Molecular modeling study of diltiazem mimics at L-type calcium channels

The inhibition of experimentally induced visceral hyperalgesia by nifedipine - a voltage-gated Ca(2+) channels blocker (VGCCs) in sheep

Present study examined the effect of VGCC L-type blocker - nifedipine given i.c.v. (0.25, 0.5, 1 and/or 2mg in toto) on the development of nociceptive behavior, clinical symptoms, plasma catecholamin concentration and reticulo-rumen motility following 5 min lasting mechanical duodenal distension (DD) in sheep. After 24h of fasting, all animals received i.m. ketamine analgesia (20 mg kg(-1)B.W) and anesthetized with pentobarbital (20 mg kg(-1)B.W., i.v. infusion) The permanent stainless steel cannula 29 mm in length and 2mm in diameter was inserted into the lateral cerebral ventricle (controlled by cerebro-spinal efflux) 10mm above the bregma and 5mm laterally from the midline sutures using stereotaxic method. Under the same general anesthesia/analgesia a T-shaped silicon cannula (inside diameter of 21 mm), was inserted into the duodenum (12 cm from pylorus). Second identical cannule was inserted into the dorsal sac of the rumen, a previously described. After surgery each animal was kept in individual boxes for 10 days prior to experiment and was treated i.m. with benzyl procaine penicillin 30,000 I.U kg(-1)B.W.)+dihydrostreptomycine sulfate (10 g kg(-1)B.W.)+prednisolone acetate (1.2 mg kg(-1)B.W.) combination and i.m. ketamine (20 mg kg(-1)B.W.) every day by seven consecutive days. Experimental DD was conducted by insertion and then distension of rubber balloon (containing 40 ml of warm water) inserted into sheep duodenum. Duodenal distension produced a significant increase in behavioral pain manifestations, tachycardia, hyperventilation, inhibition of reticulo-ruminal contractions rate (from 87.2 to 38.0% during 15-20 min), an increase of plasma catecholamine concentration (over 6.4-fold increase of epinephrine during 2h following DD, 2-times norepinephrine and 84% increase of dopamine). Nifedipine infusion administered 10 min prior to DD decreased intensity of visceral pain manifestations such as: behavioral changes, hyperventilation, reticulo-rumen motility and efficiently prevent appearance of catecholamine release. These data demonstrated that the development and persistence of duodenal hyperalgesia depends on the activation of Ca(2+) ion flux leading to neurotransmitters release and modulation of membrane excitability. It seems that nifedipine given i.c.v. 10 min prior to DD (as a source of visceral pain), inhibited specific receptors 1 subunits of VGCCs in target tissues, prevented depolarization of cell membranes and release of neurotransmitters responsible for pain sensitivity in sheep. The observed antinociceptive action of VGCCs type L blockers suggest that these channels play a crucial role in the modulation of acute visceral hyperalgesia in sheep.

PROFEAT: a web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence

Sequence-derived structural and physicochemical features have frequently been used in the development of statistical learning models for predicting proteins and peptides of different structural, functional and interaction profiles. PROFEAT (Protein Features) is a web server for computing commonly-used structural and physicochemical features of proteins and peptides from amino acid sequence. It computes six feature groups composed of ten features that include 51 descriptors and 1447 descriptor values. The computed features include amino acid composition, dipeptide composition, normalized Moreau-Broto autocorrelation, Moran autocorrelation, Geary autocorrelation, sequence-order-coupling number, quasi-sequence-order descriptors and the composition, transition and distribution of various structural and physicochemical properties. In addition, it can also compute previous autocorrelations descriptors based on user-defined properties. Our computational algorithms were extensively tested and the computed protein features have been used in a number of published works for predicting proteins of functional classes, protein-protein interactions and MHC-binding peptides. PROFEAT is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/prof/prof.cgi.

Prediction of transporter family from protein sequence by support vector machine approach

Transporters play key roles in cellular transport and metabolic processes, and in facilitating drug delivery and excretion. These proteins are classified into families based on the transporter classification (TC) system. Determination of the TC family of transporters facilitates the study of their cellular and pharmacological functions. Methods for predicting TC family without sequence alignments or clustering are particularly useful for studying novel transporters whose function cannot be determined by sequence similarity. This work explores the use of a machine learning method, support vector machines (SVMs), for predicting the family of transporters from their sequence without the use of sequence similarity. A total of 10,636 transporters in 13 TC subclasses, 1914 transporters in eight TC families, and 168,341 nontransporter proteins are used to train and test the SVM prediction system. Testing results by using a separate set of 4351 transporters and 83,151 nontransporter proteins show that the overall accuracy for predicting members of these TC subclasses and families is 83.4% and 88.0%, respectively, and that of nonmembers is 99.3% and 96.6%, respectively. The accuracies for predicting members and nonmembers of individual TC subclasses are in the range of 70.7-96.1% and 97.6-99.9%, respectively, and those of individual TC families are in the range of 60.6-97.1% and 91.5-99.4%, respectively. A further test by using 26,139 transmembrane proteins outside each of the 13 TC subclasses shows that 90.4-99.6% of these are correctly predicted. Our study suggests that the SVM is potentially useful for facilitating functional study of transporters irrespective of sequence similarity.

Pharmacophore modelling of structurally unusual diltiazem mimics at L-type calcium channels

The purpose of this theoretical study was to investigate the molecular features of some structurally unusual calcium antagonists with experimentally proved affinity to the diltiazem-binding site at L-type calcium channels. Therefore, sterical and electronic characteristics of cis-/trans-diclofurime, the verapamil-like derivatives McN-5691 and McN-6186 as well as the natural products papaverine, laudanosine, antioquine and tetrandrine were compared with the pharmacophoric requirements detected for classical diltiazem-like derivatives. This yielded a common pharmacophore model for all of these compounds. Based on this model, one single negative molecular electrostatic potential induced by the free electron pairs of the oxime oxygen of trans-diclofurime was detected that might be responsible for the stronger effects compared to the cis isomer. Furthermore, the dual diltiazem- and verapamil-like features of McN-5691 (and McN-6186) as well as the distinct pharmacophoric assignment of the laudanosine enantiomers may be interpreted on a molecular level. Finally, the crucial partial structure of the bis-benzylisoquinoline derivatives antioquine and tetrandrine being responsible for the calcium antagonistic effects could be revealed by superposition on the most active benzothiazepinone derivative 8-methoxydiltiazem. The results obtained for these unusual diltiazem mimics are discussed taking into consideration earlier findings for classical diltiazem-like derivatives.