A hybrid approach to protein folding problem integrating constraint programming with local search

<p>Abstract</p> <p>Background</p> <p>The protein folding problem remains one of the most challenging open problems in computational biology. Simplified models in terms of lattice structure and energy function have been proposed to ease the computational hardness of this optimization problem. Heuristic search algorithms and constraint programming are two common techniques to approach this problem. The present study introduces a novel hybrid approach to simulate the protein folding problem using constraint programming technique integrated within local search.</p> <p>Results</p> <p>Using the face-centered-cubic lattice model and 20 amino acid pairwise interactions energy function for the protein folding problem, a constraint programming technique has been applied to generate the neighbourhood conformations that are to be used in generic local search procedure. Experiments have been conducted for a few small and medium sized proteins. Results have been compared with both pure constraint programming approach and local search using well-established local move set. Substantial improvements have been observed in terms of final energy values within acceptable runtime using the hybrid approach.</p> <p>Conclusion</p> <p>Constraint programming approaches usually provide optimal results but become slow as the problem size grows. Local search approaches are usually faster but do not guarantee optimal solutions and tend to stuck in local minima. The encouraging results obtained on the small proteins show that these two approaches can be combined efficiently to obtain better quality solutions within acceptable time. It also encourages future researchers on adopting hybrid techniques to solve other hard optimization problems.</p

Modern techniques for constraint solving the CASPER experience

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Informática, pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaConstraint programming is a well known paradigm for addressing combinatorial problems which has enjoyed considerable success for solving many relevant industrial and academic problems. At the heart of constraint programming lies the constraint solver, a computer program which attempts to find a solution to the problem, i.e. an assignment of all the variables in the problemsuch that all the constraints are satisfied. This dissertation describes a set of techniques to be used in the implementation of a constraint solver. These techniques aim at making a constraint solver more extensible and efficient,two properties which are hard to integrate in general, and in particular within a constraint solver. Specifically, this dissertation addresses two major problems: generic incremental propagation and propagation of arbitrary decomposable constraints. For both problemswe present a set of techniques which are novel, correct, and directly concerned with extensibility and efficiency. All the material in this dissertation emerged from our work in designing and implementing a generic constraint solver. The CASPER (Constraint Solving Platformfor Engineering and Research)solver does not only act as a proof-of-concept for the presented techniques, but also served as the common test platform for the many discussed theoretical models. Besides the work related to the design and implementation of a constraint solver, this dissertation also presents the first successful application of the resulting platform for addressing an open research problem, namely finding good heuristics for efficiently directing search towards a solution

Heuristics, Optimizations, and Parallelism for Protein Structure Prediction in CLP(FD)

The paper describes a constraint-based solution to the protein folding problem on face-centered cubic lattices - a biologically meaningful approximation of the general protein folding problem. The paper improves the results presented in [15] and introduces new ideas for improving efficiency: (i) proper reorganization of the constraint structure; (ii) development of novel, both general and problem-specific, heuristics; (iii) exploitation of parallelism. Globally, we obtain a speed up in the order of 60 w.r.t. [15]. We show how these results can be employed to solve the folding problem for large proteins containing subsequences whose conformation is already known.

Proceedings of the 22nd Conference on Formal Methods in Computer-Aided Design – FMCAD 2022

The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing

Proceedings of the 22nd Conference on Formal Methods in Computer-Aided Design – FMCAD 2022

The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing

Programming Languages and Systems

This open access book constitutes the proceedings of the 28th European Symposium on Programming, ESOP 2019, which took place in Prague, Czech Republic, in April 2019, held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2019

Actas del XXIV Workshop de Investigadores en Ciencias de la Computación: WICC 2022

Compilación de las ponencias presentadas en el XXIV Workshop de Investigadores en Ciencias de la Computación (WICC), llevado a cabo en Mendoza en abril de 2022.Red de Universidades con Carreras en Informátic