Structural similarity between binding sites in influenza sialidase and isocitrate dehydrogenase: implications for an alternative approach to rational drug design.

Using searching techniques based on algorithms derived from graph theory, we have established a similarity between a 3-dimensional cluster of side chains implicated in drug binding in influenza sialidase and side chains involved in isocitrate binding in Escherichia coli isocitrate dehydrogenase. The possible implications of the use of such comparative methods in drug design are discussed.     

The relationship between rational drug design and drug side effects

Previous analysis of systems pharmacology has revealed a tendency of rational drug design in the pharmaceutical industry. The targets of new drugs tend to be close with the corresponding disease genes in the biological networks. However, it remains unclear whether the rational drug design introduces disadvantages, i.e. side effects. Therefore, it is important to dissect the relationship between rational drug design and drug side effects. Based on a recently released drug side effect database, SIDER, here we analyzed the relationship between drug side effects and the rational drug design. We revealed that the incidence drug side effect is significantly associated with the network distance of drug targets and diseases genes. Drugs with the distances of three or four have the smallest incidence of side effects, whereas drugs with the distances of more than four or smaller than three show significantly greater incidence of side effects. Furthermore, protein drugs and small molecule drugs show significant differences. Drugs hitting membrane targets and drugs hitting cytoplasm targets also show differences. Failure drugs because of severe side effects show smaller network distances than approved drugs. These results suggest that researchers should be prudent on rationalizing the drug design. Too small distances between drug targets and diseases genes may not always be advantageous for rational design for drug discovery.     

An approach to peptide-based ATP receptors by a combination of random selection, rational design, and molecular imprinting

Random selection, rational design and molecular imprinting were cooperatively utilized to develop peptide-based ATP synthetic receptors. In this fusion strategy, combinatorial chemistry was utilized for screening a precursor peptide useful for construction of ATP receptors, and rational design was employed in modification of the selected precursor peptide for higher affinity and selectivity. Finally, molecular imprinting was used for pre-organizing the conformation of the precursor peptide as complementary to a target molecule ATP. The fusion strategy appeared to have advantage to sole use of the individual strategy: (1) a low hit-rate of combinatorial chemistry will be improved by customizing a higher order structure of a selected peptide by molecular imprinting, (2) combinatorial chemistry allows us to semi-automatically select components of water-compatible synthetic receptors, (3) rational design improves the selected peptide sequence for better molecularly imprinted receptors.A peptide consisting of a randomly selected sequence and a rationally designed sequence (Resin-Lys-Gly-Arg-Gly-Lys-Gly-Gly-Gly-Glu-Lys-Tyr-Leu-Lys-NHAc) was designed and synthesized as a precursor peptide. The rational design was made according to the sequence of the adenine binding site of biotin carboxylase. The on-beads peptide was cross-linked with dimethyl adipimidate in the presence of ATP. In the saturation binding tests, the cross-linked on-beads peptide showed 5.3 times higher affinity compared to the non-cross-linked peptide with the same sequence. Furthermore, the cross-linked peptide showed improved selectivity; the ratios of binding constants, K_(ATP)/K_(ADP) and K_(ATP)/K_(GTP), were increased from 2.4 to 19, and from 0.8 to 10, respectively. It would be notable that the peptide without the rationally designed sequence showed no discrimination between ATP and GTP (K_(ATP)/K_(GTP) as 0.9), suggesting that the rationally designed site was successfully engaged for recognition of the adenine base.     

The role of multiscale computational approaches for rational design of conventional and nanoparticle oral drug delivery systems

Multiscale computational modeling of drug delivery systems (DDS) is poised to provide predictive capabilities for the rational design of targeted drug delivery systems, including multi-functional nanoparticles. Realistic, mechanistic models can provide a framework for understanding the fundamental physico-chemical interactions between drug, delivery system, and patient. Multiscale computational modeling, however, is in its infancy even for conventional drug delivery. The wide range of emerging nanotechnology systems for targeted delivery further increases the need for reliable in silico predictions. This review will present existing computational approaches at different scales in the design of traditional oral drug delivery systems. Subsequently, a multiscale framework for integrating continuum, stochastic, and computational chemistry models will be proposed and a case study will be presented for conventional DDS. The extension of this framework to emerging nanotechnology delivery systems will be discussed along with future directions. While oral delivery is the focus of the review, the outlined computational approaches can be applied to other drug delivery systems as well.     

Deciphering molecular aspects of interaction between anticancer drug mitoxantrone and tRNA

Mitoxantrone (1,4-dihydroxy-5,8-bis[[2-[(2-hydroxyethyl)amino]ethyl]amino]-9,10-anthracenedione) is a synthetically designed antineoplastic agent and structurally similar to classical anthracyclines. It is widely used as a potent chemotherapeutic component against various kinds of cancer and possesses lesser cardio-toxic effects with respect to naturally occurring anthracyclines. In the present study, we have investigated the binding features of mitoxantrone–tRNA complexation at physiological pH using attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy, circular dichroism (CD) spectroscopy, isothermal titration calorimetry, and UV–visible absorption spectroscopic techniques. FTIR analysis reveals that mitoxantrone interacts mainly with heterocyclic base residues of tRNA along with slight external binding with phosphate–sugar backbone. In particular, mitoxantrone binds at uracil (C=O) and adenine (C=N) sites of biomolecule (tRNA). CD spectroscopic results suggest that there is no major conformational transition in native A-form of tRNA upon mitoxantrone–tRNA adductation except an intensification in the secondary structure of tRNA is evident. The association constant calculated for mitoxantrone–tRNA association is found to be 1.27?×?10⁵ M^?1 indicating moderate to strong binding affinity of drug with tRNA. Thermodynamically, mitoxantrone–tRNA interaction is an enthalpy-driven exothermic reaction. Investigation into drug–tRNA interaction can play an essential role in the rational development of RNA targeting chemotherapeutic agents, which also delineate the structural–functional relationship between drug and its target at molecular level.     

A multi-spectroscopic and molecular docking approach to investigate the interaction of antiviral drug oseltamivir with ct-DNA

The possible interaction between the antiviral drug oseltamivir and calf thymus DNA at physiological pH was studied by spectrophotometry, competitive spectrofluorimetry, differential pulse voltammogram (DPV), circular dichroism spectroscopy (CD), viscosity measurements, salt effect, and computational studies. Intercalation of oseltamivir between the base pairs of DNA was shown by a sharp increase in specific viscosity of DNA and a decrease of the peak current and a positive shift in differential pulse voltammogram. Competitive fluorescence experiments were performed using neutral red (NR) as a probe for the intercalation binding mode. The studies showed that oseltamivir is able to release the NR.     

Dynamic behavior of Dengue and Zika viruses NS1 protein reveals monomer–monomer interaction mechanisms and insights to rational drug design

Communicated by Ramaswamy H. Sarma     

Modeling assisted rational design of novel, potent, and selective pyrrolopyrimidine DPP-4 inhibitors

Molecular modeling was used to improve potency of the cyclohexylamine series. In addition, a 3-D QSAR method was used to gain insight for reducing off-target DPP-8/9 activities. Compounds 3, 4, and 5 were synthesized and found to be potent DPP-4 inhibitors, in particular 4 and 5 are designed to be highly selective against off-target DASH enzymes while maintaining potency on DPP-4.     

Structure-based protein-protein interaction networks and drug design

Proteins carry out their functions by interacting with other proteins and small molecules, forming a complex interaction network. In this review, we briefly introduce classical graph theory based protein-protein interaction networks. We also describe the commonly used experimental methods to construct these networks, and the insights that can be gained from these networks. We then discuss the recent transition from graph theory based networks to structure based protein-protein interaction networks and the advantages of the latter over the former, using two networks as examples. We further discuss the usefulness of structure based protein-protein interaction networks for drug discovery, with a special emphasis on drug repositioning.     

Combined spectroscopies and molecular docking approach to characterizing the binding interaction between lisinopril and bovine serum albumin

To further understand the mode of action and pharmacokinetics of lisinopril, the binding interaction of lisinopril with bovine serum albumin (BSA) under imitated physiological conditions (pH 7.4) was investigated using fluorescence emission spectroscopy, synchronous fluorescence spectroscopy, Fourier transform infrared spectroscopy (FTIR), circular dichroism (CD) and molecular docking methods. The results showed that the fluorescence quenching of BSA near 338 nm resulted from the formation of a lisinopril–BSA complex. The number of binding sites (n) for lisinopril binding on subdomain IIIA (site II) of BSA and the binding constant were ~ 1 and 2.04 × 10⁴ M^–1, respectively, at 310 K. The binding of lisinopril to BSA induced a slight change in the conformation of BSA, which retained its α‐helical structure. However, the binding of lisinopril with BSA was spontaneous and the main interaction forces involved were van der Waal's force and hydrogen bonding interaction as shown by the negative values of ΔG⁰, ΔH⁰ and ΔS⁰ for the binding of lisinopril with BSA. It was concluded from the molecular docking results that the flexibility of lisinopril also played an important role in increasing the stability of the lisinopril–BSA complex. Copyright © 2015 John Wiley & Sons, Ltd.     

Structure-based rational design of self-inhibitory peptides to disrupt the intermolecular interaction between the troponin subunits C and I in neuropathic pain

The troponin (Tn) is a ternary complex consisting of three subunits TnC, TnI and TnT; molecular disruption of the Tn complex has been recognized as an attractive strategy against neuropathic pain. Here, a self-inhibitory peptide is stripped from the switch region of TnI interaction interface with TnC, which is considered as a lead molecular entity and then used to generate potential peptide disruptors of TnC–TnI interaction based on a rational molecular design protocol. The region is a helical peptide segment capped by N- and C-terminal disorders. Molecular dynamics simulation and binding free energy analysis suggests that the switch peptide can interact with TnC in a structurally and energetically independent manner. Terminal truncation of the peptide results in a number of potent TnC binders with considerably simplified structure and moderately decreased activity relative to the native switch. We also employ fluorescence polarization assays to substantiate the computational findings; it is found that the rationally designed peptides exhibit moderate or high affinity to TnC with dissociation constants K_D at micromolar level.     

Novel urushiol derivatives as HDAC8 inhibitors: rational design,virtual screening,molecular docking and molecular dynamics studies

Three series of novel urushiol derivatives were designed by introducing a hydroxamic acid moiety into the tail of an alkyl side chain and substituents with differing electronic properties or steric bulk onto the benzene ring and alkyl side chain. The compounds’ binding affinity toward HDAC8 was screened by Glide docking. The highest-scoring compounds were processed further with molecular docking, MD simulations, and binding free energy studies to analyze the binding modes and mechanisms. Ten compounds had Glide scores of ?8.2 to ?10.2, which revealed that introducing hydroxy, carbonyl, amino, or methyl ether groups into the alkyl side chain or addition of –F, –Cl, sulfonamide, benzamido, amino, or hydroxy substituents on the benzene ring could significantly increase binding affinity. Molecular docking studies revealed that zinc ion coordination, hydrogen bonding, and hydrophobic interactions contributed to the high calculated binding affinities of these compounds toward HDAC8. MD simulations and binding free energy studies showed that all complexes possessed good stability, as characterized by low RMSDs, low RMSFs of residues, moderate hydrogen bonding and zinc ion coordination and low values of binding free energies. Hie147, Tyr121, Phe175, Hip110, Phe119, Tyr273, Lys21, Gly118, Gln230, Leu122, Gly269, and Gly107 contributed favorably to the binding; and Van der Waals and electrostatic interactions provided major contributions to the stability of these complexes. These results show the potential of urushiol derivatives as HDAC8 binding lead compounds, which have great therapeutic potential in the treatment of various malignancies, neurological disorders, and human parasitic diseases.     

Site-directed targeting of plasminogen activator inhibitor-1 as an example for a novel approach in rational drug design

As plasminogen activator inhibitor-1 (PAI-1), the physiological inhibitor of tissue-type plasminogen activator, is considered to be an important risk factor in several (patho)physiological conditions, many research activities focus on attempts to inhibit this serpin. The approach illustrated in the current study focuses on elucidating important interaction sites allowing the inhibition of PAI-1. Since monoclonal antibodies are in most cases not ideal for therapeutic use, the question of whether smaller molecules exert comparable effects is a hot issue. To answer this question, Cys residues were introduced in PAI-1 at positions previously identified as determining the epitope of a PAI-1-inhibiting antibody, MA-8H9D4, resulting in PAI-1-R300C, PAI-1-Q303C, and PAI-1-D305C. Subsequently, low molecular mass sulfhydryl-specific reagents (i.e. BODIPY 530/550 IA (molecular mass 626 Da) and BODIPY FL C(1)-IA (molecular mass 417 Da)) were allowed to react covalently with the cysteine. The functional distribution (inhibitory versus substrate) toward tissue-type plasminogen activator was determined for the labeled and the unlabeled samples. Labeling at position 300 leads to a 1.7- and 2.2-fold increase in SI value for BODIPY 530/550 IA and BODIPY FL C(1)-IA, respectively. Labeling at position 303 results in a 3.3- and 1.9-fold increase of the SI value for the large and the small label, respectively. At position 305, the SI values are 3.1-fold increased for both labels. The effect (on SI and on serpin activity) of the manipulations at these positions is in good agreement with the effect exerted by MA-8H9D4. In conclusion, our study provides proof of concept for the proposed approach in evaluating whether targeting a functional epitope with a small synthetic compound may be a feasible strategy in rational drug design.     

Modeling the relationship between body weight and energy intake: A molecular diffusion-based approach

ABSTRACT: BACKGROUND: Body weight is at least partly controlled by the choices made by a human in response to external stimuli. Changes in body weight are mainly caused by energy intake. By analyzing the mechanisms involved in food intake, we considered that molecular diffusion plays an important role in body weight changes. We propose a model based on Fick's second law of diffusion to simulate the relationship between energy intake and body weight. RESULTS: This model was applied to food intake and body weight data recorded in humans; the model showed a good fit to the experimental data. This model was also effective in predicting future body weight. CONCLUSIONS: In conclusion, this model based on molecular diffusion provides a new insight into the body weight mechanisms.