Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Inference of macromolecular assemblies from crystalline state.

J. Appl. Cryst.の発刊に際して

We review recent theoretical and experimental developments in the field of complex polymers that carry a chemical and topological disorder. The polymer classes discussed include chemically disordered crosslinked heteropolymers and liquid crystalline heteropolymers. Field theory and spin glass averaging methods are very useful to study complex disordered polymers. The field theory allows explicit account of chain conformation contributions to thermodynamical quantities and a faithful representation of experimentally observable order parameters. Spin glass averaging methods presented here are instrumental for averaging over chemical and topological disorders. The review centers on theory development, predictions for conformational and orientational ordering, phase diagram analysis and also comparison with experimental results when possible.

Phase Transformations and Orientational Ordering in Chemically Disordered Polymers — a Modern Primer

Many secreted proteins contain multiple disulfide bonds. How disulfide formation is coupled to protein folding in the cell remains poorly understood at the molecular level. Here, we combine experiment and simulation to address this question as it pertains to the SARS-CoV-2 receptor binding domain (RBD). We show that, whereas RBD can refold reversibly when its disulfides are intact, their disruption causes misfolding into a nonnative molten-globule state that is highly prone to aggregation and disulfide scrambling. Thus, non-equilibrium mechanisms are needed to ensure disulfides form prior to folding in vivo. Our simulations suggest that co-translational folding may accomplish this, as native disulfide pairs are predicted to form with high probability at intermediate lengths, ultimately committing the RBD to its metastable native state and circumventing nonnative intermediates. This detailed molecular picture of the RBD folding landscape may shed light on SARS-CoV-2 pathology and molecular constraints governing SARS-CoV-2 evolution.

/pdf/cotranslational-formation-of-disulfides-guides-folding-of-31dpzqou.pdf

Cotranslational formation of disulfides guides folding of the SARS COV-2 receptor binding domain

Elucidating intracellular drug targets is a difficult problem. While machine learning analysis of omics data has been a promising approach, going from large-scale trends to specific targets remains a challenge. Here, we develop a hierarchic workflow to focus on specific targets based on analysis of metabolomics data and growth rescue experiments. We deploy this framework to understand the intracellular molecular interactions of the multi-valent dihydrofolate reductase-targeting antibiotic compound CD15-3. We analyse global metabolomics data utilizing machine learning, metabolic modelling, and protein structural similarity to prioritize candidate drug targets. Overexpression and in vitro activity assays confirm one of the predicted candidates, HPPK (folK), as a CD15-3 off-target. This study demonstrates how established machine learning methods can be combined with mechanistic analyses to improve the resolution of drug target finding workflows for discovering off-targets of a metabolic inhibitor. 

/pdf/empowering-drug-off-target-discovery-with-metabolic-and-2257mvk2.pdf

Empowering drug off-target discovery with metabolic and structural analysis

Antibiotic resistance is a worldwide challenge. A potential approach to block resistance is to simultaneously inhibit WT and known escape variants of the target bacterial protein. Here we applied an integrated computational and experimental approach to discover compounds that inhibit both WT and trimethoprim (TMP) resistant mutants of E. coli dihydrofolate reductase (DHFR). We identified a novel compound (CD15-3) that inhibits WT DHFR and its TMP resistant variants L28R, P21L and A26T with IC50 50-75 micromole against WT and TMP-resistant strains. Resistance to CD15-3 was dramatically delayed compared to TMP in in vitro evolution. Whole genome sequencing of CD15-3 resistant strains showed no mutations in the target folA locus. Rather, gene duplication of several efflux pumps gave rise to weak (about twofold increase in IC50) resistance against CD15-3. Altogether, our results demonstrate the promise of strategy to develop evolution drugs - compounds which block evolutionary escape routes in pathogens.

/pdf/development-of-evolution-drugs-antibacterial-compounds-that-3s4p65k3nf.pdf

Development of evolution drugs - antibacterial compounds that block pathways to resistance

L'invention porte sur un systeme et un procede de conception rationnelle de medicaments sur la base d'une structure novo amelioree, faisant intervenir un procede de prediction precise de l'energie libre de liaison. Ce systeme et ce procede utilisent un modele de granulation grossiere avec des donnees potentielles basees sur une connaissance correspondante, de facon a developper des ligands candidats et des banques de ligands candidats (108). A la lumiere de la presente invention utilisant le modele de granulation grossiere, ce nouveau procede de developpement moleculaire (108) met en oeuvre une methode de selection Metropolis Monte-Carlo (218) qui donne lieu a une faible structure energetique, qui n'est pas necessairement la plus faible, mais qui, toutefois, permet d'obtenir un meilleur ligand candidat (110).

Systeme et procede de conception rationnelle de medicaments sur la base d'une structure faisant intervenir la prediction precise de l'energie libre de liaison

Eugene I. Shakhnovich

Papers

Phase Transformations and Orientational Ordering in Chemically Disordered Polymers — a Modern Primer

Cotranslational formation of disulfides guides folding of the SARS COV-2 receptor binding domain

Empowering drug off-target discovery with metabolic and structural analysis

Development of evolution drugs - antibacterial compounds that block pathways to resistance

Systeme et procede de conception rationnelle de medicaments sur la base d'une structure faisant intervenir la prediction precise de l'energie libre de liaison