CANDO and the infinite drug discovery frontier.

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 'high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

[1]  Kunal Roy,et al.  How far can virtual screening take us in drug discovery? , 2013, Expert opinion on drug discovery.

[2]  Rui Gan,et al.  Cell-free protein synthesis: applications come of age. , 2012, Biotechnology advances.

[3]  M. Qureshi,et al.  Prostate Cancer and Immunoproteome: Awakening and Reprogramming the Guardian Angels , 2012, Archivum Immunologiae et Therapiae Experimentalis.

[4]  S. Pestka,et al.  The interferon gamma (IFN-γ) receptor: a paradigm for the multichain cytokine receptor , 1997 .

[5]  W Patrick Walters,et al.  A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance , 2004, Proteins.

[6]  Tapesh Santra,et al.  Integrating Bayesian variable selection with Modular Response Analysis to infer biochemical network topology , 2013, BMC Systems Biology.

[7]  Jürgen Bajorath,et al.  Virtual compound screening in drug discovery. , 2012, Future medicinal chemistry.

[8]  Ram Samudrala,et al.  Prediction and integration of regulatory and protein-protein interactions. , 2009, Methods in molecular biology.

[9]  Michael Gross Riding the wave of biological data , 2011, Current Biology.

[10]  R. Samudrala,et al.  Caries induced cytokine network in the odontoblast layer of human teeth , 2011, BMC Immunology.

[11]  Y. Lussier,et al.  The Emergence of Genome-Based Drug Repositioning , 2011, Science Translational Medicine.

[12]  C. J. Murray,et al.  Microscale to Manufacturing Scale-up of Cell-Free Cytokine Production—A New Approach for Shortening Protein Production Development Timelines , 2011, Biotechnology and bioengineering.

[13]  Gregory D. Schuler,et al.  Database resources of the National Center for Biotechnology Information: update , 2004, Nucleic acids research.

[14]  Alexander A. Morgan,et al.  Compendia of Public Gene Expression Data Discovery and Preclinical Validation of Drug Indications Using , 2011 .

[15]  Marco G. Casteleijn,et al.  Expression without boundaries: cell-free protein synthesis in pharmaceutical research. , 2013, International journal of pharmaceutics.

[16]  R. Samudrala,et al.  The Promise and Challenge of Digital Biology , 2013, Journal of bioengineering & biomedical science.

[17]  Brian K Shoichet,et al.  Structure-based drug screening for G-protein-coupled receptors. , 2012, Trends in pharmacological sciences.

[18]  L. Ivashkiv,et al.  Glucocorticoid modulation of cytokine signaling. , 2006, Tissue antigens.

[19]  R. Samudrala,et al.  Heptad-Repeat-2 Mutations Enhance the Stability of the Enfuvirtide-Resistant HIV-1 gp41 Hairpin Structure , 2005, Antiviral therapy.

[20]  Ram Samudrala,et al.  Identification of potential multitarget antimalarial drugs. , 2005, JAMA.

[21]  Marino Zerial,et al.  A decade of molecular cell biology: achievements and challenges , 2011, Nature Reviews Molecular Cell Biology.

[22]  Ram Samudrala,et al.  Computational Multitarget Drug Discovery , 2012 .

[23]  Volker Stadler,et al.  Sensing Immune Responses with Customized Peptide Microarrays , 2012, Biointerphases.

[24]  Alexander A. Morgan,et al.  Discovery and Preclinical Validation of Drug Indications Using Compendia of Public Gene Expression Data , 2011, Science Translational Medicine.

[25]  J. Scannell,et al.  Diagnosing the decline in pharmaceutical R&D efficiency , 2012, Nature Reviews Drug Discovery.

[26]  C. Glass,et al.  Nuclear receptor transrepression pathways that regulate inflammation in macrophages and T cells , 2010, Nature Reviews Immunology.

[27]  Anthony Atala,et al.  Regenerative medicine strategies. , 2012, Journal of pediatric surgery.

[28]  Niklas Sandler,et al.  Printing technologies in fabrication of drug delivery systems , 2013, Expert opinion on drug delivery.

[29]  Jonathan R. Karr,et al.  A Whole-Cell Computational Model Predicts Phenotype from Genotype , 2012, Cell.

[30]  Marcy J. Balunas,et al.  Drug discovery from medicinal plants. , 2005, Life sciences.

[31]  Jong Hwan Sung,et al.  Organ‐on‐a‐chip technology and microfluidic whole‐body models for pharmacokinetic drug toxicity screening , 2013, Biotechnology journal.

[32]  Ram Samudrala,et al.  Novel paradigms for drug discovery: computational multitarget screening. , 2008, Trends in pharmacological sciences.

[33]  Hod Lipson,et al.  Fabricated: The New World of 3D Printing , 2013 .

[34]  Maria F. Sassano,et al.  Automated design of ligands to polypharmacological profiles , 2012, Nature.

[35]  Masaru Tomita,et al.  Toward large-scale modeling of the microbial cell for computer simulation. , 2004, Journal of biotechnology.

[36]  Michael C Schatz,et al.  Computational thinking in the era of big data biology , 2012, Genome Biology.

[37]  Raymond S H Yang,et al.  BioMOL: a computer-assisted biological modeling tool for complex chemical mixtures and biological processes at the molecular level. , 2002, Environmental health perspectives.

[38]  R. Samudrala,et al.  Virtual screening of HIV-1 protease inhibitors against human cytomegalovirus protease using docking and molecular dynamics , 2005, AIDS.

[39]  Ram Samudrala,et al.  A generalized knowledge‐based discriminatory function for biomolecular interactions , 2009, Proteins.

[40]  Bruce Ratner,et al.  Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data , 2011 .

[41]  I. Rogatsky,et al.  Minireview: Glucocorticoids in autoimmunity: unexpected targets and mechanisms. , 2011, Molecular endocrinology.

[42]  Sarah L. Kinnings,et al.  Novel computational approaches to polypharmacology as a means to define responses to individual drugs. , 2012, Annual review of pharmacology and toxicology.

[43]  Cheng Luo,et al.  Computational drug discovery , 2012, Acta Pharmacologica Sinica.

[44]  Ian A. Watson,et al.  Selectivity data: assessment, predictions, concordance, and implications. , 2013, Journal of medicinal chemistry.

[45]  Vladimir Mironov,et al.  Organ printing: from bioprinter to organ biofabrication line. , 2011, Current opinion in biotechnology.

[46]  H. Andresen,et al.  SPOT synthesis as a tool to study protein-protein interactions. , 2011, Methods in molecular biology.

[47]  Markus Lill,et al.  Virtual screening in drug design. , 2013, Methods in molecular biology.

[48]  Ram Samudrala,et al.  PIRSpred: a web server for reliable HIV-1 protein-inhibitor resistance/susceptibility prediction. , 2005, Trends in microbiology.

[49]  Arthur J. Olson,et al.  AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading , 2009, J. Comput. Chem..

[50]  Ram Samudrala,et al.  Identification of potential HIV-1 targets of minocycline , 2007, Bioinform..

[51]  Jiajie Yu,et al.  Microscale 3-D hydrogel scaffold for biomimetic gastrointestinal (GI) tract model. , 2011, Lab on a chip.

[52]  K. Sanders,et al.  G Protein-coupled Receptors in Gastrointestinal Physiology Iv. Neural Regulation of Gastrointestinal Smooth Muscle Structural Features of G Protein-coupled Receptors * Fourth in a Series of Invited Articles on G Protein-coupled Receptors in Gastrointestinal Physiology , 2022 .

[53]  Masaru Tomita,et al.  E-CELL: software environment for whole-cell simulation , 1999, Bioinform..

[54]  J. Cidlowski,et al.  Characterization of mechanisms involved in transrepression of NF-kappa B by activated glucocorticoid receptors , 1995, Molecular and cellular biology.

[55]  Paola Lecca,et al.  Methods of biological network inference for reverse engineering cancer chemoresistance mechanisms. , 2014, Drug discovery today.

[56]  S Pestka,et al.  The interferon gamma (IFN-gamma) receptor: a paradigm for the multichain cytokine receptor. , 1997, Cytokine & growth factor reviews.

[57]  S. Vilar,et al.  High-Throughput Methods for Combinatorial Drug Discovery , 2013, Science Translational Medicine.

[58]  R. Samudrala,et al.  Inferring molecular interactions pathways from eQTL data. , 2009, Methods in molecular biology.

[59]  J. W. Ward,et al.  Sequence-Specific Peptide Synthesis by an Artificial Small-Molecule Machine , 2013, Science.

[60]  R. Frank The SPOT-synthesis technique. Synthetic peptide arrays on membrane supports--principles and applications. , 2002, Journal of immunological methods.

[61]  Ali Khademhosseini,et al.  Biomimetic tissues on a chip for drug discovery. , 2012, Drug discovery today.

[62]  Michael Y. Galperin,et al.  The 2014 Nucleic Acids Research Database Issue and an updated NAR online Molecular Biology Database Collection , 2013, Nucleic Acids Res..

[63]  A. Manz,et al.  Revisiting lab-on-a-chip technology for drug discovery , 2012, Nature Reviews Drug Discovery.

[64]  M. Kutateladze,et al.  Bacteriophages as potential new therapeutics to replace or supplement antibiotics. , 2010, Trends in biotechnology.

[65]  Ssang-Goo Cho,et al.  Differentiation and transplantation of functional pancreatic beta cells generated from induced pluripotent stem cells derived from a type 1 diabetes mouse model. , 2012, Stem cells and development.

[66]  Suzanne C Brewerton,et al.  The use of protein-ligand interaction fingerprints in docking. , 2008, Current opinion in drug discovery & development.

[67]  Elizabeth Yuriev,et al.  Latest developments in molecular docking: 2010–2011 in review , 2013, Journal of molecular recognition : JMR.

[68]  Ram Samudrala,et al.  Identifying inhibitors of the SARS coronavirus proteinase , 2003, Bioorganic & Medicinal Chemistry Letters.

[69]  Stuart Kauffman,et al.  How to escape the cancer attractor: rationale and limitations of multi-target drugs. , 2013, Seminars in cancer biology.

[70]  R. Lahita,et al.  Pragmatic approaches to therapy for systemic lupus erythematosus , 2014, Nature Reviews Rheumatology.

[71]  I. Ursan,et al.  Three-dimensional drug printing: a structured review. , 2013, Journal of the American Pharmacists Association : JAPhA.

[72]  Ram Samudrala,et al.  Prediction of HIV-1 Protease Inhibitor Resistance using a Protein–Inhibitor Flexible Docking Approach , 2005, Antiviral therapy.

[73]  Alexander A. Morgan,et al.  Supplementary Materials for Computational Repositioning of the Anticonvulsant Topiramate for Inflammatory Bowel Disease , 2011 .

[74]  Alan Faulkner-Jones,et al.  Development of a valve-based cell printer for the formation of human embryonic stem cell spheroid aggregates , 2013, Biofabrication.

[75]  R. Pink,et al.  Opportunities and Challenges in Antiparasitic Drug Discovery , 2005, Nature Reviews Drug Discovery.

[76]  A Lavecchia,et al.  Virtual screening strategies in drug discovery: a critical review. , 2013, Current medicinal chemistry.

[77]  Ram Samudrala,et al.  Rappertk: a versatile engine for discrete restraint-based conformational sampling of macromolecules , 2007, BMC Structural Biology.

[78]  Márcia M. Almeida-de-Macedo,et al.  A global approach to analysis and interpretation of metabolic data for plant natural product discovery. , 2013, Natural product reports.

[79]  Sara Reardon,et al.  Project ranks billions of drug interactions , 2013, Nature.

[80]  Alexander A. Morgan,et al.  Computational Repositioning of the Anticonvulsant Topiramate for Inflammatory Bowel Disease , 2011, Science Translational Medicine.

[81]  K. Hilpert,et al.  Synthesis of antimicrobial peptides using the SPOT technique. , 2010, Methods in molecular biology.