The three-dimensional structure of a protein, formed as a result of amino-acid sequences folding into compact domains, is regarded as a key factor in its biological function. How and why proteins fold into specific topologies, remain the key focus of scientific research in the field of biophysics. By stripping down complex reactions down to the most basic elements, biophysicists aim to develop simplified models for biological phenomena such as antibody discrimination, viral fusion or self-assembly. Focusing on small model peptide systems, rather than the full proteins from which they were derived, was hoped to result in accurate structural measurements and provide a more transparent comparison between simulation and experiment. The aim of this research was therefore to investigate how accurate these models were when compared against experiment. Furthermore, while breaking down the complex biological phenomena into simple models, there was also a conscious effort to ensure that the models were representative of real biological systems, and a major focus was therefore aimed at determining whether any meaningful biomedical insight may be extrapolated from such models. Peptides found in hormones (human chorionic gonadotropin, luteinizing hormone), viruses (HIV) and amyloid diseases (transthyretin) were selected in order to probe a variety of questions in relation to the aforementioned biological phenomena. Namely, how the primary sequence influenced the three-dimensional structure (and thus its biological function), how its environment could influence such a confirmation, and how these systems aggregated. This doctoral study has made use of a combination of computer simulations and experimental techniques to investigate a selection of biologically relevant peptides; utilising classical atomistic molecular dynamics (MD) simulations to characterise the free-energy landscapes of the chosen peptides, and compare these findings with the secondary structure content predicted by spectroscopic methods such as circular dichroism and infrared spectroscopy. The peptide systems studied within, were found to be characterised by rugged free-energy landscapes unlike their protein counterparts (defined by singular, deep minima). Furthermore, these landscapes were found to be highly plastic and sensitive to changes in the local environment.

No description available.

When the states of a system can be described by the extrema of a high-dimensional function, the characterisation of its complexity, i.e. the enumeration of the accessible stable states, can be reduced to a sampling problem. In this thesis a robust numerical protocol is established, capable of producing numerical estimates of the total number of stable states for a broad class of systems, and of computing the a-priori probability of observing any given state. The approach is demonstrated within the context of the computation of the configurational entropy of two and three-dimensional jammed packings. By means of numerical simulation we show the extensivity of the granular entropy as proposed by S.F. Edwards for three-dimensional jammed soft-sphere packings and produce a direct test of the Edwards conjecture for the equivalent two dimensional systems. We find that Edwards’ hypothesis of equiprobability of all jammed states holds only at the (un)jamming density, that is precisely the point of practical significance for many granular systems. Furthermore, two new recipes for the computation of high-dimensional volumes are presented, that improve on the established approach by either providing more statistically robust estimates of the volume or by exploiting the trajectories of the paths of steepest descent. Both methods also produce as a natural by-product unprecedented details on the structures of high-dimensional basins of attraction. Finally, we present a novel Monte Carlo algorithm to tackle problems with fluctuating weight functions. The method is shown to improve accuracy in the computation of the ‘volume’ of high dimensional ‘fluctuating’ basins of attraction and to be able to identify transition states along known reaction coordinates. We argue that the approach can be extended to the optimisation of the experimental conditions for observing certain phenomena, for which individual measurements are stochastic and provide little guidance.

In this thesis, I discuss engineering colloidal particles to have specific, isotropic interactions and studying their cluster geometries in equilibrium. I discuss light scattering experiments showing that a highly specific protein, Dscam, is unstable against thermal aggregation. This result lead me to use DNA instead to control interparticle specificity. I coated 1-micron diameter polystyrene particles uniformly with DNA. I used fluorescence microscopy with oxygen-scavenging enzymes to observe these particles self-assembling in clusters. These experiments show that a packing of 6 spheres that is rarely seen in a single-component system is observed very often in an optimized 3-species system. Then I show experiments using the same 3 species but 9 total particles, finding that the equilibrium yields of the most likely cluster relative to other stable clusters are lower than at 6 particles. I conclude from these experiments that optimizing the assembly of an otherwise unlikely configuration may require nearly as many species as particles. Finally, I investigate the scalability of self-assembly of particles with isotropic and specific interactions theoretically. I use both exact and approximate partition functions to show that spheres with specific interactions can have energy landscapes with thermodynamically large numbers of strictly local minima relative to the number of their ground states. Compared to single-component systems, these systems of many different species may spend much more time in kinetic traps and never reach their ground states. Finally, I discuss briefly some directions for further study, including questions of how the results in this thesis may be related to protein folding and complex formation. / Engineering and Applied Sciences

Submitted by Antonio Bento de Oliveira Junior null (junioreif@hotmail.com) on 2018-01-23T13:42:06Z No. of bitstreams: 1 Tese-final.pdf: 43113195 bytes, checksum: 7cc85051e3a1420a2983ce716e0ae144 (MD5) / Rejected by Elza Mitiko Sato null (elzasato@ibilce.unesp.br), reason: Solicitamos que realize correções na submissão seguindo as orientações abaixo: Problema 01 : A data na capa deve conter somente o ano; Problema 02: A data na folha de aprovação deve ser a data da defesa; Problema 03: Se você teve financiamento da FAPESP é obrigatório constar também na folha de rosto e o numero do processo; Problema 04: As páginas viii, xvi, xviii, 10, 34, 38, 46 e 60 estão em branco; Problema 05: A numeração das páginas deve ser contínua. Caso ainda tenha dúvida consulte, por gentileza o modelo que consta na página da seção de pós-graduação, link Instruções para Qualificação e Defesas :http://www.ibilce.unesp.br/#!/pos-graduacao/instrucoes-para-aluno-que-vai-defender/ Agradecemos a compreensão. on 2018-01-23T17:41:25Z (GMT) / Submitted by Antonio Bento de Oliveira Junior null (junioreif@hotmail.com) on 2018-01-23T18:20:41Z No. of bitstreams: 1 Tese-final.pdf: 42848208 bytes, checksum: 26d4aab1e2a66d06ba87e4533f1cdd40 (MD5) / Approved for entry into archive by Elza Mitiko Sato null (elzasato@ibilce.unesp.br) on 2018-01-24T12:12:56Z (GMT) No. of bitstreams: 1 oliveirajunior_ab_dr_sjrp.pdf: 42589488 bytes, checksum: 6433ad3adeeb7e56b159e54ad745abe2 (MD5) / Made available in DSpace on 2018-01-24T12:12:56Z (GMT). No. of bitstreams: 1 oliveirajunior_ab_dr_sjrp.pdf: 42589488 bytes, checksum: 6433ad3adeeb7e56b159e54ad745abe2 (MD5) Previous issue date: 2017-12-05 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / O enovelamento de proteínas acontece em um espaço de fase multidimensional, onde o número conformações possíveis é exponencialmente alta. Uma forma comum de representar essas conformações é utilizar uma coordenada de reação efetiva (por exemplo, fração de contatos nativos). Porém, como a informação de cada conformação não é representada neste tipo de aproximação estatistifica, alguns mecanismos do enovelamento de proteínas não são possíveis de ser descritos ou analisados. Neste trabalho, usou-se uma métrica para descrever a distancia entre quaisquer duas conformações, essa métrica é calculada levando em conta as distâncias internas dos aminoácidos presentes em cada estrutura. Utilizando-se um método de projeção efetiva é possível ir além da representação em uma dimensão e visualizar a superfície de enovelamento da proteína em duas ou três dimensões. Para aplicar essa metodologia realizou-se simulações computacionais do enovelamento de proteínas utilizando o modelo baseado em estrutura, com aproximação para Cα. Três proteínas foram analisadas: CI-2, o Domínio SH3 e a Proteína A. Dos resultados, foi possível observar que para cada tipo de "motifs"estrutural (folha-β e/ou α-hélice) projetou funis de enovelamento distintos. A partir da visualização foi possível analisar o processo de enovelamento em detalhes, sendo possível identificar a conectividade entre as conformações assim como, possíveis rotas de enovelamento (f olding pathsways). Analisou-se também as diferenças estruturais da rota dominante no domínio SH3 e a competitividade entre a estrutura do estado nativo e do estado espelhado que acontece em proteínas que possuem somente α-hélice, como é o caso da proteína A. / Protein folding occurs in a very high dimensional phase space, in which an exponentially large number of states is represented in terms of one effective reaction coordinate. Since the role of each local minimum is not considered in this statistical approach, the folding mechanism is unveiled by describing the local minima in an effective onedimensional representation. In this work, we used a metric to describe the distance between any two conformations, which is based on internal distances between amino acids in each conformation. A effective projection method allows to go beyond the one-dimensional representation and visualizing a 2D folding funnel representation. Computer simulations of protein folding were performed using Cα structure-based model. Three proteins have been studied: CI2, SH3 Domain and Protein-A. Distinct funnels have been generated according to the major motifs in each proteins, (β-sheet or/and α-helix). The visualization allows assessing the folding process in detail, e.g. by identifying the connectivity between conformations and establishing the paths that lead to the native state and we analyzed structural differences in the dominant route of SH3 and the competitiveness between the native and mirror structures in protein A.

RNAs are biomolecules ubiquitous in all living cells. Usually, they fold into complex molecular structures, which often mediate their biological function. In this work, models of RNA folding have been studied in detail. One can distinguish two fundamentally different approaches to RNA folding. The first one is the thermodynamic approach, which yields information about the distribution of structures in the ensemble in its equilibrium. The second approach, which is required to study the dynamics of folding during the course of time, is the kinetic folding analysis. It is much more computationally expensive, but allows to incorporate changing environmental parameters as well as time-dependent effects into the analysis. Building on these methods, the BarMap framework (Hofacker, Flamm, et al., 2010) allows to chain several pre-computed models and thus simulate folding reactions in a dynamically changing environment, e. g., to model co- transcriptional folding. However, there is no obvious way to identify spurious output, let alone assessing the quality of the simulation results. As a remedy, BarMap-QA, a semi-automatic software pipeline for the analysis of cotranscriptional folding, has been developed. For a given input sequence, it automatically generates the models for every step of the RNA elongation, applies BarMap to link them together, and runs the simulation. Post-processing scripts, visualizations, and an integrated viewer are provided to facilitate the evaluation of the unwieldy BarMap output. Three novel, complementary quality measures are computed on-the-fly, allowing the analyst to evaluate the coverage of the computed models, the exactness of the computed mapping between the individual states of each model, and the fraction of correctly mapped population during the simulation run. In case of deficiencies, the output is automatically re-rendered after parameter adjustment. Statistical evidence is presented that, even when coarse graining the ensemble, kinetic simulations quickly become infeasible for longer RNAs. However, within the individual gradient basins, most high-energy structures only have a marginal probability and could safely be excluded from the analysis. To tell relevant and irrelevant structures apart, a precise knowledge of the distribution of probability mass within a basin is necessary. Both a theoretical result concerning the shape of its density, and possible applications like the prediction of a basin’s partition function are given. To demonstrate the applicability of computational folding simulations to a real-world task of the life sciences, we conducted an in silico design process for a synthetic, transcriptional riboswitch responding to the ligand neomycin. The designed constructs were then transfected into the bacterium Escherichia coli by a collaborative partner and could successfully regulate a fluorescent reporter gene depending on the presence of its ligand. Additionally, it was shown that the sequence context of the riboswitch could have detrimental effects on its functionality, but also that RNA folding simulations are often capable to predict these interactions and provide solutions in the form of decoupling spacer elements. Taken together, this thesis offers the reader deep insights into the world of RNA folding and its models, and how these can be applied to design novel biomolecules.

Proteins are involved in numerous functions in the human body, including chemical transport, molecular recognition, and catalysis. To perform their function most proteins must adopt a specific structure (often referred to as the folded structure). A microscopic description of folding is an important prerequisite for elucidating the underlying basis of protein misfolding and rational drug design. However, protein folding occurs on heterogeneous length and time scales, presenting a grand challenge to both experiments and simulations. In computer simulations, challenges are generally mitigated by adopting coarse-grained descriptions of the physical environment, employing enhanced sampling strategies, and improving computing code and hardware. While significant advances have been made in these areas, for numerous systems a large spatiotemporal gap between experiment and simulations still exists, due to the limited time and length scales achieved by simulation, and the inability of many experimental techniques to probe fast motions and short distances. In this thesis, kinetic transition networks (KTNs) are constructed for various protein folding systems, via approaches based on the potential energy landscape (PEL) framework. By applying geometry optimisation techniques, the PEL is discretised into stationary points (i.e.~low-energy minima and the transition states that connect them). Essentially, minima characterise the low-lying regions of the PEL (thermodynamics) and transition states encode the motion between these regions (dynamics). Principles from statistical mechanics and unimolecular rate theory may then be employed to derive free energy surfaces and folding rates, respectively, from the KTN. Furthermore, the PEL framework can take advantage of parallel and distributed computing, since stationary points from separate simulations can be easily integrated into one KTN. Moreover, the use of geometry optimisation facilitates greater conformational sampling than conventional techniques based on molecular dynamics. Accordingly, this framework presents an appealing means of probing complex processes, such as protein folding. In this dissertation, we demonstrate the application of state-of-the-art theory, combining PEL analysis and KTNs to three diverse protein systems. First, to improve the efficiency of protein folding simulations, the intrinsic rigidity of proteins is exploited by implementing a local rigid body (LRB) approach. The LRB approach effectively integrates out irrelevant degrees of freedom from the geometry optimisation procedure and further accelerates conformational sampling. The effects of this approach on the underlying PEL are analysed in a systematic fashion for a model protein (tryptophan zipper\,1). We demonstrate that conservative local rigidification can reproduce the thermodynamic and dynamic properties for the model protein. Next, the PEL framework is employed to model large-scale conformational changes in proteins, which have conventionally been difficult to probe in silico. Methods based on geometry optimisation have proved useful in overcoming the broken ergodicity issue, which is associated with proteins that switch morphology. The latest PEL-based approaches are utilised to investigate the most extreme case of fold-switching found in the literature:~the α-helical hairpin to β-barrel transition of the C-terminal domain of RfaH, a bacterial transcription factor. PEL techniques are employed to construct the free energy landscape (FEL) for the refolding process and to discover mechanistic details of the transition at an atomistic level. The final part of the thesis focuses on modelling intrinsically disordered proteins (IDPs). Due to their inherent structural plasticity, IDPs are generally difficult to characterise, both experimentally and via simulations. An approach for studying IDPs within the PEL framework is implemented and tested with various contemporary potential energy functions. The cytoplasmic tail of the human cluster of differentiation 4 (CD4), implicated in HIV-1 infection, is characterised. Metastable states identified on the FEL help to unify, and are consistent with, several earlier predictions.

L’utilisation croissante du vocable de la transition dans le débat public contribue à l’émergence de nouvelles méthodes de recherche dont les géographes commencent à se saisir. La transition invite à réfléchir dans un cadre d’action nouveau. Appliquée au domaine des énergies, elle rencontre le géographe dans ses interprétations des dynamiques spatiales. Ce cadre spatio-temporel inédit, où sont introduites les notions de territorialisation de l’énergie et de réversibilité, constitue une opportunité pour le géographe de penser ces enjeux nouveaux selon des approches du couple espace-temps réinterprétées. Dans ce contexte, la thèse vise à comprendre et à analyser les mécanismes socio-spatiaux mis à l’épreuve par le développement des énergies renouvelables, et plus particulièrement des éoliennes. La spécificité de la démarche réside dans une traduction géographique de l’Analyse de Cycle de Vie. Pour ce faire, la thèse réinvestit le concept de paysage dans son interprétation dynamique. Cependant, l’analyse de cycle de vie nous invite à repenser la dynamique paysagère selon la notion d’événement. La thèse interroge l’arrivée d’un projet éolien comme un événement et s’intéresse à ses modes de surgissement, les déstabilisations socio-spatiales induites et les mécanismes de régulation entrepris par les individus. L’objectif de la recherche est d’expérimenter la conduite d’une Analyse sociale de Cycle de Vie des représentations paysagères de l’éolien. L’ambition se voit confrontée à une contrainte majeure, celle du temps. Le temps imparti de la thèse rencontre les temps politiques et les temps de l’expérience. Événements construits ou événement subis, ils impactent différemment les représentations socio-spatiales selon des échelles de temps variables. L’intention d’une recherche diachronique nous enjoint à réfléchir aux enjeux épistémologiques et méthodologiques stimulants de l’élaboration d‘un corpus particulier où peuvent être analysées conjointement des données de natures et de sources diverses. L’analyse est menée sur les discours et particulièrement sur les références spatiales et les sensibilités des individus face à l’arrivée d’éoliennes sur un territoire. La thèse retrace les étapes des cycles de vie de l’événement-éolien traduites et interprétées selon les contextes de terrains. / The increasing use of the transition terms in the public debate contributes to the emergence of new research methods whom geographers begin to apprehend. Transition invites to consider a new action framework. In the matter of energy domain, the transition concept involves geographers in their socio-spatial interpretations. This new spatiotemporal frame, where are introduced the notions of territorialisation of the energy and the reversibility, provides an opportunity to consider these issues from a reinterpretation of the space-time couple. In this context, the thesis aims in understanding and analyzing of socio-spatial mechanisms tested by the renewable energies development, especially wind turbines. The specificity of this approach may be a geographical rendition of the Life Cycle Assessment method. For this purpose, the thesis requires the concept of landscape in its dynamic meaning. However, the life cycle assessment invites us to reshape the idea of landscape dynamics according to the notion of event. The thesis explores the arrival of a wind turbines project as an event and it focus on its sudden emergence, the induced socio-spatial destabilizations and the individual and social adaptations. The purpose of this research is to investigate a Social Life Cycle Assessment of the landscape representations of the wind energy. This ambition faces a time constraint. The allowed time of a PhD thesis faces political times and the times of the experience. Created events or suffered events impact the socio-spatial representations differently and over various timescales. Considering a diachronic study brings about rethinking the epistemological and methodological issues raised by a corpus which gathers several types of data, from different sources and which would be analyzed together. The analysis is led on discourses and especially on spatial textual references along with the individual sensibilities revealed when a wind turbines project is initiated on territory. The thesis tracks the life cycle steps of windpower-events that we interpret according to the socio-spatial context of the study terrains.

[pt] A energia nuclear no Brasil tem uma longa e rica história, que inclui complexos acordos comerciais internacionais, domínio tecnológico, segredos militares e um grande acidente radiológico. Entretanto, ela é pouco estudada por nossa Geografia, que poderia ampliar o debate sobre o tema para além das tradicionais perspectivas técnico-econômicas. Neste estudo tomamos como base a teoria relacional do lugar, a tipologia das paisagens energéticas e o conceito de nuclearidade para narrar as transformações socioespaciais ocorridas a partir da instalação da Central Nuclear em Angra dos Reis, bem como as conexões desse empreendimento com o ciclo do combustível nuclear. Utilizamos múltiplas metodologias, que incluem: análise documental; entrevistas semiestruturadas com especialistas; análise de séries históricas de imagens, incluindo a aplicação de técnicas de Sensoriamento Remoto e Geoprocessamento; e trabalho de campo exploratório e confirmatório. Apresentamos os marcos iniciais na localização de reatores nucleares pelo mundo, para contextualizar os estudos realizados no Brasil que levaram à escolha da Praia de Itaorna, Angra dos Reis (RJ), para receber a primeira central nuclear do país. Essa escolha tornou Itaorna um lugar nuclear. A instalação da Central Nuclear em 1970 e sua expansão lenta e descontínua nas cinco décadas seguintes levou à uma série de alterações na composição do lugar e no seu grau de nuclearidade. Durante esse período o domínio do significado se manteve estável, enquanto os domínios da natureza e das relações sociais tiveram mudanças significativas, indicando transformações na paisagem. Estas devem ser entendidas dentro de um contexto mais amplo de transformações socioespaciais no município de Angra dos Reis, que inclui a ascensão (terminal de petróleo e Central Nuclear) e o declínio (matas carvoeiras) de paisagens energéticas. A Central Nuclear tornouse um marco na paisagem, modificou a linha de costa e criou uma área de exclusão que permitiu, em certa medida, a regeneração da vegetação no seu entorno. Por outro lado, estimulou o crescimento de um núcleo populacional em Mambucaba que reduziu a vegetação por lá. A paisagem energética da Central Nuclear é caracterizada por sua alta densidade energética, por sua dominância espacial e permanência temporal. A instalação da Central Nuclear ocorreu simultaneamente às instalações da Fábrica de Combustível Nuclear (Resende – RJ) e do Complexo Mínero-industrial do Planalto de Poços de Caldas (Caldas – MG). Esses três lugares se conectam por meio do ciclo do combustível nuclear e sua existência depende de fluxos de materiais (principalmente urânio), de pessoas e de recursos financeiros, que se estabelecem (ou se estabeleciam) entre eles. Essa interdependência diferencia as paisagens energéticas nucleares de outras, como aquelas formadas por hidrelétricas ou parques eólicos. As três paisagens nucleares possuem alta densidade energética. Dentre elas, o Complexo Mínero-industrial é responsável pela transformação mais profunda, maior dominância espacial e permanência temporal, enquanto a Fábrica de Combustível situa-se no outro extremo. A teoria relacional do lugar, a tipologia das paisagens energéticas, e o conceito de nuclearidade se revelaram uma base teórica robusta para o estudo das transformações socioespaciais no ciclo do combustível nuclear e constituem ferramentas promissoras para aplicação no planejamento energético. / [en] Nuclear power in Brazil has a long and rich history, including complex international trade agreements, technological dominance, military secrets, and a major radiological accident. However, it has received little attention from Brazilian Geography, which could broaden the debate on the subject beyond the traditional technical-economic perspectives. We applied the relational theory of place, the typology of energy landscapes, and the concept of nuclearity to describe the sociospatial transformations that occurred after the establishment of the Nuclear Power Station in Angra dos Reis, as well as the connections of this enterprise with the nuclear fuel cycle. We used mixed methods that include: document analysis; semistructured interviews with experts; analysis of historical series of images, including the application of Remote Sensing and Geoprocessing techniques; and exploratory and confirmatory fieldwork. We presented the initial milestones in the siting of nuclear reactors around the world, to put in context Brazilian studies that led to the selection of Praia de Itaorna, Angra dos Reis (RJ), to receive the first nuclear power plant in the country. This choice made Itaorna a nuclear place. The installation of the Nuclear Power Station in 1970 and its slow and discontinuous expansion over the next five decades led to a series of alterations in the composition of the place and in its degree of nuclearity. During this period, the domain of meaning remained stable, while the domains of nature and social relations had significant changes, indicating landscape transformations. These must be understood within a broader context of socio-spatial transformations in the municipality of Angra dos Reis, which includes the rise (petroleum terminal and Nuclear Power Station) and fall (charcoal forests) of energy landscapes. The Nuclear Power Station became a landmark, modified the coastline, and created an exclusion area that allowed, to a certain extent, the regeneration of the surrounding vegetation. On the other hand, it stimulated the growth of a population center in Mambucaba that reduced the vegetation there. The energy landscape of the Nuclear Power Station is characterized by high energy density, spatial dominance, and temporal permanence. The establishment of the Nuclear Power Station took place simultaneously with the establishment of the Nuclear Fuel Factory (Resende – RJ) and the Planalto de Poços de Caldas Mining Plant (Caldas – MG). These three places are connected through the nuclear fuel cycle and their existence depends on flows of materials (mainly uranium), people and financial resources, which are (or were) established between them. This interdependence differentiates nuclear energy landscapes from others, such as those formed by hydroelectric plants or wind farms. The three nuclear landscapes have high energy density. Among them, the Mining Plant causes the deepest transformation, has greater spatial dominance and temporal permanence, while the Fuel Factory is located at the other extreme. The relational theory of place, the typology of energy landscapes, and the concept of nuclearity proved to be a robust theoretical basis for the study of socio-spatial transformations in the nuclear fuel cycle and constitute promising tools to be applied to energy planning.

In this project, various computational energy landscape methods were accelerated using graphics processing units (GPUs). Basin-hopping global optimisation was treated using a version of the limited-memory BFGS algorithm adapted for CUDA, in combination with GPU-acceleration of the potential calculation. The Lennard-Jones potential was implemented using CUDA, and an interface to the GPU-accelerated AMBER potential was constructed. These results were then extended to form the basis of a GPU-accelerated version of hybrid eigenvector-following. The doubly-nudged elastic band method was also accelerated using an interface to the potential calculation on GPU. Additionally, a local rigid body framework was adapted for GPU hardware. Tests were performed for eight biomolecules represented using the AMBER potential, ranging in size from 81 to 22\,811 atoms, and the effects of minimiser history size and local rigidification on the overall efficiency were analysed. Improvements relative to CPU performance of up to two orders of magnitude were obtained for the largest systems. These methods have been successfully applied to both biological systems and atomic clusters. An existing interface between a code for free energy basin-hopping and the SuiteSparse package for sparse Cholesky factorisation was refined, validated and tested. Tests were performed for both Lennard-Jones clusters and selected biomolecules represented using the AMBER potential. Significant acceleration of the vibrational frequency calculations was achieved, with negligible loss of accuracy, relative to the standard diagonalisation procedure. For the larger systems, exploiting sparsity reduces the computational cost by factors of 10 to 30. The acceleration of these computational energy landscape methods opens up the possibility of investigating much larger and more complex systems than previously accessible. A wide array of new applications are now computationally feasible.