Computer modeling of solution X-ray scattering intensity for biomacromolecules

Increasing amounts of scattering data are obtained from high-throughput Solution X-ray scattering (SXS) experiments, including small-angle X-ray scattering (SAXS) and wide-angle X-ray scattering (WAXS). There is a great demand of computational methods that can retrieve useful structural information or build structure model from these data. We have proposed substantial improvements to current methods that model the scattering profiles from protein structure at both atomistic scale and coarse-grained (CG) scale. In addition, our coarse-grained approach can be conveniently applied to structure optimization based on target scattering intensity. Firstly, a fast Fourier transform (FFT) based orientational average method is proposed to improve the computational efficiency of modeling scattering profiles using an atomistic protein structure representation, especially in case of considering explicit hydration water molecules. Comparing with the popular spherical average method, our method will become more efficient for systems with more than 3000 atoms. Moreover, the computational time of our FFT-based method remains nearly unchanged as the system size increases, making it suitable for very large protein complexes. CG representations are also widely used to improve the computational efficiency of theoretical scattering intensity computation. Given the importance of accuracy for CG approaches, we have proposed the electron density matching (EDM) method to parameterize the CG form factors. Comparing with the CG form factors used in literature, our EDM-derived ones result in better agreement to atomistic scattering intensities. Furthermore, the resulting CG xxform factors are shown to reproduce the experimental scattering profiles well by including the contribution of hydration layer and the correction of protein excluded volume. Finally, in order to perform structure modeling with our EDM-derived CG form factors, we have proposed an implicit hydration term to take account the contribution of the hydration layer scattering. This term is only related to the surface accessible solvent area (SASA) of protein atoms, making our formulation to evaluate scattering intensity analytically differentiable to the protein coordinates. The implicit hydration term is fitted to best reproduce the overall scattering intensity computed using explicit hydration water molecules. It is shown that the conjugate gradient structure optimization based on the target scattering intensity can produce final molecular structures very close to the known target structure.DOCTOR OF PHILOSOPHY (SBS

Modeling solution X-ray scattering of biomacromolecules using an explicit solvent model and the fast Fourier transform

A novel computational method based on atomic form factors and the fast Fourier transform (FFT) is developed to compute small- and near-wide-angle X-ray scattering profiles of biomacromolecules from explicit solvent modeling. The method is validated by comparing the results with those from non-FFT approaches and experiments, and good agreement with experimental data is observed for both small and near-wide angles. In terms of computational efficiency, the FFT-based method is advantageous for protein solution systems of more than 3000 atoms. Furthermore, the computational cost remains nearly constant for a wide range of system sizes. The FFT-based approach can potentially handle much larger molecular systems compared with popular existing methods.MOE (Min. of Education, S’pore)Published versio

Robust Heterogeneous Anisotropic Elastic Network Model Precisely Reproduces the Experimental B‑factors of Biomolecules

A computational method called the progressive fluctuation matching (PFM) is developed for constructing robust heterogeneous anisotropic network models (HANMs) for biomolecular systems. An HANM derived through the PFM approach consists of harmonic springs with realistic positive force constants, and yields the calculated B-factors that are basically identical to the experimental ones. For the four tested protein systems including crambin, trypsin inhibitor, HIV-1 protease, and lysozyme, the root-mean-square deviations between the experimental and the computed B-factors are only 0.060, 0.095, 0.247, and 0.049 Ų, respectively, and the correlation coefficients are 0.99 for all. By comparing the HANM/ANM normal modes to their counterparts derived from both an atomistic force field and an NMR structure ensemble, it is found that HANM may provide more accurate results on protein dynamics

B-spline tight frame based force matching method

In molecular dynamics simulations, compared with popular all-atom force field approaches, coarse-grained (CG) methods are frequently used for the rapid investigations of long time- and length-scale processes in many important biological and soft matter studies. The typical task in coarse-graining is to derive interaction force functions between different CG site types in terms of their distance, bond angle or dihedral angle. In this paper, an L1-regularized least squares model is applied to form the force functions, which makes additional use of the B-spline wavelet frame transform in order to preserve the important features of force functions. The B-spline tight frames system has a simple explicit expression which is useful for representing our force functions. Moreover, the redundancy of the system offers more resilience to the effects of noise and is useful in the case of lossy data. Numerical results for molecular systems involving pairwise non-bonded, three and four-body bonded interactions are obtained to demonstrate the effectiveness of our approach.MOE (Min. of Education, S’pore)Accepted versio

Robust Heterogeneous Anisotropic Elastic Network Model Precisely Reproduces the Experimental B‑factors of Biomolecules

A computational method called the progressive fluctuation matching (PFM) is developed for constructing robust heterogeneous anisotropic network models (HANMs) for biomolecular systems. An HANM derived through the PFM approach consists of harmonic springs with realistic positive force constants, and yields the calculated B-factors that are basically identical to the experimental ones. For the four tested protein systems including crambin, trypsin inhibitor, HIV-1 protease, and lysozyme, the root-mean-square deviations between the experimental and the computed B-factors are only 0.060, 0.095, 0.247, and 0.049 Ų, respectively, and the correlation coefficients are 0.99 for all. By comparing the HANM/ANM normal modes to their counterparts derived from both an atomistic force field and an NMR structure ensemble, it is found that HANM may provide more accurate results on protein dynamics

Robust Heterogeneous Anisotropic Elastic Network Model Precisely Reproduces the Experimental B‑factors of Biomolecules

A computational method called the progressive fluctuation matching (PFM) is developed for constructing robust heterogeneous anisotropic network models (HANMs) for biomolecular systems. An HANM derived through the PFM approach consists of harmonic springs with realistic positive force constants, and yields the calculated B-factors that are basically identical to the experimental ones. For the four tested protein systems including crambin, trypsin inhibitor, HIV-1 protease, and lysozyme, the root-mean-square deviations between the experimental and the computed B-factors are only 0.060, 0.095, 0.247, and 0.049 Ų, respectively, and the correlation coefficients are 0.99 for all. By comparing the HANM/ANM normal modes to their counterparts derived from both an atomistic force field and an NMR structure ensemble, it is found that HANM may provide more accurate results on protein dynamics

Plasticity and second messengers during synapse development

Effective function of the locomotor system in the Drosophila larva requires a continuous adjustment of synaptic architecture and neurotransmission at the neuromuscular junction (NMJ). This feature has made the larval NMJ a favorite model to study the genetic and molecular mechanisms underlying synapse plasticity. This chapter will review experimental strategies used to study plasticity at the NMJ, the cellular parameters affected during plastic changes, and many of the known molecules involved in plastic changes. In addition, signal transduction pathways activated during plasticity will be discussed