Physics-based enzyme design: predicting binding affinity and catalytic activity

c-MET tyrosine kinase inhibitors reverse drug resistance mediated by the ATP-binding cassette transporter B1 (ABCB1) in cancer cells

This study investigated the potential of MET kinase inhibitors, cabozantinib, crizotinib, and PHA665752, in reversing multidrug resistance (MDR) mediated by ABCB1 in cancer cells. The accumulation of the fluorescent probe, Rhodamine 123, was assessed using flow cytometry and fluorescence microscopy in MDR MES-SA/DX5 and parental cells. The growth inhibitory activity of MET inhibitors as monotherapies and in combination with chemotherapeutic drugs was evaluated by MTT assay. CalcuSyn software was used to analyze the combination index (CI) as an index of drug-drug interaction in combination treatments. Results showed that at concentrations of 5, and 25 μM, c-MET inhibitors significantly increased Rhodamine 123 accumulation in MDR cells, with ratios up to 17.8 compared to control cells, while exhibiting no effect in parental cells. Additionally, the combination of c-MET inhibitors with the chemotherapeutic agent doxorubicin synergistically enhanced cytotoxicity in MDR cells, as evidenced by combination index (CI) values of 0.54 ± 0.08, 0.69 ± 0.1, and 0.85 ± 0.07 for cabozantinib, crizotinib, and PHA665752, respectively. While all three c-MET inhibitors stimulated ABCB1 ATPase activity in different manners at certain concentrations, PHA-665752 suppressed it at high concentration. In silico analysis also suggested that the transmembrane domains (TMD) of ABCB1 transporters could be considered potential target for these agents. Our results suggest that c-MET inhibitors can serve as promising MDR reversal agents in ABCB1-medicated drug-resistant cancer cells.

An evaluation of the precision of computational methods used in drug development initiatives

Computational approaches are commonly employed to expedite and provide decision-making for the drug development process. Drug development programs that involve targets without known crystal structures can be quite challenging. In many cases, a viable approach is to generate reliable homology models using the amino acid sequence of the target. This is followed by a series of validation steps, druggable pocket detection, and then moving forward with lead identification and validation. This study commenced by conducting an initial benchmark exercise using a series of computationally designed sequences for steroid-binding proteins. By conducting an unbiased comparison with the released X-ray crystal structures, the homology models that were generated demonstrated reliable outcomes. The aligned homology models showed a root mean square deviation (RMSD) of less than 0.6 Å when compared to the corresponding X-ray structures. Three different methods were used to detect the druggable cavities for comparison, and the identified pockets closely resembled those of the crystal structures. The achievement of near-native pose prediction was made possible by utilizing the comprehensive binding energy function that characterizes the interaction between each pose and the neighboring residues. In order to address the issue of limited correlation between entropy and internal energy in docking, an alternative was devised by incorporating entropy as a post-docking optimization step to enhance the accuracy of ligand binding affinity predictions and improve the overall quality of the results.

Categorization of hotspots into three types - weak, moderate and strong to distinguish protein-protein versus protein-peptide interactions

Protein-protein and protein-peptide interactions (PPI and PPepI) belong to a similar category of interactions, yet seemingly subtle differences exist among them. To characterize differences between protein-protein (PP) and protein-peptide (PPep) interactions, we have focussed on two important classes of residues-hotspot and anchor residues. Using implicit solvation-based free energy calculations, a very large-scale alanine scanning has been performed on benchmark datasets, consisting of over 5700 interface residues. The differences in the two categories are more pronounced, if the data were divided into three distinct types, namely - weak hotspots (having binding free energy loss upon Ala mutation, ΔΔG, ∼2-10 kcal/mol), moderate hotspots (ΔΔG, ∼10-20 kcal/mol) and strong hotspots (ΔΔG ≥ ∼20 kcal/mol). The analysis suggests that for PPI, weak hotspots are predominantly populated by polar and hydrophobic residues. The distribution shifts towards charged and polar residues for moderate hotspot and charged residues (principally Arg) are overwhelmingly present in the strong hotspot. On the other hand, in the PPepI dataset, the distribution shifts from predominantly hydrophobic and polar (in the weak type) to almost similar preference for polar, hydrophobic and charged residues (in moderate type) and finally the charged residue (Arg) and Trp are mostly occupied in the strong type. The preferred anchor residues in both categories are Arg, Tyr and Leu, possessing bulky side chain and which also strike a delicate balance between side chain flexibility and rigidity. The present knowledge should aid in effective design of biologics, by augmentation or disruption of PPIs with peptides or peptidomimetics.Communicated by Ramaswamy H. Sarma.

Investigation on the mechanisms by which the herbal remedies induce anti-prostate cancer activity: uncovering the most practical natural compound

Prostate cancer (PCa) is one of the most reported cancers among men worldwide. Targeting the essential proteins associated with PCa could be a promising method for cancer treatment. Traditional and herbal remedies (HRs) are the most practical approaches for PCa treatment. Here, the proteins and enzymes associated with PCa were determined based on the information obtained from the DisGeNET database. The proteins with a gene-disease association (GDA) score greater than 0.7 and the genes that have a disease specificity index (DSI) = 1 were selected as the target proteins. 28 HRs with anti-PCa activity as a traditional treatment for PCa were chosen as potential bioactive compounds. More than 500 compound-protein complexes were screened to find the top-ranked bioactives. The results were further evaluated using the molecular dynamics (MD) simulation and binding free energy calculations. The outcomes revealed that procyanidin B2 3,3'-di-O-gallate (B2G2), the most active ingredient of grape seed extract (GSE), can act as an agonist for PTEN. PTEN has a key role in suppressing PCa cells by applying phosphatase activity and inhibiting cell proliferation. B2G2 exhibited a considerable binding affinity to PTEN (11.643 kcal/mol). The MD results indicated that B2G2 could stabilize the key residues of the phosphatase domain of PTEN and increase its activity. Based on the obtained results, the active ingredient of GSE, B2G2, could play an agonist role and effectively increase the phosphatase activity of PTEN. The grape seed extract is a useful nutrition that can be used in men's diets to inhibit PCa in their bodies.Communicated by Ramaswamy H. Sarma.

Tracing the pathways and mechanisms involved in the anti-breast cancer activity of glycyrrhizin using bioinformatics tools and computational methods

A complete investigation to understand the pathways that could be affected by glycyrrhizin (licorice), as anti-breast cancer (BC) agent, has not been performed to date. This study aims to investigate the pathways involved in the anti-cancer activity of glycyrrhizin against BC. For this purpose, the target genes of glycyrrhizin were obtained from the ChEMBL database. The BC-associated genes for three types of BC (breast carcinoma, malignant neoplasm of breast, and triple-negative breast neoplasms) were retrieved from DisGeNET. The target genes of glycyrrhizin and the BC-associated genes were compared, and the genes with disease specificity index (DSI) > 0.6 were selected for further evaluation using in silico methods. The protein-protein interaction (PPI) network was constructed, and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed. The potential complexes were further evaluated using molecular dynamics (MD) simulation. The results revealed that among 80 common genes, ten genes had DSI greater than 0.6, which included POLK, TACR2, MC3R, TBXAS1, HH1R, SLCO4A1, NPY2R, ADRA2C, ADRA1A, and SLCO2B1. The binding affinity of glycyrrhizin to the cognate proteins and binding characteristics were assessed using molecular docking and binding free energy calculations (MM/GBSA). POLK, TBXAS1, and ADRA1A showed the highest binding affinity with -8.9, -9.3, and -9.6 kcal/mol, respectively. The final targets had an association with BC at several stages of tumor growth. By affecting these targets, glycyrrhizin could influence and control BC efficiently. MD simulation suggested the pathways triggered by the complex glycyrrhizin-ADRA1A were more likely to happen.Communicated by Ramaswamy H. Sarma.

Evaluation of the FDA-approved kinase inhibitors to uncover the potential repurposing candidates targeting ABC transporters in multidrug-resistant cancer cells: an in silico approach

Multiple drug resistance (MDR) is characterized by the resistance of cancer cells to a broad spectrum of anticancer drugs. The main mechanism underlying the MDR phenotype is the overexpression of ATP-binding cassette (ABC) transporters by promoting active drug efflux from cancer cells. Some small-molecule protein kinase inhibitors have been found to overcome MDR by inhibiting ABC transporters as substrates or modulators. This study investigated the chemical activity of 58 FDA-approved anticancer kinase inhibitors against three multidrug resistance-related proteins. The studied proteins are ATP-Binding Cassette Sub-Family B Member 1 (ABCB1), ATP-Binding Cassette Subfamily C Member 1 (ABCC1), and ATP-binding cassette superfamily G member 2 (ABCG2). The drug-binding domain and ATP binding sites of the proteins were considered the kinase inhibitors' probable target. High-throughput virtual screening and molecular docking were employed to find the hit drugs, and the drugs with the highest binding affinity were further evaluated using the molecular dynamics (MD) simulation. The virtual screening revealed that several kinase inhibitors could be considered potential inhibitors of ABCB1, ABCC1, and ABCG2, among which larotrectinib, entrectinib, and infigratinib showed the highest binding affinity, respectively. Based on the obtained results from MD simulation, these drugs can form strong interactions with the essential residues of the target proteins. In silico investigation revealed that larotrectinib, entrectinib, and infigratinib can target the key residues of the studied proteins. Therefore, these approved kinase inhibitors could be considered potential therapies for MDR cancers by targeting these transporters.Communicated by Ramaswamy H. Sarma.

Identification of novel pyrazole containing ɑ-glucosidase inhibitors: insight into pharmacophore, 3D-QSAR, virtual screening, and molecular dynamics study

Pharmacophore modelling, 3 D QSAR modelling, virtual screening, and molecular dynamics study, all-in-one combination were employed successfully design and develop an alpha-glucosidase inhibitor. To explain the structural prerequisites of biologically active components, 3 D-QSAR models were generated using the selected best hypothesis (AARRR) for compounds 55 included in the model C. The selection of 3 D-QSAR models showed that the Gaussian steric characteristic is crucial to alpha glucosidase's inhibitory potential. The alpha-glucosidase inhibitory potency of the compound is enhanced by other components, including Gaussian hydrophobic groups, Gaussian hydrogen bond acceptor or donor groups, Gaussian electrostatic characteristics, and a Gaussian steric feature. An identification of structure-activity relationships can be obtained from the developed 3 D-QSAR, C model, with R2 = 0.77 and SD = 0.02 for training set, and Q2 = 0.66, RMSE 0.02, and Pearson R = 0.81 for testing set, corresponding to elevated predictive ability. Additionally, docking and MM/GBSA experiments on 1146023 showed that it interacts with critical amino acids in the binding site when coupled with acarbose. Further, five compounds that display a high affinity for alpha-glucosidase were found, and these compounds may serve as potent leads for alpha-glucosidase inhibitor development. Biological activity will be tested for these compounds in the future.Communicated by Ramaswamy H. Sarma.

Development of thiazole-appended novel hydrazones as a new class of α-amylase inhibitors with anticancer assets: an in silico and in vitro approach

Hyperamylasemia is reported to be associated with numerous chronic diseases, including diabetes and cancer. Considering this fact, we developed a series of thiazole-clubbed hydrazones. The derivatives were explored for their in vitro α-amylase inhibitory activity, which was further corroborated with their anticancer assets using a panel of cancer cells, including colon cancer (HCT-116), lung cancer (A549), and breast cancer (MDA-MB-231). To better understand pharmacokinetics, the synthetic derivatives were subjected to in silico ADMET prediction. The in vitro based biological investigation revealed that compared to the reference drug acarbose (IC50 = 0.21 ± 0.008 μM), all the synthesized compounds (5a-5aa) exhibited in vitro α-amylase inhibitory response in the range of IC50 values from 0.23 ± 0.003 to 0.5 ± 0.0 μM. Along with this, the proliferations of the HCT-116, A549 and MDA-MB-231 cells were inhibited when treated with the synthesized compounds. Notable cancer cell growth inhibition was observed for compounds 5e, 5f and 5y, which correlated with their α-amylase inhibition. Additionally, the kinetics investigation revealed that 5b, 5e, 5f and 5y exhibit uncompetitive inhibition. 5b was found to be the least cytotoxic and most potent α-amylase inhibitor and was further validated by absorption and fluorescence quenching technique.

QSAR study of tetrahydropteridin derivatives as polo-like kinase 1(PLK1) Inhibitors with molecular docking and dynamics study

PLK1 is the key target for dealing with different cancer because it plays an important role in cell proliferation. According to the regulation of OECD, a QSAR model was developed from a dataset of 68 tetrahydropteridin derivatives. Three descriptors (maxHaaCH, ATSC7i, AATS7m) were considered for the development of the QSAR model. The reliability and predictability of the developed QSAR model were evaluated by various statistical parameters (r² = 0.8213, r²_ext = 0.8771 and CCC_ext = 0.9364). The maxHaaCH descriptor is positively correlated to pIC₅₀ whereas, the ATSC7i and AATS7m are negatively correlated with pIC₅₀. The QSAR model explains all the structural features and shows a good correlation with the activity. Based on molecular modelling techniques, five compounds (D1-D5) were designed. Molecular docking and dynamics studies of the most active compound were performed with PDB ID: 2RKU. The results of the present investigation may be employed to identify and develop effective inhibitors for the treatment of PLK1-related pathophysiological disorders.

Modeling and affinity maturation of an anti-CD20 nanobody: a comprehensive in-silico investigation

B-cell Non-Hodgkin lymphomas are the malignancies of lymphocytes. CD20 is a membrane protein, which is highly expressed on the cell surface of the B-cells in NHL. Treatments using monoclonal antibodies (mAbs) have resulted in failure in some cases. Nanobodies (NBs), single-domain antibodies with low molecular weights and a high specificity in antigen recognition, could be practical alternatives for traditional mAbs with superior characteristics. To design an optimized NB as a candidate CD20 inhibitor with raised binding affinity to CD20, the structure of anti-CD20 NB was optimized to selectively target CD20. The 3D structure of the NB was constructed based on the optimal templates (6C5W and 5JQH), and the key residues were determined by applying a molecular docking study. After identifying the key residues, some mutations were introduced using a rational protocol to improve the binding affinity of the NB to CD20. The rational mutations were conducted using the experimental design (Taguchi method). Six residues (Ser27, Thr28, Phe29, Ile31, Asp99, and Asn100) were selected as the key residues, and five residues were targeted for rational mutation (Trp, Phe, His, Asp, and Tyr). Based on the mutations suggested by the experimental design, two optimized NB structures were constructed. NB2 showed a remarkable binding affinity to CD20 in docking studies with a binding energy of - 853 kcal/mol. The optimized NB was further evaluated using molecular dynamics simulation. The results revealed that CDR1 (complementarity determining regions1) and CDR3 are essential loops for recognizing the antigen. NB2 could be considered as a potential inhibitor of CD20, though experimental evaluations are needed to confirm it.

Molecular Docking and Dynamics Simulation of Natural Compounds from Betel Leaves (Piper betle L.) for Investigating the Potential Inhibition of Alpha-Amylase and Alpha-Glucosidase of Type 2 Diabetes

Piper betle L. is widely distributed and commonly used medicinally important herb. It can also be used as a medication for type 2 diabetes patients. In this study, compounds of P. betle were screened to investigate the inhibitory action of alpha-amylase and alpha-glucosidase against type 2 diabetes through molecular docking, molecular dynamics simulation, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis. The molecule apigenin-7-O-glucoside showed the highest binding affinity among 123 (one hundred twenty-three) tested compounds. This compound simultaneously bound with the two-target proteins alpha-amylase and alpha-glucosidase, with high molecular mechanics-generalized born surface area (MM/GBSA) values (ΔG Bind = -45.02 kcal mol^-1 for alpha-amylase and -38.288 for alpha-glucosidase) compared with control inhibitor acarbose, which had binding affinities of -36.796 kcal mol^-1 for alpha-amylase and -29.622 kcal mol^-1 for alpha-glucosidase. The apigenin-7-O-glucoside was revealed to be the most stable molecule with the highest binding free energy through molecular dynamics simulation, indicating that it could compete with the inhibitors' native ligand. Based on ADMET analysis, this phytochemical exhibited a wide range of physicochemical, pharmacokinetic, and drug-like qualities and had no significant side effects, making them prospective drug candidates for type 2 diabetes. Additional in vitro, in vivo, and clinical investigations are needed to determine the precise efficacy of drugs.

The Impact of D614G Mutation of SARS-COV-2 on the Efficacy of Anti-viral Drugs: A Comparative Molecular Docking and Molecular Dynamics Study

D614G is one of the most reported mutations in the spike protein of SARS-COV-2 that has altered some crucial characteristics of coronaviruses, such as rate of infection and binding affinities. The binding affinity of different antiviral drugs was evaluated using rigid molecular docking. The reliability of the docking results was evaluated with the induced-fit docking method, and a better understanding of the drug-protein interactions was performed using molecular dynamics simulation. The results show that the D614G variant could change the binding affinity of antiviral drugs and spike protein remarkably. Although Cytarabine showed an appropriate interaction with the wild spike protein, Ribavirin and PMEG diphosphate exhibited a significant binding affinity to the mutated spike protein. The parameters of the ADME/T analysis showed that these drugs are suitable for further in-vitro and in-vivo investigation. D614G alteration affected the binding affinity of the RBD and its receptor on the cell surface.

In silico SELEX screening and statistical analysis of newly designed 5mer peptide-aptamers as Bcl-xl inhibitors using the Taguchi method

Drug development for cancer treatment is a complex process that requires special efforts. Targeting crucial proteins is the most essential purpose of drug design in cancers. Bcl-xl is an anti-apoptotic protein that binds to pro-apoptotic proteins and interrupts their signals. Pro-apoptotic Bcl-xl effectors are short BH3 sequences that form an alpha helix and bind to anti-apoptotic proteins to inhibit their activity. Computational systematic evolution of ligands by exponential enrichment (SELEX) is an exclusive approach for developing peptide aptamers as potential effectors. Here, the amino acids with a high tendency for constructing an alpha-helical structure were selected. Due to the enormous number of pentapeptides, Taguchi method was used to study a selected number of peptides. The binding affinity of the peptides to Bcl-xl was assessed using molecular docking, and after analysis of the obtained results, a final set of optimized peptides was arranged and constructed. For a better comparison, three chemical compounds with approved anti-Bcl-xl activity were selected for comparison with the top-ranked 5mer peptides. The optimized peptides showed considerable binding affinity to Bcl-xl. The molecular dynamics (MD) simulation indicated that the designed peptide (PO5) could create considerable interactions with the BH3 domain of Bcl-xl. The MM/GBSA calculations revealed that these interactions were even stronger than those created by chemical compounds. In silico SELEX is a novel approach to design and evaluate peptide-aptamers. The experimental design improves the SELEX process considerably. Finally, PO5 could be considered a potential inhibitor of Bcl-xl and a potential candidate for cancer treatment.

sVmKTx, a transcriptome analysis-based synthetic peptide analogue of Vm24, inhibits Kv1.3 channels of human T cells with improved selectivity

Kv1.3 K⁺ channels play a central role in the regulation of T cell activation and Ca²⁺ signaling under physiological and pathophysiological conditions. Peptide toxins targeting Kv1.3 have a significant therapeutic potential in the treatment of autoimmune diseases; thus, the discovery of new toxins is highly motivated. Based on the transcriptome analysis of the venom gland of V. mexicanus smithi a novel synthetic peptide, sVmKTx was generated, containing 36 amino acid residues. sVmKTx shows high sequence similarity to Vm24, a previously characterized peptide from the same species, but contains a Glu at position 32 as opposed to Lys32 in Vm24. Vm24 inhibits Kv1.3 with high affinity (K_d = 2.9 pM). However, it has limited selectivity (~1,500-fold) for Kv1.3 over hKv1.2, hKCa3.1, and mKv1.1. sVmKTx displays reduced Kv1.3 affinity (K_d = 770 pM) but increased selectivity for Kv1.3 over hKv1.2 (~9,000-fold) as compared to Vm24, other channels tested in the panel (hKCa3.1, hKv1.1, hKv1.4, hKv1.5, rKv2.1, hKv11.1, hKCa1.1, hNav1.5) were practically insensitive to the toxin at 2.5 μM. Molecular dynamics simulations showed that introduction of a Glu instead of Lys at position 32 led to a decreased structural fluctuation of the N-terminal segment of sVmKTx, which may explain its increased selectivity for Kv1.3. sVmKTx at 100 nM concentration decreased the expression level of the Ca²⁺ -dependent T cell activation marker, CD40 ligand. The high affinity block of Kv1.3 and increased selectivity over the natural peptide makes sVmKTx a potential candidate for Kv1.3 blockade-mediated treatment of autoimmune diseases.

Rational Development and Characterization of a Ubiquitin Variant with Selectivity for Ubiquitin C-Terminal Hydrolase L3

There is currently a lack of reliable methods and strategies to probe the deubiquitinating enzyme UCHL3. Current small molecules reported for this purpose display reduced potency and selectivity in cellular assays. To bridge this gap and provide an alternative approach to probe UCHL3, our group has carried out the rational design of ubiquitin-variant activity-based probes with selectivity for UCHL3 over the closely related UCHL1 and other DUBs. The approach successfully produced a triple-mutant ubiquitin variant activity-based probe, UbV^{Q40V/T66K/V70F}-PRG, that was ultimately 20,000-fold more selective for UCHL3 over UCHL1 when assessed by rate of inactivation assays. This same variant was shown to selectively form covalent adducts with UCHL3 in MDA-MB-231 breast cancer cells and no reactivity toward other DUBs expressed. Overall, this study demonstrates the feasibility of the approach and also provides insight into how this approach may be applied to other DUB targets.

Accurate Prediction of Protein Thermodynamic Stability Changes upon Residue Mutation using Free Energy Perturbation

This work describes the application of a physics-based computational approach to predict the relative thermodynamic stability of protein variants, and evaluates the quantitative accuracy of those predictions compared to experimental data obtained from a diverse set of protein systems assayed at variable pH conditions. Physical stability is a key determinant of the clinical and commercial success of biological therapeutics, vaccines, diagnostics, enzymes and other protein-based products. Although experimental techniques for measuring the impact of amino acid residue mutation on the stability of proteins exist, they tend to be time consuming and costly, hence the need for accurate prediction methods. In contrast to many of the commonly available computational methods for stability prediction, the Free Energy Perturbation approach applied in this paper explicitly accounts for solvent effects and samples conformational dynamics using a rigorous molecular dynamics simulation process. On the entire validation dataset, consisting of 328 single point mutations spread across 14 distinct protein structures, our results show good overall correlation with experiment with an R² of 0.65 and a low mean unsigned error of 0.95 kcal/mol. Application of the FEP approach in conjunction with experimental assessment techniques offers opportunities to lower the time and expense of product development and reduce the risk of costly late-stage failures.

3D-QSAR, molecular docking, molecular dynamics, and ADME/T analysis of marketed and newly designed flavonoids as inhibitors of Bcl-2 family proteins for targeting U-87 glioblastoma

Glioblastoma is the most common and destructive brain tumor with increasing complexity. Flavonoids are versatile natural compounds with the approved anticancer activity, which could be considered as a potential treatment for glioblastoma. A quantitative structure-activity relationship (QSAR) can provide adequate data for understanding the role of flavonoids structure against glioblastoma. The IC₅₀ of various flavonoids for the U-87 cell line was used to prepare an adequate three-dimensional QSAR (3D-QSAR) model. The validation of the model was carried out using some statistical parameters such as R² and Q² . Based on the QSAR model, the activities of other marketed and newly designed flavonoids were predicted. Molecular docking study and molecular dynamics (MD) simulation were conducted for better recognition of the interactions between the most active compounds and Bcl-2 family proteins. Moreover, an AMDE/T analysis was performed for the most active flavonoids. A reliable 3D-QSAR was performed with R² and Q² of 0.91 and 0.82. The molecular docking study revealed that BCL-XL has a higher binding affinity with the most active compounds, and the MD simulation showed that some residues of the BH3 domain, such as Phe97, Tyr101, Arg102, and Phe105 create remarkable hydrophobic interactions with the ligands. ADME/T analysis also showed the potential of the active compounds for further investigation. 3D-QSAR study is a beneficial method to evaluate and design anticancer compounds. Considering the results of the molecular docking study, MD simulation, and ADME/T analysis, the designed compound 54 could be considered as a potential treatment for glioblastoma.

Evaluation of binding of potential ADMET/tox screened saquinavir analogues for inhibition of HIV-protease via molecular dynamics and binding free energy calculations

Developing novel drug molecules against HIV is a scientific quest necessitated by development of drug resistance against used drugs. We report comparative results of molecular dynamics simulation studies on 11 structural analogues of Saquinavir (SQV) - against HIV-protease that were earlier examined for pharmacodynamic and pharmacokinetic properties. We reported analogues S1, S5 and S8 to qualify the ADMET criterion and may be considered as potential lead molecules. In this study the designed molecules were successively docked with native HIV-protease at AutoDock. Docking scores established relative goodness of the 11 analogues against the benchmark for Saquinavir. The docked complexes were subjected to molecular dynamics simulation studies using GROMACS 4.6.2. Four parameters viz. H-bonding, RMSD, Binding energy and Protein-Ligand Distance were used for comparative analyses of the analogues relative to Saquinavir. The comparison and analysis of the results are indicative that analogues S8, S9 and S1 are promising candidates among all the analogues studied. From our earlier work and present study it is evident that among the three S8 and S1 qualify the ADMET criterion and between S1 and S8, the analogue S8 shows more target efficacy and specificity over S1 and have better molecular dynamics simulation results. Thus, of the 11 de novo Saquinavir analogues, the S8 appears to be the most promising candidate as lead molecule for HIV-protease inhibitor and is best suited for testing under biological system. Further validation of the proposed lead molecules through wet lab studies involving antiviral assays however is required.Communicated by Ramaswamy H. Sarma.

Development of Ubiquitin Variants with Selectivity for Ubiquitin C-Terminal Hydrolase Deubiquitinases

Ubiquitin (Ub) is a highly conserved protein that is covalently attached to substrate proteins as a post-translational modification to regulate signaling pathways such as proteasomal degradation and cell cycle/transcriptional regulation in the eukaryotic cellular environment. Ub signaling is regulated by the homeostasis of substrate protein ubiquitination/deubiquitination by E3 ligases and deubiquitinating enzymes (DUBs) in healthy eukaryotic systems. One such DUB, ubiquitin C-terminal hydrolase L1 (UCHL1), is endogenously expressed in the central nervous system under normal physiological conditions, but overexpression and/or mutation has been linked to various cancers and neurodegenerative diseases. The lack of UCHL1 probing strategies suggests development of a selective Ub variant (UbV) for probing UCHL1's role in these disease states would be beneficial. We describe a computational design approach to investigate UbVs that lend selectivity, both binding and inhibition, to UCHL1 over the close structural homologue UCHL3 and members of other DUB families. A number of UbVs, mainly those containing Thr9 mutations, displayed appreciable binding and inhibition selectivity for UCHL1 over UCHL3, compared to wild-type Ub in in vitro assays. By appending reactive electrophiles to the C-terminus of the UbVs, we created the first activity-based probe (ABP) with demonstrated reaction selectivity for UCH family DUBs over other families in cell lysates. Further kinetic analysis of covalent inhibition by the UbV-ABP with UCHL1 and UCHL3 offers insight into the future design of UCHL1 selective UbV-ABP. These studies serve as a proof of concept of the viability of the in silico design of ubiquitin variants for UCH family DUBs as a step toward the development of macromolecular UCHL1 inhibitors.

Mechanistic Insights into Zika Virus NS3 Helicase Inhibition by Epigallocatechin-3-Gallate

Since 2007, repeated outbreaks of Zika virus (ZIKV) have affected millions of people worldwide and created a global health concern with major complications like microcephaly and Guillain Barre's syndrome. To date, there is not a single Zika-specific licensed drug present in the market. However, in recent months, several antiviral molecules have been screened against ZIKV. Among those, (-)-epigallocatechin-3-gallate (EGCG), a green tea polyphenol, has shown great virucidal potential against flaviviruses including ZIKV. The mechanistic understanding of EGCG-targeting viral proteins is not yet entirely deciphered except that little is known about its interaction with viral envelope protein and viral protease. We designed our current study to find inhibitory actions of EGCG against ZIKV NS3 helicase. NS3 helicase performs a significant role in viral replication by unwinding RNA after hydrolyzing NTP. We employed molecular docking and simulation approach and found significant interactions at the ATPase site and also at the RNA binding site. Further, the enzymatic assay has shown significant inhibition of NTPase activity with an IC₅₀ value of 295.7 nM and Ki of 0.387 ± 0.034 μM. Our study suggests the possibility that EGCG could be considered as a prime backbone molecule for further broad-spectrum inhibitor development against ZIKV and other flaviviruses.

Rapid Evolution of Reduced Susceptibility against a Balanced Dual-Targeting Antibiotic through Stepping-Stone Mutations

Multitargeting antibiotics, i.e., single compounds capable of inhibiting two or more bacterial targets, are generally considered to be a promising therapeutic strategy against resistance evolution. The rationale for this theory is that multitargeting antibiotics demand the simultaneous acquisition of multiple mutations at their respective target genes to achieve significant resistance. The theory presumes that individual mutations provide little or no benefit to the bacterial host. Here, we propose that such individual stepping-stone mutations can be prevalent in clinical bacterial isolates, as they provide significant resistance to other antimicrobial agents. To test this possibility, we focused on gepotidacin, an antibiotic candidate that selectively inhibits both bacterial DNA gyrase and topoisomerase IV. In a susceptible organism, Klebsiella pneumoniae, a combination of two specific mutations in these target proteins provide an >2,000-fold reduction in susceptibility, while individually, none of these mutations affect resistance significantly. Alarmingly, strains with decreased susceptibility against gepotidacin are found to be as virulent as the wild-type Klebsiella pneumoniae strain in a murine model. Moreover, numerous pathogenic isolates carry mutations which could promote the evolution of clinically significant reduction of susceptibility against gepotidacin in the future. As might be expected, prolonged exposure to ciprofloxacin, a clinically widely employed gyrase inhibitor, coselected for reduced susceptibility against gepotidacin. We conclude that extensive antibiotic usage could select for mutations that serve as stepping-stones toward resistance against antimicrobial compounds still under development. Our research indicates that even balanced multitargeting antibiotics are prone to resistance evolution.

α-bisabolol β-D-fucopyranoside as a potential modulator of β-amyloid peptide induced neurotoxicity: An in vitro &in silico study

Alzheimer's disease (AD) is a multifaceted neurodegenerative disorder affecting the elderly people. For the AD treatment, there is inefficiency in the existing medication, as these drugs reduce only the symptoms of the disease. Since multiple pathological proteins are involved in the development of AD, searching for a single molecule targeting multiple AD proteins will be a new strategy for the management of AD. In view of this, the present study was designed to synthesize and evaluate the multifunctional neuroprotective ability of the sesquiterpene glycoside α-bisabolol β-D-fucopyranoside (ABFP) against multiple targets like acetylcholinesterase, oxidative stress and β-amyloid peptide aggregation induced cytotoxicity. In silico computational docking and simulation studies of ABFP with acetylcholinesterase (AChE) showed that it can interact with Asp74 and Thr75 residues of the enzyme. The in vitro studies showed that the compound possess significant ability to inhibit the AChE enzyme apart from exhibiting antioxidant, anti-aggregation and disaggregation properties. In addition, molecular dynamics simulation studies proved that the interacting residue between Aβ peptide and ABFP was found to be involved in Leu34 and Ile31. Furthermore, the compound was able to protect the Neuro2 a cells against Aβ_25-35 peptide induced toxicity. Overall, the present study evidently proved ABFP as a neuroprotective agent, which might act as a multi-target compound for the treatment of Alzheimer's disease.

Computational identification and antifungal bioassay reveals phytosterols as potential inhibitor of Alternaria arborescens

Alternaria arborescens is a major pathogen for crops like tomato, tangerine and so on and its control is mostly dependent on the application of chemical agents. Plants as the sources of natural products are very attractive option for developing eco-friendly and natural antifungal agents. In this study, we modeled three-dimensional structure of chorismate synthase (CS) enzyme from A. arborescens. Docking studies of phytosterols, namely, γ-sitosterol and β-sitosterol, with CS showed them to be potential inhibitor of CS. To explore the stability and conformational flexibility of all the AaCS complex systems, molecular dynamics simulations were performed. None of the putative inhibitors as well as β- and γ-sitosterol showed interaction with the FMNH₂ binding pocket of the tomato CS (major host of A. arborescens) indicating their suitability as antifungal compounds inhibiting the shikimate pathway without causing any harm to the host. An in vivo antifungal bioassay showed a significant reduction in fungal growth in the presence of β-sitosterol (500 ppm) which resulted in ∼23% and ∼17% reduction in fungal fresh and dry weight, respectively, at 8 days after inoculation. This study provides experimental evidence establishing natural sterols like β-sitosterol can be useful in curbing A. arborescens damage in an eco-friendly manner.Communicated by Ramaswamy H. Sarma.

Structure based identification and biological evaluation of novel and potent inhibitors of PCAF catalytic domain

p300/CBP Associated Factor (PCAF), a GNAT family member protein, represent a valid target for therapeutic interventions since its dysfunction has implicated in variety of diseases like cancer, diabetes, inflammatory diseases, etc. Despite its potential for therapeutics, only a small number of PCAF inhibitors were reported. Hence, in this study, the catalytic domain of PCAF was explored to screen novel, potent and cell permeable inhibitor from three small molecule databases like Life Chemical, Maybridge and Chembridge by using Structure Based Virtual Screening (SBVS) method. Further, Induced Fit Docking, Binding Free Energy calculation, Single Point Energy calculation and Molecular Dynamics Simulation were performed on selected hits. In silico results revealed that F2209-0381 has higher binding energy of -109.722 and have greater cell permeability (QPPCaco = 1456.764; QPPMDCK = 742.941) than rest of hits. Cytotoxicity effect and protein expression analysis of F2209-0381 on A549 cells reveals that it exhibited strong inhibition with IC₅₀ value of 58.31 μg/ml and significantly reduced the expression of PCAF after 72 h time point. Thus, this study warrants that F2209-0381 could become a novel, potent and cell permeable drug of PCAF thereby it could combat its mediated diseases.

Deciphering the binding mode and mechanistic insights of pentadecylidenemalonate (1b) as activator of histone acetyltransferase PCAF

Histone acetyltransferases (HATs) is one among the conspicuous posttranslational modification in eukaryotic cells. p300/CBP Associated Factor (PCAF) and CREB-binding protein (CBP) are the two highly homologous HAT family which are vastly implicated in several diseases like cancer, diabetes, etc. Pentadecylidenemalonate, a simplified analog of anacardic acid, was reported as first mixed inhibitor/activator of HATs which inhibits p300/CBP and activates PCAF. It was appointed earlier as a valuable biological tool to understand the mechanism of lysine acetyltransferases due to its powerful apoptotic effect. In this study, pentadecylidenemalonate was taken for deciphering the binding mode, key interacting residues as well as mechanistic insights on PCAF and CBP as activator and inhibitor, respectively. This study is highly believed to help in rational design on antineoplastic drugs against PCAF. Communicated by Ramaswamy H. Sarma.

β-Sitosterol targets Trx/Trx1 reductase to induce apoptosis in A549 cells via ROS mediated mitochondrial dysregulation and p53 activation

β-Sitosterol (BS), a major bioactive constituent present in plants and vegetables has shown potent anticancer effect against many human cancer cells, but the underlying mechanism remain elusive on NSCLC cancers. We found that BS significantly inhibited the growth of A549 cells without harming normal human lung and PBMC cells. Further, BS treatment triggered apoptosis via ROS mediated mitochondrial dysregulation as evidenced by caspase-3 & 9 activation, Annexin-V/PI positive cells, PARP inactivation, loss of MMP, Bcl-2-Bax ratio alteration and cytochrome c release. Moreover, generation of ROS species and subsequent DNA stand break were found upon BS treatment which was reversed by addition of ROS scavenger (NAC). Indeed BS treatment increased p53 expression and its phosphorylation at Ser15, while silencing the p53 expression by pifithrin-α, BS induced apoptosis was reduced in A549 cells. Furthermore, BS induced apoptosis was also observed in NCI-H460 cells (p53 wild) but not in the NCI-H23 cells (p53 mutant). Down-regulation of Trx/Trx1 reductase contributed to the BS induced ROS accumulation and mitochondrial mediated apoptotic cell death in A549 and NCI-H460 cells. Taken together, our findings provide evidence for the novel anti-cancer mechanism of BS which could be developed as a promising chemotherapeutic drug against NSCLC cancers.

Effects of Distal Mutations on the Structure, Dynamics and Catalysis of Human Monoacylglycerol Lipase

An understanding of how conformational dynamics modulates function and catalysis of human monoacylglycerol lipase (hMGL), an important pharmaceutical target, can facilitate the development of novel ligands with potential therapeutic value. Here, we report the discovery and characterization of an allosteric, regulatory hMGL site comprised of residues Trp-289 and Leu-232 that reside over 18 Å away from the catalytic triad. These residues were identified as critical mediators of long-range communication and as important contributors to the integrity of the hMGL structure. Nonconservative replacements of Trp-289 or Leu-232 triggered concerted motions of structurally distinct regions with a significant conformational shift toward inactive states and dramatic loss in catalytic efficiency of the enzyme. Using a multimethod approach, we show that the dynamically relevant Trp-289 and Leu-232 residues serve as communication hubs within an allosteric protein network that controls signal propagation to the active site, and thus, regulates active-inactive interconversion of hMGL. Our findings provide new insights into the mechanism of allosteric regulation of lipase activity, in general, and may provide alternative drug design possibilities.

Molecular dynamic simulations reveal suboptimal binding of salbutamol in T164I variant of β2 adrenergic receptor

The natural variant C491T (rs1800088) in ADRB2 gene substitutes Threonine to Isoleucine at 164^th position in β2AR and results in receptor sequestration and altered binding of agonists. Present investigation pursues to identify the effect of T164I variation on function and structure of β2AR through systematic computational approaches. The study, in addition, addresses altered binding of salbutamol in T164I variant through molecular dynamic simulations. Methods involving changes in free energy, solvent accessibility surface area, root mean square deviations and analysis of binding cavity revealed structural perturbations in receptor to incur upon T164I substitution. For comprehensive understanding of receptor upon substitution, OPLS force field aided molecular dynamic simulations were performed for 10 ns. Simulations revealed massive structural departure for T164I β2AR variant from the native state along with considerably higher root mean square fluctuations of residues near the cavity. Affinity prediction by molecular docking showed two folds reduced affinity of salbutamol in T164I variant. To validate the credibility docking results, simulations for ligand-receptor complex were performed which demonstrated unstable salbutamol-T164I β2AR complex formation. Further, analysis of interactions in course of simulations revealed reduced ligand-receptor interactions of salbutamol in T164I variant. Taken together, studies herein provide structural rationales for suboptimal binding of salbutamol in T164I variant through integrated molecular modeling approaches.

Simultaneous engineering of an enzyme's entrance tunnel and active site: the case of monoamine oxidase MAO-N

A new directed evolution approach is presented to enhance the activity of an enzyme and to manipulate stereoselectivity by focusing iterative saturation mutagenesis (ISM) simultaneously on residues lining the entrance tunnel and the binding pocket. This combined mutagenesis strategy was applied successfully to the monoamine oxidase from Aspergillus niger (MAO-N) in the reaction of sterically demanding substrates which are of interest in the synthesis of chiral pharmaceuticals based on the benzo-piperidine scaffold. Reversal of enantioselectivity of Turner-type deracemization was achieved in the synthesis of (S)-1,2,3,4-tetrahydro-1-methyl-isoquinoline, (S)-1,2,3,4-tetrahydro-1-ethylisoquinoline and (S)-1,2,3,4-tetrahydro-1-isopropylisoquinoline. Extensive molecular dynamics simulations indicate that the altered catalytic profile is due to increased hydrophobicity of the entrance tunnel acting in concert with the altered shape of the binding pocket.

Molecular modeling and structural analysis of nAChR variants uncovers the mechanism of resistance to snake toxins

Nicotinic acetylcholine receptors (nAChRs) are neuromuscular proteins responsible for muscle contraction upon binding with chemical stimulant acetylcholine (ACh). The α-neurotoxins of snake mimic the structure of ACh and attacks nAChRs, which block the flow of ACh and leads to numbness and paralysis. The toxin-binding site of alpha subunit in the nAChRs is highly conserved throughout chordate lineages with few exceptions in resistance organisms. In this study, we have analyzed the sequence and structures of toxin-binding/resistant nAChRs and their interaction stability with toxins through molecular docking and molecular dynamics simulation (MDS). We have reported the potential glycosylation residues within the toxin-binding cleft adding sugar moieties through N-linked glycosylation in resistant organisms. Residue variations at key positions alter the secondary structure of binding cleft, which might interfere with toxin binding and it could be one of the possible explanations for the resistance to snake venoms. Analysis of nAChR-α-neurotoxin complexes has confirmed the key interacting residues. In addition, drastic variation in the binding stability of Mongoose nAChR-α-Bungarotoxin (α-BTX) and human nAChR-α-BTX complexes were found at specific phase of MDS. Our findings suggest that specific mutations in the binding site of toxin are potentially preventing the formation of stable complex of receptor-toxin, which might lead to mechanism of resistance. This in silico study on the binding cleft of nAChR and the findings of interacting residues will assist in designing potential inhibitors as therapeutic targets.

Chemical basis for the recognition of trimethyllysine by epigenetic reader proteins

A large number of structurally diverse epigenetic reader proteins specifically recognize methylated lysine residues on histone proteins. Here we describe comparative thermodynamic, structural and computational studies on recognition of the positively charged natural trimethyllysine and its neutral analogues by reader proteins. This work provides experimental and theoretical evidence that reader proteins predominantly recognize trimethyllysine via a combination of favourable cation-π interactions and the release of the high-energy water molecules that occupy the aromatic cage of reader proteins on the association with the trimethyllysine side chain. These results have implications in rational drug design by specifically targeting the aromatic cage of readers of trimethyllysine.

Designing High-Affinity Peptides for Organic Molecules by Explicit Solvent Molecular Dynamics

Short peptides offer a cheap alternative to antibodies for developing sensing units in devices for concentration measurement. We here describe a computational procedure that allows designing peptides capable of binding with high affinity a target organic molecule in aqueous or nonstandard solvent environments. The algorithm is based on a stochastic search in the space of the possible sequences of the peptide, and exploits finite temperature molecular dynamics simulations in explicit solvent to check if a proposed mutation improves the binding affinity or not. The procedure automatically produces peptides which form thermally stable complexes with the target. The estimated binding free energy reaches the 13 kcal/mol for Irinotecan anticancer drug, the target considered in this work. These peptides are by construction solvent specific; namely, they recognize the target only in the solvent in which they have been designed. This feature of the algorithm calls for applications in devices in which the peptide-based sensor is required to work in denaturants or under extreme conditions of pressure and temperature.

Computational design of enzyme-ligand binding using a combined energy function and deterministic sequence optimization algorithm

Enzyme amino-acid sequences at ligand-binding interfaces are evolutionarily optimized for reactions, and the natural conformation of an enzyme-ligand complex must have a low free energy relative to alternative conformations in native-like or non-native sequences. Based on this assumption, a combined energy function was developed for enzyme design and then evaluated by recapitulating native enzyme sequences at ligand-binding interfaces for 10 enzyme-ligand complexes. In this energy function, the electrostatic interaction between polar or charged atoms at buried interfaces is described by an explicitly orientation-dependent hydrogen-bonding potential and a pairwise-decomposable generalized Born model based on the general side chain in the protein design framework. The energy function is augmented with a pairwise surface-area based hydrophobic contribution for nonpolar atom burial. Using this function, on average, 78% of the amino acids at ligand-binding sites were predicted correctly in the minimum-energy sequences, whereas 84% were predicted correctly in the most-similar sequences, which were selected from the top 20 sequences for each enzyme-ligand complex. Hydrogen bonds at the enzyme-ligand binding interfaces in the 10 complexes were usually recovered with the correct geometries. The binding energies calculated using the combined energy function helped to discriminate the active sequences from a pool of alternative sequences that were generated by repeatedly solving a series of mixed-integer linear programming problems for sequence selection with increasing integer cuts.