Prediction of Optimal Folding Routes of Proteins That Satisfy the Principle of Lowest Entropy Loss: Dynamic Contact Maps and Optimal Control

An optimization model is introduced in which proteins try to evade high energy regions of the folding landscape, and prefer low entropy loss routes during folding. We make use of the framework of optimal control whose convenient solution provides practical and useful insight into the sequence of events during folding. We assume that the native state is available. As the protein folds, it makes different set of contacts at different folding steps. The dynamic contact map is constructed from these contacts. The topology of the dynamic contact map changes during the course of folding and this information is utilized in the dynamic optimization model. The solution is obtained using the optimal control theory. We show that the optimal solution can be cast into the form of a Gaussian Network that governs the optimal folding dynamics. Simulation results on three examples (CI2, Sso7d and Villin) show that folding starts by the formation of local clusters. Non-local clusters generally require the formation of several local clusters. Non-local clusters form cooperatively and not sequentially. We also observe that the optimal controller prefers “zipping” or small loop closure steps during folding. The folding routes predicted by the proposed method bear strong resemblance to the results in the literature

A stitch in time: Efficient computation of genomic DNA melting bubbles

Background: It is of biological interest to make genome-wide predictions of the locations of DNA melting bubbles using statistical mechanics models. Computationally, this poses the challenge that a generic search through all combinations of bubble starts and ends is quadratic. Results: An efficient algorithm is described, which shows that the time complexity of the task is O(NlogN) rather than quadratic. The algorithm exploits that bubble lengths may be limited, but without a prior assumption of a maximal bubble length. No approximations, such as windowing, have been introduced to reduce the time complexity. More than just finding the bubbles, the algorithm produces a stitch profile, which is a probabilistic graphical model of bubbles and helical regions. The algorithm applies a probability peak finding method based on a hierarchical analysis of the energy barriers in the Poland-Scheraga model. Conclusions: Exact and fast computation of genomic stitch profiles is thus feasible. Sequences of several megabases have been computed, only limited by computer memory. Possible applications are the genome-wide comparisons of bubbles with promotors, TSS, viral integration sites, and other melting-related regions.Comment: 16 pages, 10 figure

The Energy Computation Paradox and ab initio Protein Folding

The routine prediction of three-dimensional protein structure from sequence remains a challenge in computational biochemistry. It has been intuited that calculated energies from physics-based scoring functions are able to distinguish native from nonnative folds based on previous performance with small proteins and that conformational sampling is the fundamental bottleneck to successful folding. We demonstrate that as protein size increases, errors in the computed energies become a significant problem. We show, by using error probability density functions, that physics-based scores contain significant systematic and random errors relative to accurate reference energies. These errors propagate throughout an entire protein and distort its energy landscape to such an extent that modern scoring functions should have little chance of success in finding the free energy minima of large proteins. Nonetheless, by understanding errors in physics-based score functions, they can be reduced in a post-hoc manner, improving accuracy in energy computation and fold discrimination

A mixed methods approach to evaluating community drug distributor performance in the control of neglected tropical diseases

BACKGROUND: Trusted literate, or semi-literate, community drug distributors (CDDs) are the primary implementers in integrated preventive chemotherapy (IPC) programmes for Neglected Tropical Disease (NTD) control. The CDDs are responsible for safely distributing drugs and for galvanising communities to repeatedly, often over many years, receive annual treatment, create and update treatment registers, monitor for side-effects and compile treatment coverage reports. These individuals are 'volunteers' for the programmes and do not receive remuneration for their annual work commitment. METHODS: A mixed methods approach, which included pictorial diaries to prospectively record CDD use of time, structured interviews and focus group discussions, was used to triangulate data on how 58 CDDs allocated their time towards their routine family activities and to NTD Programme activities in Uganda. The opportunity costs of CDD time were valued, performance assessed by determining the relationship between time and programme coverage, and CDD motivation for participating in the programme was explored. RESULTS: Key findings showed approximately 2.5 working weeks (range 0.6-11.4 working weeks) were spent on NTD Programme activities per year. The amount of time on NTD control activities significantly increased between the one and three deliveries that were required within an IPC campaign. CDD time spent on NTD Programme activities significantly reduced time available for subsistence and income generating engagements. As CDDs took more time to complete NTD Programme activities, their treatment performance, in terms of validated coverage, significantly decreased. Motivation for the programme was reported as low and CDDs felt undervalued. CONCLUSIONS: CDDs contribute a considerable amount of opportunity cost to the overall economic cost of the NTD Programme in Uganda due to the commitment of their time. Nevertheless, programme coverage of at least 75 %, as required by the World Health Organisation, is not being achieved and vulnerable individuals may not have access to treatment as a consequence of sub-optimal performance by the CDDs due to workload and programmatic factors

No effect of 24 h severe energy restriction on appetite regulation and ad libitum energy intake in overweight and obese males

Background/Objectives: Long-term success of weight loss diets might depend on how the appetite regulatory system responds to energy restriction (ER). This study determined the effect of 24 h severe ER on subjective and hormonal appetite regulation, subsequent ad libitum energy intake and metabolism. Subjects/Methods: In randomised order, eight overweight or obese males consumed a 24 h diet containing either 100% (12105 (1174 kJ; energy balance; EB) or 25% (3039 (295) kJ; ER) of estimated daily energy requirements (EER). An individualised standard breakfast containing 25% of EER (3216 (341) kJ) was consumed the following morning and resting energy expenditure, substrate utilisation and plasma concentrations of acylated ghrelin, glucagon-like peptide-1 (GLP-17–36), glucose-dependant insulinotropic peptide (GIP1–42), glucose, insulin and non-esterified fatty acid (NEFA) were determined for 4 h after breakfast. Ad libitum energy intake was assessed in the laboratory on day 2 and via food records on day 3. Subjective appetite was assessed throughout. Results: Energy intake was not different between trials for day 2 (EB: 14946 (1272) kJ; ER: 15251 (2114) kJ; P=0.623), day 3 (EB: 10580 (2457) kJ; 10812 (4357) kJ; P=0.832) or day 2 and 3 combined (P=0.693). Subjective appetite was increased during ER on day 1 (P0.381). Acylated ghrelin, GLP-17–36 and insulin were not different between trials (P>0.104). Post-breakfast area under the curve (AUC) for NEFA (P<0.05) and GIP1–42 (P<0.01) were greater during ER compared with EB. Fat oxidation was greater (P<0.01) and carbohydrate oxidation was lower (P<0.01) during ER, but energy expenditure was not different between trials (P=0.158). Conclusions: These results suggest that 24 h severe ER does not affect appetite regulation or energy intake in the subsequent 48 h. This style of dieting may be conducive to maintenance of a negative EB by limiting compensatory eating behaviour, and therefore may assist with weight loss

Capturing the essence of folding and functions of biomolecules using Coarse-Grained Models

The distances over which biological molecules and their complexes can function range from a few nanometres, in the case of folded structures, to millimetres, for example during chromosome organization. Describing phenomena that cover such diverse length, and also time scales, requires models that capture the underlying physics for the particular length scale of interest. Theoretical ideas, in particular, concepts from polymer physics, have guided the development of coarse-grained models to study folding of DNA, RNA, and proteins. More recently, such models and their variants have been applied to the functions of biological nanomachines. Simulations using coarse-grained models are now poised to address a wide range of problems in biology.Comment: 37 pages, 8 figure

Compactness Determines the Success of Cube and Octahedron Self-Assembly

Nature utilizes self-assembly to fabricate structures on length scales ranging from the atomic to the macro scale. Self-assembly has emerged as a paradigm in engineering that enables the highly parallel fabrication of complex, and often three-dimensional, structures from basic building blocks. Although there have been several demonstrations of this self-assembly fabrication process, rules that govern a priori design, yield and defect tolerance remain unknown. In this paper, we have designed the first model experimental system for systematically analyzing the influence of geometry on the self-assembly of 200 and 500 µm cubes and octahedra from tethered, multi-component, two-dimensional (2D) nets. We examined the self-assembly of all eleven 2D nets that can fold into cubes and octahedra, and we observed striking correlations between the compactness of the nets and the success of the assembly. Two measures of compactness were used for the nets: the number of vertex or topological connections and the radius of gyration. The success of the self-assembly process was determined by measuring the yield and classifying the defects. Our observation of increased self-assembly success with decreased radius of gyration and increased topological connectivity resembles theoretical models that describe the role of compactness in protein folding. Because of the differences in size and scale between our system and the protein folding system, we postulate that this hypothesis may be more universal to self-assembling systems in general. Apart from being intellectually intriguing, the findings could enable the assembly of more complicated polyhedral structures (e.g. dodecahedra) by allowing a priori selection of a net that might self-assemble with high yields

Do Small Headgroups of Phosphatidylethanolamine and Phosphatidic Acid Lead to a Similar Folding Pattern of the K+ Channel?

Phospholipid headgroups act as major determinants in proper folding of oligomeric membrane proteins. The K+-channel KcsA is the most popular model protein among these complexes. The presence of zwitterionic nonbilayer lipid phosphatidylethanolamine (PE) is crucial for efficient tetramerization and stabilization of KcsA in a lipid bilayer. In this study, the influence of PE on KcsA folding properties was analyzed by tryptophan fluorescence and acrylamide quenching experiments and compared with the effect of anionic phosphatidic acid (PA). The preliminary studies suggest that the small size and hydrogen bonding capability of the PE headgroup influences KcsA folding via a mechanism quite similar to that observed for anionic PA