Fung, A. | Search bioRxiv

bioRxiv2021

Transferability of Geometric Patterns from Protein Self-Interactions to Protein-Ligand Interactions

There is significant interest in developing machine learning methods to model protein-ligand interactions but a scarcity of experimentally resolved protein-ligand structures to learn from. Protein self-contacts are a much larger source of structural data that could be leveraged, but currently it is not well understood how this data source differs from the target domain. Here, we characterize the 3D geometric patterns of protein self-contacts as probability distributions. We then present a flexible statistical framework to assess the transferability of these patterns to protein-ligand contacts. We observe that the level of transferability from protein self-contacts to protein-ligand contacts depends on contact type, with many contact types exhibiting high transferability. We then demonstrate the potential of leveraging information from these geometric patterns to aid in ligand pose-selection problems in protein-ligand docking. We publicly release our extracted data on geometric interaction patterns to enable further exploration of this problem.

biophysics↗

bioRxiv2021

A high throughput bispecific antibody discovery pipeline

Bispecific antibodies (BsAbs) represent an emerging class of immunotherapy but inefficiency in the current BsAb discovery paradigm has limited their broad clinical availability. Here we report a high throughput, agnostic, single-cell-based BsAb functional screening pipeline, comprising molecular and cell engineering for efficient generation of BsAb library cells, followed by functional interrogation at the single-cell level to identify and sort positive clones and downstream sequence identification with single-cell PCR and sequencing and functionality characterization. Using a CD19xCD3 bispecific T cell engager (BiTE) as a model system, we demonstrate that our single cell platform possesses a high throughput screening efficiency of up to one and half million variant library cells per run and can isolate rare functional clones at low abundance of 0.008%. Using a complex CD19xCD3 BiTE-expressing cell library with approximately 22,300 unique variants comprising combinatorially varied scFvs, connecting linkers and VL/VH orientations, we have identified 98 unique clones including extremely rare ones ([~] 0.001% abundance). We also discovered BiTEs that exhibit novel properties contradictory to conventional wisdom, including harboring rigid scFv connecting peptide linkers yet with in vitro cytotoxicity comparable to that of clinically approved Blinatumomab. Through sequencing analyses on sorted BiTE clones, we discovered multiple design variable preferences for functionality including the CD19VL-VH- CD3VH-VL and CD19VH-VL-CD3VH-VL arrangements being the most favored orientation. Sequence analysis further interrogated the sequence composition of the CDRH3 domain in scFvs and identified amino acid residues conserved for function. We expect our single cell platform to not only significantly increase the development speed of high quality of new BsAb therapeutics for cancer and other disorders, but also enable identifying generalizable design principles for new BsAbs and other immunotherapeutics based on an in-depth understanding of the inter-relationships between sequence, structure, and function.

bioengineering↗