A Computational Approach Applied to the Study of Potential Allosteric Inhibitors Protease NS2B/NS3 from Dengue Virus

Dengue virus (DENV) is a danger to more than 400 million people in the world, and there is no specific treatment. Thus, there is an urgent need to develop an effective method to combat this pathology. NS2B/NS3 protease is an important biological target due it being necessary for viral replication and the fact that it promotes the spread of the infection. Thus, this study aimed to design DENV NS2B/NS3pro allosteric inhibitors from a matrix compound. The search was conducted using the Swiss Similarity tool. The compounds were subjected to molecular docking calculations, molecular dynamics simulations (MD) and free energy calculations. The molecular docking results showed that two compounds, ZINC000001680989 and ZINC000001679427, were promising and performed important hydrogen interactions with the Asn152, Leu149 and Ala164 residues, showing the same interactions obtained in the literature. In the MD, the results indicated that five residues, Lys74, Leu76, Asn152, Leu149 and Ala166, contribute to the stability of the ligand at the allosteric site for all of the simulated systems. Hydrophobic, electrostatic and van der Waals interactions had significant effects on binding affinity. Physicochemical properties, lipophilicity, water solubility, pharmacokinetics, druglikeness and medicinal chemistry were evaluated for four compounds that were more promising, showed negative indices for the potential penetration of the Blood Brain Barrier and expressed high human intestinal absorption, indicating a low risk of central nervous system depression or drowsiness as the the side effects. The compound ZINC000006694490 exhibited an alert with a plausible level of toxicity for the purine base chemical moiety, indicating hepatotoxicity and chromosome damage in vivo in mouse, rat and human organisms. All of the compounds selected in this study showed a synthetic accessibility (SA) score lower than 4, suggesting the ease of new syntheses. The results corroborate with other studies in the literature, and the computational approach used here can contribute to the discovery of new and potent anti-dengue agents.     

Computational Analysis Reveals Monomethylated Triazolopyrimidine as a Novel Inhibitor of SARS-CoV-2 RNA-Dependent RNA Polymerase (RdRp)

The human population is still facing appalling conditions due to several outbreaks of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) virus. The absence of specific drugs, appropriate vaccines for mutants, and knowledge of potential therapeutic agents makes this situation more difficult. Several 1, 2, 4-triazolo [1, 5-a] pyrimidine (TP)-derivative compounds were comprehensively studied for antiviral activities against RNA polymerase of HIV, HCV, and influenza viruses, and showed immense pharmacological interest. Therefore, TP-derivative compounds can be repurposed against the RNA-dependent RNA polymerase (RdRp) protein of SARS-CoV-2. In this study, a meta-analysis was performed to ensure the genomic variability and stability of the SARS-CoV-2 RdRp protein. The molecular docking of natural and synthetic TP compounds to RdRp and molecular dynamic (MD) simulations were performed to analyse the dynamic behaviour of TP compounds at the active site of the RdRp protein. TP compounds were also docked against other non-structural proteins (NSP1, NSP2, NSP3, NSP5, NSP8, NSP13, and NSP15) of SARS-CoV-2. Furthermore, the inhibition potential of TP compounds was compared with Remdesivir and Favipiravir drugs as a positive control. Additionally, TP compounds were analysed for inhibitory activity against SARS-CoV RdRp protein. This study demonstrates that TP analogues (monomethylated triazolopyrimidine and essramycin) represent potential lead molecules for designing an effective inhibitor to control viral replication. Furthermore, in vitro and in vivo studies will strengthen the use of these inhibitors as suitable drug candidates against SARS-CoV-2.     

A 3D-QSAR Study of HIV-1 Integrase Inhibitors Using RASMS and Topomer CoMFA

Acquired Immunodeficiency Syndrome(AIDS) is a significant human health threat around the world. Therefore, the study of anti-human immunodeficiency virus(HIV) drug design has become an important task for today's society. In this paper, a three-dimensional quantitative structure-activity relationships study(3 D-QSAR) was conducted on 53 HIV-1 integrase inhibitors(IN) using random sampling analysis on molecular surface(RASMS) and Topomer comparative molecular field analysis(Topomer CoMFA). The multiple correlation coefficients of fitting, cross-validation, and external validation of two models were 0.926, 0.815 and 0.908 and 0.930, 0.726 and 0.855, respectively. The results indicated that two models obtained had both favorable estimation stability and good prediction capability. Topomer Search was used to search appropriate R groups from ZINC database, and 28 new compounds were designed thereby. The Topomer CoMFA model was subsequently used to predict the biological activity of these compounds, showing that 24 of the new compounds were more active than the template molecule. Ligands of the template molecule and new designed compounds were used for molecular docking to study the interaction of these compounds with the protein receptor. The results show that the ligands would form hydrogen-bonding interactions with the residues LEU58, THR83, GLN62, MET155, LYS119 and ALA154 of the protein receptor generally, thereby providing additional insights for the design of even more effective HIV/AIDS drugs.     

Study of Aldo-keto Reductase 1C3 Inhibitor with Novel Framework for Treating Leukaemia Based on Virtual Screening and In vitro Biological Activity Testing

Aldo-keto reductase 1C3(AKR1C3) is a potential target for the treatment of acute myeloid leukaemia and T-cell acute lymphoblastic leukaemia. In this study, pharmacophore models, molecular docking and virtual screening of target prediction were used to find a potential AKR1C3 inhibitor. Firstly, eight bacteriocin derivatives(Z1-Z8) were selected as training sets to construct 20 pharmacophore models. The best pharmacophore model MODEL_016 was obtained by Decoy test(the enrichment degree was 21.5117, and the fitting optimisation degree was 0.9668). Secondly, MODEL_016 was used for the virtual screening of ZINC database. Thirdly, the hit 83256 molecules were docked into the AKR1C3 protein. Compared to the total scores and interactions between compounds and protein, 16532 candidate compounds with higher docking scores and interactions with important residues PHE306 and TRP227 were screened. Lastly, eight compounds(A1-A8) that had good absorption, distribution, metabolism, excretion and toxicity(ADMET) properties were obtained by target prediction. Compounds A3 and A7 with high total score and good target prediction results were selected for in vitro biological activity test, whose IC₅₀ values were 268.3 and 88.94 μmol/L, respectively. The results provide an important foundation for the discovery of novel AKR1C3 inhibitors. The research methods used in this study can also provide important references for the research and development of new drugs.     

In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of Mycobacterium tuberculosis

With tuberculosis still being one of leading causes of death in the world and the emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb), researchers have been seeking to find further therapeutic strategies or more specific molecular targets. PknB is one of the 11 Ser/Thr protein kinases of Mtb and is responsible for phosphorylation-mediated signaling, mainly involved in cell wall synthesis, cell division and metabolism. With the amount of structural information available and the great interest in protein kinases, PknB has become an attractive target for drug development. This work describes the optimization and application of an in silico computational protocol to find new PknB inhibitors. This multi-level computational approach combines protein–ligand docking, structure-based virtual screening, molecular dynamics simulations and free energy calculations. The optimized protocol was applied to screen a large dataset containing 129,650 molecules, obtained from the ZINC/FDA-Approved database, Mu.Ta.Lig Virtual Chemotheca and Chimiothèque Nationale. It was observed that the most promising compounds selected occupy the adenine-binding pocket in PknB, and the main interacting residues are Leu17, Val26, Tyr94 and Met155. Only one of the compounds was able to move the active site residues into an open conformation. It was also observed that the P-loop and magnesium position loops change according to the characteristics of the ligand. This protocol led to the identification of six compounds for further experimental testing while also providing additional structural information for the design of more specific and more effective derivatives.     

Comparative performance of several flexible docking programs and scoring functions: enrichment studies for a diverse set of pharmaceutically relevant targets

Virtual screening by molecular docking has become a widely used approach to lead discovery in the pharmaceutical industry when a high-resolution structure of the biological target of interest is available. The performance of three widely used docking programs (Glide, GOLD, and DOCK) for virtual database screening is studied when they are applied to the same protein target and ligand set. Comparisons of the docking programs and scoring functions using a large and diverse data set of pharmaceutically interesting targets and active compounds are carried out. We focus on the problem of docking and scoring flexible compounds which are sterically capable of docking into a rigid conformation of the receptor. The Glide XP methodology is shown to consistently yield enrichments superior to the two alternative methods, while GOLD outperforms DOCK on average. The study also shows that docking into multiple receptor structures can decrease the docking error in screening a diverse set of active compounds.     

Drug promiscuity: Exploring the polypharmacology potential of 1, 3, 6-trisubstituted 1, 4-diazepane-7-ones as an inhibitor of the ‘god father’ of immune checkpoint

High production cost, instability, low tumor penetration are some of the shortcomings that have characterized and undermined the use of antibodies as a target for Cytotoxic T-lymphocytes associated protein 4 (CTLA-4). Design and discovery of small molecule inhibitors have therefore become a sine qua non in targeting immune proteins implicated in immune disorders. In this study, we utilized a drug repositioning approach to explore the characteristic feature of unrelated proteins to have similar binding sites and the promiscuity of drugs to repurpose an existing drug to target CTLA-4. CTLA-4 and Kallikrein-7 were found to have similar binding sites, we therefore used 1, 3, 6-trisubstituted 1, 4-diazepane-7-ones (TDSO) which is an inhibitor of Kallikrein-7 as our lead compound. High throughput screening using TDSO as a lead compound resulted in 9 hits with ZINC04515726 and ZINC08985213 having the highest binding score. We went ahead to investigate the interaction of these compounds with CTLA-4 by conducting a molecular dynamic simulation. Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) estimations revealed that TDSO had the highest binding energy value of -28.51Kcal/mol, with ZINC04515726 and ZINC08985213 having -23.76Kcal/mol and -21.03Kcal/mol respectively. The per-residue decomposition highlighted Tyr24, Ala25, Gly28, Ala30, Tyr53 and Asn72 as having significantly high electrostatic energy contributions and the main contributing residues to the binding of TDSO, ZINC04515726 and ZINC08985213 to Cytotoxic T lymphocytes CTLA-4. Summarily, from the results gathered, we proposed that TDSO can be an effective immune check point small molecule inhibitor against the suppression of T-cell activation, proliferation, and tumor cell eradication.     

Searching Anti-Zika Virus Activity in 1H-1,2,3-Triazole Based Compounds

Zika virus (ZIKV) is a mosquito-borne virus belonging to the Flaviviridae family and is responsible for an exanthematous disease and severe neurological manifestations, such as microcephaly and Guillain-Barré syndrome. ZIKV has a single strand positive-sense RNA genome that is translated into structural and non-structural (NS) proteins. Although it has become endemic in most parts of the tropical world, Zika still does not have a specific treatment. Thus, in this work we evaluate the cytotoxicity and antiviral activities of 14 hybrid compounds formed by 1H-1,2,3-triazole, naphthoquinone and phthalimide groups. Most compounds showed low cytotoxicity to epithelial cells, specially the 3b compound. After screening with all compounds, 4b was the most active against ZIKV in the post-infection test, obtaining a 50% inhibition concentration (IC₅₀) of 146.0 µM and SI of 2.3. There were no significant results for the pre-treatment test. According to the molecular docking compound, 4b was suggested with significant binding affinity for the NS5 RdRp protein target, which was further corroborated by molecular dynamic simulation studies.     

Efficient inclusion of receptor flexibility in grid-based protein-ligand docking

Accounting for receptor flexibility is an essential component of successful protein-ligand docking but still marks a major computational challenge. For many target molecules of pharmaceutical relevance, global backbone conformational changes are relevant during the ligand binding process. However, popular methods that represent the protein receptor molecule as a potential grid typically assume a rigid receptor structure during ligand-receptor docking. A new approach has been developed that combines inclusion of global receptor flexibility with the efficient potential grid representation of the receptor molecule. This is achieved using interpolation between grid representations of the receptor protein deformed in selected collective degrees of freedom. The method was tested on the docking of three ligands to apo protein kinase A (PKA), an enzyme that undergoes global structural changes upon inhibitor binding. Structural variants of PKA were generated along the softest normal mode of an elastic network representation of apo PKA. Inclusion of receptor deformability during docking resulted in a significantly improved docking performance compared with rigid PKA docking, thus allowing for systematic virtual screening applications at small additional computational cost.     

Synthesis and antimicrobial bioassays of 1,3,4-thiadiazole sulfone derivatives containing amide moiety: A study based on molecular dynamics (MD) simulations,MM/GBSA,and molecular docking

The backbone structure (1,3,4-thiadiazole sulfone derivatives containing amide moiety) of target compounds was determined by modification and optimization of the theoretical design based on commercial chemical carboxin, including molecular docking, scaffold hopping, ligand expansion, etc.In this paper, 23 target compounds were synthesized by the combination of theoretical design and chemical synthesis, and characterized by ¹H NMR, ¹³C NMR and HR MS. Addtionally, the antibacterical bioassay showed that most target compounds performed excellent inhibition on Xanthomonas axonopodis pv. citri (Xac) and Xanthomonas oryzae pv. oryzae (Xoo) in vitro. Meanwhile, molecular docking, molecular dynamics (MD) simulations, and studies on ligand/protein (carboxin/2FBW and 4n/2FBW) complex systems were displayed, and the interaction patterns of ligand/protein complex system were predicted by molecular docking. Besides, the ligand/protein complex system was subject to MD simulation. The analysis of molecular dynamics such as RMSD values suggested that compound/2FBW complexes were stable. MM/GBSA (Molecular mechanics generalized born surface area) dynamic binding affinity results revealed that the active residues (TYR58, HIS26, ARG43, SER39, etc.) played an essential part in the binding of the compound(s) to form a stable low-energy ligand/protein complex, while the MD trajectories demonstrated that the interactions of drugs with 2FBW affected the tertiary structure and increased the stability of protein. Besides, compound 4n also showed control efficacies (curative and protective) on Xoo in vivo, where the curative efficacy was 35.91% and the protective efficacy was 18.97%. In a word, this study showed that 1,3,4-thiadiazole sulfone derivatives containing amide moiety designed based on the structure of carboxin were promising agricultural antibacterial agents, featuring certain stability of binding affinity to proteins and carboxin.     

芬太尼类化合物与阿片μ受体相互作用的分子对接与分子动力学模拟

采用分子对接和分子动力学(MD)模拟方法研究了芬太尼类化合物与阿片μ受体的相互作用机制.先用AutoDock4.0程序将芬太尼类化合物对接到同源模建的阿片μ受体结构中,再用GROMACS程序包在水溶液体系中分别对12个芬太尼激动剂和阿片μ受体蛋白复合物进行了MD模拟研究,优化对接复合物的结构,最后利用MM-PBSA方法,在APBS程序中计算芬太尼类衍生物与阿片μ受体的结合自由能,计算出的受体配合物结合常数(Ki)与其实验值吻合较好,并预测了化合物的活性排序.结果表明,复合物蛋白结构与空载受体蛋白结构有较大差异,特别是胞内区IL2、IL3和跨膜区段TM4骨架构象变化较大,不同的化合物对受体结构影响也有差异,活性较好的化合物会增加蛋白特定区域结构的柔性.芬太尼类化合物可能是通过和受体结合后诱导阿片μ受体构象转变为活性构象,引起一系列的信号传导激活G蛋白,从而引发生理效应.     

Virtual Screening of Natural Compounds as Potential PI3K-AKT1 Signaling Pathway Inhibitors and Experimental Validation

A computational screening for natural compounds suitable to bind the AKT protein has been performed after the generation of a pharmacophore model based on the experimental structure of AKT1 complexed with IQO, a well-known inhibitor. The compounds resulted as being most suitable from the screening have been further investigated by molecular docking, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis and toxicity profiles. Two compounds selected at the end of the computational analysis, i.e., ZINC2429155 (also named STL1) and ZINC1447881 (also named AC1), have been tested in an experimental assay, together with IQO as a positive control and quercetin as a negative control. Only STL1 clearly inhibited AKT activation negatively modulating the PI₃K/AKT pathway.     

Epitopes based drug design for dengue virus envelope protein: A computational approach

Dengue virus (DENV) has emerged as a rapidly spreading epidemic throughout the tropical and subtropical regions around the globe. No suitable drug has been designed yet to fight against DENV, therefore, the need for safe and effective antiviral drug has become imperative. The envelope protein of DENV is responsible for mediating the fusion process between viral and host membranes. This work reports an in silico approach to target B and T cell epitopes for dengue envelope protein inhibition. A conserved region “QHGTI” in B and T cell epitopes of dengue envelope glycoprotein was confirmed to be valid for targeting by visualizing its interactions with the host cell membrane TIM-1 protein which acts as a receptor for serotype 2 and 3. A reverse pharmacophore mapping approach was used to generate a seven featured pharmacophore model on the basis of predicted epitope. This pharmacophore model as a 3D query was used to virtually screen a chemical compounds dataset “Chembridge”. A total of 1010 compounds mapped on the developed pharmacophore model. These retrieved hits were subjected to filtering via Lipinski’s rule of five, as a result 442 molecules were shortlisted for further assessment using molecular docking. Finally, 14 hits of different structural properties having interactions with the active site residues of dengue envelope glycoprotein were selected as lead candidates. These structurally diverse lead candidates have strong likelihood to act as further starting structures in the development of novel and potential drugs for the treatment of dengue fever.     

Molecular Docking and 3D QSAR Research of Indolocarbazole Series as Cyclin-Dependent Kinase Inhibitors

Fifty indolocarbazole series as cyclin-dependent kinase inhibitors (CDKs) are used to establish a threedimensional quantitative structure-activity relationship (3D QSAR) model based on docking conformations resulting from the Topomer comparative molecular field analysis (Topomer CoMFA). The statistic parameters show that the cross-validation (q²), the multiple correlation coefficient of fitting (r²), and external validation statistic (Q_ext²) are 0.953, 0.968, and 0.954, respectively. It is demonstrated that this Topomer CoMFA model has good stability and prediction ability. The methodology of the fragment-based drug design (FBDD) was also used to virtually screen new CDKs by the Topomer Search technology. Four similar substitutional groups selected from the ZINC database were added to the basic scaffold. As a result, 18 new CDKs with high activities were obtained. The template molecule and new designed compounds are used to study the binding relationship between the ligands and the receptor protein with Surflex-Dock. The docking results suggest good binding interactions of the designed compounds with protein. There are several hydrogen bondings between CDKs with amino acid residues of LYS33, LYS89, ASP86, LEU83, GLU81.     

Computational Approaches for the Design of Novel Anticancer Compounds Based on Pyrazolo[3,4-d]pyrimidine Derivatives as TRAP1 Inhibitor

In the present in-silico study, various computational techniques were applied to determine potent compounds against TRAP1 kinase. The pharmacophore hypothesis DHHRR_1 consists of important features required for activity. The 3D QSAR study showed a statistically significant model with R² = 0.96 and Q² = 0.57. Leave one out (LOO) cross-validation (R² CV = 0.58) was used to validate the QSAR model. The molecular docking study showed maximum XP docking scores (−11.265, −10.532, −10.422, −10.827, −10.753 kcal/mol) for potent pyrazole analogs (42, 46, 49, 56, 43), respectively, with significant interactions with amino acid residues (ASP 594, CYS 532, PHE 583, SER 536) against TRAP1 kinase receptors (PDB ID: 5Y3N). Furthermore, the docking results were validated using the 100 ns MD simulations performed for the selected five docked complexes. The selected inhibitors showed relatively higher binding affinities than the TRAP1 inhibitor molecules present in the literature. The ZINC database was used for a virtual screening study that screened ZINC05297837, ZINC05434822, and ZINC72286418, which showed similar binding interactions to those shown by potent ligands. Absorption, distribution, metabolism, and excretion (ADME) analysis showed noticeable results. The results of the study may be helpful for the further development of potent TRAP1 inhibitors     

Optimization of high throughput virtual screening by combining shape-matching and docking methods

Receptor flexibility is a critical issue in structure-based virtual screening methods. Although a multiple-receptor conformation docking is an efficient way to account for receptor flexibility, it is still too slow for large molecular libraries. It was reported that a fast ligand-centric, shape-based virtual screening was more consistent for hit enrichment than a typical single-receptor conformation docking. Thus, we designed a "distributed docking" method that improves virtual high throughput screening by combining a shape-matching method with a multiple-receptor conformation docking. Database compounds are classified in advance based on shape similarities to one of the crystal ligands complexed with the target protein. This classification enables us to pick the appropriate receptor conformation for a single-receptor conformation docking of a given compound, thereby avoiding time-consuming multiple docking. In particular, this approach utilizes cross-docking scores of known ligands to all available receptor structures in order to optimize the algorithm. The present virtual screening method was tested for reidentification of known PPARgamma and p38 MAP kinase active compounds. We demonstrate that this method improves the enrichment while maintaining the computation speed of a typical single-receptor conformation docking.     

Computational fragment-based design of Wee1 kinase inhibitors with tricyclic core scaffolds

Wee1 is cell cycle protein comprising a kinase domain and is a validated cancer target. We have designed molecules with variable tricyclic core scaffolds [6-6-5] system and extended them based on the chemical space available in the active site of Wee1 kinase using de novo drug design. The core scaffolds and linking fragments were extracted from pharmacophore-based virtual screening of ZINC and PubChem databases and Ludi library. These molecules bind the hinge region of kinase active site and form hydrogen bonds as confirmed from molecular docking, molecular dynamics simulations, and MM_PBSA calculations. When compared with reference inhibitors, AZD1775 and PHA-848125, the de novo designed molecules also show good docking scores and stability, retained non-covalent interactions, and high binding free energies contributed from active site residues.

     

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.     

Computer-aided molecular design of (E)-N-Aryl-2-ethene-sulfonamide analogues as microtubule targeted agents in prostate cancer

Microtubules are tube-shaped, filamentous and cytoskeletal proteins that are essential in all eukaryotic cells. Microtubule is an attractive and promising target for anticancer agents. In this study, three-dimensional quantitative structure activity relationships (3D-QSAR) including comparative molecular field analysis, CoMFA, and comparative molecular similarity indices analysis, CoMSIA, were performed on a set of 45 (E)-N-Aryl-2-ethene-sulfonamide analogues as microtubule-targeted anti-prostate cancer agents. Automated grid potential analysis, AutoGPA module in Molecular Operating Environment 2009.10 (MOE) as a new 3D-QSAR approach with the pharmacophore-based alignment was carried out on the same dataset. AutoGPA-based 3D-QSAR model yielded better prediction parameters than CoMFA and CoMSIA. Based on the contour maps generated from the models, some key features were identified in (E)-N-Aryl-2-arylethene-sulfonamide analogues that were responsible for the anti-cancer activity. Virtual screening was performed based on pharmacophore modeling and molecular docking to identify the new inhibitors from ZINC database. Seven top ranked compounds were found based on Gold score fitness function. In silico ADMET studies were performed on compounds retrieved from virtual screening in compliance with the standard ranges.