An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022

In the technical report, we provide our solution for OGB-LSC 2022 Graph Regression Task. The target of this task is to predict the quantum chemical property, HOMO-LUMO gap for a given molecule on PCQM4Mv2 dataset. In the competition, we designed two kinds of models: Transformer-M-ViSNet which is an geometry-enhanced graph neural network for fully connected molecular graphs and Pretrained-3D-ViSNet which is a pretrained ViSNet by distilling geomeotric information from optimized structures. With an ensemble of 22 models, ViSNet Team achieved the MAE of 0.0723 eV on the test-challenge set, dramatically reducing the error by 39.75% compared with the best method in the last year competition

ViSNet: an equivariant geometry-enhanced graph neural network with vector-scalar interactive message passing for molecules

Geometric deep learning has been revolutionizing the molecular modeling field. Despite the state-of-the-art neural network models are approaching ab initio accuracy for molecular property prediction, their applications, such as drug discovery and molecular dynamics (MD) simulation, have been hindered by insufficient utilization of geometric information and high computational costs. Here we propose an equivariant geometry-enhanced graph neural network called ViSNet, which elegantly extracts geometric features and efficiently models molecular structures with low computational costs. Our proposed ViSNet outperforms state-of-the-art approaches on multiple MD benchmarks, including MD17, revised MD17 and MD22, and achieves excellent chemical property prediction on QM9 and Molecule3D datasets. Additionally, ViSNet achieved the top winners of PCQM4Mv2 track in the OGB-LCS@NeurIPS2022 competition. Furthermore, through a series of simulations and case studies, ViSNet can efficiently explore the conformational space and provide reasonable interpretability to map geometric representations to molecular structures

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

Computational simulation of chemical and biological systems using ab initio molecular dynamics has been a challenge over decades. Researchers have attempted to address the problem with machine learning and fragmentation-based methods, however the two approaches fail to give a satisfactory description of long-range and many-body interactions, respectively. Inspired by fragmentation-based methods, we propose the Long-Short-Range Message-Passing (LSR-MP) framework as a generalization of the existing equivariant graph neural networks (EGNNs) with the intent to incorporate long-range interactions efficiently and effectively. We apply the LSR-MP framework to the recently proposed ViSNet and demonstrate the state-of-the-art results with up to $40\%$ error reduction for molecules in MD22 and Chignolin datasets. Consistent improvements to various EGNNs will also be discussed to illustrate the general applicability and robustness of our LSR-MP framework

Human Angiostrongyliasis Outbreak in Dali, China

Angiostrongyliasis, caused by the rat lungworm Angiostrongylus cantonensis, is a potentially fatal food-borne disease. It is endemic in parts of Southeast Asia, the Pacific Islands, Australia, and the Caribbean. Outbreaks have become increasingly common in China due to the spread of efficient intermediate host snails, most notably Pomacea canaliculata. However, infections are difficult to detect since the disease has a rather long incubation period and few diagnostic clinical symptoms. Reliable diagnostic tests are not widely available. The described angiostrongyliasis epidemic in Dali, China lasted for eight months. Only 11 of a total of 33 suspected patients were clinically confirmed based on a set of diagnostic criteria. Our results demonstrate that the rapid and correct diagnosis of the index patient is crucial to adequately respond to an epidemic, and a set of standardized diagnostic procedures is needed to guide clinicians. Integrated control and management measures including health education, clinical guidelines and a hospital-based surveillance system, should be implemented in areas where snails are a popular food item

Microstructure and properties of a new high density alloy

A new high density alloy NiW750 was developed, which was based on the faced-center cubic solid solution structure and aging strengthening mechanism. Microstructure of the alloy was observed by SEM and TEM. The material characteristics under dynamic compressing loading were investigated by using the split Hopkinson pressure bar test. The comparison among the NiW750, ultra high strength steel G50 and tungsten 93WNiFe was also conducted.The results show that the NiW750 high density alloy has the best comprehensive properties among three materials. After aging at 750℃/5h,the tensile strength of NiW750 can achieve up to 1746MPa,while the impact toughness (akU) can achieve 113J/cm2. Under the condition of dynamic loading, the material shows strain rate hardening effect obviously as its dynamic flow stress can reach about 2250MPa. The adiabatic shear bands are formed within specimens in the direction of 45° to the central axis with a bandwidth of 80-150μm at the strain rate of about 5500s-1 and a wide transition zone, so as to avoid the premature emergence of the shear fracture

Cloning and functional characterization of SAD genes in potato.

Stearoyl-acyl carrier protein desaturase (SAD), locating in the plastid stroma, is an important fatty acid biosynthetic enzyme in higher plants. SAD catalyzes desaturation of stearoyl-ACP to oleyl-ACP and plays a key role in determining the homeostasis between saturated fatty acids and unsaturated fatty acids, which is an important player in cold acclimation in plants. Here, four new full-length cDNA of SADs (ScoSAD, SaSAD, ScaSAD and StSAD) were cloned from four Solanum species, Solanum commersonii, S. acaule, S. cardiophyllum and S. tuberosum, respectively. The ORF of the four SADs were 1182 bp in length, encoding 393 amino acids. A sequence alignment indicated 13 amino acids varied among the SADs of three wild species. Further analysis showed that the freezing tolerance and cold acclimation capacity of S. commersonii are similar to S. acaule and their SAD amino acid sequences were identical but differed from that of S. cardiophyllum, which is sensitive to freezing. Furthermore, the sequence alignments between StSAD and ScoSAD indicated that only 7 different amino acids at residues were found in SAD of S. tuberosum (Zhongshu8) against the protein sequence of ScoSAD. A phylogenetic analysis showed the three wild potato species had the closest genetic relationship with the SAD of S. lycopersicum and Nicotiana tomentosiformis but not S. tuberosum. The SAD gene from S. commersonii (ScoSAD) was cloned into multiple sites of the pBI121 plant binary vector and transformed into the cultivated potato variety Zhongshu 8. A freeze tolerance analysis showed overexpression of the ScoSAD gene in transgenic plants significantly enhanced freeze tolerance in cv. Zhongshu 8 and increased their linoleic acid content, suggesting that linoleic acid likely plays a key role in improving freeze tolerance in potato plants. This study provided some new insights into how SAD regulates in the freezing tolerance and cold acclimation in potato

Sequences of primers.

<p>Sequences of primers.</p

Process of buds induction from potato tuber dish A: Nov.26th, 2012; B: Dec.1th, 2012; C: Dec.5th, 2012; D: Dec.10th, 2012.

<p>Process of buds induction from potato tuber dish A: Nov.26th, 2012; B: Dec.1th, 2012; C: Dec.5th, 2012; D: Dec.10th, 2012.</p

Nonacclimated freezing tolerance (RFT) and acclimation capacity (ΔRFT) of Genetically modified lines and control (WT).

<p>T13-T33, <i>ScoSAD</i>-overexpressing lines. WT, wild-type Zhongshu No. 8.</p><p>Nonacclimated freezing tolerance (RFT) and acclimation capacity (ΔRFT) of Genetically modified lines and control (WT).</p