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7 Computational protein design and discovery

Sheldon Park, Xiaoran Fu Stowell, Wei Wang, Xi Yang, Jeffery G. Saven
2004 Annual Reports Section C (Physical Chemistry)  
As many of these forces are subtle and their simultaneous optimization is a problem of great complexity, sophisticated sequence prediction algorithms have been developed to aid in the design of novel proteins  ...  to a large-scale design of de novo proteins.  ...  S. is a Cottrell Scholar of Research Corporation and an Arnold and Mabel Beckman Foundation Young Investigator.  ... 
doi:10.1039/b313669h fatcat:4v7kua5e75hu3ke2ogp5zka4ua

An algorithm to parse segment packing in predicted protein contact maps

William R. Taylor
2016 Algorithms for Molecular Biology  
For the larger protein, this involved examples of the algorithm apportioning parts of a single large secondary structure element between two different interactions.  ...  The method was shown to be effective when applied to the transmembrane class of protein and error tolerant even when the signal becomes degraded.  ...  Availability of data and materials All data and program souce codes can be found in the Supplementary Material associated with this paper.  ... 
doi:10.1186/s13015-016-0080-x pmid:27330543 pmcid:PMC4912788 fatcat:zzqnriogrzcgpjbariggukupei

Learning the Language of Biological Sequences [chapter]

François Coste
2016 Topics in Grammatical Inference  
, it is still a source of open and nice inspirational problems for grammatical inference, enabling us to confront our ideas to real fundamental applications.  ...  Learning the language of biological sequences is an appealing challenge for the grammatical inference research field.  ...  proteins [96] and transmembrane regions in proteins [97] , whose performances are close to those of dedicated tools built with human expertise.  ... 
doi:10.1007/978-3-662-48395-4_8 fatcat:eojckskf65f5phcbmjsfbq7era

Artificial intelligence and molecular biology

1994 ChoiceReviews  
See [Baddeley, 1986] for an overview of algorithms for two-dimensional segmentation.  ...  For a detailed description of the frame representation for imagery and the implementation of the depict function see [Papadias 1990 ]. 2.  ...  of the folded protein.  ... 
doi:10.5860/choice.31-3826 fatcat:5jmryy7mkbcrvifz6ahlbbdceu

Current Progress in Static and Dynamic Modeling of Biological Networks [chapter]

Bernie J. Daigle, Balaji S. Srinivasan, Jason A. Flannick, Antal F. Novak, Serafim Batzoglou
2010 Systems Biology for Signaling Networks  
In this review we discuss techniques for both of these modeling paradigms, illustrating each by reference to important recent papers.  ...  This first step in this process is reconstructing molecular anatomy through static modeling, the determination of which pieces (DNA, RNA, protein, and metabolite) is present, and how they are related (  ...  Acknowledgements We thank Russ Altman for helpful discussions.  ... 
doi:10.1007/978-1-4419-5797-9_2 fatcat:7pwcze2sbraszfcy5yacypur7e

Transition path sampling and forward flux sampling. Applications to biological systems

Fernando A Escobedo, Ernesto E Borrero, Juan C Araque
2009 Journal of Physics: Condensed Matter  
folding, and enzyme catalysis.  ...  While path sampling methods have a widespread application to many types of rare transitional events, here only recent applications involving biomolecules are reviewed, including isomerizations, protein  ...  Bolhuis for allowing us to modify their picture files.  ... 
doi:10.1088/0953-8984/21/33/333101 pmid:21828593 fatcat:zhovbj6frjcvrnd75674x3z47i

Learning Cellular Sorting Pathways Using Protein Interactions and Sequence Motifs [chapter]

Tien-ho Lin, Ziv Bar-Joseph, Robert F. Murphy
2011 Lecture Notes in Computer Science  
Using our motif-based predictions we were also able to correct annotation errors in public databases for the location of some of the proteins.  ...  Proteins are transported by different cellular sorting pathways, some of which take a protein through several intermediate locations until reaching its final destination.  ...  DME (Discriminative Matrix Enumerator) [49] uses a different approach for discriminative learning of a PWM. A global, enumerative search on a discrete space of PWM.  ... 
doi:10.1007/978-3-642-20036-6_20 fatcat:jc2zx6wmrzbzjgiczc6pcosn7e

Learning Cellular Sorting Pathways Using Protein Interactions and Sequence Motifs

Tien-Ho Lin, Ziv Bar-Joseph, Robert F. Murphy
2011 Journal of Computational Biology  
Using our motif-based predictions we were also able to correct annotation errors in public databases for the location of some of the proteins.  ...  Proteins are transported by different cellular sorting pathways, some of which take a protein through several intermediate locations until reaching its final destination.  ...  DME (Discriminative Matrix Enumerator) [49] uses a different approach for discriminative learning of a PWM. A global, enumerative search on a discrete space of PWM.  ... 
doi:10.1089/cmb.2011.0193 pmid:21999284 pmcid:PMC3216107 fatcat:fzqi5tdydbgb5jkwc7oqjexjuu

Input–output behavior of ErbB signaling pathways as revealed by a mass action model trained against dynamic data

William W Chen, Birgit Schoeberl, Paul J Jasper, Mario Niepel, Ulrik B Nielsen, Douglas A Lauffenburger, Peter K Sorger
2009 Molecular Systems Biology  
To quantify signal flow through ErbB-activated pathways we have constructed, trained and analyzed a mass action model of immediate-early signaling involving ErbB1-4 receptors (EGFR, HER2/Neu2, ErbB3 and  ...  Modeling predicts log-linear amplification so that significant ERK and Akt activation is observed at ligand concentrations far below the K d for receptor binding.  ...  Acknowledgements We thank Laura Sontag-Kleiman, Julio Saez-Rodriguez and Carlos Lopez for discussion and editing and Taeshin Park for assistance with Jacobian.  ... 
doi:10.1038/msb.2008.74 pmid:19156131 pmcid:PMC2644173 fatcat:kkzeuupzanamhmakcdiamcl3ci

A Survey of Computational Methods for Protein Function Prediction [chapter]

Amarda Shehu, Daniel Barbará, Kevin Molloy
2016 Big Data Analytics in Genomics  
Here we review these methods and the state of protein function prediction, emphasizing recent algorithmic developments, remaining challenges, and prospects for future research.  ...  neighbors in a protein-protein interaction network, from microarray data, or a combination of these different types of data.  ...  Acknowledgements Funding for this work is provided in part by NSF-IIS1144106. References  ... 
doi:10.1007/978-3-319-41279-5_7 fatcat:pejwmwpoarhyjhulevmkbavocm

Molecular Design in Synthetically Accessible Chemical Space via Deep Reinforcement Learning [article]

Julien Horwood, Emmanuel Noutahi
2020 arXiv   pre-print
We instead propose a novel Reinforcement Learning framework for molecular design in which an agent learns to directly optimize through a space of synthetically-accessible drug-like molecules.  ...  We validate our method by demonstrating that it outperforms existing state-of the art approaches in the optimization of pharmacologically-relevant objectives, while results on multi-objective optimization  ...  The methods and algorithms presented here were developed at InVivo AI.  ... 
arXiv:2004.14308v2 fatcat:dbmnzvy3mfdl5np7hlnwsz3ama

Pathway analysis for BioAmbients

Henrik Pilegaard, Flemming Nielson, Hanne Riis Nielson
2008 The Journal of Logic and Algebraic Programming  
Systems Biology aims for a holistic understanding of biological processes. In order to make this understanding operational and testable it can be recorded into formal process calculus models.  ...  This is a difficult task, however, because such formal models and their, often infinitely many, consequences are hard to enumerate and understand.  ...  We model the transmembranal LDL receptors and the membrane patch that will later fold into the early endosome as a process capable of evolving into the EE ambient (lines [19] [20] [21] .  ... 
doi:10.1016/j.jlap.2008.05.006 fatcat:rr52l4n2bbco7m6ns3lrmtgb6a

Mechanistic model of MAPK signaling reveals how allostery and rewiring contribute to drug resistance [article]

Fabian Froehlich, Luca Gerosa, Jeremy L Muhlich, Peter K Sorger
2022 bioRxiv   pre-print
responsible for adaptive rewiring.  ...  Causal tracing demonstrates that this provides a sufficient quantitative explanation for initial and acquired responses to multiple different RAF and MEK inhibitors individually and in combination.  ...  .), a Novartis Foundation fellowship to L.G., HFSP grant LT000259/2019-L1 to F.F..  ... 
doi:10.1101/2022.02.17.480899 fatcat:2cvmttald5gppokgs3o5is2umq

Computational Methods in Drug Discovery

G. Sliwoski, S. Kothiwale, J. Meiler, E. W. Lowe
2013 Pharmacological Reviews  
Authorship Contributions Wrote or contributed to the writing of the manuscript: Sliwoski, Kothiwale, Meiler, Lowe.  ...  Melo and Sali (2007) applied a genetic algorithm that used 21 input model features like sequence alignment scores, measures of protein packing, and geometric descriptors to assess folds of models.  ...  Anton has been used successfully for full atomic resolution protein folding (Lindorff-Larsen et al., 2011) .  ... 
doi:10.1124/pr.112.007336 pmid:24381236 pmcid:PMC3880464 fatcat:4dzrdkspkjecnombnchznma2ny

Computational Strategies for a System-Level Understanding of Metabolism

Paolo Cazzaniga, Chiara Damiani, Daniela Besozzi, Riccardo Colombo, Marco Nobile, Daniela Gaglio, Dario Pescini, Sara Molinari, Giancarlo Mauri, Lilia Alberghina, Marco Vanoni
2014 Metabolites  
To this aim, a plethora of methods have been developed, yet it is generally hard to identify which computational strategy is most suited for the investigation of a specific aspect of metabolism.  ...  , especially when dealing with a shortage of experimental measurements.  ...  If a gene is repressed, the fluxes of reactions involving the corresponding protein product will be constrained to zero.  ... 
doi:10.3390/metabo4041034 pmid:25427076 pmcid:PMC4279158 fatcat:phwvjs7sebbkpkj5i7plfkjm54
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