Hunting for predictive computational drug-discovery models.
نویسنده
چکیده
The Keystone Symposium on Computer-Aided Drug Design was held at Steamboat Springs (CO, USA), from March 29th to the 3rd of April, 2008. The organizers brought together approximately 180 participants, representing a cross-section of viewpoints from academia and the pharmaceutical industry. Since it is a young discipline, it was a privilege to have a keynote introduction from one of the original pioneers of the field, Irwin Kuntz. By avoiding pitfalls, and addressing active debates, the young field can become more reliably predictive. Accordingly, this report focuses on best practices. As reliability improves, drug-discovery programs will increasingly use models to determine which high-throughput screens to run.
منابع مشابه
Comparative QSAR Analysis of 3,5-bis (Arylidene)-4-Piperidone Derivatives: the Development of Predictive Cytotoxicity Models
1-[4-(2-Alkylaminoethoxy)phenylcarbonyl]-3,5-bis(arylidene)-4-piperidones are a novel class of potent cytotoxic agents. These compounds demonstrate low micromolar to submicromolar IC50 values against human Molt 4/C8 and CEM T-lymphocytes and murine leukemia L1210 cells. In this study, a comparative QSAR investigation was performed on a series of 3,5-bis(arylidene)-4-piperidones using different ...
متن کاملApplying computational modeling to drug discovery and development.
Computational models of cells, tissues and organisms are necessary for increased understanding of biological systems. In particular, modeling approaches will be crucial for moving biology from a descriptive to a predictive science. Pharmaceutical companies identify molecular interventions that they predict will lead to therapies at the organism level, suggesting that computational biology can p...
متن کاملComparative QSAR Analysis of 3,5-bis (Arylidene)-4-Piperidone Derivatives: the Development of Predictive Cytotoxicity Models
1-[4-(2-Alkylaminoethoxy)phenylcarbonyl]-3,5-bis(arylidene)-4-piperidones are a novel class of potent cytotoxic agents. These compounds demonstrate low micromolar to submicromolar IC50 values against human Molt 4/C8 and CEM T-lymphocytes and murine leukemia L1210 cells. In this study, a comparative QSAR investigation was performed on a series of 3,5-bis(arylidene)-4-piperidones using different ...
متن کاملComputational quantum chemistry and adaptive ligand modeling in mechanistic QSAR.
Drugs are adaptive molecules. They realize this peculiarity by generating different ensembles of prototropic forms and conformers that depend on the environment. Among the impressive amount of available computational drug discovery technologies, quantitative structure-activity relationship approaches that rely on computational quantum chemistry descriptors are the most appropriate to model adap...
متن کاملLarge-scale ligand-based predictive modelling using support vector machines
The increasing size of datasets in drug discovery makes it challenging to build robust and accurate predictive models within a reasonable amount of time. In order to investigate the effect of dataset sizes on predictive performance and modelling time, ligand-based regression models were trained on open datasets of varying sizes of up to 1.2 million chemical structures. For modelling, two implem...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Expert review of anti-infective therapy
دوره 6 3 شماره
صفحات -
تاریخ انتشار 2008