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ModBase (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by ModPipe, an automated modeling pipeline that relies primarily on Modeller for fold assignment, sequence-structure alignment, model building and model assessment (http://salilab.org/modeller/). ModBase currently contains almost 30 million reliable models for domains in 4.7 million unique protein sequences. ModBase allows users to compute or update comparative models on demand, through an interface to the ModWeb modeling server (http://salilab.org/modweb). ModBase models are also available through the Protein Model Portal (http://www.proteinmodelportal.org/). Recently developed associated resources include the AllosMod server for modeling ligand-induced protein dynamics (http://salilab.org/allosmod), the AllosMod-FoXS server for predicting a structural ensemble that fits an SAXS profile (http://salilab.org/allosmod-foxs), the FoXSDock server for protein-protein docking filtered by an SAXS profile (http://salilab.org/foxsdock), the SAXS Merge server for automatic merging of SAXS profiles (http://salilab.org/saxsmerge) and the Pose & Rank server for scoring protein-ligand complexes (http://salilab.org/poseandrank). In this update, we also highlight two applications of ModBase: a PSI:Biology initiative to maximize the structural coverage of the human alpha-helical transmembrane proteome and a determination of structural determinants of human immunodeficiency virus-1 protease specificity.
Pubmed ID: 24271400 RIS Download
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View all literature mentionsThe Tropical Disease Initiative aims to provide a kernel for open source drug discovery. Such kernel should allow scientists from laboratories, universities, institutes, and corporations to work together for a common cause: find new drugs against tropical disieases such as Malaria or Tuberculosis. Computation plays an increasing role in biology. The convergence between computing and biology suggests that open source methods can be used to organize early phase drug discovery. We argue that a new approach, which we call open source drug discovery, would significantly reduce the cost of discovering, developing and manufacturing cures for tropical diseases. First, it would give hundreds of scientists a practical way to donate urgently needed manpower. Second, open source discoveries would not be patented, permitting sponsors to award development contracts to the company that offered the lowest bid. Finally, competition from generic drug makers would keep manufacturing prices at or near the cost of production, significantly accelerating drug development for the 500 million people who currently suffer from tropical diseases. The TDI was initiated by: Thomas Kepler - Duke University Marc A. Marti-Renom - Prince Felipe Research Center, Valencia, Spain Stephen Maurer - University of California, Berkeley Arti Rai - Duke University Andrej Sali- University of California, San Francisco
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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