Relative free energy of binding and binding mode calculations of HIV-1 RT inhibitors based on dock-MM-PB/GS

Virtual and in Vitro Screening Employing a Repurposing Approach Reveal 13-cis-Retinoic Acid is a PTP1B Inhibitor

Current treatments for type 2 diabetes (T2D) mainly rely on exercise, dietary control, and anti-diabetic drugs to enhance insulin secretion and improve insulin sensitivity. However, there is a need for more therapeutic options, as approved drugs targeting different pharmacological objectives are still unavailable. One potential target that has attracted attention is the protein tyrosine phosphatase 1B (PTP1B), which negatively regulates the insulin signaling pathway. In this work, a comprehensive computational screening was carried out using cheminformatics and molecular docking on PTP1B, employing a rigorous repurposing approach. The screening involved approved drugs and compounds under research as anti-diabetics that bind to targets such as peroxisome proliferator-activated receptor gamma (PPAR-γ) and α-glucosidase. Several computational hits were then meticulously tested in vitro against PTP1B, with 13-cis-retinoic acid (3a) showing an IC50 of 0.044 mM and competitive inhibition. Molecular dynamics studies further confirmed that 3a can bind to the catalytic binding site of PTP1B. Finally, 3a is the first time it has been reported as an inhibitor of PTP1B, making it a potentially valuable candidate for further studies in D2T treatment.

3-Benzylaminomethyl Lithocholic Acid Derivatives Exhibited Potent and Selective Uncompetitive Inhibitory Activity Against Protein Tyrosine Phosphatase 1B (PTP1B)

Protein tyrosine phosphatase 1B (PTP1B) is a promising drug target for treating type 2 diabetes (T2DM) and obesity. As a result, developing new therapies that target PTP1B is an attractive strategy for treating these diseases. Herein, we detail the synthesis of 15 lithocholic acid (LA) derivatives, each containing different benzylaminomethyl groups attached to the C3 position of the steroid skeleton. The derivatives were assessed against two forms of PTP1B enzyme (hPTP1B1-400 and hPTP1B1-285), and the most potent compounds were then tested against T-cell protein tyrosine phosphatase (TCPTP) to determine their selectivity. The results showed that compounds 6m and 6n were more potent than the reference compounds (ursolic acid, chlorogenic acid, suramin, and TCS401). Additionally, both compounds exhibited greater potency over hPTP1B1-400. Furthermore, enzyme kinetic studies on hPTP1B1-400 revealed that these two lithocholic acid derivatives have an uncompetitive inhibition against hPTP1B1-400 with K i values of 2.5 and 3.4 μM, respectively. Interestingly, these compounds were around 75-fold more selective for PTP1B over TCPTP. Finally, docking studies and molecular dynamics simulations (MDS) were conducted to determine how these compounds interact with PTP1B. The docking studies revealed hydrophobic and H-bond interactions with amino acid residues in the unstructured region. MDS showed that these interactions persisted throughout the 200 ns simulation, indicating the crucial role of the unstructured zone in the biological activity and inhibition of PTP1B.

Inhibition of FGFR2 Signaling by Cynaroside Attenuates Liver Fibrosis

Liver fibrosis represents a significant health hazard with a high morbidity rate and an increased risk of liver cancer. Targeting overactivated Fibroblast growth factor receptor 2 (FGFR2) is a promising strategy to counteract collagen accumulation during liver fibrosis. However, there is a shortage of drugs to specifically block the activation of FGFR2 in liver fibrosis patients. Data mining, cell validation, and animal studies showed a positive correlation between FGFR2 overexpression and liver fibrosis development. Novel FGFR2 inhibitors were screened using a microarray-based high-throughput binding analysis. The effectiveness of each candidate was validated through simulated docking, binding affinity verification, single-point mutation validation, and in vitro kinase inhibition measurements to demonstrate the ability of each inhibitor to block the catalytic pocket and reverse FGFR2 overactivation. A specific FGFR2 inhibitor, cynaroside (CYN, also known as luteoloside), was screened based on the finding that FGFR2 promotes hepatic stellate cell (HSC) activation and collagen secretion in hepatocytes. The results from cellular assays showed that CYN can inhibit FGFR2 hyperactivation resulting from its overexpression and excessive basic fibroblast growth factor (bFGF), reducing HSC activation and collagen secretion in hepatocytes. Animal experiments on a carbon tetrachloride (CCl4) mouse model and a nonalcoholic steatohepatitis mouse model indicate that CYN treatment reduces liver fibrosis during fibrosis formation. These findings suggest that CYN prevents liver fibrosis formation at the cell level and in mouse models.

In vitro and computational studies on the antiglycation activity of compounds isolated from antidiabetic Tetracera alnifolia stem bark

The continuous search for new compounds in natural-based plants is a promising strategy for the prevention of diseases. This work examined antiglycation activity compounds isolated from the antidiabetic extract of T. alnifolia stem bark via in vitro and computational [molecular dynamics (MD)] approach. Phytochemical investigation of ethyl acetate fraction and the application of spectroscopic methods led to the isolation and elucidation of 3 compounds: quercetin (1), kaempferol (2), and gallic acid (3). Compounds 1, 2 and 3 were then screened for antioxidant and antiglycation activities. Results show that the ethanol extract of T. alnifolia demonstrated good antioxidant activity compared to the standard gallic acid. There was a significant reduction in fasting blood glucose level progressively in diabetic rats, for 21 days compared to diabetic control. Consequently, the antiglycation activity of ethyl acetate fraction had the highest antiglycation activities, followed by dichloromethane (DCM) fraction. Compounds isolated from ethyl acetate fraction, exhibited the highest antiglycation effect for kaempferol followed by quercetin, while gallic acid had the least antiglycation effect. The root mean square of deviation (RMSD) and MM/GBSA energies obtained from molecular dynamics agree with the in vitro antiglycation activity with the sequence of structural stability in the order; kaempferol > quercetin > gallic acid. Therefore, findings from these results suggest that compounds isolated from T. alnifolia possess antiglycation activity.Communicated by Ramaswamy H. Sarma.

Bisindolylmaleimides New Ligands of CaM Protein

In the present study, we reported the interactions at the molecular level of a series of compounds called Bisindolylmaleimide, as potential inhibitors of the calmodulin protein. Bisindolylmaleimide compounds are drug prototypes derived from Staurosporine, an alkaloid with activity for cancer treatment. Bisindolylmaleimide compounds II, IV, VII, X, and XI, are proposed and reported as possible inhibitors of calmodulin protein for the first time. For the above, a biotechnological device was used (fluorescent biosensor hCaM M124C-mBBr) to directly determine binding parameters experimentally (K_d and stoichiometry) of these compounds, and molecular modeling tools (Docking, Molecular Dynamics, and Chemoinformatic Analysis) to carry out the theoretical studies and complement the experimental data. The results indicate that this compound binds to calmodulin with a K_d between 193–248 nM, an order of magnitude lower than most classic inhibitors. On the other hand, the theoretical studies support the experimental results, obtaining an acceptable correlation between the ΔG_Experimental and ΔG_Theoretical (r² = 0.703) and providing us with complementary molecular details of the interaction between the calmodulin protein and the Bisindolylmaleimide series. Chemoinformatic analyzes bring certainty to Bisindolylmaleimide compounds to address clinical steps in drug development. Thus, these results make these compounds attractive to be considered as possible prototypes of new calmodulin protein inhibitors.

Natural phyto, compounds as possible noncovalent inhibitors against SARS-CoV2 protease: computational approach

At present, there is no cure or vaccine for the devastating new highly infectious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that has affected people globally. Herein, we identified potent phytocompounds from two antiviral plants Momordica charantia L. and Azadirachta indica used locally for the treatment of viral and parasitic infections. Structure-based virtual screening and molecular dynamics (MD) simulation have been employed to study their inhibitory potential against the main protease (Mpro) SARS-CoV-2. A total of 86 compounds from M. charantia L. and A. indica were identified. The top six phytocompounds; momordicine, deacetylnimninene, margolonone, momordiciode F2, nimbandiol, 17-hydroxyazadiradione were examined and when compared with three FDA reference drugs (remdesivir, hydroxychloroquine and ribavirin). The top six ranked compounds and FDA drugs were then subjected to MD simulation and pharmacokinetic studies. These phytocompounds showed strong and stable interactions with the active site amino acid residues of SARS-CoV-2 Mpro similar to the reference compound. Results obtained from this study showed that momordicine and momordiciode F2 exhibited good inhibition potential (best MMGBA-binding energies; -41.1 and -43.4 kcal/mol) against the Mpro of SARS-CoV-2 when compared with FDA reference anti-viral drugs (Ribavirin, remdesivir and hydroxychloroquine). Per-residue analysis, root mean square deviation and solvent-accessible surface area revealed that compounds interacted with key amino acid residues at the active site of the enzyme and showed good system stability. The results obtained in this study show that these phytocompounds could emerge as promising therapeutic inhibitors for the Mpro of SARS-CoV-2. However, urgent trials should be conducted to validate this outcome.Communicated by Ramaswamy H. Sarma.

Protein tyrosine phosphatase 1B inhibitors from the fungus Malbranchea albolutea

From solid rice-based cultures of Malbranchea albolutea, three undescribed ardeemins and sartoryglabrins analogs were discovered and named alboluteins A-C. 1H-Indole-3-carbaldehyde, and anthranilic acid were also isolated. 1D and 2D-NMR techniques, as well as DFT-calculated chemical shifts, allowed characterizing alboluteins A-C. Testing these compounds against PTP1B indicated their inhibitory activity with IC₅₀'s ranging from 19 to 129 μM (ursolic acid IC₅₀ = 29.8 μM, positive control). Kinetic analysis revealed that albolutein C behaved as a non-competitive inhibitor. Docking studies of alboluteins A-C into the crystal structure of PTP1B (PDB ID: 1T49) predicted that all compounds prefer to bind at the allosteric site of the enzyme, with Ki values of 2.02 × 10^-4, 1.31 × 10^-4, and 2.67 × 10^-4 mM, respectively. Molecular dynamic studies indicated that the active compounds remained tied to the enzyme with good binding energy.

Targeting a conserved pocket (n-octyl-β-D-glucoside) on the dengue virus envelope protein by small bioactive molecule inhibitors

Dengue virus enters the cell by receptor-mediated endocytosis followed by a viral envelope (DENVE) protein-mediated membrane fusion. A small detergent molecule n-octyl-β-D-glucoside (βOG) occupies the hydrophobic pocket which is located in the hinge region plays a major role in the rearrangement. It has been reported that mutations occurred in this binding pocket lead to the alterations of pH threshold for fusion. In addition to this event, the protonation of histidine residues present in the hydrophobic pocket would also impart the conformational change of the E protein evidence this pocket as a promising target. The present study identified novel cinnamic acid analogs as significant blockers of the hydrophobic pocket through molecular modeling studies against DENVE. A library of seventy-two analogs of cinnamic acid was undertaken for the discovery process of DENV inhibitors. A Molecular docking study was used to analyze the binding mechanism between these compounds and DENV followed by ADMET prediction. Binding energies were predicted by the MMGBSA study. The Molecular dynamic simulation was utilized to confirm the stability of potential compound binding. The compounds CA and SCA derivatives have been tested against HSV-1 & 2 viruses. From the computational results, the compounds CA1, CA2, SCA 60, SCA 57, SCA 37, SCA 58, and SCA 14 exhibited favorable interaction energy. The compounds have in-vitro antiviral activity; the results clearly indicate that the compounds showed the activity against both the viruses (HSV-1 & HSV-2). Our study provides valuable information on the discovery of small molecules DENVE inhibitors.Communicated by Ramaswamy H. Sarma.

TYK2 Variants in B-Acute Lymphoblastic Leukaemia

B-cell precursor acute lymphoblastic leukaemia (B-ALL) is a malignancy of lymphoid progenitor cells with altered genes including the Janus kinase (JAK) gene family. Among them, tyrosine kinase 2 (TYK2) is involved in signal transduction of cytokines such as interferon (IFN) α/β through IFN−α/β receptor alpha chain (IFNAR1). To search for disease-associated TYK2 variants, bone marrow samples from 62 B-ALL patients at diagnosis were analysed by next-generation sequencing. TYK2 variants were found in 16 patients (25.8%): one patient had a novel mutation at the four-point-one, ezrin, radixin, moesin (FERM) domain (S431G) and two patients had the rare variants rs150601734 or rs55882956 (R425H or R832W). To functionally characterise them, they were generated by direct mutagenesis, cloned in expression vectors, and transfected in TYK2-deficient cells. Under high-IFNα doses, the three variants were competent to phosphorylate STAT1/2. While R425H and R832W induced STAT1/2-target genes measured by qPCR, S431G behaved as the kinase-dead form of the protein. None of these variants phosphorylated STAT3 in in vitro kinase assays. Molecular dynamics simulation showed that TYK2/IFNAR1 interaction is not affected by these variants. Finally, qPCR analysis revealed diminished expression of TYK2 in B-ALL patients at diagnosis compared to that in healthy donors, further stressing the tumour immune surveillance role of TYK2.

In Silico Repurposing of J147 for Neonatal Encephalopathy Treatment: Exploring Molecular Mechanisms of Mutant Mitochondrial ATP Synthase

BACKGROUND

Neonatal Encephalopathy (NE) is a mitochondrial ATP synthase (mATPase) disease, which results in the death of infants. The case presented here is reportedly caused by complex V deficiency as a result of mutation of Arginine to Cysteine at residue 329 in the mATPase. A recent breakthrough was the discovery of J147, which targets mATPase in the treatment of Alzheimer's disease. Based on the concepts of computational target-based drug design, this study investigated the possibility of employing J147 as a viable candidate in the treatment of NE.

OBJECTIVE/METHODS

The structural dynamic implications of this drug on the mutated enzyme are yet to be elucidated. Hence, integrative molecular dynamics simulations and thermodynamic calculations were employed to investigate the activity of J147 on the mutated enzyme in comparison to its already established inhibitory activity on the wild-type enzyme.

RESULTS

A correlated structural trend occurred between the wild-type and mutant systems whereby all the systems exhibited an overall conformational transition. Equal observations in favorable free binding energies further substantiated uniformity in the mobility, and residual fluctuation of the wild-type and mutant systems. The similarity in the binding landscape suggests that J147 could as well modulate mutant mATPase activity in addition to causing structural modifications in the wild-type enzyme.

CONCLUSION

Findings suggest that J147 can stabilize the mutant protein and restore it to a similar structural state as the wild-type which depicts functionality. These details could be employed in drug design for potential drug resistance cases due to mATPase mutations that may present in the future.

Effective prediction model and determination of binding residues influential for inhibitors targeting HIV-1 integrase-LEDGF/p75 interface by employing solvent accessible surface area energy as key determinant

Development of a highly accurate prediction model for protein-ligand inhibition has been a major challenge in drug discovery. Herein, we describe a novel predictive model for the inhibition of HIV-1 integrase (IN)-LEDGF/p75 protein-protein interaction. The model was constructed using energy parameters approximated from molecular dynamics (MD) simulations and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. Chemometric analysis using partial least squares (PLS) regression revealed that solvent accessible surface area energy (ΔG_SASA) is the major determinant parameter contributing greatly to the prediction accuracy. PLS prediction model on the ΔG_SASA values collected from 41 complexes yielded a strong correlation between the predicted and the actual inhibitory activities (R² = 0.9666, RMSEC of pIC₅₀ values = 0.0890). Additionally, for the test set of 14 complexes, the model performed satisfactorily with very low pIC₅₀ errors (Q² = 0.5168, RMSEP = 0.3325). A strong correlation between the buried surface areas on the IN protein, when bound with IN-LEDGF/p75 inhibitors, and the respective ΔG_SASA values was also obtained. Furthermore, the current method could identify 'hot spots'of amino acid residues highly influential to the inhibitory activity prediction. This could present fruitful implications in binding site determination and future inhibitor developments targeting protein-protein interactions.Communicated by Ramaswamy H. Sarma.

Induced Mutation Proves a Potential Target for TB Therapy: A Molecular Dynamics Study on LprG

Molecular dynamics (MD) simulations of wild-type and V91W mutant Mycobacterium tuberculosis-LprG (Mtb-LprG) were performed with the goal to provide a comprehensive understanding of the Mtb-LprG as a potential antimycobacterial target. A long-range MD simulations and post-MD analyzes led us to various results that plainly explained the impact of V91W mutation on Mtb-LprG. Herein, the results revealed that the wild-type is less stable compared to V91W mutant. This was further supported by root mean square fluctuation, where the V91W mutant showed a higher degree of flexibility compared to the wild-type. Dynamic cross-correlation analysis revealed that induced mutation leads to higher residual flexibility in the mutant structure as compared to the wild-type structure thus resulting in the existence of negatively correlated motions. The difference in principal component analysis scatter plot across the first two normal modes suggests a greater mobility of the V91W mutant conformation compared to the wild-type. Thermodynamic calculations revealed that the van der Waals (E_vdw) forces contribute the most towards binding free energy in a case of the V91W mutant as compared to the wild-type LprG complex. In addition, the residue interaction networks revealed more of E_vdw interaction existence among residues in case of the V91W mutant. This study supports the Mtb-LprG as a potential antimycobacterial target and also serves as a cornerstone to identifying new potential targets that have no inhibitors.

Tailored-pharmacophore model to enhance virtual screening and drug discovery: a case study on the identification of potential inhibitors against drug-resistant Mycobacterium tuberculosis (3R)-hydroxyacyl-ACP dehydratases

Aim: Virtual screening (VS) is powerful tool in discovering molecular inhibitors that are most likely to bind to drug targets of interest. Herein, we introduce a novel VS approach, so-called ‘tailored-pharmacophore’, in order to explore inhibitors that overcome drug resistance. Methodology & results: The emergence and spread of drug resistance strains of tuberculosis is one of the most critical issues in healthcare. A tailored-pharmacophore approach was found promising to identify in silico predicted hit with better binding affinities in case of the resistance mutations in MtbHadAB as compared with thiacetazone, a prodrug used in the clinical treatment of tuberculosis. Conclusion: This approach can potentially be enforced for the discovery and design of drugs against a wide range of resistance targets.

α-Glucosidase Inhibitors from Salvia circinata

A dried infusion prepared from the aerial parts of Salvia circinata did not provoke acute toxicity in mice (LD₅₀ > 5 g/kg). This infusion showed poor hypoglycemic and antihyperglycemic effects (100-570 mg/kg) when tested in normal and hyperglycemic mice using acute and oral glucose tolerance tests, respectively. However, this infusion possessed antihyperglycemic action in vivo during an oral sucrose tolerance test (31.6-316 mg/kg), suggesting the presence of α-glucosidase inhibitors in S. circinata. Fractionation of a nonpolar extract of the aerial parts of the plant yielded a new biflavone (1) and four new neoclerodane diterpenoid glucosides (2-5) along with the known compounds amarisolide (6), pedalitin (7), apigenin-7-O-β-d-glucoside (8), and the flavone 2-(3,4-dimethoxyphenyl)-5,6-dihydroxy-7-methoxy-4H-chromen-4-one (9). Compounds 1 and 6-9 were active against mammalian α-glucosidases; 6 and 7 were also active against a recombinant α-glucosidase from Ruminococcus obeum and reduced significantly the postprandial peak during an oral sucrose tolerance test in healthy mice, consistent with their α-glucosidase inhibitory activity. Molecular docking and dynamic studies revealed that compounds 6 and 7 might bind to α-glucosidases at the catalytic center of the enzyme.

Insights into molecular interactions between CaM and its inhibitors from molecular dynamics simulations and experimental data

In order to contribute to the structural basis for rational design of calmodulin (CaM) inhibitors, we analyzed the interaction of CaM with 14 classic antagonists and two compounds that do not affect CaM, using docking and molecular dynamics (MD) simulations, and the data were compared to available experimental data. The Ca(2+)-CaM-Ligands complexes were simulated 20 ns, with CaM starting in the "open" and "closed" conformations. The analysis of the MD simulations provided insight into the conformational changes undergone by CaM during its interaction with these ligands. These simulations were used to predict the binding free energies (ΔG) from contributions ΔH and ΔS, giving useful information about CaM ligand binding thermodynamics. The ΔG predicted for the CaM's inhibitors correlated well with available experimental data as the r(2) obtained was 0.76 and 0.82 for the group of xanthones. Additionally, valuable information is presented here: I) CaM has two preferred ligand binding sites in the open conformation known as site 1 and 4, II) CaM can bind ligands of diverse structural nature, III) the flexibility of CaM is reduced by the union of its ligands, leading to a reduction in the Ca(2+)-CaM entropy, IV) enthalpy dominates the molecular recognition process in the system Ca(2+)-CaM-Ligand, and V) the ligands making more extensive contact with the protein have higher affinity for Ca(2+)-CaM. Despite their limitations, docking and MD simulations in combination with experimental data continue to be excellent tools for research in pharmacology, toward a rational design of new drugs.

Computational investigation of the HIV-1 Rev multimerization using molecular dynamics simulations and binding free energy calculations

The HIV Rev protein mediates the nuclear export of viral mRNA, and is thereby essential for the production of late viral proteins in the replication cycle. Rev forms a large organized multimeric protein-protein complex for proper functioning. Recently, the three-dimensional structures of a Rev dimer and tetramer have been resolved and provide the basis for a thorough structural analysis of the binding interaction. Here, molecular dynamics (MD) and binding free energy calculations were performed to elucidate the forces thriving dimerization and higher order multimerization of the Rev protein. It is found that despite the structural differences between each crystal structure, both display a similar behavior according to our calculations. Our analysis based on a molecular mechanics-generalized Born surface area (MM/GBSA) and a configurational entropy approach demonstrates that the higher order multimerization site is much weaker than the dimerization site. In addition, a quantitative hot spot analysis combined with a mutational analysis reveals the most contributing amino acid residues for protein interactions in agreement with experimental results. Additional residues were found in each interface, which are important for the protein interaction. The investigation of the thermodynamics of the Rev multimerization interactions performed here could be a further step in the development of novel antiretrovirals using structure based drug design. Moreover, the variability of the angle between each Rev monomer as measured during the MD simulations suggests a role of the Rev protein in allowing flexibility of the arginine rich domain (ARM) to accommodate RNA binding.

Postprocessing of protein-ligand docking poses using linear response MM-PB/SA: application to Wee1 kinase inhibitors

Prediction of the binding strength of untested ligands is a central issue in structure-based drug design. In order to rapidly screen large compound databases, simple scoring schemes are often used in target-based virtual screening. The resulting scores often correlate poorly with biological affinities. More rigorous scoring methods, such as MM-PB/SA, correlate better with biological data by considering solvation effects and protein flexibility in the calculation of the binding free energy of a ligand. Here we describe the performance of a modified MM-PB/SA method on 222 Wee1 kinase inhibitors (48 pyridopyrimidine and 174 pyrrolocarbazole derivatives). Docking of these inhibitors into the available Wee1 kinase crystal structure yielded a consistent binding mode, and the derived MM-PB/SA models showed a significant correlation between calculated and experimental data (r(2) values between 0.64 and 0.67). Further study of these models on external test sets of Wee1 kinase inhibitors and structurally related decoys showed that a model based on a single kinase-inhibitor conformation can discriminate the active inhibitors from decoys. We also tested whether the linear interaction energy method with continuum electrostatics (LIECE) yields comparable results to MM-PB/SA and whether the LIECE and MM-PB/SA models can be applied for virtual screening of compound libraries.

Design, synthesis, and testing of an 6-O-linked series of benzimidazole based inhibitors of CDK5/p25

Alzheimer's disease (AD) is a progressive neurodegenerative disease resulting in cognitive and behavioral impairment. The two classic pathological hallmarks of AD include extraneuronal deposition of amyloid β (Aβ) and intraneuronal formation of neurofibrillary tangles (NFTs). NFTs contain hyperphosphorylated tau. Tau is the major microtubule-associated protein in neurons and stabilizes microtubules (MTs). Cyclin dependent kinase 5 (CDK5), when activated by the regulatory binding protein p25, phosphorylates tau at a number of proline-directed serine/threonine residues, resulting in formation of phosphorylated tau as paired helical filaments (PHFs) then in subsequent deposition of PHFs as NFTs. Beginning with the structure of Roscovitine, a moderately selective CDK5 inhibitor, we sought to conduct structural modifications to increase inhibitory potency of CDK5 and increase selectivity over a similar enzyme, cyclin dependent kinase 2 (CDK2). The design, synthesis, and testing of a series of 1-isopropyl-4-aminobenzyl-6-ether-linked benzimidazoles is presented.

Therapeutic strategies underpinning the development of novel techniques for the treatment of HIV infection

The HIV replication cycle offers multiple targets for chemotherapeutic intervention, including the viral exterior envelope glycoprotein, gp120; viral co-receptors CXCR4 and CCR5; transmembrane glycoprotein, gp41; integrase; reverse transcriptase; protease and so on. Most currently used anti-HIV drugs are reverse transcriptase inhibitors or protease inhibitors. The expanding application of simulation to drug design combined with experimental techniques have developed a large amount of novel inhibitors that interact specifically with targets besides transcriptase and protease. This review presents details of the anti-HIV inhibitors discovered with computer-aided approaches and provides an overview of the recent five-year achievements in the treatment of HIV infection and the application of computational methods to current drug design.

Computational analysis of the cathepsin B inhibitors activities through LR-MMPBSA binding affinity calculation based on docked complex

Cathepsin B, a ubiquitous lysosomal cysteine protease, is involved in many biological processes related to several human diseases. Inhibitors targeting the enzyme have been investigated as possible diseases treatments. A set of 37 compounds were recently found active in a high throughput screening assay to inhibit the catalytic activity of Cathepsin B, with chemical structures and biological test results available to the public in the PubChem BioAssay Database (AID 820). In this study, we compare these experimental activities to the results of theoretical predictions from binding affinity calculation with a LR-MM-PNSA approach based on docked complexes. Strong correlations (r(2) = 0.919 and q(2) = 0.887 for the best) are observed between the theoretical predictions and experimental biological activity. The models are cross-validated by four independent predictive experiments with randomly split compounds into training and test sets. Our results also show that the results based on protein dimer show better correlations with experimental activity when compared to results based on monomer in the in silico calculations.

High-performance drug discovery: computational screening by combining docking and molecular dynamics simulations

Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, this method is not completely reliable and therefore unsatisfactory. In this study, we used massive molecular dynamics simulations of protein-ligand conformations obtained by molecular docking in order to improve the enrichment performance of molecular docking. Our screening approach employed the molecular mechanics/Poisson-Boltzmann and surface area method to estimate the binding free energies. For the top-ranking 1,000 compounds obtained by docking to a target protein, approximately 6,000 molecular dynamics simulations were performed using multiple docking poses in about a week. As a result, the enrichment performance of the top 100 compounds by our approach was improved by 1.6–4.0 times that of the enrichment performance of molecular dockings. This result indicates that the application of molecular dynamics simulations to virtual screening for lead discovery is both effective and practical. However, further optimization of the computational protocols is required for screening various target proteins.

Lead discovery is one of the most important processes in rational drug design. To improve the rate of the detection of lead compounds, various technologies such as high-throughput screening and combinatorial chemistry have been introduced into the pharmaceutical industry. However, since these technologies alone may not improve lead productivity, computational screening has become important. A central method for computational screening is molecular docking. This method generally docks many flexible ligands to a rigid protein and predicts the binding affinity for each ligand in a practical time. However, its ability to detect lead compounds is less reliable. In contrast, molecular dynamics simulations can treat both proteins and ligands in a flexible manner, directly estimate the effect of explicit water molecules, and provide more accurate binding affinity, although their computational costs and times are significantly greater than those of molecular docking. Therefore, we developed a special purpose computer “MDGRAPE-3” for molecular dynamics simulations and applied it to computational screening. In this paper, we report an effective method for computational screening; this method is a combination of molecular docking and massive-scale molecular dynamics simulations. The proposed method showed a higher and more stable enrichment performance than the molecular docking method used alone.

Antiviral compounds discovered by virtual screening of small-molecule libraries against dengue virus E protein

Infection by the mosquito-borne dengue virus causes dengue fever and the sometimes fatal dengue hemorrhagic fever. The increasing number of dengue infections per year suggests that the virus is becoming more virulent and its transmission is expanding. Nevertheless, no effective treatment for dengue infection currently exists. In a search for antiviral agents effective against dengue virus, we investigated the potential of targeting a structural protein site rather than an enzymatic one. Using this approach, we now report the discovery of a small molecule ligand that inhibits viral growth. Our results also provide the first evidence that the binding site, a pocket located at the hinge between domains 1 and 2 of the envelope protein (E protein) on the virus surface, is a valid target for antiviral therapy. Ligand candidates were identified from libraries of approximately 142,000 compounds using a computational high-throughput screening protocol targeting this pocket of the E protein. Cell-based assays were conducted on 23 top-ranked compounds. Among four with good antiviral activity profiles, the compound P02 was found to inhibit viral reproduction at micromolar concentrations. Using saturation transfer difference NMR spectroscopy, we also show that the compound binds virus and competes for binding E protein with the known ligand N-octyl-beta-D-glucoside. Together, the results are consistent with an inhibition mechanism against maturation or host-cell entry mediated by ligand binding to the E-protein pocket. P02 is a promising lead compound for future development of an effective treatment against dengue virus and related flaviviruses.

Additional level of information about complex interaction between non-nucleoside inhibitor and HIV-1 reverse transcriptase using biosensor-based thermodynamic analysis

The thermodynamics of the interaction between mutant HIV-1 reverse transcriptase (K103N and Y181C) and a non-nucleoside reverse transcriptase inhibitor (NNRTI), the phenylethylthiazolylurea compound MIV-150, was obtained by determining the temperature dependence of the kinetic rate constants. Large entropic changes in the forward and backward steps of the isomerization between a non-binding competent and a binding competent conformation of the enzyme, as well as in the binding steps, implied the involvement of major structural rearrangements upon interaction with the inhibitor. Despite of the entropic character of the overall interaction, the equilibrium for the binding of inhibitor was found to be predominantly enthalpy-driven. The high affinity and the low affinity interactions of the heterogeneously interacting inhibitor showed different energetics in the analysis, revealing an expectedly higher enthalpic component for the high-affinity interaction. The thermodynamic profiles of the two enzyme variants displayed significant differences, which could not be derived from their kinetics at a single temperature.

Calculation of binding affinities of HIV-1 RT and beta-secretase inhibitors using the linear interaction energy method with explicit and continuum solvation approaches

The linear interaction energy (LIE) approach has been applied to estimate the binding free energies of representative sets of HIV-1 RT and beta-Secretase inhibitors, using both molecular dynamics (MD) and tethered energy minimization sampling protocols with the OPLS-AA potential, using a range of solvation methodologies. Generalized Born (GB), 'shell' and periodic boundary condition (PBC) solvation were used, the latter with reaction field (RF) electrostatics. Poisson-Boltzmann (PB) and GB continuum electrostatics schemes were applied to the simulation trajectories for each solvation type to estimate the electrostatic ligand-water interaction energy in both the free and bound states. Reasonable agreement of the LIE predictions was obtained with respect to experimental binding free energy estimates for both systems: for instance, 'PB' fits on MD trajectories carried out with PBC solvation and RF electrostatics led to models with standard errors of 1.11 and 1.03 kcal mol(-1) and coefficients of determination, r (2) of 0.76 and 0.75 for the HIV-1 RT and beta-Secretase sets. However, it was also found that results from MD sampling using PBC solvation provided only slightly better fits than from simulations using shell or Born solvation or tethered energy minimization sampling.

Affinity and specificity of protein U1A-RNA complex formation based on an additive component free energy model

An MM-GBSA computational protocol was used to investigate wild-type U1A-RNA and F56 U1A mutant experimental binding free energies. The trend in mutant binding free energies compared to wild-type is well-reproduced. Following application of a linear-response-like equation to scale the various energy components, the binding free energies agree quantitatively with observed experimental values. Conformational adaptation contributes to the binding free energy for both the protein and the RNA in these systems. Small differences in DeltaGs are the result of different and sometimes quite large relative contributions from various energetic components. Residual free energy decomposition indicates differences not only at the site of mutation, but throughout the entire protein. MM-GBSA and ab initio calculations performed on model systems suggest that stacking interactions may nearly, but not completely, account for observed differences in mutant binding affinities. This study indicates that there may be different underlying causes of ostensibly similar experimentally observed binding affinities of different mutants, and thus recommends caution in the interpretation of binding affinities and specificities purely by inspection.

Structure modeling, ligand binding, and binding affinity calculation (LR-MM-PBSA) of human heparanase for inhibition and drug design

Human heparanase is an endo-beta-D-glycosidase that cleaves heparan sulphate (HS) chains in the extracellular matrix and basement membrane. It is known that the cleavage of HS by heparanase results in cell invasion and metastasis of cancer. Therefore, heparanase is considered an important target for cancer drug development. The three-dimensional structure of heparanase would be useful in the rational design of inhibitors targeted to the enzyme; however, the three-dimensional structure has not yet been determined. In our effort to design inhibitors, we developed a three-dimensional structure of heparanase using a homology-modeling approach. The homology-built structure is consistent to previous bioinformatics and site-mutation experimental results. The heparanase features a (alpha/beta)(8) TIM-barrel fold with two glutamate residues (Glu225 and Glu343) located in the active-site cleft. This feature supports the putative mechanism of proton donor and nucleophilic sites. Docking simulations yielded 41 complex structures, which indicate that the bound inhibitor could block ligand binding into the catalytic site. A free energy of binding model was established for 25 heparanase inhibitors with a training set of 25 heparanase inhibitors using the linear response MM-PBSA approach (LR-MM-PBSA). The correlation between calculated and experimental activity was 0.79 and the reliability of the model was validated with leave-one-out cross-validation method. Its predictive capability was further validated using a test set of 16 inhibitors similar to the training set of inhibitors. The correlation between the predicted and observed activities is significantly improved by the protein "induced-fit" that accounts for the flexibility of the receptor. These interaction and pharmacophore elements provide a unique insight to the rational design of new ligands targeted to the enzyme.

Molecular mechanics methods for predicting protein–ligand binding

Ligand binding affinity prediction is one of the most important applications of computational chemistry. However, accurately ranking compounds with respect to their estimated binding affinities to a biomolecular target remains highly challenging. We provide an overview of recent work using molecular mechanics energy functions to address this challenge. We briefly review methods that use molecular dynamics and Monte Carlo simulations to predict absolute and relative ligand binding free energies, as well as our own work in which we have developed a physics-based scoring method that can be applied to hundreds of thousands of compounds by invoking a number of simplifying approximations. In our previous studies, we have demonstrated that our scoring method is a promising approach for improving the discrimination between ligands that are known to bind and those that are presumed not to, in virtual screening of large compound databases. In new results presented here, we explore several improvements to our computational method including modifying the dielectric constant used for the protein and ligand interiors, and empirically scaling energy terms to compensate for deficiencies in the energy model. Future directions for further improving our physics-based scoring method are also discussed.