Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Towards a General Intermolecular Binding Affinity Calculator

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Version 1 : Received: 10 August 2022 / Approved: 11 August 2022 / Online: 11 August 2022 (08:40:37 CEST)

How to cite: Li, W. Towards a General Intermolecular Binding Affinity Calculator. Preprints 2022, 2022080213 (doi: 10.20944/preprints202208.0213.v1). Li, W. Towards a General Intermolecular Binding Affinity Calculator. Preprints 2022, 2022080213 (doi: 10.20944/preprints202208.0213.v1).

Abstract

Thanks to the continued development of experimental structural biology and the half-a-century old Protein Data Bank, 2021 saw a big step forward in the development of protein structure prediction with deep learning algorithms. Recently, DeepMinds AlphaFold has determined the structures of ∼ 200 million proteins from 1 million species. The speed of this progress raise the question of what becomes possible for computational drug discovery and design when we have a systems-wide account of the structures and motions of most proteins. Therefore, this article puts forward the concept of a general intermolecular binding affinity calculator (GIBAC): Kd = f(molA, molB, envPara), towards the acceleration of traditional computer-aided drug design (CADD) and artificial intelligence-integrated drug discovery (AIDD), for both small molecules and biologics such as therapeutic proteins.

Keywords

intermolecular binding affinity; drug target binding affinity; computer-aided drug design (CADD); artificial intelligence-integrated drug discovery (AIDD); machine learning

Subject

LIFE SCIENCES, Biophysics

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