We describe the methodology, parametrization, and application of a conformational search method, called ConfGen, designed to efficiently generate bioactive conformers. We define efficiency as the ability to generate a bioactive conformation within a small total number of conformations using a reasonable amount of computer time. The method combines physics-based force field calculations with empirically derived heuristics designed to achieve efficient searching and prioritization of the ligand's conformational space. While many parameter settings are supported, four modes spanning a range of speed and quality trades-offs are defined and characterized. The validation set used to test the method is composed of ligands from 667 crystal structures covering a broad array of target and ligand classes. With the fastest mode, ConfGen uses an average of 0.5 s per ligand and generates only 14.3 conformers per ligand, at least one of which lies within 2.0 A root-mean-squared deviation of the crystal structure for 96% of the ligands. The most computationally intensive mode raises this recovery rate to 99%, while taking 8 s per ligand. Combining multiple search modes to "fill-in" holes in the conformation space or energy minimizing using an all-atom force field each lead to improvements in the recovery rates at higher resolutions. Overall, ConfGen is at least as good as competing programs at high resolution and demonstrates higher efficiency at resolutions sufficient for many downstream applications, such as pharmacophore modeling.

Sampling low energy conformations of macrocycles is challenging due to the large size of many of these molecules and the constraints imposed by the macrocycle. We present a new conformational search method (implemented in MacroModel) that uses brief MD simulations followed by minimization and normal-mode search steps. The method was parametrized using a set of 100 macrocycles from the PDB and CSD. It was then tested on a publicly available data set for which there are published results using alternative methods; we found that when the same force field is used (in this case MMFFs in vacuum), our method tended to identify conformations with lower energies than what the other methods identified. The performance on a new set of 50 macrocycles from the PDB and CSD was also quite good; the mean and median RMSD values for just the ring atoms were 0.60 and 0.33 Å, respectively. However, the RMSD values for macrocycles with more than 30 ring-atoms were quite a bit larger compared to the smaller macrocycles. Possible origins for this and ideas for improving the performance on very large macrocycles are discussed.

The acceleration of bioprocess development for biologics and vaccines can be enabled by automated high throughput technologies. This will alleviate the significant resource burden from the multi-factorial statistical experimentation required for controlling product quality attributes of complex biologics. Recent technology advances have improved clone evaluation and screening, but have struggled to combine the scale down criteria required for both high cell density cell culture and microbial processes, with sufficient automation and disposable technologies to accelerate process development. This article describes the proof of concept evaluations of an automated disposable small scale reactor for high throughput upstream process development. Characterization studies established the small scale stirred tank disposable 250 mL reactor as similar to those of lab and pilot scale. The reactor generated equivalent process performance for industrial biologics processes for therapeutic protein and monoclonal antibody production using CHO cell culture, Pichia pastoris and E. coli. This included similar growth, cell viability, product titer, and product quality. The technology was shown to be robust across multiple runs and met the requirements for the ability to run high cell density processes (>400 g/L wet cell weight) with exponential feeds and sophisticated event triggered processes. Combining this reactor into an automated array of reactors will ultimately be part of a high throughput process development strategy. This will combine upstream, small scale purification with rapid analytics that will dramatically shorten timelines and costs of developing biological processes.

Glycoengineering enabled the production of proteins with human N-linked glycans by Pichia pastoris. This study used a glycoengineered P. pastoris strain which is capable of producing humanized glycoprotein with terminal galactose for monoclonal antibody production. A design of experiments approach was used to optimize the process parameters. Followed by further optimization of the specific methanol feed rate, induction duration, and the initial induction biomass, the resulting process yielded up to 1.6 g/L of monoclonal antibody. This process was also scaled-up to 1,200-L scale, and the process profiles, productivity, and product quality were comparable with 30-L scale. The successful scale-up demonstrated that this glycoengineered P. pastoris fermentation process is a robust and commercially viable process.