Computational Methods and the Development/Production of Biologics and Biosimilars

For a long time the pharmaceutical industry has been dominated by the production of small organic molecules as drugs. This has changed recently with the introduction of biological medicines or biologics. Biologics, as opposed to synthetic organic small molecules, are derived from living cells and are typically larger-sized molecules. As a group they include therapeutic and fusion proteins, monoclonal antibodies and DNA vaccines. They are much more difficult to manufacture and characterize than typical small molecular organic drugs and are almost always taken by injection (as opposed to orally). The development of biologics, hormone therapies and targeted monoclonal antibodies, has contributed greatly to enhanced cancer treatments for patients. Biosimilars are similar, but not identical copies of a biologic drug. Generic drugs are identical copies of small organic molecues but, because biologics are much more complex, biosimilars cannot be identical copies of them. The manufacturing of biologics and biosimilars adds a level of complexity because biologics are not made with a standard set of starting materials like typical drugs, but are made by genetically engineered living cells. A number of steps involved in creating a biological drug are much more complex than for a typical drug and any slight process variation can affect the biological product in terms of stability, efficacy and immunogenic properties. In 2009 the World Health Organization developed guidelines for regulating biosimilars and biological pathways, and for ensuring that their manufacturing process should meet the same standards as required for the originator products. However, even simple issues such as naming conventions and compound registration systems can be of concern. This symposium sought to initiate discussion on some of these issues. 

Dr. Roger Sayle of NextMove Software gave a presentation entitled “Classification, representation, and analysis of cyclic peptides and peptide-like analogs,” which described some of the difficulties involved in naming nonstandard amino acids, as well as defining macrocyclics due to the diverse ways in which peptides can form cyclic linkages. The naming and machine-recognition of synthetic macrocylic peptides provide significant informatics challenges. For example, covalently cross-linked side-chains may have multiple possible (degenerate) primary sequences, requiring the selection of a preferred canonical form during biological registration. In this presentation, Dr. Sayle described the development of a software program “Sugar and Spice,” which can provide some assistance in standardization and machine-recognition of non-standard amino acids. There is a need for standardized naming conventions and notations, which currently are not in place for designed and engineered non-alpha-amino acids, acyclic peptide backbones, and different types of peptide disulfide bridges.

Dr. Suman Sirimulla, St. Louis College of Pharmacy, gave a talk entitled “Non-covalent interactions in protein-ligand interactions: Applications of halogen bonds and carbon bonds in designing PTSD drugs,” in which he presented the significance of considering non-covalent protein-ligand interactions in drug design. There is a growing need to consider the significance of halogen bonds and carbon bonds in protein-ligand interactions. He presented an application in designing drugs for post-traumatic Stress Disorder (PTSD) with the nociceptin receptor as a target, and the design and development of nociceptin analogues using halogen-bond information and halogen-amino acid interaction data to search and mine the Protein Data Bank.

Dr. Sandeepkumar K Kothiwale, Chemistry, Vanderbilt University, Nashville, Tennessee, presented  “BCL:Conf A knowledge based ligand flexibility algorithm and application in computational drug discovery like online drug design game Foldit,” on a derived fragment conformational database created from frequently sampled  experimental structures within the Crystallographic Structure Database (CSD) and the Protein Data Bank (PDB). The likely sampled fragments were stored as a rotamer library. A hierarchical search algorithm was used to perform substructure searching: a random Monte Carlo conformational sampling. 

All the talks presented illustrated the development of novel computational methods to the area of biologics drug design.

Rachelle Bienstock, Symposium Organizer



The Future of the History of Chemical Information
Editors: Leah McEwen, Robert Buntrock
Volume 1164
Sponsoring Division: ACS Division of Chemical Information
Publication Date (Web): August 6, 2014
ISBN: 9780841229457; eISBN: 9780841229464

The aim of this collection is to critically examine trajectories in chemistry, information and communication as determined by the authors in the light of current and possible future practices of the chemical information profession. Along with some additional areas primarily related to present and future directions, this book contains most of the topics covered in the meeting symposium held on August 20, 2012, at the 244th American Chemical Society Meeting in Philadelphia, PA.


Presentation titles, abstracts and slides (#47-51 & 59-65) are listed at: /node/347.

A symposium summary was published in Chemical Information Bulletin, Winter 2012, at:  /node/393