Lead molecules identified by combinatorial chemistry approaches are preferred starting points for straightforward improvements of compound profiles. Structure-guided rationales can be supported and complemented by systematic variations based on the modular nature of the molecules. A peptoidic compound (CGP 64222), previously identified from a sequential unrandomization process, was shown to specifically inhibit the interaction between the HIV-1 trans-activator Tat and its RNA response element TAR. To improve the compound's pharmaceutical attractiveness an approach to reduce both, size and number of charges was pursued. Because this resulted in activity decrease, parallel synthesis with variations on one rationally defined position aimed at the identification of structural determinants was undertaken to regain in vitro activity in biochemical and cellular Tat-TAR interaction assays. As a result CGP74026 was identified, a drastically simplified but highly active Tat antagonist, which is able to block HIV-1 replication even in primary human cells.

Acridines↗

PubMedDate not supplied

Duplication of the blood glucose curve of an OGTT in dogs by a prospectively programmed I.V. infusion: infusion pattern and IRI response.

In conscious dogs the peripheral venous blood glucose profile of an OGTT (1.0 g/kg) was individually duplicated by a computed i.v. glucose infusion. The correspondence reached between both tests was demonstrated by the correlation between the paired increments of the reactive blood glucose concentration areas. The average total dose needed for duplication was 0.52 +/-0.04 g/kg (no. = 11). There was a more rapid and greater IRI increase in OGTT than in the infusion test. When 1.0 g glucose per kg was given according to the same pattern by a computed infusion, the integrated areas both of blood glucose and of IRI was twice that in OGTT. We concluded that the IRI increase in OGTT reinforced by enteral mechanisms favors the direct hepatic uptake of absorbed glucose. This could also protect the body from an excessive insulin release provoked by the entire oral load if it reached the peripheral circulation.

Administration, Oral↗

PubMedDate not supplied

Computer-aided systems in the management of type I diabetes: the application of a model-based strategy.

One approach of improving metabolic control in type I diabetic patients is the application of computer-aided procedures aimed at supporting the decision on optimal therapeutic regimens. To accomplish this, a complex strategy was developed which in an individual patient permits (1) the evaluation of metabolic data by means of statistical and graphical methods, and (2) the prediction of the outcome in feedback and in non-feedback-controlled insulin therapy. The latter is realized by means of simulation, employing a structured model of the glucose-insulin control system where the model parameters can either be identified individually or be taken at random. The practical applicability was validated in C-peptide-negative type I diabetic patients who were on intensified insulin injection therapy. The comparison between theoretical predictions and daily glycaemic profiles measured by the patients under ambulatory conditions showed close correspondence which justifies the application of this method as a clinical decision support.

Blood Glucose↗

PubMedDate not supplied

Experimental validation of a glucose-insulin control model to stimulate patterns in glucose turnover.

To verify a structured model of the glucose-insulin system, metabolic measurements were compared with model-based simulations in insulin-dependent diabetic dogs which had been previously identified in terms of model parameters. Glycaemia, glucosuria, plasma insulin, and the rates of appearance Ra and disappearance Rd of glucose (kinetics of double-labelled glucose, evaluated according to Steele's equation in its non-steady-state version) were observed under the following conditions, starting from normoglycaemia during glucose-controlled insulin infusion (GCII): (I) insulin withdrawal, (II) insulin withdrawal and glucose infusion, (III) constant i.v. infusion of glucose and insulin, (IV) glucose infusion during GCII. After fitting the patterns of glycaemia, simulations of the other state variables were accomplished, employing the individual model parameters, the preset experimental inputs, and the GCII control constants (test IV only). Under nearly all conditions, correspondence was excellent between measured and simulated data. There were, however, the following exceptions: incomplete representation by the model of kinetics in glucose utilisation after interruption of insulin supply, overestimation of glucosuria by the model in the presence of insulin. It is concluded that the model provides a reasonable representation of metabolic processes which are of importance in the treatment of insulin-dependent diabetes mellitus and that it might thus appropriately simulate the outcome of metabolic regimens.

Absorption↗