The tumor suppressor protein p53 can lose its function upon single-point missense mutations in the core DNA-binding domain ("cancer mutants"). Activity can be restored by second-site suppressor mutations ("rescue mutants"). This paper relates the functional activity of p53 cancer and rescue mutants to their overall molecular dynamics (MD), without focusing on local structural details. A novel global measure of protein flexibility for the p53 core DNA-binding domain, the number of clusters at a certain RMSD cutoff, was computed by clustering over 0.7 µs of explicitly solvated all-atom MD simulations. For wild-type p53 and a sample of p53 cancer or rescue mutants, the number of clusters was a good predictor of in vivo p53 functional activity in cell-based assays. This number-of-clusters (NOC) metric was strongly correlated (r(2) = 0.77) with reported values of experimentally measured ΔΔG protein thermodynamic stability. Interpreting the number of clusters as a measure of protein flexibility: (i) p53 cancer mutants were more flexible than wild-type protein, (ii) second-site rescue mutations decreased the flexibility of cancer mutants, and (iii) negative controls of non-rescue second-site mutants did not. This new method reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants.

The International Society for Computational Biology (ISCB) is dedicated to advancing human knowledge at the intersection of computation and life sciences.On behalf of the ISCB members, this public policy statement expresses strong support for open access, reuse, integration, and distillation of the publicly funded archival scientific and technical research literature, and for the infrastructure to achieve that goal.Knowledge is the fruit of the research endeavor, and the archival scientific and technical research literature is its practical expression and means of communication.Shared knowledge multiplies in utility because every new scientific discovery is built upon previous scientific knowledge.Access to knowledge is access to the power to solve new problems and make informed decisions.Free, open, public, online access to the archival scientific and technical research literature will empower citizens and scientists to solve more problems and make better, more informed decisions.Attribution to the original authors will maintain consistency and accountability within the knowledge base.Computational reuse, integration, and distillation of that literature will produce new and as yet unforeseen knowledge.We strongly encourage open software, data, and databases, issues that are not addressed here.A prior ISCB public policy statement on sharing software provides very clear support for open source/open access (http://www.iscb.org/iscb-policy-

Many protein engineering problems involve finding mutations that produce proteins with a particular function. Computational active learning is an attractive approach to discover desired biological activities. Traditional active learning techniques have been optimized to iteratively improve classifier accuracy, not to quickly discover biologically significant results. We report here a novel active learning technique, Most Informative Positive (MIP), which is tailored to biological problems because it seeks novel and informative positive results. MIP active learning differs from traditional active learning methods in two ways: (1) it preferentially seeks Positive (functionally active) examples; and (2) it may be effectively extended to select gene regions suitable for high throughput combinatorial mutagenesis. We applied MIP to discover mutations in the tumor suppressor protein p53 that reactivate mutated p53 found in human cancers. This is an important biomedical goal because p53 mutants have been implicated in half of all human cancers, and restoring active p53 in tumors leads to tumor regression. MIP found Positive (cancer rescue) p53 mutants in silico using 33% fewer experiments than traditional non-MIP active learning, with only a minor decrease in classifier accuracy. Applying MIP to in vivo experimentation yielded immediate Positive results. Ten different p53 mutations found in human cancers were paired in silico with all possible single amino acid rescue mutations, from which MIP was used to select a Positive Region predicted to be enriched for p53 cancer rescue mutants. In vivo assays showed that the predicted Positive Region: (1) had significantly more (p<0.01) new strong cancer rescue mutants than control regions (Negative, and non-MIP active learning); (2) had slightly more new strong cancer rescue mutants than an Expert region selected for purely biological considerations; and (3) rescued for the first time the previously unrescuable p53 cancer mutant P152L.

Proteins that bind to specific locations in genomic DNA control many basic cellular functions. Proteins detect their binding sites using both direct and indirect recognition mechanisms. Deformation energy, which models the energy required to bend DNA from its native shape to its shape when bound to a protein, has been shown to be an indirect recognition mechanism for one particular protein, Integration Host Factor (IHF). This work extends the analysis of deformation to two other DNA-binding proteins, CRP and SRF, and two endonucleases, I-CreI and I-PpoI. Known binding sites for all five proteins showed statistically significant differences in mean deformation energy as compared to random sequences. Binding sites for the three DNA-binding proteins and one of the endonucleases had mean deformation energies lower than random sequences. Binding sites for I-PpoI had mean deformation energy higher than random sequences. Classifiers that were trained using the deformation energy at each base pair step showed good cross-validated accuracy when classifying unseen sequences as binders or nonbinders. These results support DNA deformation energy as an indirect recognition mechanism across a wider range of DNA-binding proteins. Deformation energy may also have a predictive capacity for the underlying catalytic mechanism of DNA-binding enzymes.

Many biomedical problems relate to mutant functional properties across a sequence space of interest, e.g., flu, cancer, and HIV. Detailed knowledge of mutant properties and function improves medical treatment and prevention. A functional census of p53 cancer rescue mutants would aid the search for cancer treatments from p53 mutant rescue. We devised a general methodology for conducting a functional census of a mutation sequence space by choosing informative mutants early. The methodology was tested in a double-blind predictive test on the functional rescue property of 71 novel putative p53 cancer rescue mutants iteratively predicted in sets of three (24 iterations). The first double-blind 15-point moving accuracy was 47 percent and the last was 86 percent; r = 0.01 before an epiphanic 16th iteration and r = 0.92 afterward. Useful mutants were chosen early (overall r = 0.80). Code and data are freely available (http://www.igb.uci.edu/research/research.html, corresponding authors: R.H.L. for computation and R.K.B. for biology).

MOTIVATION: Direct recognition, or direct readout, of DNA bases by a DNA-binding protein involves amino acids that interact directly with features specific to each base. Experimental evidence also shows that in many cases the protein achieves partial sequence specificity by indirect recognition, i.e., by recognizing structural properties of the DNA. (1) Could threading a DNA sequence onto a crystal structure of bound DNA help explain the indirect recognition component of sequence specificity? (2) Might the resulting pure-structure computational motif manifest itself in familiar sequence-based computational motifs? RESULTS: The starting structure motif was a crystal structure of DNA bound to the integration host factor protein (IHF) of E. coli. IHF is known to exhibit both direct and indirect recognition of its binding sites. (1) Threading DNA sequences onto the crystal structure showed statistically significant partial separation of 60 IHF binding sites from random and intragenic sequences and was positively correlated with binding affinity. (2) The crystal structure was shown to be equivalent to a linear Markov network, and so, to a joint probability distribution over sequences, computable in linear time. It was transformed algorithmically into several common pure-sequence representations, including (a) small sets of short exact strings, (b) weight matrices, (c) consensus regular patterns, (d) multiple sequence alignments, and (e) phylogenetic trees. In all cases the pure-sequence motifs retained statistically significant partial separation of the IHF binding sites from random and intragenic sequences. Most exhibited positive correlation with binding affinity. The multiple alignment showed some conserved columns, and the phylogenetic tree partially mixed low-energy sequences with IHF binding sites but separated high-energy sequences. The conclusion is that deformation energy explains part of indirect recognition, which explains part of IHF sequence-specific binding.

This paper describes a novel anytime branch-and-bound threading search algorithm for gapped block protein sequence-structure alignment with general se-quence residue pair interactions. The new algorithm (1) returns a good approximate answer quickly, (2) iteratively improves that answer to the global opti-mum if allowed more time, (3) eventually produces a proof that the final answer found is indeed the global optimum, and (4) always terminates correctly within a bounded number of steps if allowed sufficient space and time. Using previously published data sets and the Bryant-Lawrence (1993) objective function, the algorithm found the true (proven) global optimum in less than five minutes in alI search spaces size 1O25 or smaller (sequences to 478 residues), and a putative (not guaranteed) optimum in less than five hours in all search spaces size 10 ” or smaller (sequences to 793 residues, cores to 42 secondary structure seg-ments). If the threading in the largest case were eventually proven to be globally optimal, then the corresponding search speed in the largest case stud-ied would be the equivalent of 1.5 x 1O56 threadings per second, a speed-up exceeding 1O25 over previ-ously published batch branch-and-bound speeds, and exceeding 1050 over previously published exhaustive search speeds, using the same objective function and threading paradigm. Implementation independent measures of search efficiency are defined for equiva-lent branching factor, depth, and probability of suc-cess per draw; empirical data on these measures is given. The general approach should apply to other alignment methodologies and search methods that use a divide-and-conquer strategy. permission to make. digital or hard copies of all or part of this work for personu ~ or classroom usc is pnted without fee provided that copies are not made or distributed for prolit or commercial advantage and that copies bear this notice and the full citation on thC fif’d IWF. TCI ‘22’ otherwise. to republish, to post on servers or to redistribute to listsrequires prior specific permission and:‘w a fee.

Article The threading approach to the inverse protein folding problem Share on Authors: Temple F. Smith BioMolecular Engineering Research Center, College of Engineering, Boston University, 36 Cummington Street, Boston, MA BioMolecular Engineering Research Center, College of Engineering, Boston University, 36 Cummington Street, Boston, MAView Profile , Loredana Lo Conte BioMolecular Engineering Research Center, College of Engineering, Boston University, 36 Cummington Street, Boston, MA and Department of Computer Science, College of Arts and Sciences, Boston University, Boston, MA BioMolecular Engineering Research Center, College of Engineering, Boston University, 36 Cummington Street, Boston, MA and Department of Computer Science, College of Arts and Sciences, Boston University, Boston, MAView Profile , Jadwiga Bienkowska BioMolecular Engineering Research Center, College of Engineering, Boston University, 36 Cummington Street, Boston, MA BioMolecular Engineering Research Center, College of Engineering, Boston University, 36 Cummington Street, Boston, MAView Profile , Bob Rogers BioMolecular Engineering Research Center, College of Engineering, Boston University, 36 Cummington Street, Boston, MA BioMolecular Engineering Research Center, College of Engineering, Boston University, 36 Cummington Street, Boston, MAView Profile , Chrysanthe Gaitatzes BioMolecular Engineering Research Center, College of Engineering, Boston University, 36 Cummington Street, Boston, MA BioMolecular Engineering Research Center, College of Engineering, Boston University, 36 Cummington Street, Boston, MAView Profile , Richard Lathrop Department of Infomation and Computer Science, University of California, Irvine, CA Department of Infomation and Computer Science, University of California, Irvine, CAView Profile Authors Info & Claims RECOMB '97: Proceedings of the first annual international conference on Computational molecular biologyJanuary 1997 Pages 287–292https://doi.org/10.1145/267521.267887Online:19 January 1997Publication History 3citation95DownloadsMetricsTotal Citations3Total Downloads95Last 12 Months3Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

High-level functional (or behavioral) simulation models are difficult, time-consuming, and expensive to develop. We report on a method for automatically generating the program code for a high-level functional simulation model. The high-level model is produced directly from the program code for the circuit components' functional models and a netlist description of their connectivity. A prototype has been implemented in LISP for the SIMMER functional simulator.

CONSTELLATION, a general LISP-based tool for structure recognition and manipulation, is described. CONSTELLATION is a design refinement tool for the later stages of the design process, when a complete (or nearly so) design is available. It is intended to recognize local sub-structures in the design and carry out specific associated manipulations. The recognition phase is driven by a design precedent. This is a pattern which an experienced designer points out in an existing design, together with an associated action to perform. The action is normally stated in the system's native Y hardware description language, though we also support the use of LISP or mixtures. CONSTELLATION has also been interfaced to a general abstract functional simulator (SIMMER[11]). It is in experimental use in a production environment where we are exploring its applications to rationalizing existing flat designs, interactive structure editing performance enhancements, identifying candidates for new cell-generators, and in-circuit functional simulation.

Robot mechanisms during many typical interactions with their environment have long posed a difficulty to computer simulation. This is due to the coupling of effects from the base and the tip (the closed loop problem), often complicated by mixtures of known and unknown endpoint forces and accelerations. This paper presents a linear-time (recursive) algorithm for the closed-loop forward dynamics of kinematic chains under very general environmental endpoint constraints. The statement of very complex systems of endpoint constraints is particularly easy, and the algorithm is conceptually simple and physically intuitive. The algorithm is then generalized to branching kinematic chains (trees), where every endpoint may be subject to environmental (closed-loop) constraints. The time complexity for constrained kinematic trees remains also linear in the number of joints. An appendix sketches an extension of the algorithm to general kinematic structures with one-dof joints, but containing arbitrary internal closed loops. The time complexity with internal loops is no worse than O(n) + O(l2, for n joints and l internal loops; for many structures the algorithm attains O(n)+ O[l\log(l)].

A LISP-based functional simulation system supporting a general concept of function and abstraction is described. SIMMER was developed primarily to support research into the relation of structure to function and associated description languages, and also to provide assistance to the designer analyzing especially difficult circuits. It consists of a general object-oriented message-passing functional simulator; a user-extensible intermediate-level base language for describing complex systems; and a supporting integrated database (not described). We introduce the versional module, a generalized notion of state, and busses as active functional objects. Message-passing LISP objects are used to represent physical and abstract entities.

This paper presents two highly parallel "mathematically exact" formulations of the inverse Dynamics especially suited to high-speed implementations using VLSI devices. The first is a parallel formulation of the existing linear recursive Newton-Euler algorithm, with the real-time coefficients reduced almost two orders of magnitude. The second reports a new parallel algorithm which improves the linear time dependency to O(log2) of the number of joints, with small coefficients. Either formulation is susceptible to a systolic pipelined architecture, requiring four floating-point operations per complete set of joint torques. Hardware requirements are not excessive, and a VLSI implementation architecture is possible.