new liberty proteomics/alion pharmaceuticals Collaboration announcement
New Liberty Proteomics is pleased and proud to announce its collaboration with Alion Pharmaceuticals. NLP joins companies such as LamdaGen and Knowledge Synthesis in Alion’s pursuit of novel therapeutics for Alzheimer’s and Parkinson’s diseases. RAPTOR, RAVEN and Reverse Screening, New Liberty’s game-changing protein interaction and degradation technologies, will provide key evaluation input for Alion’s multi-factorial, multi-target programs.
"Action, events, Movement." the essentials of biology
"Life is a relationship between molecules, not a property of any one molecule. So is therefore disease, which endangers life."* In isolation, proteins, DNA, RNA, phospholipids, metabolites, trace minerals and even water and table salt are simply things. In composite, extracellular proteins bind to transmembrane receptors triggering multiple binding and digestion events that, in turn, initiate nuclear events that govern genetic activity. Or inhibit cell growth. Or initiate metabolism. Or defend against pathogens. Or become thoughts. Or . . . and the list goes on. A galaxy’s worth of actors engaged in a universe’s worth of actions, events and movement.
Successful drugs modulate protein interactions, whether the interactions are with other proteins, DNA/RNA, cells or small molecules. In turn, those interactions often initiate chemical reactions, such as protein degradation. Modulation of protein interactions by a drug must, then, be the minimal screening for drug activity at a molecular level.
Action, Events, and Movement encompass health and disease, and are the natural context for drug evaluation. The potential payoff of a more rigorous evaluation of drug candidates in drug discovery is enormous. Unfortunately, real time assessment of events in bio-complex systems is beyond the scope of most analytical methods. New Liberty Proteomics brings two, transformative capabilities into the arena: the ability to assess protein-anything interactions (RAPTOR) and assess protein degradation (RAVEN) in real time and under conditions of any bio-relevant complexity. Reflecting the overwhelming majority of biological activity, protein interactions and degradation comprise a general framework for biological research, disease characterization and that most fundamental evaluation in drug discovery: Gauging the Impact of Drugs on Biological Activity.
No other evaluation suffices.
Successful drugs modulate protein interactions, whether the interactions are with other proteins, DNA/RNA, cells or small molecules. In turn, those interactions often initiate chemical reactions, such as protein degradation. Modulation of protein interactions by a drug must, then, be the minimal screening for drug activity at a molecular level.
Action, Events, and Movement encompass health and disease, and are the natural context for drug evaluation. The potential payoff of a more rigorous evaluation of drug candidates in drug discovery is enormous. Unfortunately, real time assessment of events in bio-complex systems is beyond the scope of most analytical methods. New Liberty Proteomics brings two, transformative capabilities into the arena: the ability to assess protein-anything interactions (RAPTOR) and assess protein degradation (RAVEN) in real time and under conditions of any bio-relevant complexity. Reflecting the overwhelming majority of biological activity, protein interactions and degradation comprise a general framework for biological research, disease characterization and that most fundamental evaluation in drug discovery: Gauging the Impact of Drugs on Biological Activity.
No other evaluation suffices.
drug discovery paradigms: too little action, too much action
target-based drug discovery
Far and away, the dominant paradigm in drug discovery is Target-based Drug Discovery or TDD. In its minimalist reflection of biological activity, TDD is best described as reductio ad absurdum – reduced to the point of absurdity. TDD relies wholly on a priori identification of a drug “target,” usually a single protein identified by a genetic mutation. TDD then focuses on designing or selecting a molecule to attach to the target. Binding of the drug candidate to the target is the key test of target-based discovery: a test that includes one biological entity and no biological events. TDD, therefore, restricts its view to a single, possibly irrelevant action of the drug. The paradigm’s fortunes are not helped by the recent discovery that two out of three target identification studies, the bedrock of the paradigm, cannot be repeated. Whoops. Is it a surprise that the dramatic decline in pharma industry R&D perfectly tracks the increasing dominance of TDD? Nonetheless, target-based discovery can be fixed.
phenotypic or disease-centric drug discovery
At the other extreme, phenotypic drug discovery (PDD) screens for drug candidates in animals or cell lines. The choice of animal or cell line is crucial in that it must manifest disease in an analogous manner to that in humans. Assuming that the choice is appropriate, PDD screening has the enormous advantage of selecting drug candidates that ameliorate the disease. For this reason, PDD is sometimes called Disease-Centric drug discovery or DCDD. By whatever name, the paradigm is far more effective in selecting drug candidates that succeed in the clinic. Its shortcoming is that the screening process samples too much biological activity. Even within a single cell there are millions of potential protein interactions and PDD/DCDD screening points in no particular molecular direction. This failing, if such it should be termed, does not allow for precise redesign of the drug to achieve improved performance, nor does it allow for development of biomarkers or other tools required for precision medicine or patient stratification. PDD can be augmented to address these issues.
Despite the enormous differences in concept and practice, both target-based and disease-centric approaches demand further evaluation of the drug candidate’s performance under controlled, bio-relevant conditions. New Liberty Proteomics’ RAPTOR and RAVEN are perfect tools for the job. For TDD, confirmation of the drug candidate’s ability to modulate protein interactions (or degradation) boosts the value of and confidence in the candidate. Subsequent studies can evaluate the candidate’s activity in increasingly complex systems, validating both the desired effect along with elucidating non-target candidate interactions. For PDD/DCDD New Liberty’s methods and approaches are ideal for identifying the candidate’s actions at a molecular level.
Despite the enormous differences in concept and practice, both target-based and disease-centric approaches demand further evaluation of the drug candidate’s performance under controlled, bio-relevant conditions. New Liberty Proteomics’ RAPTOR and RAVEN are perfect tools for the job. For TDD, confirmation of the drug candidate’s ability to modulate protein interactions (or degradation) boosts the value of and confidence in the candidate. Subsequent studies can evaluate the candidate’s activity in increasingly complex systems, validating both the desired effect along with elucidating non-target candidate interactions. For PDD/DCDD New Liberty’s methods and approaches are ideal for identifying the candidate’s actions at a molecular level.
methods that don't measure up
Methods that directly assess fundamental biological events as they occur are few and far between. For measurement of protein-protein interactions (PPI), recent work has demonstrated that no traditional methods suffice. In a head-to-head comparison of popular PPI methods on 92 known interactions, the best performer detected only 36% of the interactions, the worst detected only 21%. In other words, popular methods (including multiple “affinity/pull down” methods and yeast two-hybrid) have false negative rates of 64-79%. Ouch. Making the situation even worse, there was very little overlap between the methods, virtually eliminating confirmation of an interaction by use of “orthogonal” methods. Therefore, even should a conscientious investigator attempt to fully assess the impact of a drug candidate on key events, reliable tools have simply not been available. Few are aware of this shortcoming of a key analytical area, and that lack of awareness no doubt has produced many drug failures in the clinic.
For protein degradation/proteolysis, the problems with traditional methods are subtler though no less troubling. Most proteolysis analysis takes one of two forms: the use of small molecules as surrogates for whole proteins, or interruption of proteolysis followed by fractionation and product identification. The use of small-molecule, “unnatural” surrogates can, at best, only point to a single possible degradation event out of hundreds possible in a complex bio-relevant system. At worst the measurement is simply irrelevant. Doubtless many thousands of crucial signaling and control events have simply been missed. Interrupting proteolysis in complex systems is difficult, and full interruption at a specific point in time is virtually impossible to confirm. The resulting mixture of reactants and products is extremely difficult to analyze and the process is both time-consuming and expensive. Neither attribute lends itself to assessment of drug candidate behavior.
For protein degradation/proteolysis, the problems with traditional methods are subtler though no less troubling. Most proteolysis analysis takes one of two forms: the use of small molecules as surrogates for whole proteins, or interruption of proteolysis followed by fractionation and product identification. The use of small-molecule, “unnatural” surrogates can, at best, only point to a single possible degradation event out of hundreds possible in a complex bio-relevant system. At worst the measurement is simply irrelevant. Doubtless many thousands of crucial signaling and control events have simply been missed. Interrupting proteolysis in complex systems is difficult, and full interruption at a specific point in time is virtually impossible to confirm. The resulting mixture of reactants and products is extremely difficult to analyze and the process is both time-consuming and expensive. Neither attribute lends itself to assessment of drug candidate behavior.
real time assessment of protein interaction and degradation
RAPTOR: Any protein that binds to another protein, polynucleotide or cell surface must slow down.
Period.
RAVEN: Digestion of proteins must produce products that move faster.
Period.
Period.
RAVEN: Digestion of proteins must produce products that move faster.
Period.
Both RAPTOR and RAVEN assess changes in angular mobility that must accompany protein binding and protein degradation. Protein interactions and degradation are literally “seen,” in situ and without qualification. The range of RAPTOR and RAVEN – from molecular weight equivalents of 200 Dalton to 2 MegaDalton – insures application for essentially the whole population of biological molecules. Measurements are made in real time on intact, bioactive systems regardless of whether samples are transparent or opaque. Therefore, a single measurement technology suffices for all relevant testing conditions from simple molecular systems to lysates/homogenates and even intact cells or tissues. Flexibility in experimental design permits each interaction partner to act as a reporter in turn, effectively providing an “orthogonal” confirmation with a single approach.
RAPTOR and RAVEN exploit the dependence of EMR spectra (electron magnetic resonance spectroscopy, aka EPR and ESR) of spin labels on angular mobility. Actual spectra from in-house work and patent filings are presented throughout this website. Highlights include observation of protease interaction with whole-protein substrate as the substrate is digested, and promotion of proteolysis by a drug approved as a protease inhibitor for treatment of HIV and cancer!
RAPTOR and RAVEN are game changers.
RAPTOR and RAVEN exploit the dependence of EMR spectra (electron magnetic resonance spectroscopy, aka EPR and ESR) of spin labels on angular mobility. Actual spectra from in-house work and patent filings are presented throughout this website. Highlights include observation of protease interaction with whole-protein substrate as the substrate is digested, and promotion of proteolysis by a drug approved as a protease inhibitor for treatment of HIV and cancer!
RAPTOR and RAVEN are game changers.
reverse screening: multi-target, multi-factorial, multi-drug,
multi-moa
Click for larger image.
Regardless of the selection process for a drug candidate – target-based or disease-centric – the venue for further vetting the candidate must be biology itself. The impact of the drug on biological activity constitutes the only meaningful criteria for advancing the candidate. This truism is the fundamental basis for New Liberty Proteomics’ Reverse Screening drug evaluation approach.
RAPTOR and RAVEN uniquely allow the complexity of the test media to range from a few molecular species to the thousands present in, e.g., a lysate. Samples remain intact as protein interactions or protein degradation are detected and quantified. No separations, no washes, no affinity agents, no fused proteins, no tinker-toy replacements for whole biomolecules. Reverse Screening exploits this extraordinary and unique flexibility. Through a carefully orchestrated battery of observations, competition for the drug among diverse biological entities may be evaluated.
Assume, for example, that the drug candidate is shown to inhibit binding of Factor A, a soluble protein, to Factor A Receptor, a transmembrane protein. Now the fun starts! The drug candidate’s other activities can be determined by observing perturbation in this inhibition. Consider a second, simple test: addition of another bio-relevant entity (BE) such as another protein or polynucleotide. Two outcomes are possible: BE does not alter the drug’s inhibition of Factor A/ Receptor OR BE does alter the inhibition of Factor A/ Receptor. If BE has no effect on the drug’s behavior then the drug has no apparent interaction with BE. If BE does effect the drug’s ability to inhibit binding, then interaction of the drug and BE is likely. In effect, modulation of the drug’s modulation of a single bio-event signals the drug’s interactions with any range of biomolecules or structures. Taken to its logical conclusion, Reverse Screening traces out all possible interactions of the drug, the Drug Interactome.
The power inherent in Reverse Screening, made possible only by the incredible flexibility of RAPTOR and RAVEN, is enormous and unprecedented. Target confirmation, determination of MOA, off-target interactions and even anticipation of side effects and toxicity become practical goals. Reverse Screening is also amenable to multi-factorial, multi-MOA, multi-drug testing. On a more routine scale, detection of drug interactions with unwanted or unexpected bio-entities can provide feedback for drug redesign or selection of an alternate candidate. Even dosing and delivery considerations should be forthcoming. Perhaps most importantly, a candidate that passes the test of NLP’s Reverse Screening is demonstrably more valuable and suitable for further investment.
Reverse Screening provides fertile ground for development of interactome and/or degradome biomarkers: biomarkers that reflect real time biology and that differentiate patient populations. Finally, data collected via Reverse Screening are crucial for Systems Biology, other in silico work and “bottom up” ontology.
“Action, events, movements” open lots of doors.
RAPTOR and RAVEN uniquely allow the complexity of the test media to range from a few molecular species to the thousands present in, e.g., a lysate. Samples remain intact as protein interactions or protein degradation are detected and quantified. No separations, no washes, no affinity agents, no fused proteins, no tinker-toy replacements for whole biomolecules. Reverse Screening exploits this extraordinary and unique flexibility. Through a carefully orchestrated battery of observations, competition for the drug among diverse biological entities may be evaluated.
Assume, for example, that the drug candidate is shown to inhibit binding of Factor A, a soluble protein, to Factor A Receptor, a transmembrane protein. Now the fun starts! The drug candidate’s other activities can be determined by observing perturbation in this inhibition. Consider a second, simple test: addition of another bio-relevant entity (BE) such as another protein or polynucleotide. Two outcomes are possible: BE does not alter the drug’s inhibition of Factor A/ Receptor OR BE does alter the inhibition of Factor A/ Receptor. If BE has no effect on the drug’s behavior then the drug has no apparent interaction with BE. If BE does effect the drug’s ability to inhibit binding, then interaction of the drug and BE is likely. In effect, modulation of the drug’s modulation of a single bio-event signals the drug’s interactions with any range of biomolecules or structures. Taken to its logical conclusion, Reverse Screening traces out all possible interactions of the drug, the Drug Interactome.
The power inherent in Reverse Screening, made possible only by the incredible flexibility of RAPTOR and RAVEN, is enormous and unprecedented. Target confirmation, determination of MOA, off-target interactions and even anticipation of side effects and toxicity become practical goals. Reverse Screening is also amenable to multi-factorial, multi-MOA, multi-drug testing. On a more routine scale, detection of drug interactions with unwanted or unexpected bio-entities can provide feedback for drug redesign or selection of an alternate candidate. Even dosing and delivery considerations should be forthcoming. Perhaps most importantly, a candidate that passes the test of NLP’s Reverse Screening is demonstrably more valuable and suitable for further investment.
Reverse Screening provides fertile ground for development of interactome and/or degradome biomarkers: biomarkers that reflect real time biology and that differentiate patient populations. Finally, data collected via Reverse Screening are crucial for Systems Biology, other in silico work and “bottom up” ontology.
“Action, events, movements” open lots of doors.
*Zuckerkandl E, Pauling L. Molecular disease, evolution, and genic heterogeneity. In: Kasha M, Pullman B, (eds). Horizons in Biochemistry. New York: Academic Press, 1962;
189.
189.
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