N1 and N2) and the most active molecule over 100 ns revealed that all three molecules establish multiple hydrogen interactions with several residues and also exhibit frequent stability throughout the simulation period. As a result, it is strongly recommended to consider the two newly proposed molecules, N1 and N4, as promising candidates for novel anti-cancer agents specifically designed to target COX-2 inhibition.