NEURAL-NETWORK SYSTEM FOR THE EVALUATION OF SIDE-CHAIN PACKING IN PROTEIN STRUCTURES

An artificial neural network system is used for pattern recognition in protein side-chain-side-chain contact maps, A back-propagation networ k was trained on a set of patterns which are popular in side-chain con tact maps of protein structures, Several neural network architectures and different training parameters were tested to decide on the best co mbination for the neural network, The resulting network can distinguis h between original (from protein structures) and randomized patterns w ith an accuracy of 84.5% and a Matthews' coefficient of 0.72 for the t esting set. Applications of this system for protein structure evaluati on and refinement are also proposed. Examples include structures obtai ned after the application of molecular dynamics to crystal structures, structures obtained from X-ray crystallography at various stages of r efinement, structures obtained from a de novo folding algorithm and de liberately misfolded structures.