Open Source Drug Discovery with the Malaria Box Compound Collection for Neglected Diseases and Beyond (original) (raw)
Related papers
The Open Access Malaria Box: A Drug Discovery Catalyst for Neglected Diseases
PLoS ONE, 2013
Historically, one of the key problems in neglected disease drug discovery has been identifying new and interesting chemotypes. Phenotypic screening of the malaria parasite, Plasmodium falciparum has yielded almost 30,000 submicromolar hits in recent years. To make this collection more accessible, a collection of 400 chemotypes has been assembled, termed the Malaria Box. Half of these compounds were selected based on their drug-like properties and the others as molecular probes. These can now be requested as a pharmacological test set by malaria biologists, but importantly by groups working on related parasites, as part of a program to make both data and compounds readily available. In this paper, the analysis and selection methodology and characteristics of the compounds are described.
Drug discovery for malaria: a very challenging and timely endeavor
The prevalence of resistance to known antimalarial drugs has resulted in the expansion of antimalarial drug discovery efforts. Academic and nonprofit institutions are partnering with the pharmaceutical industry to develop new antimalarial drugs. Several new antimalarial agents are undergoing clinical trials, mainly those resurrected from previous antimalarial drug discovery programs. Novel antimalarials are being advanced through the drug development process, of course, with the anticipated high failure rate typical of drug discovery. Many of these are summarized in this review. Mechanisms for funding antimalarial drug discovery and genomic information to aid drug target selection have never been better. It remains to be seen whether ongoing efforts will be sufficient for reducing malaria burden in the developing world.
Malaria Journal, 2010
Despite increasing efforts and support for anti-malarial drug R&D, globally anti-malarial drug discovery and development remains largely uncoordinated and fragmented. The current window of opportunity for large scale funding of R&D into malaria is likely to narrow in the coming decade due to a contraction in available resources caused by the current economic difficulties and new priorities (e.g. climate change). It is, therefore, essential that stakeholders are given well-articulated action plans and priorities to guide judgments on where resources can be best targeted. The CRIMALDDI Consortium (a European Union funded initiative) has been set up to develop, through a process of stakeholder and expert consultations, such priorities and recommendations to address them. It is hoped that the recommendations will help to guide the priorities of the European anti-malarial research as well as the wider global discovery agenda in the coming decade.
A Kernel for Open Source Drug Discovery in Tropical Diseases
PLoS Neglected Tropical Diseases, 2009
Background: Conventional patent-based drug development incentives work badly for the developing world, where commercial markets are usually small to non-existent. For this reason, the past decade has seen extensive experimentation with alternative R&D institutions ranging from private-public partnerships to development prizes. Despite extensive discussion, however, one of the most promising avenues-open source drug discovery-has remained elusive. We argue that the stumbling block has been the absence of a critical mass of preexisting work that volunteers can improve through a series of granular contributions. Historically, open source software collaborations have almost never succeeded without such ''kernels''.
Malaria Journal, 2006
The organization and mining of malaria genomic and post-genomic data is important to significantly increase the knowledge of the biology of its causative agents, and is motivated, on a longer term, by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should, therefore, be as reliable and versatile as possible. In this context, five aspects of the organization and mining of malaria genomic and post-genomic data were examined: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes, particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5) the determination and prediction of protein structures and their molecular docking with drug candidate structures. Recent progress towards a grid-enabled chemogenomic knowledge space is discussed.